PRESSURE OXIDATION OF ENARGITE CONCENTRATES CONTAINING GOLD AND SILVER

Abstract

Disclosed herein is a treated ore solid comprising a reduced amount of a contaminant, for example arsenic, compared to the ore solid prior to treatment. Also disclosed are temperature and pressure modifications, parameters, and methods for treating an ore solid by pressure oxidation leaching of enargite concentrates. The disclosed methods and processes may be applied to copper sulfide orebodies and concentrates containing arsenic. In some cases, the disclosed methods and systems extract, remove, or reduce contaminants, for example arsenic, from an ore containing solution at moderately increased temperature, pressure, and oxygen concentration, and in the presence of an acid.

Description

FIELD

The disclosed methods, systems, and compositions are directed to extraction of elements, metals, minerals, and compounds from ore solids.

BACKGROUND

Chapter 1

Introduction

Most of the copper produced worldwide comes from sulfide minerals, and a majority of production is through pyrometallurgy as opposed to the use of hydrometallurgical methods.

As easily-accessed sulfide mineral deposits are depleted, producers should mine the more complex sulfides, which are more difficult to process. The concentrates from these sulfides contain various impurities, like arsenic, in copper minerals such as enargite and tennantite. These minerals are evermore present in many copper orebodies.

Copper producers worldwide are required to meet increasingly stringent environmental regulations for gaseous, aqueous and solid waste emissions to the atmosphere. As a result of these regulations, difficulties may be encountered with conventional smelting technology when treating minerals with elements such as arsenic. Conventional smelting/converting technology has a limited capacity and capability to treat arsenic-contaminated concentrates because of the risk of atmospheric pollution and copper cathode quality.

When treated pyrometallurgically, arsenic minerals tend to react easily forming volatile oxides or sulfides or an impure copper product. Many globally significant copper properties have copper sulfide mineralogy high in arsenic present as enargite, Cu₃AsS₄. The enargite may contain significant amounts of contained precious metals.

Development of a selective hydrometallurgical approach to efficiently treat copper concentrates containing large amounts of arsenic would mitigate the issue of atmospheric pollution and may be relatively easily integrated into existing pyrometallurgical operations. In order to evaluate an economic hydrometallurgical process to treat enargite, a background understanding of copper processing, arsenic behavior and enargite mineralogy is essential and follows in this dissertation.

1.1 EPA Position on Arsenic

Arsenic occurs naturally throughout the environment but most exposures of arsenic to people are through food. Acute (short-term) high-level inhalation exposure to arsenic dust or fumes has resulted in gastrointestinal effects (nausea, diarrhea, abdominal pain); central and peripheral nervous system disorders have occurred in workers acutely exposed to inorganic arsenic. Chronic (long-term) inhalation exposure to inorganic arsenic in humans is associated with irritation of the skin and mucous membranes. Chronic oral exposure has resulted in gastrointestinal effects, anemia, peripheral neuropathy, skin lesions, hyperpigmentation, and liver or kidney damage in humans. Inorganic arsenic exposure in humans, by the inhalation route, has been shown to be strongly associated with lung cancer, while ingestion of inorganic arsenic in humans has been linked to a form of skin cancer and also to bladder, liver, and lung cancer. The EPA has classified inorganic arsenic as a Group A, human carcinogen.

Arsine, AsH₃, is a gas consisting of arsenic and hydrogen. It is extremely toxic to humans, with headaches, vomiting, and abdominal pains occurring within a few hours of exposure. The EPA has not classified arsine for carcinogenicity. The following FIG. 1.1 shows regulatory values for inhalation exposure to arsenic (“Arsenic Compounds|Technology Transfer Network Air Toxics Web Site|US EPA” 2012).

1.2 Copper Smelting

Because copper smelters deal with a variety of feed materials from a variety of locations, they should develop a method of evaluating the value of what they are processing, also known as a smelter schedule. A smelter schedule from FMI Miami is shown below and again in Chapter 10. Of note is the low acceptable arsenic limit and substantial unit penalties if the concentrate is accepted by the smelter at all.

TABLE 1.1
FMI Miami Copper Smelter Schedule
Element	Symbol	Penalty Formula
Alumina	Al2O3	$0.50 ea 0.1% > 5%
Iron	Fe	>15% = increased treatment charge for more flux needed
Arsenic	As	$0.50/lb > 1% (20 lb) OR 2$/dt ea 0.1% > 0.1% Max 0.2%
Barium	Ba	0.5 to 1% limit
Beryllium	Be	<10 ppm limit
Bismuth	Bi	($1.10 to $7.50)/dt ea 0.1% > (0.1% to 0.4%) Max 0.4%
Cyanide	CN	<10 ppm!
Cadmium	Cd	($2.20 to $7.50)/dt ea 0.1% > (0.05% to 0.2%) Max 0.4%
Chloride	Cl	BAD PLAYER, DO NOT WANT ANY	5$/dt ea 0.1% > 2%
Cobalt	Co	0.5% limit
Chromium	Cr	$0.50 dt ea 0. 1% > 3% no hex chrome, 5% max on tri v Cr	NO Cu CHROMATE!
Fluoride	F	$5 dt ea 0.1% > 0.2% 0.5% max
Mercury	Hg	($1.85 to $2)/dt ea 10 ppm > 10 ppm
Magnesium	MgO	Normally 10% limit, desirable element in feed???
Ox
Manganese	Mn	2.0% limit
Sodium	Na	5.0% limit
Nickel	Ni	$2 dt ea 0.1% > 2%
Phosphorus	P	3.0% limit
Lead	Pb	$1 dt ea 0.1& > 1% OR $1/lb > 0.5% (more severe)
Antimony	Sb	BAD PLAYER, DO NOT WANT ANY	($2 to $2.20) dt ea 0.1% > 0.3%
Selenium	Se	0.1% limit
Tin	Sn	($1.10 to $3) dt ea 0.1% > (0.2 to 3%) Max 3%
Tellurium	Te	0.01% limit
Thallium	Tl	0.01% limit
Zinc	Zn	$0.50 dt ea 0.1% > 3% 4.0% limit
Moisture	H2O	$2.50 Wt ea 1% > (15% to 50%) what is the material?
Manifest		$30 ea
Bag		$20 ea
containers
Liners		? # & size?
Refining Fees Cu = 12¢ to 14¢ per pound paid	Recovery Rates	Cu = 96.5%
Au = $6.50 to $7.50 per oz paid		Au = 90%+
Ag = 50¢ per oz paid		As = 90%+
10,000 g or ppm = 1%
1,000 = 0.1%	ppm = opt	gmt = # ÷ 31.103481 = opt
100 = 0.01%	31.103481
10 = 0.001%		453 gr = 1 lb.
31.1035 gr = 1 troy oz	14.583 troy oz = 1 pound	Kg/Mt = # × 32.151 = opt

This smelter schedule shows that this smelter would accept a maximum of 0.2% arsenic before penalties occur. For an orebody processing an enargite ore with high arsenic, sending their concentrate to a smelter can be extremely costly.

BRIEF DESCRIPTIONS OF THE DRAWINGS

The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee.

FIG. 1.1: Health Data from Inhalation Exposure (Inorganic Arsenic); ACGIH TLV—American Conference of Governmental and Industrial Hygienists' threshold limit value expressed as a time-weighted average; the concentration of a substance to which most workers can be exposed without adverse effects; NIOSH IDLH—National Institute of Occupational Safety and Health's immediately dangerous to life or health concentration; NIOSH recommended exposure limit to ensure that a worker can escape from an exposure condition that is likely to cause death or immediate or delayed permanent adverse health effects or prevent escape from the environment; NIOSH REL ceiling value—NIOSH's recommended exposure limit ceiling; the concentration that should not be exceeded at any time; OSHA PEL—Occupational Safety and Health Administration's permissible exposure limit expressed as a time-weighted average; the concentration of a substance to which most workers can be exposed without adverse effect averaged over a normal 8-h workday or a 40-h workweek (“Arsenic Compounds|Technology Transfer Network Air Toxics Web Site|US EPA” 2012).

FIG. 2.1: World mine production of copper in the 20th and 21st centuries through November 2011 (Kelly and Matos 2011).

FIG. 2.2: Goldman Sachs copper supply/demand balance (“Europe: Metals & Mining: Base Metals” 2012).

FIG. 2.3: Primary copper concentrate smelters of the world in 2010 (Schlesinger et al. 2011).

FIG. 2.4: Primary copper concentrate smelters of the world circa 2002 (Davenport et al. 2002).

FIG. 2.5: Historical price of copper (23 years) (“Chart Builder|Charts & DataMine” 2012).

FIG. 2.6: Viscosity of molten sulfur as a function of temperature (Bacon and Fanelli 1943), (J. O. Marsden, Wilmot, and Hazen 2007a). The sulfur tends to wet sulfide surfaces and may agglomerate to form “prills” (J. O. Marsden, Wilmot, and Hazen 2007a).

FIG. 2.7: Anaconda Arbiter process flowsheet (Arbiter and McNulty 1999).

FIG. 2.8: Sherritt Gordon process flowsheet (“Uses Ammonia Leach for Lynn Lake Ni—Cu—Co Sulphides” 1953).

FIG. 2.9: Generalized flowsheet for the processing of copper sulfide ores by cupric chloride leaching.

FIG. 2.10: Intec process flowsheet (Milbourne et al. 2003).

FIG. 2.11: CLEAR process flowsheet (Atwood and Livingston 1980).

FIG. 2.12: Cymet process flowsheet (McNamara, Ahrens, and Franek 1978).

FIG. 2.13: Outotec's HydroCopper process flowsheet (“Outotec—Application—HydroCopper®” 2012).

FIG. 2.14: Activox process flowsheet (Palmer and Johnson 2005).

FIG. 2.15: CESL process flowsheet (Milbourne et al. 2003).

FIG. 2.16: NSC process flowsheet from Sunshine (Ackerman and Bucans 1986).

FIG. 2.17: Dynatec process flowsheet (Milbourne et al. 2003).

FIG. 2.18: Proposed Chelopech PDX process flowsheet (Chadwick 2006).

FIG. 2.19: Mt. Gordon process flowsheet (Arnold, Glen, and Richmond 2003).

FIG. 2.20: Kansanshi process flowsheet (Mwale and Megaw).

FIG. 2.21: NENATECH process flowsheet.

FIG. 2.22: Sepon process flowsheet (Baxter, Dreisinger, and Pratt 2003).

FIG. 2.23: Galvanox process flowsheet (Dixon, Mayne, and Baxter 2008).

FIG. 2.24: Phelps Dodge Morenci PDX flowsheet (Cole and Wilmot 2009).

FIG. 3.1: Eh-pH equilibrium diagram for the As—H2O system at 25° C. and unit activity of all species (Robins 1988).

FIG. 5.1: Eh-pH diagram of the Cu3AsS4-H2O system at 25° C. where the activities of soluble Cu, As and S are equal to 0.1. The dashed lines represent S—H2O equilibria and short dashed lines are As—H2O equilibria (Padilla, Rivas, and Ruiz 2008).

FIG. 5.2: Eh-pH diagram of the Cu3AsS4-H2O system at 200° C. where the activities of soluble Cu, As and S are equal to 0.1. The dashed lines represent S—H2O equilibria and short dashed lines are As—H2O equilibria (Padilla, Rivas, and Ruiz 2008).

FIG. 5.3: Stabcal Eh-pH diagram of the Cu3AsS4-H2O system at 25° C. where the activities of soluble Cu, As and S are equal to 0.1. The blue lines represent S—H2O equilibria and As—H2O equilibria.

FIG. 5.4: Stabcal Eh-pH diagram of the Cu3AsS4-H2O system at 200° C. where the activities of soluble Cu, As and S are equal to 0.1. The blue lines represent S—H2O equilibria and As—H2O equilibria.

FIG. 6.1: XRD qualitative analysis on Marca Punta indicates that the primary minerals are enargite, Cu3AsS4 and Villamaninite, Cu, FeS2.

FIG. 6.2: MLA-determined particle size distribution for the Marca Punta Sample.

FIG. 6.3: Classified MLA false color image of Marca Punta Sample. Particle inset units are in pixels (upper right) and concentration palette values are in surface area percentage for the overall sample (upper left).

FIG. 6.4: BSE image of the Marca Punta Sample with enargite (En) and pyrite (Py) grains in the agglomerate.

FIG. 6.5: BSE image of the Marca Punta Sample.

FIG. 6.6: Marca Punta FMI QEMSCAN Liberation.

FIG. 6.7: High grade enargite specimens from Butte, Mont.

FIG. 6.8: XRD qualitative analysis on High Grade Enargite Sample indicated the presence of enargite, quartz, sphalerite and pyrite.

FIG. 6.9: Measured and WPPF-calculated diffractograms and residual plot for the High Grade Enargite Sample.

FIG. 6.10: Classified MLA image of the High Grade Enargite Sample. Particle inset units are in pixels and concentration palette values are in surface area percentage.

FIG. 6.11: BSE image of the High Grade Enargite Sample.

FIG. 8.1: Atmospheric pressure agitated leach experimental equipment setup.

FIG. 8.2: Plot of hourly pH readings on PLS samples from Tests 1-19.

FIG. 8.3: Plot of hourly ORP readings on PLS samples from Tests 1-19.

FIG. 8.4: Stat-Ease Design Expert 3-D surface plot of arsenic extraction as a function of initial acid concentration and temperature.

FIG. 8.5: Classified MLA false color image from the #7 residue sample. Concentration palette values are in surface area percentage.

FIG. 8.6: BSE image from the #7 leach residue sample.

FIG. 9.1: Pressure oxidation autoclave experimental equipment setup.

FIG. 9.2: Stat-Ease Design Expert 3-D surface plot of arsenic extraction as a function of time and solids.

FIG. 9.3: Classified MLA false color image from the #33 composite leach residue. Particle inset units are in pixels (upper right) and concentration palette values are in surface area percentage for the overall sample.

FIG. 9.4: BSE image from the #33 composite leach residue with enargite (En) and pyrite (Py).

FIG. 9.5: Particle size distribution (left) and mineral grain size distributions (right) of enargite and pyrite for the #33 composite leach residue.

FIG. 9.6: Mineral locking for pyrite and enargite for the #33 composite leach residue.

FIG. 9.7: Classified MLA image from the K−1 leach residue.

FIG. 9.8: BSE image from the K−1 leach residue.

FIG. 9.9: Particle size distribution (left) and mineral grain size distributions (right) of enargite and pyrite for the K−1 leach residue.

FIG. 9.10: Mineral locking for pyrite and enargite for the K−1 leach residue.

FIG. 9.11: Classified MLA image from the K−2 leach residue.

FIG. 9.12: BSE image from the K−2 leach residue.

FIG. 9.13: Particle size distribution (left) and mineral grain size distributions (right) of enargite and pyrite for the K−2 leach residue.

FIG. 9.14: Mineral locking for pyrite and enargite for the K−2 leach residue.

FIG. 9.15: Covellite is highlighted in the MLA image from the K−3 leach residue.

FIG. 9.16: BSE image from the K−3 leach residue.

FIG. 9.17: Particle size distribution (left) and mineral grain size distributions (right) of enargite and pyrite for the K−3 leach residue.

FIG. 9.18: Mineral locking for pyrite and enargite for the K−3 leach residue.

FIG. 9.19: MLA image from the K−4 leach residue with quartz in pyrite. The BSE image shows the pyrite particle with a quartz inclusion in FIG. 9.20.

FIG. 9.20: BSE image from the K−4 leach residue.

FIG. 9.21: Particle size distribution (left) and mineral grain size distributions (right) of enargite and pyrite for the K−4 leach residue.

FIG. 9.22: Mineral locking for pyrite and enargite for the K−4 leach residue.

FIG. 9.23: MLA image from the K−5 leach residue.

FIG. 9.24: BSE image from the K−5 leach residue.

FIG. 9.25: Particle size distribution (left) and mineral grain size distributions (right) of enargite and pyrite for the K−5 leach residue.

FIG. 9.26: Mineral locking for pyrite and enargite for the K−5 leach residue.

FIG. 9.27: Representation of concentrations of reactants and products for the reaction A(g)+bB(s)→solid product for a particle of unchanging size (Levenspiel 1999).

FIG. 9.28: Representation of a reacting particle when diffusion through film is the controlling resistance (Levenspiel 1999).

FIG. 9.29: Representation of a reacting particle when diffusion through the ash layer is the controlling resistance (Levenspiel 1999).

FIG. 9.30: Representation of a reacting particle when chemical reaction is the controlling resistance, the reaction being A(g)+bB(s)→products (Levenspiel 1999).

FIG. 9.31: Progress of reaction of a single spherical particle with surrounding fluid measured in terms of time for complete reaction (Levenspiel 1999).

FIG. 9.32: Progress of reaction of a single spherical particle with surrounding fluid measured in terms of time for complete conversion (Levenspiel 1999).

FIG. 9.33: Progress of PDX kinetic reactions.

FIG. 9.34: Kinetic data plotted for fluid film control.

FIG. 9.35: Kinetic data plotted for chemical control.

FIG. 9.36: Kinetic data plotted for pore diffusion control.

FIG. 10.1: Schematic of proposed enargite pressure oxidation flowsheet.

Figure A.1: HSC 7.1 Eh-pH stability diagram for the Cu—S—H2O system at 25° C.

Figure A.2: HSC 7.1 Eh-pH stability diagram for the Cu—S—H2O system at 50° C.

Figure A.3: HSC 7.1 Eh-pH stability diagram for the Cu—S—H2O system at 75° C.

Figure A.4: HSC 7.1 Eh-pH stability diagram for the Cu—S—H2O system at 100° C.

Figure A.5: HSC 7.1 Eh-pH stability diagram for the Cu—S—H2O system at 125° C.

Figure A.6: HSC 7.1 Eh-pH stability diagram for the Cu—S—H2O system at 150° C.

Figure A.7: HSC 7.1 Eh-pH stability diagram for the Cu—S—H2O system at 175° C.

Figure A.8: HSC 7.1 Eh-pH stability diagram for the As—H2O system at 25° C.

Figure A.9: HSC 7.1 Eh-pH stability diagram for the As—H2O system at 50° C.

Figure A.10: HSC 7.1 Eh-pH stability diagram for the As—H2O system at 75° C.

Figure A.11: HSC 7.1 Eh-pH stability diagram for the As—H2O system at 100° C.

Figure A.12: HSC 7.1 Eh-pH stability diagram for the As—H2O system at 125° C.

Figure A.13: HSC 7.1 Eh-pH stability diagram for the As—H2O system at 150° C.

Figure A.14: HSC 7.1 Eh-pH stability diagram for the As—H2O system at 175° C.

Figure A.15: HSC 7.1 Eh-pH stability diagram for the S—H2O system at 25° C.

Figure A.16: HSC 7.1 Eh-pH stability diagram for the S—H2O system at 50° C.

Figure A.17: HSC 7.1 Eh-pH stability diagram for the S—H2O system at 75° C.

Figure A.18: HSC 7.1 Eh-pH stability diagram for the S—H2O system at 100° C.

Figure A.19: HSC 7.1 Eh-pH stability diagram for the S—H2O system at 125° C.

Figure A.20: HSC 7.1 Eh-pH stability diagram for the S—H2O system at 150° C.

Figure A.21: HSC 7.1 Eh-pH stability diagram for the S—H2O system at 175° C.

Figure B.1: HSC 7.1 Eh-pH stability diagram at 25° C. for the Cu—S—H2O system at 0.1 molal.

Figure B.2: HSC 7.1 Eh-pH stability diagram at 25° C. for the Cu—S—H2O system at 0.3 molal.

Figure B.3: HSC 7.1 Eh-pH stability diagram at 25° C. for the Cu—S—H2O system at 0.5 molal.

Figure B.4: HSC 7.1 Eh-pH stability diagram at 25° C. for the Cu—S—H2O system at 0.7 molal.

Figure B.5: HSC 7.1 Eh-pH stability diagram at 25° C. for the As—H2O system at 0.1 molal.

Figure B.6: HSC 7.1 Eh-pH stability diagram at 25° C. for the As—H2O system at 0.3 molal.

Figure B.7: HSC 7.1 Eh-pH stability diagram at 25° C. for the As—H2O system at 0.5 molal.

Figure B.8: HSC 7.1 Eh-pH stability diagram at 25° C. for the As—H2O system at 0.7 molal.

Figure B.9: HSC 7.1 Eh-pH stability diagram at 25° C. for the S—H2O system at 0.1 molal.

Figure B.10: HSC 7.1 Eh-pH stability diagram at 25° C. for the S—H2O system at 0.3 molal.

Figure B.11: HSC 7.1 Eh-pH stability diagram at 25° C. for the S—H2O system at 0.5 molal.

Figure B.12: HSC 7.1 Eh-pH stability diagram at 25° C. for the S—H2O system at 0.7 molal.

Figure D.1: Stat-Ease Normal Plot of Residuals for arsenic extraction model.

Figure D.2: Stat-Ease Residuals vs. Predicted for arsenic extraction model.

Figure D.3: Stat-Ease Residuals vs. Run for arsenic extraction model.

Figure D.4: Stat-Ease Predicted vs. Actual for arsenic extraction model.

Figure D.5: Stat-Ease Box-Cox Plot for Power Transformations for arsenic extraction model.

Figure D.6: Stat-Ease Residuals vs. Initial Acid for arsenic extraction model.

Figure D.7: Stat-Ease Externally Studentized Residuals for arsenic extraction model.

Figure D.8: Stat-Ease Leverage vs. Run for arsenic extraction model.

Figure D.9: Stat-Ease DFFITS vs. Run for arsenic extraction model.

Figure D.10: Stat-Ease DFBETAS for Intercept vs. Run for arsenic extraction model.

Figure D.11: Stat-Ease Cook's Distance for arsenic extraction model.

Figure D.12: Stat-Ease Normal Plot of Residuals for copper difference model.

Figure D.13: Stat-Ease Residuals vs. Predicted for copper difference model.

Figure D.14: Stat-Ease Residuals vs. Run for copper difference model.

Figure D.15: Stat-Ease Predicted vs. Actual for copper difference model.

Figure D.16: Stat-Ease Box-Cox Plot for Power Transforms for copper difference model.

Figure D.17: Stat-Ease Residuals vs. Initial Acid for copper difference model.

Figure D.18: Stat-Ease Externally Studentized Residuals for copper difference model.

Figure D.19: Stat-Ease Leverage vs. Run for copper difference model.

Figure D.20: Stat-Ease DFFITS vs. Run for copper difference model.

Figure D.21: Stat-Ease DFBETAS for Intercept vs. Run for copper difference model.

Figure D.22: Stat-Ease Cook's Distance for copper difference model.

Figure D.23: Stat-Ease Normal Plot of Residuals for iron extraction model.

Figure D.24: Stat-Ease Residuals vs. Predicted for iron extraction model.

Figure D.25: Stat-Ease Residuals vs. Run for iron extraction model.

Figure D.26: Stat-Ease Predicted vs. Actual for iron extraction model.

Figure D.27: Stat-Ease Box-Cox Plot for Power Transforms for iron extraction model.

Figure D.28: Stat-Ease Residuals vs. Initial Acid for iron extraction model.

Figure D.29: Stat-Ease Externally Studentized Residuals for iron extraction model.

Figure D.30: Stat-Ease Leverage vs. Run for iron extraction model.

Figure D.31: Stat-Ease DFFITS vs. Run for iron extraction model.

Figure D.32: Stat-Ease DFBETAS for Intercept vs. Run for iron extraction model.

Figure D.33: Stat-Ease Cook's Distance for iron extraction model.

Figure D.34: Stat-Ease Normal Plot of Residuals for acid consumption model.

Figure D.35: Stat-Ease Residuals vs. Predicted for acid consumption model.

Figure D.36: Stat-Ease Residuals vs. Run for acid consumption model.

Figure D.37: Stat-Ease Predicted vs. Actual for acid consumption model.

Figure D.38: Stat-Ease Box-Cox Plot for Power Transformations for acid consumption model.

Figure D.39: Stat-Ease Residuals vs. Initial Acid for acid consumption model.

Figure D.40: Stat-Ease Externally Studentized Residuals for acid consumption model.

Figure D.41: Stat-Ease Leverage vs. Run for acid consumption model.

Figure D.42: Stat-Ease DFFITS vs. Run for acid consumption model.

Figure D.43: Stat-Ease DFBETAS for Intercept vs. Run for acid consumption model.

Figure D.44: Stat-Ease Cook's Distance for acid consumption model.

Figure D.45: Stat-Ease 3-D plot of effect of initial acid and temperature on arsenic extraction.

Figure D.46: Stat-Ease initial acid and temperature perturbation for arsenic extraction model.

Figure D.47: Stat-Ease initial acid factor plot for arsenic extraction model.

Figure D.48: Stat-Ease temperature factor plot for arsenic extraction model.

Figure D.49: Stat-Ease initial acid and temperature contour plot for arsenic extraction model.

Figure D.50: Stat-Ease cube plot for arsenic extraction model.

Figure D.51: Stat-Ease Normal Plot of Residuals for arsenic extraction model.

Figure D.52: Stat-Ease Residuals vs. Predicted for arsenic extraction model.

Figure D.53: Stat-Ease Residuals vs. Run for arsenic extraction model.

Figure D.54: Stat-Ease Predicted vs. Actual for arsenic extraction model.

Figure D.55: Stat-Ease Box-Cox Plot for Power Transforms for arsenic extraction model.

Figure D.56: Stat-Ease Residuals vs. Time for arsenic extraction model.

Figure D.57: Stat-Ease Externally Studentized Residuals for arsenic extraction model.

Figure D.58: Stat-Ease Leverage vs. Run for arsenic extraction model.

Figure D.59: Stat-Ease DFFITS vs. Run for arsenic extraction model.

Figure D.60: Stat-Ease DFBETAS for Intercept vs. Run for arsenic extraction model.

Figure D.61: Stat-Ease Cook's Distance for arsenic extraction model.

Figure D.62: Stat-Ease Normal Plot of Residuals for copper difference model.

Figure D.63: Stat-Ease Residuals vs. Predicted for copper difference model.

Figure D.64: Stat-Ease Residuals vs. Run for copper difference model.

Figure D.65: Stat-Ease Predicted vs. Actual for copper difference model.

Figure D.66: Stat-Ease Box-Cox Plot for Power Transforms for copper difference model.

Figure D.67: Stat-Ease Residuals vs. Time for copper difference model.

Figure D.68: Stat-Ease Externally Studentized Residuals for copper difference model.

Figure D.69: Stat-Ease Leverage vs. Run for copper difference model.

Figure D.70: Stat-Ease DFFITS vs. Run for copper difference model.

Figure D.71: Stat-Ease DFBETAS for Intercept vs. Run for copper difference model.

Figure D.72: Stat-Ease Cook's Distance for copper difference model.

Figure D.73: Stat-Ease Normal Plot of Residuals for iron extraction model.

Figure D.74: Stat-Ease Residuals vs. Predicted for iron extraction model.

Figure D.75: Stat-Ease Residuals vs. Run for iron extraction model.

Figure D.76: Stat-Ease Predicted vs. Actual for iron extraction model.

Figure D.77: Stat-Ease Box-Cox Plot for Power Transforms for iron extraction model.

Figure D.78: Stat-Ease Residuals vs. Time for iron extraction model.

Figure D.79: Stat-Ease Externally Studentized Residuals for iron extraction model.

Figure D.80: Stat-Ease Leverage vs. Run for iron extraction model.

Figure D.81: Stat-Ease DFFITS vs. Run for iron extraction model.

Figure D.82: Stat-Ease DFBETAS for Intercept vs. Run for iron extraction model.

Figure D.83: Stat-Ease Cook's Distance for iron extraction model.

Figure D.84: Stat-Ease Normal Plot of Residuals for acid consumption model.

Figure D.85: Stat-Ease Residuals vs. Predicted for acid consumption model.

Figure D.86: Stat-Ease Residuals vs. Run for acid consumption model.

Figure D.87: Stat-Ease Predicted vs. Actual for acid consumption model.

Figure D.88: Stat-Ease Box-Cox Plot for Power Transforms for acid consumption model.

Figure D.89: Stat-Ease Residuals vs. Time for acid consumption model.

Figure D.90: Stat-Ease Externally Studentized Residuals for acid consumption model.

Figure D.91: Stat-Ease Leverage vs. Run for acid consumption model.

Figure D.92: Stat-Ease DFFITS vs. Run for acid consumption model.

Figure D.93: Stat-Ease DFBETAS for Intercept vs. Run for acid consumption model.

Figure D.94: Stat-Ease Cook's Distance for acid consumption model.

Figure D.95: Stat-Ease 3-D plot of effect of time and solids on arsenic extraction.

Figure D.96: Stat-Ease perturbation plot for arsenic extraction model.

Figure D.97: Stat-Ease solids factor plot for arsenic extraction model.

Figure D.98: Stat-Ease time factor plot for arsenic extraction model.

Figure D.99: Stat-Ease time and solids contour plot for arsenic extraction model.

Figure D.100: Stat-Ease cube plot for arsenic extraction model.

Figure D.101: Stat-Ease cube plot for arsenic extraction model.

DETAILED DESCRIPTION

Chapter 2

Copper Processing

Disclosed herein is a treated ore solid comprising a reduced amount of a contaminant, for example arsenic, compared to the ore solid prior to treatment. Also disclosed are temperature and pressure approaches to treating an ore solid by pressure oxidation leaching of enargite concentrates. The disclosed methods and processes may be applied to copper sulfide orebodies and concentrates containing arsenic. In some cases, the disclosed methods and systems extract contaminants, for example arsenic, from an ore containing solution at moderately increased temperature, pressure, and oxygen concentration, and in the presence of an acid.

The disclosed compositions, methods, and system involve low temperature, low pressure controlled oxygen addition for separation of copper and arsenic. The disclosure provides for the transition of enargite to covellite along with the copper mass balance indicating copper increases in the solid. The process and systems use moderate temperature and pressure with controlled oxygen addition for the separation of copper and arsenic. In some embodiments, the process provides for a transition of enargite to covellite along with the copper mass balance indicate copper increased in the solid and arsenic was leached, reducing the arsenic content in the concentrate. Disclosed compositions include an upgraded copper concentrate that may contain precious metals, and a stabilized arsenic precipitate for disposal. The disclosed processes and systems may be used on copper sulfide orebodies and concentrates containing significant arsenic. The disclosed processes and systems provide for advantages over existing technologies including reducing the arsenic penalty at a smelter, operating at lower temperature and possibly lower oxygen pressure or oxygen consumption.

Previous industrial methods have employed sulfuric acid-oxygen pressure leaching, alkaline sulfide leaching, and roasting. The disclosed approach may include evaluating the chemical reactions taking place and the effects of pressure, temperature, pH and redox potential on the fate of the minerals present in the concentrates as well as creating a fundamental understanding of the thermodynamics, kinetics and mineralogy aspects of the system. Applicants disclose the development and confirmation of an innovative, alternative approach to selectively upgrade enargite concentrates to recover the copper, gold and silver values while selectively leaching the arsenic. Also described are thermodynamic, kinetic and optimization studies of the disclosed method utilizing a bench scale batch autoclave. In these studies, enargite concentrate minerals were characterized before and after the experiments to determine any changes in mineralogy, composition and morphology. In one embodiment, the disclosed pressure oxidation process resulted in arsenic extraction of up to 47%. Mineralogically, the leached residues showed higher pyrite content than the feed sample by 6.5-15 weight percent with a slight decrease in the enargite content. Iron content increased in the solid leach residues by 1-3 weight percent, copper decreased slightly by 1-3 weight percent, and arsenic decreased about 1.5 weight percent. There was an apparent change and qualitative increase in copper mineral phases other than enargite indicating a possible separation of arsenic from copper. For example, in PDX Test #33 with the highest arsenic extraction, the copper mass balance gain in the solids was about 12.5%, which would increase the amount paid for copper from the concentrate sent to the smelter. In summary, the propensity for moderate temperature selective pressure oxidation for separation of arsenic from enargite appears to be promising.

2.1 Background of Copper

The name copper comes from the Latin cuprum, from the island of Cyprus and is abbreviated as Cu. The discovery of copper dates from prehistoric times and is said to have been mined for more than 5000 years. It is one of the most important metals used by man (Haynes and Lide 2011).

Metallic copper will occur occasionally in nature so it was known to man about 10,000 B.C. It has been used for many things including jewelry, utensils, tools and weapons. Use increased gradually over the years and in the 20^th century with electricity it grew dramatically and continues today with China's industrialization (Schlesinger et al. 2011).

FIG. 2.1 below shows the dramatic increase in the world production of copper since 1900, and FIG. 2.2: shows Goldman Sachs copper supply/demand balance (“Europe: Metals & Mining: Base Metals” 2012).

A comparison of world supply and demand of copper is presented below since 2006 and estimated through 2016, which was compiled by Goldman Sachs Global Investment Group.

TABLE 2.1
Goldman Sachs Copper Supply/Demand Balance
(“Europe: Metals & Mining: Base Metals” 2012)
Refined copper supply/
demand balance (kt)	2006	2007	2008	2009	2010	2011	2012E
Consumption
Developmed Markets	9,391	9,067	8,475	6,967	7,426	7,321	7,219
China	3,606	4,777	5,050	6,373	7,200	7,628	8,048
Other Emerging Markets	3,970	4,176	4,270	3,578	3,926	4,151	4,151
Total global consumption	16,967	18,020	17,795	16,918	18,552	19,100	19,589
% change y/y	1.9%	6.2%	−1.3%	−4.9%	9.7%	3.0%	2.5%
Production
Mine production	15,167	15,699	15,680	15,994	16,117	15,841	16.584
% change y/y	1.3%	3.5%	−0.1%	2.0%	0.8%	−1.7%	4.7%
Total refined copper production	17,232	17,853	18,116	18,141	18,778	18,845	19,516
% change y/y	4.6%	3.6%	1.5%	0.1%	3.5%	0.4%	3.6%
Global Balance-surplus/(deficit)	265	(167)	321	1,223	226	(255)	(70)
Total reported inventory	592	565	713	978	864	867	797
Reported stocks (days consumption)	12.7	11.4	14.6	21.1	17.0	16.6	14.8
Price forecast
US$/t	6,735	7,139	6,957	5,145	7,532	8,829	8,378
USc/lb	306	324	316	233	342	400	380
Refined copper supply/					CAGRs
demand balance (kt)	2013E	2014E	2015E	2016E	′11-′16	′06-′11
Consumption
Developmed Markets	7,441	7,636	7,753	7,842	1.4%	−4.9%
China	8,651	9,257	9,905	10,598	6.8%	16.2%
Other Emerging Markets	4,574	4,810	5,060	5,353	5.2%	0.9%
Total Global Consumption	20,666	21,703	22,718	23,793	4.5%	2.4%
% change y/y	5.5%	5.0%	4.7%	4.7%
Production
Mine production	17,714	18,647	19,235	20,046	4.8%	0.9%
% change y/y	6.8%	5.3%	3.2%	4.2%
Total refined copper production	20,838	21,934	22,724	23,732	4.7%	1.8%
% change y/y	6.8%	5.3%	3.6%	4.4%
Global Balance-surplus/(deficit)	171	231	6	(61)
Total reported inventory	969	1199	1205	1144
Reported stocks (days consumption)	17.1	20.2	19.4	17.6
					Long-term
Price forecast					(2017$ nominal)
US$/t	7,496	7,606	7,716	7,937	7,000
USc/lb	340	345	350	360	318

2.1.1 Sources of Copper

Copper occasionally occurs in its native form and is found in many minerals such as cuprite, malachite, azurite, chalcopyrite and bornite. Large copper ore deposits are found in the U.S., Chile, Zambia, Zaire, Peru and Canada. The most important copper ores are the sulfides, oxides and carbonates (Haynes and Lide 2011).

World copper mine production is primarily in the western mountain (Andes) region of South America. The remaining production is scattered around the world (Schlesinger et al. 2011).

The primary copper smelters of the world in 2010 compared to those in 2002 are shown in the FIGS. 2.3 and 2.4.

2.1.2 Properties of Copper

Copper has an atomic number of 29 on the periodic table with an atomic weight of 63.546 grams/mole. It has a freezing point of 1084.62° C. and a boiling point of 2562° C. The specific gravity of copper is 8.96 at 20° C., a valence of +1 or +2, atomic radius of 128 pm and an electronegativity of 1.90. Copper is reddish colored, takes on a bright metallic luster, and is malleable, ductile, and a good conductor of heat and electricity, second only to silver in electrical conductivity. It is soluble in nitric acid and hot sulfuric acid. Natural copper contains two isotopes. Twenty-six other radioactive isotopes and isomers are known (Haynes and Lide 2011; Perry and Green 2008).

2.1.3 Applications of Copper

The electrical industry is one of the greatest users of copper. Its alloys, brass and bronze have been used for a long time and are still very important. All American coins are now copper alloys, and monel and gun alloys also contain copper. The most important compounds are the oxide and the sulfate, blue vitriol. Blue vitriol has wide use as an agricultural poison and as an algicide in water purification. Copper compounds such as Fehling's solution are widely used in analytical chemistry in tests for sugar. High-purity copper (99.999+%) is readily available commercially. The price of commercial copper has fluctuated widely (Haynes and Lide 2011). The average price of LME high-grade copper in 2011 was $4.00 per pound (Edelstein 2012). Shown in FIG. 2.5 is the historical copper price.

2.2 Background to Copper Ore Processing and Copper Extraction

Copper minerals are approximately 0.5 to 2% Cu in the ore and as a result, are not eligible for direct smelting from an economic perspective. Ores that will be treated pyrometallurgically are usually concentrated resulting in a sulfide concentrate containing approximately 30% copper prior to smelting. By comparison, ores treated hydrometallurgically are not commonly concentrated since copper is usually extracted by leaching ore that has only been blasted or crushed.

Most of the copper present in the earth's crust exists as copper-iron-sulfides and copper sulfide minerals such as chalcopyrite (CuFeS₂), bornite (Cu₅FeS₄) and chalcocite (Cu₂S). Copper also occurs in oxidized minerals as carbonates, oxides, hydroxy-silicates, and sulfates, but to a lesser extent. Copper metal is usually produced from these oxidized minerals by hydrometallurgical methods such as heap or dump leaching, solvent extraction and electrowinning. Hydrometallurgy is also used to produce copper metal from chalcocite, Cu₂S, oxides, silicates and carbonates.

Another major source of copper is from scrap copper alloys. Production of copper from recycled used objects is 10 or 15% of mine production. In addition, there is considerable re-melting/re-refining of scrap generated during fabrication and manufacture.

A majority of the world's copper-from-ore originates in Cu—Fe—S ores. Cu—Fe—S minerals are not easily dissolved by aqueous solutions by leaching, so most copper extraction from these minerals is pyrometallurgical. The extraction entails:

• • (a) isolating an ore's Cu—Fe—S(and Cu—S) mineral particles into a concentrate by froth flotation
  • (b) smelting this concentrate to molten high-Cu matte
  • (c) converting the molten matte to impure molten copper
  • (d) fire- and electrorefining this impure copper to ultra-pure copper.

The objective of the smelting is to oxidize S and Fe from the Cu—Fe—S concentrate to produce a Cu-enriched molten sulfide phase (matte). The oxidant is commonly oxygen-enriched air.

Example reactions for smelting are:

2CuFeS₂+13/4O₂→Cu₂S.½FeS+3/2FeO+5/2SO₂  (2.1)

2FeO+SiO₂→2FeO.SiO₂  (2.2)

The enthalpies of the reactions above, respectively are:

$\begin{array}{cc}\Delta H_{25°C.}^0=-450\frac{\mathrm{MJ}}{\mathrm{kg}\mathrm{mol}{\mathrm{CuFeS}}_2}\mathrm{and}& \left(2.3\right)\\ \Delta H_{25°C.}^0=-20\frac{\mathrm{MJ}}{\mathrm{kg}\mathrm{mol}\mathrm{FeO}}.& \left(2.4\right)\end{array}$

SO₂-bearing offgas (10-60% SO₂) is also generated during smelting and is harmful to the environment so it should be removed before the offgas is released to the atmosphere. This is commonly done by capturing the SO₂ as sulfuric acid.

Many anode impurities from electrorefining are insoluble in the electrolyte such as gold, lead, platinum metals and tin so they are collected as ‘slimes’ and treated for Cu and byproduct recovery. Other impurities such as arsenic, bismuth, iron, nickel and antimony are partially or fully soluble. They do not plate with the copper though at the low voltage of the electrorefining cell. They should be kept from accumulating in the electrolyte to avoid physical contamination of the copper cathode by continuously bleeding part of the electrolyte through a purification circuit (Davenport et al. 2002).

As mentioned before, most of copper from ore is obtained by flotation, smelting and refining. The rest is obtained though hydrometallurgical extraction by:

• • (a) sulfuric acid leaching of copper from broken or crushed ore in heaps, stockpiles, vats, agitated tanks or under pressure to produce Cu-bearing aqueous solution
  • (b) transfer of Cu from this solution to pure, high-Cu electrolyte via solvent extraction, if necessary
  • (c) electrowinning pure cathode copper from this pure electrolyte.

Ores most commonly treated this way include ‘oxide’ copper minerals such as carbonates, hydroxy-silicates, sulfates and hydroxy-chlorides and chalcocite, Cu₂S.

The leaching is performed by sprinkling dilute sulfuric acid on top of heaps of broken or crushed ore with a lower copper content than that which is concentrated and sent to smelting. The acid trickles through the heap to collection ponds over several months.

Oxidized minerals are rapidly dissolved by sulfuric acid by reactions like:

CuO+H₂SO₄→Cu²⁺+SO₄²⁻+H₂O.  (2.5)

Sulfide minerals, on the other hand, require oxidation:

Cu₂S+5/2O₂+H₂SO₄→2Cu²⁺+2SO₄²⁻+H₂O.  (2.6)

The copper in electrowinning electrolytes is recovered by plating pure metallic cathode copper. Pure metallic copper with less than 20 ppm undesirable impurities is produced at the cathode and gaseous O₂ at the anode (Davenport et al. 2002).

As well, concentrates comprised of chalcopyrite and enargite can be treated by sulfidation with elemental sulfur at 350-400° C. to transform the chalcopyrite to covellite and pyrite without transforming the enargite by:

CuFeS₂(s)+Cu₃AsS₄(s)+½S₂(g)→CuS(s)+FeS₂(s)+Cu₃AsS₄(s).  (2.7)

The results of this work showed that temperature had the largest effect on the dissolution rate of copper and arsenic (Padilla, Vega, and Ruiz 2007).

2.2.1 Other Hydrometallurgical Extraction Processes

Pressure oxidation provides another process option when smelting and refining costs are high and variable, smelting capacity is limited and provides a better economic alternative to installing new smelting capacity. When kinetics in a heap leach are too slow, the elevated temperature and pressure affect both the thermodynamics and kinetics of leaching (Schlesinger et al. 2011). These processes are discussed further in Section 2.3.

2.2.2 Copper Metathesis

The leaching of Cu—Ni—Co mattes from pyrometallurgical operations is performed by four processes: metathetic leaching; sulfuric oxidative leaching; hydrochloric chlorine leaching (ClH+Cl₂); and ammoniacal oxidative leaching. They allow selective dissolution of nickel sulfide.

Metathetic leaching is represented by the reaction:

MeS(s)+CuSO₄→MeSO₄+CuS(s)↑  (2.8)

The driving force for this reaction is the lower solubility of copper sulfide.

This process is used as the first stage of the processing of the INCO's pressure carbonyl residue. The residue is leached at an elevated temperature while under pressure with sulfuric acid and copper sulfate. The sulfides and Ni, Co, Fe metals are dissolved by the metathetic reaction and the cementation reactions. The Cu₂S passes through this leaching step unchanged (Vignes 2011).

The ability of nickel-copper matte to precipitate Cu²⁺ ions is well known. The general consensus in the modern literature is on the overall reaction (metathesis):

Ni₃S₂+2Cu²⁺→Cu₂S+NiS+2Ni²⁺.  (2.9)

The reaction proceeds when hydrogen ions are present and accelerate with increasing acid concentration. The generally accepted reaction is:

Ni₃S₂+2H⁺+0.5O₂→2NiS+Ni²⁺+H₂O.  (2.10)

Work carried out at Sherritt Gordon has indicated that the reaction above proceeds stepwise:

3Ni₃S₂+4H⁺+O₂→Ni₇S₆+2Ni²⁺+H₂O  (2.11)

Ni₇S₆+2H⁺+0.5O₂→6NiS+Ni²⁺+H₂O.  (2.12)

Ferrous ion is released into solution and is rapidly reduced to the ferrous state and assumed to act as an electron carrier and enhance the leaching rate:

Copper metathesis ceases at a pH of about 2.5. At pH values above 2-2.5 the reactions of iron dissolution and its reduction to the ferrous state appear to cease and the ferrous ion is oxidized to the ferric ion by the oxygen in air:

2Fe²⁺+2H⁺+0.5O₂→2Fe³⁺+H₂O  (2.15)

The ferric ion becomes unstable above a pH of 3.5 and begins to hydrolyze to ferric hydroxide or basic ferric sulfate:

Fe³⁺+3H₂O→Fe(OH)₃+H⁺  (2.16)

Fe³⁺+HSO₄⁻+H₂O→Fe(OH)SO₄+2H⁺  (2.17)

Under normal operating conditions iron hydrolysis is completed at a pH of 4.5-5 and the residual iron in solution is generally below 10 mg/l. At a residual iron concentration in solution below 0.1 g/l, the pH rises above the stability of the cupric ion, which hydrolyzes to form basic cupric sulfate Cu₃(OH)₄SO₄:

3Cu²⁺+HSO₄⁻+4H₂O→Cu₃(OH)₄SO₄+5H⁺  (2.18)

The reaction releases acid into solution, which is consumed by the unreacted Ni₃S₂ or Ni₇S₆. Good aeration is required to promote hydrogen ion removal and shift the equilibrium in favor of precipitation.

At a residual copper concentration in solution below 0.05 g/l, hydrogen ion production by hydrolysis becomes slower than its removal, and the pH rapidly rises to maximum of 6.5-6.7. At this pH, basic nickel sulfates may start to precipitate (Hofirek and Kerfoot 1992).

2.3 Background of Pressure Hydrometallurgy

Habashi divides pressure hydrometallurgy into two areas: leaching and precipitation. Pressure leaching has been used commercially both in the absence of oxygen and in the presence of oxygen and applied in the copper industry. These leaching processes involve removing the metal through oxidation as an ion in solution. Precipitation described by Habashi is a reduction process. He describes the developments of pressure hydrometallurgy in detail as shown in the table below (Habashi 2004).

TABLE 2.2
Historical Developments in Pressure Hydrometallurgy (Habashi 2004)
Type	Year		Location	Reaction
Precipitation	1859	Nikolai N. Beketoff	France	2Ag+ + H2 → 2Ag + 2H+
	1900	Vladimir N. Ipatieff	Russia	M2+ + H2 → M + 2H+
	1903	G.D. Van Arsdale	USA	Cu2+ + SO2 + 2H2 →
			Cu + 4H+ + SO42−
	1909	A. Jumau	France	CuSO4 + (NH4)2SO3 + 2NH3 +
			H2O → Cu + 2(NH4)2SO4
	1952	H.A. Pray, et al.	USA	Solubility of hydrogen in water
			at high temperature and
			pressure
	1952	CHEMICO/Howe	USA	Ni3+ + H2 → Ni + 2H+
		Sound, National Lead		Co2+ + H2 → Co + 2H+
			Cu2+ + H2 → Cu + 2H+
	1952	CHEMICO/Freeport	USA	Ni2+ + H2S → NiS + 2H+
			Co2+ + H2S → CoS + 2H+
	1955	Sherritt-Gordon	Canada	[Ni(NH3)2]2+ + H2 →
			Ni + 2NH4+
	1960	Bunker Hill	USA	PbS + 2O2 → PbSO4
			ZnS + 2O2 → ZnSO4
	1970	Benilite	USA	FeTiO3 + 2HCl →
			FeCl2 + TiO2 + H2O
	1970	Anaconda	USA	Cu2SO3 · (NH4)2SO3 →
			2Cu + SO2 + 2NH4+ + SO42−
Leaching	1892	Karl Josef Bayer	Russia	Al(OH)3 + OH− →
			[Al(OH)4]−
	1903	M. Malzac	France	MS + 2O2 + nNH3 →
				[M(NH3)n]3+ + SO42−
	1927	F.A. Henglein	Germany	ZnS + 2O2 → Zn2+ + SO42−
	1940	Mines Branch	Canada	UO3 + 3CO32− + ⅓O2 + H2O →
				[UO2(CO3)3]4− + 2OH−
	1952	H.A. Pray, et al.	USA	Solubility of hydrogen in water
			at high temperature and
			pressure
	1952	CHEMICO/Calera	USA	CoAsS + 7/3O2 + H2O →
			Co3+ + SO42− + AsO45− + 2H+
	1952	CHEMICO/Freeport	USA	NiO (in laterite) + H2SO4 →
		Nickel		NiSO4 + H2O
	1955	Sherritt-Gordon	Canada	NiS + 2O2 + 2NH3 →
			[Ni(NH3)2]2+ + SO42−
	1975	Gold industry	World-	2FeS2 + 7½O2 + 4H2O →
		wide	Fe2O3 + 4SO43− + 8H+
	1980	Sherritt-Gordon	Canada	ZnS + 2H+ + ½O2 →
			ZN2+ + S + H3O
	2004	Phelps Dodge	USA	4CuFeS2 + 17O2 + 4H2O →
			4CuSO4 + 2Fe2O3 + 4H2SO4

2.3.1 Copper Concentrate Pressure Oxidation and Leaching

Chalcopyrite (CuFeS₂) is the most abundant of the copper sulfides and the most stable because of its structural configuration having a face-centered tetragonal lattice, as a result it is very refractory to hydrometallurgical processing. Recovery of copper from chalcopyrite involves froth flotation that produces a concentrate of the valuable metal sulfides which is smelted and electrorefined to produce copper. Treating chalcopyrite concentrates hydrometallurgically has received increasing attention over the last several decades.

The many different processing options are discussed in the following sections.

2.3.2 Acidic Pressure Oxidation

Freeport-McMoRan Copper & Gold has developed a sulfate-based pressure leaching technology for the treatment of copper sulfide concentrates. The main drivers for the activity were the relatively high and variable cost of external smelting and refining capacity, the limited availability of smelting and refining capacity and the need to cost-effectively generate sulfuric acid at mine sites for use in stockpile leaching operations. Freeport was looking to treat chalcopyrite concentrates with this technology. FMI developed both high and medium temperature processes. The following chemistry provides detail on chalcopyrite oxidation in the presence of free acid at medium temperatures, meaning above 119° C. and below 200° C., showing that some of the sulfide sulfur is converted to molten elemental sulfur:

4CuFeS₂+5O₂+4H₂SO₄→4Cu²⁺+4SO₄²⁻+2Fe₂O₃+8S⁰+4H₂O  (2.19)

but, under these conditions, oxidation may also occur by:

4CuFeS₂+17O₂+2H₂SO₄→4Cu²⁺+10SO₄²⁻+4Fe³⁺+2H₂O.  (2.20)

It should be noted that the first reaction consumes approximately 70% less oxygen per mole of chalcopyrite oxidized that the latter but the second reaction requires less acid. Pressure leaching sulfide minerals at temperatures above the melting point of sulfur at 119° C., but below 200° C., is complicated by the relationship between sulfur viscosity and temperature, which can be seen in the figure in FIG. 2.6.The sulfur tends to wet sulfide surfaces and may agglomerate to form “prills” (J. O. Marsden, Wilmot, and Hazen 2007a).

Work has also been performed by Anaconda Copper Company on ores from the Butte, Mont. area to evaluate the possibility of converting chalcopyrite to digenite at about 200° C. to upgrade and clean the concentrate to the point where it could be shipped as a feed to a copper smelter. They showed that this reaction is possible and a significant amount of the iron and arsenic (along with other impurities) were removed from the solid product while retaining the majority of the copper, gold and silver in the concentrate. The upgrading process also results in lower mass of concentrate to ship thereby decreases shipping costs. Primarily, the process consists of chemical enrichment that releases iron and sulfur from the chalcopyrite, followed by solid-liquid separation with treatment of the liquid effluent. This is followed by flotation with recycle of the middling product back to the enrichment process and rejection of the tailing. The resultant product is digenite formed as a reaction product layer around the shrinking core of each chalcopyrite grain by the following reaction:

1.8CuFeS₂+0.8H₂O+4.8O₂=Cu_1.8S+1.8FeSO₄+0.8H₂SO₄.  (2.21)

In this work, about 80% of the zinc impurities reported to the liquor while arsenic, bismuth and antimony were evenly distributed between the discharge liquor and the enriched product. Gold, silver and selenium followed the copper. (Bartlett et al. 1986; Bartlett 1992). This cleaned concentrate may also be utilized in a cyanidation-SART type process. It may also be possible to perform a similar process on enargite concentrates at lower pressure and using less acid.

2.4 Alkaline Sulfide Leaching

Other work has indicated that leaching with sodium sulfide in 0.25 molar NaOH at 80-105° C. will dissolve sulfides of arsenic, antimony and mercury. Enargite is solubilized by the following reaction (Nadkarni and Kusik 1988; C. G. Anderson 2005; C. Anderson and Twidwell 2008):

2Cu₃AsS₄+3Na₂S=2Na₃AsS₄+3Cu₂S.  (2.22)

In the case of gold-bearing enargite concentrates, leaching with basic Na₂S has been shown to selectively solubilize the arsenic and some gold but does not affect the copper. The copper is transformed in the leach residue to a species Cu_1.5S and the gold is partly solubilized in the form of various anionic Au—S complexes. The gold and arsenic could then be recovered from solution (Curreli et al. 2009).

2.5 Example Copper Hydrometallurgical Processes

Many processes have been developed over the last few decades for the hydrometallurgical extraction of copper from chalcopyrite. Processes using various lixiviants, including ammonia, chloride, chloride-enhanced, alkaline sulfide leaching, nitrogen species catalyzed pressure leaching and sulfate have been receiving attention and are discussed below. Problems with these processes for chalcopyrite include how to overcome a passivating sulfur layer forming on the mineral surfaces during leaching and how to deal with excess sulfuric acid or elemental sulfur production (Wang 2005).

2.5.1 Ammonia

Ammonia leaching was first applied at Kennecott, Ak. in 1916 on gravity concentration tailings of a carbonate ore and on gravity tailings from a native copper ore at Calumet and Hecla, Mich. By driving off the ammonia through steaming, both recovered copper oxide (Arbiter and Fletcher 1994). The Anaconda Arbiter Process, which has been shut down, and the Sherritt Gordon process treat concentrates using low pressure and temperature, but are expensive. Flowsheets for both processes are shown in FIG. 2.7.

The Anaconda Arbiter Process leached using ammonia in vessels at 5 psig with oxygen to dissolve copper from sulfide concentrates which is concentrated and then purified using ion exchange and is then electrowon (Chase and Sehlitt 1980).

Sherritt Gordon developed two potential processes which were successfully piloted at Fort Saskatchewan. One, shown in FIG. 2.8, was based on ammoniacal pressure oxidation leaching, followed by recovery of the copper as powder from solution using hydrogen with byproduct ammonium sulfate. The second process leached used sulphuric acid oxidation and produces elemental sulphur as a byproduct (Chalkley et al.).

2.5.2 Chloride

Using a chloride system provides the possibility of a direct leach at atmospheric pressure and recovery of sulfur, gold and PGMs. Many metal chlorides are considerably more soluble than their sulfate salts allowing the use of more concentrated solutions and there can be effective recycling of leachant. Electrowinning can be performed in diaphragm cells theoretically requiring less energy but with low copper recovery.

Typically chlorides of metals in a higher valence state, such as ferric or cupric chloride, will leach metals from their sulfides because oxidation is necessary. Of the many chloride routes, ferric chloride (FeCl₃) leaching of chalcopyrite concentrates received significant attention. The processes developed by Duval Corporation (CLEAR), Imperial Chemical Industries, Technicas Reunidas and the Nerco Minerals Company (Cuprex), Cyprus Metallurgical Processes Corporation (Cymet), as well as Intec Limited (Intec) and Outotec (HydroCopper) have demonstrated significant potential for the production of copper by the chloride leaching process (Wang 2005).

Acidified cupric chloride-bearing brine solutions have been used as a leachant for copper sulfides, complex metal sulfides, and metal scraps. A flow chart is shown in FIG. 2.9.

This process is based on four basic steps. The first is leaching at 105° C. and ambient pressure to dissolve copper and iron:

CuFeS₂+3Cu²⁺→4Cu⁺+Fe²⁺+2S  (2.1)

The second is treatment of the residue for elemental sulfur recovery and purification of leach liquor by precipitating impurity elements as hydroxides. The third step is electrolysis in a diaphragm cell to deposit copper from the cathode and regenerate the leachant in the anolyte. The fourth and final step is recycling of the anolyte as a leaching agent. Success is highly dependent on achieving a high leaching efficiency with minimum reagent consumption and conversion of most of the cupric chloride to cuprous chloride (Gupta and Mukherjee 1990).

The principal chemical reactions in the ferric chloride leaching of chalcopyrite concentrate are shown below.

CuFeS₂+3FeCl₃→CuCl+4FeCl₂+2S⁰  (2.2)

CuFeS₂+4FeCl₂→CuCl₂+5FeCl₂+2S⁰  (2.3)

The corresponding reactions for CuCl₂ attack are shown below.

CuFeS₂+3CuCl₂→4CuCl+FeCl₂+2S⁰  (2.4)

S⁰+4H₂O+6CuCl₂→6CuCl+6HCl+H₂SO₄  (2.5)

The Intec process involves a four-stage countercurrent leach with chloride/bromide solution at atmospheric pressure. Leach residue is filtered and discharged from stage 4 to waste, while copper-rich pregnant liquor leaves stage 1. Gold and silver are solubilized along with copper. Gold is recovered from solution through a carbon filter, and silver is cemented along with mercury ions to form an amalgam. Both of these are then further treated. Impurities in the liquor are precipitated with lime and removed by filtration. The purified copper solution is electrowon to produce pure copper metal and to regenerate the solution for recycling in leaching. An extremely important feature of the process is that heat is provided by the exothermic leach reactions. This, along with the flow of air in leaching, evaporates water and keeps the water balance close to neutral so no liquid effluent is produced from the plant. Another equally important note is that all impurities including mercury are either recovered or stabilized (Wang 2005).

The chloride/bromide chemistry in the Intec process provides a strong oxidant at nearly ambient (85° C., atmospheric pressure) conditions. This process for has been run at demonstration plant scale for copper. The Intec process flowsheet is shown in FIG. 2.10 (Milbourne et al. 2003).

The CLEAR process was developed by Duval Corporation as a new approach to copper sulfide concentrate processing. CLEAR is an acronym for the processing steps—Copper Leach Electrolysis And Regeneration. It is designed to solubilize copper in a recycling chloride solution; to electrolytically deposit metallic copper with any associated silver; to discharge a residue of elemental sulfur, iron and all else associated with the copper minerals and to do so without solid, liquid or gaseous pollution. The aqueous solutions of certain metal chloride salts will chemically attack most metal sulfides taking into solution the metals and leaving behind a residue of elemental sulfur. CLEAR has the capability of completely leaching copper and silver values from copper concentrate consisting of any combination of copper sulfide and/or copper-iron-sulfide mineralization. A process flowsheet is shown in FIG. 2.11 (Atwood and Livingston 1980).

The Cuprex process leaches chalcopyrite concentrate at atmospheric pressure with ferric chloride solution in two stages. The pregnant liquor containing copper, iron, and minor impurities, mainly zinc, lead, and silver, is sent to the extraction stage of the SX circuit. The copper is selectively transferred to the organic phase and the aqueous solution of copper chloride is then sent to the electrolysis section as catholyte, which is fed to the cathode compartment of an EW cell to produce granular copper. Electrowinning of copper from takes place in a diaphragm cell. Chlorine generated at the anode is recovered and used to reoxidize the cuprous chloride generated in the catholyte during EW (Wang 2005).

The Cyprus Copper Process, or Cymet, converts copper concentrates into copper metal. Copper concentrates are dissolved in a ferric chloride—copper chloride solution in a countercurrent two-stage leach as shown in the flowsheet in FIG. 2.12.

The pregnant solution from the first leach is high in cuprous ion concentration. This solution is cooled and cuprous chloride crystals are precipitated. These crystals are washed, dried and fed to a fluid-bed reactor, where hydrogen reduction takes place. Copper nodules are produced which are suitable for melting, fire-refining and casting into wirebars. The fluidized bed also produces HCl, which is recycled to the wet end of the process where it is mixed with the mother liquor from the crystallizer, reacted with oxygen to regerate ferric and cupric lixiviant, and recycled to the leaching section (McNamara, Ahrens, and Franek 1978).

The Outotec HydroCopper process involves countercurrent leaching of chalcopyrite concentrates using air and chlorine as oxidants as shown below.

CuFeS₂+CuCl₂+¾O₂→2CuCl+½Fe₂O₃+2S  (2.6)

After leaching, the cuprous bearing solution is oxidized by chlorine to cupric that is recycled back in leaching as shown below.

CuCl+½Cl₂→2CuCl₂  (2.7)

The remaining cuprous solution, after purification for silver and impurity removal is treated with sodium hydroxide to precipitate cuprous oxide that is then reduced to metal. The process produces, in a standard chloro-alkali cell, and provides all of the chlorine, sodium hydroxide, and hydrogen needed to operate as shown below (Wang 2005).

CuCl+NaOH→½Cu₂O+NaCl+½H₂O  (2.8)

½Cu₂O+½H₂→Cu+½H₂O  (2.9)

2NaCl+2H₂O→2NaOH+Cl₂+H₂  (2.10)

A process flowsheet for the process is shown in FIG. 2.13.

2.5.3 Chloride-Enhanced

Chloride-enhanced processes use chlorine to enhance leaching in another medium. The process should be able to tolerate the chlorine in the system but none have been demonstrated commercially long term.

The Activox process, depicted in FIG. 2.14, is a mild pressure leaching process employing fine grinding (P80 5-15 micron, 100-110° C., 1000 kPa oxygen). This process has been demonstrated at the continuous pilot plant level (Milbourne et al. 2003). The process uses 4 g/L addition of chlorides as sodium chloride salt solution (Palmer and Johnson 2005).

The CESL process is a low-severity pressure oxidation process where a high portion of sulfide sulfur remains in the elemental form in the leach residue. The process also employs a chloride-enhanced oxidative pressure leach in a controlled amount of acid to convert the copper to a basic copper sulfate salt, the iron to hematite, and the sulfur to elemental sulfur. The CESL process is composed of two leaching stages. First is a pressure oxidation leach and leaching residue is fed to the second atmospheric leach mainly by the reactions shown below.

3CuFeS₄+7.5O₂+H₂O+H₂SO₄→  (2.11)

CuSO₄.2Cu(OH)₂+1.5Fe₂O₃+6S

CuSO₄.2Cu(OH)_2(s)+2H₂SO₄→3CuSO_4(aq)+4H₂O  (2.12)

Part of the first leach solution is recycled into the autoclave while the rest is mixed with the second leach solution and fed to SX. After SX, stripping, and EW, the process produces high-quality copper cathodes (Wang 2005). The process flowsheet is shown in FIG. 2.15.CESL has patented a process for the recovery of gold from the leach residue, which includes the following steps:

• • removal of elemental sulfur using a hot perchloroethylene (PCE) leach,
  • total oxidation of the remaining sulfides to release refractory gold,
  • neutralization, and
  • cyanide leaching of the solids for gold recovery.This process has been extensively tested for copper at demonstration plant scale, but not for copper-nickel (Milbourne et al. 2003).

2.5.4 Nitric/Sulfuric Acid

The Sunshine plant used nitrogen species catalyzed (NSC) sulfuric acid where copper was produced by SX-EW, silver recovered by precipitation as silver chloride, then reduced to silver metal. It offers a non-cyanide approach for gold recovery as well.

In the NSC process, a sulfate leach system is augmented with 2 g/L sodium nitrite. Both total and partial oxidation processes have been proposed. It operates with mild conditions of 125° C., 400 kPa total pressure. The partial oxidation process was commercialized as a batch operation at the Sunshine Mine in Idaho on chalcocite-tetrahedrite minerals (Milbourne et al. 2003). FIG. 2.16 shows a NSC process flowsheet from Sunshine (Ackerman and Bucans 1986).

2.5.5 Sulfate

Sulfate processes are well established for copper concentrates and ores but tend to require higher temperature and fine grinding. Final copper recovery is by SX-EW and precious metals can be recovered by cyanidation.

The Dynatec process involved oxidative leaching of chalcopyrite concentrate at 150° C. using coal at a modest dosage (25 kg/t of concentrate) as an effective anti-agglomerant. The sulfide oxidation chemistry is similar to the CESL process and produces elemental sufur in a sulfate medium. Coal is used as a source of surfactant for elemental sulfur dispersion. It is likely to dissolve less PGMs than the chloride-enhanced CESL process. A high extraction of copper (98+%) is achieved by either recycling the unreacted sulfide to the leach after flotation and removal of elemental sulfur by melting and filtration or pretreating the concentrates with a fine grinding of P90˜25 μm. This process, shown in FIG. 2.17 has been piloted but not demonstrated; its operating conditions have a good pedigree in zinc leaching (Wang 2005; Milbourne et al. 2003).

The Chelopech mine in Bulgaria proposed the use of PDX at 225° C. and pressure of 3,713 kPa. The autoclave discharge goes to a CCD circuit for solid-liquid separation, allowing subsequent treatment of the solution that contains copper, zinc and other base metals. The gold values are in the solid phase. Solution from the clarifier goes to solvent extraction then electrowinning for copper. Impurities such as arsenic, zinc, iron and others are removed in a separate circuit. The pressure oxidation is a pre-treatment for the ore which is then sent to a CIL circuit for gold recovery. The proposed process flowsheet is shown in FIG. 2.18.

The Mt. Gordon process is a whole ore, hot acid ferric leach process developed to treat chalcocite ores in Australia. It uses low temperature pressure oxidation to leach copper from the ore followed by SX/EW. Chalcocite is leached to form covellite, and then leached to form soluble copper and elemental sulfur. A total pressure of 7.7 bars and oxygen partial pressure of 4.2 bars are used in an autoclave with about 60 minutes of residence time (Dreisinger 2006; Arnold, Glen, and Richmond 2003) as depicted in FIG. 2.19.

Kansanshi, shown in FIG. 2.20, uses a high pressure leach (HPL) to treat copper concentrates in two autoclaves operating at 225° C. Using sulfuric acid and oxygen, chalcopyrite is oxidized to copper sulfate and ferric sulfate. The autoclave discharge is cooled and pumped to an oxide leach circuit where high temperature and ferric ion drive the leaching reaction. This is followed by SX/EW (Chadwick 2011).

The Albion, or Nenatech, shown in FIG. 2.21, process is another sulfate-based process employing fine grinding (10-15 micron) at mild conditions (85-90° C. atmospheric leach, 24 hours residence time). Oxygen and air sparging are used for oxidation. The process has been demonstrated at the continuous pilot plant level. Mount Isa Mines, the process owners, have said they wish to keep the technology internal for use in their own projects. A flowsheet is shown below (Milbourne et al. 2003).

The Sepon Copper Project in Laos is primarily a chalcocite ore. The autoclave circuit is designed to oxidize a high-grade pyrite concentrate to produce iron and acid. A flowsheet is shown in FIG. 2.22.

The Galvanox process is a galvanically-assisted atmospheric leach (˜80° C.) of chalcopyrite concentrates in a ferric/ferrous sulfate medium to extract copper. The process consumes approximately a stoichiometic amount of oxygen and generates mostly elemental sulfur. It operates below the melting point of sulfur to eliminate the need for surfactants. A flowsheet is shown in FIG. 2.23.

Phelps Dodge, now Freeport-McMoRan, constructed a concentrate leaching demonstration plant in Bagdad, Ariz. to demonstrate the viability of the total pressure oxidation process developed by Phelps Dodge and Placer Dome (J. O Marsden, Brewer, and Hazen 2003). It treats about 136 t/day of concentrate to produce about 16,000 t/y of copper cathode via conventional SX/EW. After 18 months of continuous operation, the Bagdad Concentrate Leach Plant has demonstrated that the high-temperature process is suitable for applications where the dilute acid can be used beneficially. Recently, PD has started its development of medium-temperature pressure leaching in sulfate media at 140-180° C. With its MT-DEW-SX process (Wilmot, Smith, and Brewer 2004), chalcopyrite concentrate is first super-finely ground and then pressure leached at medium temperature in an autoclave. After solid-liquid separation, the leach solution is directly electrowon to produce copper and the electrolyte, with a relatively low content of copper, is either recycled in the autoclave or mixed with stockpile returned leach solution and fed to SX. The SX raffinate is sent to stockpile leach and the stripped solution is then electrowon for final copper cathode production (Wang 2005). The subsequent commercial scale process flowsheet from Morenci is in FIG. 2.24.

2.5.6 Competing Technologies

One competing technology to copper pressure oxidation is Outotec's Partial Roasting Process. Outotec has developed a two-stage partial roasting process to remove impurities such as arsenic, antimony and carbon from copper and gold concentrates as a pre-treatment to actual extraction processes. They are currently building the world's largest arsenic-removing roasting furnace at Codelco's Mina Ministro Hales mine in Chile, which will use this process. More than 90% of the arsenic in the concentrate can be removed to produce clean copper calcine. Depending on the composition of the concentrate and the plant's capacity, the process can either be run in a stationary fluidized bed or in a circulating fluidized bed. The partial roasting process for copper concentrates is a single-stage roasting process. The impurities are volatilized and the process produces calcine, which is rich in copper sulfide but has a low impurity content. The calcine is mixed and can be further processed in copper smelters. The partial roasting process is also combined with post-combustion of process gas to convert all volatile compounds into oxides. The roasting process for refractory gold concentrates contaminated with arsenic and carbon is a two-stage process. Arsenic is removed in the first roasting stage while carbon and remaining sulfur are removed in the second stage. All sulfur, iron and carbon are fully oxidized in the process and calcine suitable for actual gold leaching is produced (“Outotec Launches a New Partial Roasting Process to Purify Contaminated Copper and Gold Concentrates” 2011).

2.6 Namibia Custom Smelter

The Namibia Custom Smelter (NCS), owned by Dundee Precious Metals, Inc. (DPM), is located in Tsumeb, Namibia which is approximately 430 km north of the capital, Windhoek. The smelter is one of only a few in the world able to treat arsenic and lead bearing copper concentrate. The Chelopech mine, also owned by DPM, sends their concentrate to be processed by this smelter. For the year of 2011, NCS processed 88,514 mt of Chelopech concentrate and 91, 889 mt of concentrate from third parties for a total of 180,403 mt.

Since acquiring NCS in 2010, DPM has embarked on an expansion and modernization program designed to bring the smelter into the 20^st century from a health, safety and environmental perspective. The first phase of the project is designed to address arsenic handling. They are expanding the Ausmelt furnace, a superior furnace from an environmental point of view, enabling them to perform all primary smelting through the Ausmelt, allowing the older reverbatory furnace to be used as a holding furnace. A new baghouse is also being installed and all the existing systems designed to manage the arsenic are being upgraded. When this phase is completed, expected in December of 2012, the smelter will be one of the most modern in the world with respect to the safe management and disposal of arsenic.

When the two phases of the project are completed, the specialty smelter at Tsumeb will be repositioned to be one of the most unique smelters in the world, with the ability to treat DPM and third party complex concentrates in a responsible and sustainable manner that meets Namibian as well as global health, safety and environmental standards.

In December 2011, an independent team of technical experts was retained by the Namibian Government to ensure that both the Government and DPM had properly identified the issues with respect to concerns raised regarding the disposal and management of arsenic in concentrate processed at NCS. The review was completed in January 2012 and the report is expected to be issued in the near future. They believe that the program of upgrades and improvements completed to date and scheduled over the coming years properly addresses the issues and concerns raised and that the report will support that view (“Annual Review 2011” 2012).

Chapter 3

Arsenic Processing and Fixation

3.1 Background of Arsenic

The name arsenic comes from the Latin arsenicum, Greek arsenikon, and yellow orpiment identified with arsenikos, meaning male, from the belief that metals were different sexes. Arabic Az-zernikh was the orpiment from Persian zerni-zar for gold. It is abbreviated as As and it is believed that Albert Magnus obtained arsenic as an element in 1250 A.D. In 1649 Shroeder published two methods of preparing the element (Haynes and Lide 2011).

3.1.1 Sources of Arsenic

Elemental arsenic occurs in two solid forms: yellow and gray or metallic. Several other allotropic forms of arsenic are reported in the literature. Arsenic is found in its native form, in the sulfides realgar and orpiment, as arsenides and sulfarsenides of heavy metals, as the oxide, and as arsenates. Mispickel, arsenopyrite, (FeSAs) is the most common mineral, from which on heating the arsenic sublimes leaving ferrous sulfide. (Haynes and Lide 2011).

3.1.2 Properties of Arsenic

Arsenic has an atomic number of 33 on the periodic table with an atomic weight of 74.92160 grams/mole. It can have a valence of −3, 0, +3, or +5. Yellow arsenic has a specific gravity of 1.97 while gray, or metallic, is 5.75. Gray arsenic is the ordinary stable form. It has a triple point of 817° C., sublimes at 616° C. and has a critical temperature of 1400° C. The element is a steel gray, very brittle, crystalline, semimetallic solid; it tarnishes in air, and when heated is rapidly oxidized to arsenous oxide (As₂O₃) with the odor of garlic. Arsenic and its compounds are poisonous. Exposure to arsenic and its compounds should not exceed 0.01 mg/m³ as elemental arsenic during an eight hour work day. Natural arsenic is made of one isotope ⁷⁵As. Thirty other radioactive isotopes and isomers are known (Haynes and Lide 2011).

3.1.3 Applications of Arsenic

Arsenic trioxide and arsenic metal have not been produced as primary mineral commodity forms in the United States since 1985. However, arsenic metal has been recycled from gallium-arsenide semiconductors. Owing to environmental concerns and a voluntary ban on the use of arsenic trioxide for the production of chromate copper arsenate wood preservatives at year end 2003, imports of arsenic trioxide averaged 6,100 tons annually during 2006-10 compared with imports of arsenic trioxide that averaged more than 20,000 tons annually during 2001-02. Ammunition used by the United States military was hardened by the addition of less than 1% arsenic metal, and the grids in lead-acid storage batteries were strengthened by the addition of arsenic metal. Arsenic metal was also used as an antifriction additive for bearings, to harden lead shot, and in clip-on wheel weights. Arsenic compounds were used in fertilizers, fireworks, herbicides, and insecticides. High-purity arsenic (99.9999%) was used by the electronics industry for allium-arsenide semiconductors that are used for solar cells, space research, and telecommunication. Arsenic was also used for germanium-arsenide-selenide specialty optical materials. Indium-gallium-arsenide was used for short-wave infrared technology. The value of arsenic compounds and metal consumed domestically in 2011 was estimated to be about $3 million (Brooks 2012).

Arsenic is used in bronzing, pyrotechny, and for hardening and improving the sphericity of shot. The most important compounds are white arsenic (As₂O₃), the sulfide, Paris green 3Cu(AsO₂)₂.Cu(C₂H₃O₂)₂, calcium arsenate, and lead arsenate. The last three have been used as agricultural insecticides and poisons. Marsh's test makes use of the formation and ready decomposition of arsine (AsH₃), which is used to detect low levels of arsenic, especially in cases of poisoning. Arsenic is available in high-purity form. It is finding increasing uses as a doping agent in solid-state devices such as transistors. Gallium arsenide is used as a laser material to convert electricity directly into coherent light. Arsenic (99%) costs about $75 for 50 grams. Purified arsenic (99.9995%) costs about $50 per gram (Haynes and Lide 2011).

3.2 Arsenic Extraction Processes

The removal of arsenic from process solutions and effluents has been practiced by the mineral industries for many years. Removal by existing hydrometallurgical techniques is adequate for present day product specifications but the stability of waste materials for long term disposal will not meet the regulatory requirements of the future. The aqueous inorganic chemistry of arsenic as it relates to the hydrometallurgical methods that have been applied commercially for arsenic removal, recovery, and disposal, as well as those techniques which have been used in the laboratory or otherwise suggested as a means of eliminating or recovering arsenic from solution. The various separation methods which are then referenced include: oxidation-reduction, adsorption, electrolysis, solvent extraction, ion exchange, membrane separation, precipitate flotation, ion flotation, and biological processes. The removal and disposal of arsenic from metallurgical process streams will become a greater problem as minerals with much higher arsenic content are being processed in the future.

It is mostly the arsenic sulfide minerals which cause impurity levels in hydrometallurgical processes. The main sulfide mineral to cause arsenic impurity problems in arsenopyrite, FeAsS, but in certain locations enargite, Cu₃AsS₄, tennantite, Cu₁₂As₄S₁₃, cobaltite, CoAsS, rammelsbergite, NiAs₂, skutterudite, (Co, Ni, Fe)As₃, safflorite, (Co, Fe)As₂, pararammelsbergite, NiAs₂, and seligmannite, PbCuAsS₃, are the major source.

After smelting of sulfides or in wholly hydrometallurgical treatment, arsenic appears in solution as either arsenic (iii) or arsenic (v) but occasionally as arsenic (-iii).

Speciation in uncomplexed solution is described most conveniently by means of the potential-pH diagram shown in FIG. 3.1

Oxidation-reduction reactions between arsenic (v) and arsenic (iii) is possible using sulfur dioxide or sulfite. On an industrial scale this process is used to precipitate arsenic trioxide from arsenic acid solutions as a commercial commodity. There appears to be little likelihood of applying more powerful reductants in hydrometallurgical processing due to the concern of producing arsine, AsH₃. Arsine gas is produced commercially, however, as an intermediate to pure arsenic metal for semiconductor use.

Arsenate complexes are very similar to those of phosphate, and there is a fairly extensive literature on the metal phosphate complexes which has been reviewed by Robins, Twidwell and Dahnke. A model for ferric arsenate complexing has been proposed by Khoe and Robins which has significant effect on free energies of formation which have been used previously to describe the solubility of ferric arsenate (FeAsO₄.2H₂O) a compound of low solubility which is used extensively for removing arsenate from hydrometallurgical process solutions (Robins 1988).

Arsenic can be leached specifically from enargite using various methods such as alkaline sulfide leaching, acidic sulfate and chloride media, acidified ferric sulfate, and others, which will be discussed in the next chapter.

3.3 Arsenic Fixation Processes

Because arsenic is most hazardous when mobile, it should be fixed as a solid precipitate to get it in a stable form for long-term storage. Two stable forms include ferrihydrite and scorodite which are discussed in the sections to follow.

3.3.1 Ferrihydrite

Ferrihydrite is a ferric oxyhydroxide precipitate that forms very small particles with a large surface area.

In treating hydrometallurgical solutions and waste streams for the removal of arsenic, the use of coprecipitation with Fe (III) has been specified by the US EPA as the Best Demonstrated Available Technology (BDAT). This technology has been widely adopted over the last century, and developments have been well reviewed (L. G. Twidwell, Robins, and Hohn 2005). This technology has also been selected as one of the Best Available Technologies (BAT) for removing arsenic from drinking waters (L. Twidwell and McCloskey 2011).

R. G. Robins was the first investigator to recognize and to alert the gold industry that arsenic storage as calcium arsenate was inappropriate. Twidwell & McCloskey have continued work until the present and a number of research summaries are available from the EPA Mine Waste Technology Program (MWTP), e.g. arsenic, arsenic & selenium cementation using elemental iron and catalyzed elemental iron, formation and stability of arsenatephosphate apatites, ferric and ferrous treatment of mine waters (Berkeley Pitlake and Acid Drainage mine water), ferrihydrite/arsenic co-precipitation and aluminum-modified-ferrihydrite (AMF)/arsenic treatment of waste water and long-term storage, influence of anion species on ferrihydrite/arsenic co-precipitation and long-term storage, and ferrihydrite/AMF/metals co-precipitation and long-term storage.

Twidwell quoted two other authors; one says arsenical ferrihydrite can be considered stable provided that: the Fe/As molar ratio is greater than 3, the pH is slightly acidic, and it does not come into contact with reducing substances such as reactive sulfides or reducing conditions such as deep water, bacteria or algae. Another author says that there is no clear experimental evidence that either process is better for safe disposal of arsenic. Local storage conditions will greatly affect stability of arsenic product. Some factors influencing arsenic removal include initial arsenic concentration, valence state, Fe/As mole ratio, presence of associated solution ions, structural modifications to ferrihydrite, mode of precipitation (co-precipitation, post-precipitation, adsorption), pH, temperature and time. To form ferrihydrite different reagents can be used; usually ferric nitrate, ferric chloride, and ferric sulfate. The adsorption capacity is related to the method of preparation (L. G. Twidwell, Robins, and Hohn 2005).

Important reviews detailing conditions for formation and the stability of ferrihydrite are presented by Schwertmann and Cornell, who have published a “recipe” book that presents details of how to prepare iron oxides in the laboratory, including ferrihydrite, hematite and goethite. Many of the experimental studies reported in the literature reference this publication (L. Twidwell and McCloskey 2011).

Two ferric precipitation arsenic removal technologies are presently practiced by industry: ambient temperature ferrihydrite/arsenic co-precipitation and elevated temperature precipitation of ferric arsenate. The ambient temperature technology is relatively simple and the presence of commonly associated metals such as copper, lead and zinc and gypsum have a stabilizing effect on the long term stability of the product. The disadvantages of the adsorption technology are the formation of voluminous waste material that is difficult to filter, the requirement that the arsenic be present in the fully oxidized state as arsenate, and the question as to long term stability of the product in the presence of reducing substances. The disadvantages of the ferric arsenate precipitation are that the treatment process is more capital intensive, the compound may dissolve incongruently if the pH is >4, and it may not be stable under reducing or anaerobic bacterial conditions (L. G. Twidwell, Robins, and Hohn 2005).

Ferrihydrite is characterized by x-ray diffraction as having a two-line or six-line structure, which relates to the number of broad peaks present. Two-line ferrihydrite is formed by rapid hydrolysis to pH 7 ambient temperature. Six-line ferrihydrite is formed by rapid hydrolysis at elevated temperature and is generally more crystalline than two-line ferrihydrite (L. Twidwell and McCloskey 2011). However, Schwertmann and Cornell have demonstrated that either can be formed at ambient temperature by controlling the rate of hydrolysis (i.e., less crystalline two-line forms at rapid hydrolysis rates whereas, six-line forms if the precipitation is conducted at lower rates, and lepidocrocite forms if the rate of addition of sodium hydroxide is slow enough) (Schwertmann and Cornell 2012).

The rate of transformation of ferrihydrite to hematite or goethite has been discussed in great detail by Cornell and Schwertmann in their book. The rate of transformation is a function of time, temperature and pH (e.g., conversion of two-line ferrihydrite to hematite at 25° C. is half complete in 280 days at pH 4 but is completely converted at 100° C. in four hours) (Cornell and Schwertmann 2003). It has been pointed out by many investigators that ferrihydrite converts rapidly and that the conversion results in a significant decrease in surface area. However, the ferrihydrite conversion rate may be mitigated (changed from days to perhaps years) by the presence of other species and solution conditions during precipitation and subsequent storage (L. Twidwell and McCloskey 2011). General factors that have been shown to decrease the rate of conversion of two-line ferrihydrite to more crystalline forms include: lower pH, lower temperatures, presence of silicate, aluminum, arsenic, manganese, metals, sulfate, and organics (L. Twidwell and McCloskey 2011; Cornell and Schwertmann 2003).

3.3.2 Scorodite

Scorodite, FeAsO₄.2H₂O, is a naturally occurring mineral formed in oxidized zones of arsenic-bearing ore deposits. Its wide occurrence in comparison to other secondary arsenate minerals has led many to advocate it as an acceptable carrier for the immobilization of arsenic released during pyrometallurgical or hydrometallurgical processing of arsenic-containing ores and those of gold, copper, and uranium.

The production of scorodite, especially from arsenic-rich and iron-deficient sulfate solutions offers a number of operational advantages such as high arsenic content, stoichiometric iron demand, and excellent dewatering characteristics.

There are two process options of industrial relevance; the hydrothermal option that involves autoclave processing at elevated temperature (≧150° C.) and pressure and the atmospheric process based on supersaturation-controlled precipitation of scorodite at 90-95° C.

In addition to hydrothermal production of scorodite the work done by Demopoulos has determined that it is feasible to produce scorodite by step-wise lime neutralization at 90° C. The atmospheric scorodite possesses the same structural and solubility characteristics with the hydrothermally produced scorodite. Thermodynamic calculations determined that scorodite is stable in the presence of ferrihydrite under oxic conditions up to pH 6.75 at 22° C. or higher pH at lower temperature and gypsum-saturated solutions (Demopoulos 2005).

Crystalline scorodite has been prepared many ways. Dove and Rimstidt prepared scorodite by mixing ferric chloride and sodium arsenate solutions and equilibrating the resultant slurry for two weeks at ˜100° C. (Dove and Rimstidt 1985).

3.4 Stability of Arsenic-Bearing Residues

A review of methods for the environmentally acceptable disposal of arsenic-bearing residues, such as those produced from hydrometallurgical operations, indicated that chemical precipitation as a metal arsenate offered a solution, not only of precipitating arsenic from process liquors, but also of producing a residue sufficiently stable (giving <5 mg As/L in solution) for disposal. Since published thermodynamic data suggested that metal arsenates were not as stable as had previously been thought, the Noranda Research Centre undertook a comprehensive laboratory study of the stability of metal arsenates, such as might be precipitated from typical hydrometallurgical process solutions, as a function of time and pH. The results indicate that (i) the presence of excess ferric iron (Fe/As molar ratio >3) co-precipitated with ferric arsenate confers a high degree of stability to arsenical residue at pH ≦7, (ii) the presence of small quantities of base metals (Zn, Cu, Cd) in solution, in addition to excess ferric iron, at the time of precipitation confers stability on the residue in the pH range 4-10, and (iii) naturally-occurring crystalline ferric arsenate (scorodite) has a solubility some two orders of magnitude lower than the chemically-precipitated amorphous form (Harris and Monette 1988).

Chapter 4

Enargite

4.1 Background of Enargite

High arsenic-containing enargite concentrates can be smelted directly but most copper smelters limit their total arsenic inputs for both environmental and economic reasons. The average arsenic level in custom copper concentrates has also been increasing, further limiting the potential market for high-arsenic enargite concentrates (Peacey, Gupta, and Ford 2010).

4.1.1 Properties of Enargite

Enargite, Cu₃AsS₄, is a blackish gray mineral with a metallic luster, Mohs hardness of 3, and a density of 4.5 g/cm³. It is a semiconductor. Copper is nominally in the monovalent state, and arsenic in the pentavalent state. In most natural occurrences, enargite is associated with pyrite, and other copper and/or arsenic and/or base metal sulfides (chalcopyrite, chalcocite, covellite, digenite, tennantite, sphalerite, galena). Enargite may contain minor amounts of other elements (Sb, Ag, Fe). The presence of Sb (up to 6 wt %) is quite common, and environmentally relevant; enargite is frequently associated with Sb-bearing minerals (Lattanzi et al. 2008).

Enargite is a complex copper-arsenic sulfide mineral, that typically contains significant gold and silver values, and poses many process challenges. Large enargite deposits are found in Chile as well as other countries and the increasing demand for copper and gold have spurred research into developing more effective methods of extracting value metals from enargite concentrates (Peacey, Gupta, and Ford 2010). The compound Cu₃(As,Sb)S₄ occurs naturally in two crystallographic forms: orthorhombic and tetragonal. The orthorhombic form is enargite (Cu₃AsS₄) and the tetragonal forms are luzonite (Cu₃AsS₄) and famatinite (Cu₃SbS₄) (Springer 1969). It has been suggested that enargite is a high temperature modification of luzonite (Maske and Skinner 1971).

4.1.2 Enargite Orebodies

There are numerous properties around the world that contain enargite mineralization. The following table lists many of them.

TABLE 4.1
Worldwide Enargite Containing Orebodies
				Grade
			Resource	Cu	Au	Ag	As
Orebody	Company	Location	Tonnes	(%)	(g/t)	(g/t)	(%)
Marca Punta	El Brocal	Peru	37,916,386	1.85	0.26	15.88	0.56
(“Memoria
Anual 2011”
2012)
Tampakan	Xstrata	Philippines	2,940,000,000	0.51
(“Annual
Report 2011”
2012),
(“Xstrata
Copper:
Operations:
Tampakan”
2012)
Mount	Evolution Mining	Australia		14.70	152.98	846.86	4.2
Carlton
Chelopech	Dundee Precious	Bulgaria		1.55	4.17	8.46
(“Annual	Metals, Inc.
Review
2011” 2012)
Frieda River	Xstrata	New	1,900,000,000	0.45	0.22	0.7
(“Xstrata		Guinea
Copper
Announces
Mineral
Resources
Increase for
the Frieda
River
Copper-gold
Project in
Papua New
Guinea”
2011)
Lepanto	Lepanto Consolidated	Philippines
	Mining Co.
Caspiche	Exeter Resources	Chile	1,646,000	0.18	0.47	1.09
(“Exeter
Resource
Corporation
Caspiche
Project Pre-
Feasibility
Study” 2012)
La Coipa	Kinross Gold	Chile	21,334,000		1.28	37.1
(“Annual
Report 2011”)
Golpu	Harmony	New	868,700,000	1.03	0.69
(“Integrated	Gold/Newcrest	Guinea
Annual
Report” 2011)
Canariaco	Candente Copper Corp.	Peru	910,100,000	0.44
(“Consolidated
Financial
Statements of
Candente
Copper Corp.
Dec. 31,
2011 and
2010” 2012)
Yanacocha	Newmont Mining	Peru
El Indio	Barrick	Chile
El Galeno	China Minmetals	Peru
Andina	Codelco	Chile
Chuquicamata	Codelco	Chile
Mina Ministro	Codelco	Chile
Hales

4.2 Enargite Concentrate Treatment Options

The process used commercially in the recent past for treating large quantities of enargite concentrate is partial roasting at temperatures in the range 600-750° C. to produce a low-As calcine and arsenic trioxide for sale or storage. Roasters and fluid bed reactors have been used to treat high arsenic concentrates at Barrick's El Indio mine in Chile, Lepanto in the Philippines and Boliden in Sweden. The resulting low-As calcine was sold to Cu smelters. Sale of significant amounts of arsenic trioxide is, however, no longer possible but the scrubbing of arsenic trioxide from copper smelter gases and its fixation in an environmentally acceptable manner is well-proven by various methods at several smelters. A key issue in selecting the preferred roasting process flowsheet is minimizing the cost of arsenic fixation and disposal to satisfy the environmental regulations (“Outotec Launches a New Partial Roasting Process to Purify Contaminated Copper and Gold Concentrates” 2011), (Peacey, Gupta, and Ford 2010).

In the early 1900's arsenic kitchens were used for the recovery of arsenic and the production of arsenic trioxide. The plant at Anaconda originally consisted of a Brunton roasting furnace for treating the flue dust and a small reverberatory furnace for treating crude arsenic produced in the roasting operations. The kitchens were connected to the main flue system to condense the gases and capture the As₂O₃ which was then prepared for market. The ASARCO Tacoma Smelter used this technology and was named a Superfund Site due to arsenic and lead contamination (Bender and Goe 1934; “Asarco Smelter—Ruston” 2013).

Several new hydrometallurgical processes have been developed to treat copper sulfide concentrates and most are suitable for the treatment of enargite concentrates. These hydrometallurgical processes include atmospheric leaching and pressure oxidation. Hydrometallurgical processes have a major advantage over roasting options as the arsenic is usually precipitated directly within the leach reactor as ferric arsenate, which is generally regarded as environmentally acceptable for disposal (Peacey, Gupta, and Ford 2010).

The Outotec neutral roast may also be a possibility based on the company's press release from Dec. 27, 2011 stating that the process can “remove impurities such as arsenic, antimony and carbon from copper and gold concentrates as a pre-treatment to actual extraction processes” (“Outotec Launches a New Partial Roasting Process to Purify Contaminated Copper and Gold Concentrates” 2011).

As there has not been a commercial hydrometallurgical application to primarily treat enargite-bearing copper concentrates, there is still work to be done to understand the chemistry, thermodynamics and kinetics of a process to successfully treat concentrates containing arsenic minerals. Further, the demand for clean copper concentrates containing silver and gold as feed to a smelter is considerable. Therefore, this research will focus on the selective dissolution and fixation of arsenic while leaving behind a clean copper-precious metals bearing solid suitable as a smelter feed. This will minimize the on-site capital investment hydrometallurgically producing copper cathode on site, while taking advantage of lower smelting treatment and refining charges and precious metal recovery credits.

4.3 Enargite Literature Review

The following sections discuss work that has been performed in the areas of enargite processing and pressure oxidation.

4.3.1 Enargite Surface Properties

In a flotation study of the surface properties of enargite as a function of pH, it was observed that the sign and magnitude of enargite's zeta potential is governed by the adsorption of the hydrolysis products of the As—Cu—S—H₂O system formed at the mineral/solution interface. The zeta potential of enargite was found to be quite sensitive to changes in pH, probably due to several simultaneous ionization and disassociation reactions (Castro and Baltierra 2005). Electrochemical oxidation and reduction of enargite were performed in 0.1 M HCl solution. The presence of Cu²⁺, sulfate and chloride were detected at potentials above 0.2V, while at potentials below 0.6V the oxidation of arsenic was detected. Dissolved sulfur increased under reducing conditions forming H₂S and at oxidizing conditions forming sulfoxy species. The sulfur was believed to be responsible for the observation of an active-passive transition at 0.3V (SCE) (Ásbjörnsson et al. 2004).

Selective flotation of enargite from chalcopyrite under varied pulp potentials was conducted to investigate the feasibility of enargite removal from a chalcopyrite concentrate. The test results indicate that chalcopyrite began to oxidize quickly at a much lower potential than enargite. Selective flotation revealed that enargite can be successfully removed from chalcopyrite through controlling the pulp potential above +0.2V and below +0.55V (SCE) (Guo and Yen 2005). The electrochemical behavior of natural enargite in an alkaline solution was studied under conditions pertinent to those used in flotation of sulfide minerals. Photoelectrochemical experiments confirmed that the samples studied were p-type semiconductors. The potential range where the photocurrent was noticeable (below −0.4±0.2V vs. SCE) is more negative than the potential range of flotation (near 0.0V vs. SCE). It is believed that a surface layer forms over the potential range studied, and the law for the growth of this layer corresponds to two processes: the formation and dissolution of the layer (Pauporté and Schuhmann 1996).

The oxidation of synthetic and natural samples of enargite and tennantite were compared through dissolution and zeta potential studies. The changes in zeta potential with pH and oxidizing conditions are consistent with the presence of a copper hydroxide layer covering a metal-deficient sulfur-rich surface. The amount of copper hydroxide coverage increases with oxidation conditions. Arsenic dissolution was much lower than copper and does not appear to contribute to the mineral oxidation. The work showed that the natural samples of tennantite and enargite oxidize more than the synthetic samples in alkaline conditions, and tennantite oxidizes more than enargite (Fullston, Fornasiero, and Ralston 1999a). The surface oxidation of synthetic and natural samples of enargite and tennantite were monitored by X-ray photoelectron spectroscopy (XPS). The XPS results showed that the oxidation layer on the mineral surface is thin and the products are comprised of copper and arsenic oxide/hydroxide, sulfite, and a sulfur-rich layer of metal-deficient sulfide and/or polysulfide (Fullston, Fornasiero, and Ralston 1999b).

The extended milling of enargite concentrate in an oxygen atmosphere at elevated temperature led to increased solubility of enargite due to the formation of CuSO₄ and As₂O₃, both of which are soluble in the leachant (Welham 2001).

4.3.2 Enargite Treatments

The study of the separation of enargite and tennantite from non-arsenic copper sulfide minerals by selective oxidation or dissolution showed that it is difficult to use flotation to separate chalcocite, covellite or chalcopyrite from enargite or tennantite under normal oxidation conditions. Improved separation occurred at pH 5.0 after selective oxidation with H₂O₂, or at pH 11.0 after oxidation with H₂O₂ followed by EDTA addition to selectively remove surface oxidation products (Fornasiero et al. 2001).

Hydrometallurgical oxidation of enargite in air is a slow process. At acidic to neutral pH, oxidation/dissolution is slow but is accelerated by the presence of ferric iron and/or bacteria. When sulfuric acid and ferric iron are present, and at high potentials, +0.74 V vs. SHE, copper dissolves and there is a formation of sulfur, which may be subsequently partially oxidized to sulfate (Lattanzi et al. 2008).

Several new hydrometallurgical processes have been developed to treat copper sulfide concentrates and may be suitable for enargite including atmospheric leaching, bio-oxidation and pressure oxidation. The advantage of hydrometallurgy over roasting is that the arsenic can be precipitated directly within the leach reactor as ferric arsenate (Peacey, Gupta, and Ford 2010).

One commercial process for treating large quantities of enargite concentrates is the Outotec Partial Roasting Process. It includes partial roasting at 600-750° C. to produce a low-arsenic calcine and arsenic trioxide for sale or storage. The low-arsenic calcine was sold to copper smelters. The sale of significant amounts of arsenic trioxide is no longer possible but scrubbing from copper smelter gases and fixation in an environmentally acceptable manner is well-proven (Lattanzi et al. 2008; Peacey, Gupta, and Ford 2010).

4.3.3 Pyrometallurgical Processing

Pyrometallurgical processing of enargite concentrates has been shown to remove arsenic, but the problem is handling of the arsenic-containing species and long term stability (Kusik and Nadkarni 1988). Decomposition of enargite in a nitrogen atmosphere at 575-700° C. proceeded in two sequential steps forming tenantite as an intermediate compound (Padilla, Fan, and Wilkomirsky 2001). Sulfidation of chalcopyrite-enargite concentrate at 350-400° C. resulted in rapid conversion of the chalcopyrite to covellite and pyrite. This was followed by pressure leaching in sulfuric acid with oxygen (Padilla, Vega, and Ruiz 2007).

4.3.4 Bio-Oxidation

Enargite was leached faster by bacteria in sulfuric acid with ferric sulfate than by chemical leaching at the same or higher ion concentration (Escobar, Huenupi, and Wiertz 1997). Arsenic-bearing copper ores and concentrates could be leached by Sulfolobus B C, a strain of bacteria that can oxidize aresnite to arsenate, in the presence of ferric iron due to precipitation of ferric arsenate (Escobar et al. 2000). In evaluating bio-oxidation of a gold concentrate prior to cyanidation of high pyrite and enargite content, the bacterial attack was directed toward pyrite with minimal effect on the enargite (Canales, Acevedo, and Gentina 2002). The electrochemical study of enargite bioleaching by mesophilic and thermophilic microorganisms showed that enargite dissolution increased at higher temperatures, or thermophilic conditions (Munoz et al. 2006). Leach tests on composited sulfide ores containing enargite and covellite achieved higher copper extraction at thermophilic conditions than mesophilic conditions (Lee et al. 2011). Arsenic-tolerant acidithiobacillus ferrooxidans achieved oxidation dissolution of enargite by forming elemental sulfur, arsenate and oxidized sulfur species (Sasaki et al. 2009). The study of CO₂ supply on the biooxidation of an enargite-pyrite gold concentrate showed a marked effect on the kinetics of growth and bioleaching. Four percent carbon dioxide resulted in suspended cell population as well as maximum extraction of Fe, Cu and As (Acevedo, Gentina, and Garcia 1998).

4.3.5 Hydrometallurgical Processing

Arsenic dissolved from concentrates by leaching enargite with sodium hypochlorite under alkaline oxidizing conditions where the enargite is converted into crystalline CuO and arsenic dissolves forming AsO₄³⁻. The reaction rate was very fast and chemically controlled (Curreli et al. 2005; Vinals et al. 2003).

Dissolution of enargite in acidified ferric sulfate solutions at 60-95° C. yielded elemental sulfate and sulfate with dissolved copper and arsenic. The dissolution kinetics were linear and copper extraction increased with increasing ferric sulfate and sulfuric acid concentration (Dutrizac and MacDonald 1972). Leaching of enargite in acidic sulfate and chloride media resulted in complete dissolution at temperatures above 170° C. (Riveros, Dutrizac, and Spencer 2001). At <100° C., enargite dissolves slowly in either Fe(SO₄)_1.5 or FeCl₃ media, and the dissolution rate obeys the shrinking core model. The rate increases with increasing temperature and the apparent activation energies are 50-64 kJ/mol. The rate increases slightly with increasing FeCl₃ concentrations in 0.3M HCl media. The leaching of enargite at elevated temperatures and pressures was also investigated. Potentially useful leaching rates are achieved above 170° C., at which temperature sulfate, rather than sulfur, is produced. Lower temperatures (130-160° C.) lead to fast initial leaching rates, but the dissolution of the enargite is incomplete because of the coating of the enargite particles by elemental sulfur (Riveros and Dutrizac 2008).

Enargite dissolution in ammoniacal solutions was slow and 60% of copper was extracted after 14 hours (Gajam and Raghavan 1983).

In the case of gold-bearing enargite concentrates, leaching with basic Na₂S has been shown to selectively solubilize the arsenic, and some gold, but does not affect the copper. The copper is transformed in the leach residue to a species Cu_1.5S and the gold is partly solubilized in the form of various anionic Au—S complexes. The gold and arsenic could then be recovered from solution (Curren et al. 2009). Other work had indicated that leaching with sodium sulfide in 0.25 M NaOH at 80-105° C. will dissolve sulfides of arsenic, antimony and mercury (Nadkarni and Kusik 1988; C. G. Anderson 2005; C. Anderson and Twidwell 2008). The selective leaching of antimony and arsenic from mechanically activated tetrahedrite, jamesonite and enargite in alkaline solution of sodium sulfide is temperature-sensitive. (Baláz and Achimovicova 2006). The treatment of copper ores and concentrates with industrial nitrogen species catalyzed pressure leaching and non-cyanide precious metals recovery was effective in leaching copper and oxidizing the sulfide to sulfate in a minimum amount of time while keeping the arsenic out of solution through in-situ precipitation (C. G. Anderson 2003).

Bornite, covellite and pyrite were reacted hydrothermally with copper sulfate solutions at pH 1.1-1.4 to produce digenite which was then transformed to djurleite, chalcocite, and chalcocite-Q and trace djurleite respectively. The bornite reaction is diffusion controlled while the covellite and pyrite are chemically controlled. A Chilean copper concentrate was hydrothermally treated at 225-240° C. with copper sulfate solutions to remove impurities. The mineral phases behaved in a similar manner as described above. Arsenic was described as being moderately eliminated (20-40%) (Fuentes, Vinals, and Herreros 2009a; Fuentes, Vinals, and Herreros 2009b). Hydrothermally reacting sphalerite with acidified copper sulfate solution by metathesis reaction at 160-225° C. resulted in digenite at lower temperature and chalcocite at higher temperature. Copper sulfide formed in a compact layer around a core of sphalerite retaining the same size and shape of the original particle. The work shows that sphalerite could be removed from a digenite or chalcopyrite copper concentrate (Vinals, Fuentes, Hernandez and Herreros 2004).

Complete dissolution of enargite at 220° C., 100 psi in 120 minutes was achieved and it was found that a sulfuric acid content over 0.2 molar had a negligible effect on dissolution (Padilla, Rivas, and Ruiz 2008). Leaching of enargite in sulfuric acid, sodium chloride, and oxygen media found arsenic dissolution was very slow. About 6% of the arsenic dissolved in 7 hours at 100° C. (Padilla, Giron, and Ruiz 2005). Enargite dissolved faster when pressure leaching in the presence of pyrite at 160-200° C. than the dissolution of pure enargite which is thought to be the result of ferric ions (Ruiz, Vera, and Padilla 2011).

4.3.6 Other Processing Technologies

A pyro-hydrometallurgical approach is the acid-bake leach, or Anaconda-Treadwell process, which achieved approximately 90% copper extraction when baking at 200° C. with less than 1% of arsenic reporting to the gas phase. Results show that upon baking with 5 grams concentrated sulfuric acid per gram of contained copper, the enargite, chalcopyrite, sphalerite and galena will be converted to their corresponding sulfates (Safarzadeh, Moats, and Miller 2012a; Safarzadeh, Moats, and Miller 2012b).

4.3.7 Pressure Oxidation

Many companies have been investigating hydrometallurgical treatment methods for the leaching of copper concentrates as an alternative to conventional smelting technology by pressure oxidation. Freeport-McMoRan Copper & Gold has developed a sulfate-based pressure leaching technology for the treatment of copper sulfide concentrates. The main drivers for the activity were the relatively high and variable cost of external smelting and refining capacity, the limited availability of smelting and refining capacity and the need to cost-effectively generate sulfuric acid at mine sites for use in stockpile leaching operations. Freeport was looking to treat chalcopyrite concentrates with this technology and developed both high and medium temperature processes (J. O. Marsden, Wilmot, and Hazen 2007a); (J. O. Marsden, Wilmot, and Hazen 2007b).

Anaconda Copper Company performed work on ores from the Butte area to evaluate the possibility of converting chalcopyrite to digenite at about 200° C. to upgrade and clean the concentrate to the point where it could be shipped as a feed to a copper smelter. They showed that this reaction is possible and a significant amount of the iron and arsenic (along with other impurities) were removed from the solid product while retaining the majority of the copper, gold and silver in the concentrate. The upgrading process also results in a lower mass of concentrate to ship, thereby decreasing shipping costs. Primarily, the process consists of chemical enrichment that releases iron and sulfur from the chalcopyrite, followed by solid-liquid separation with treatment of the liquid effluent. This is followed by flotation with recycle of the middling product back to the enrichment process and rejection of the tailing. The resultant product is digenite formed as a reaction product layer around the shrinking core of each chalcopyrite grain. About 80% of the zinc impurities reported to the liquor, while arsenic, bismuth and antimony were evenly distributed between the discharge liquor and the enriched product. Gold, silver and selenium followed the copper (Bartlett 1992); (Bartlett et al. 1986).

Chapter 5

Thermodynamic Modeling

5.1 Enargite Thermodynamics

The thermodynamics associated with enargite have been studies by several people. The starting point for this evaluation is with the chemical reactions that might be occurring. Reactions related to the pressure leaching of enargite in a sulfate-oxygen media and their associated Gibbs Energies are shown below (Padilla, Rivas, and Ruiz 2008; Seal et al. 1996; Knight 1977).

Cu₃AsS₄+8.75O₂+2.5H₂O+2H⁺=3Cu²⁺+H₃AsO₄+4HSO₄⁻  (5.1)

ΔG_{r×n,25° C.}⁰=−2821.8 kJ/mole  (5.2)

ΔG_{r×n,200° C.}⁰=−2476.7 kJ/mole  (5.3)

Cu₃AsS₄+2.75O₂+6H⁺=3Cu²⁺+H₃AsO₄+4S⁰+1.5H₂O  (5.4)

ΔG_{r×n,25° C.}⁰=−747.7 kJ/mole  (5.5)

ΔG_{r×n,200° C.}⁰=−627.4 kJ/mole  (5.6)

These reactions and the resultant Gibbs Energies predict a strong thermodynamic possibility of enargite oxidation with resultant sulfate or sulfur production.

The Gibbs free energy of formation for enargite was calculated in Padilla's work from data published by Seal & Knight, shown below.

TABLE 5.1
Standard Gibbs Free Energy of Formation for Enargite
(Padilla, Rivas, and Ruiz 2008)
Compound	ΔG°, kcal/mole	Temperature Range, K
Cu3AsS4	−45.002 + 0.00707T ± 0.19	298-944

The table below shows the standard free energy for the various species used in Padilla's Eh-pH diagrams which are depicted at FIGS. 5.1-5.2.

TABLE 5.2
Standard Free Energy for the Various Species in the
Eh-pH Diagrams (Padilla, Rivas, and Ruiz 2008)
	Species	ΔG°25° C. (kJ/mol)	ΔG°200° C. (kJ/mol)
	As	0.000	0.000
	Cu	0.000	0.000
	Cu3AsS4	−177.462	−174.359
	CuH3	283.576	289.333
	CuO	−128.380	−112.273
	Cu2O	−147.982	−134.597
	CuS	−53.507	−53.135
	Cu2S	−86.524	−90.493
	S	0.000	0.000
	AsH3 (a)	80.642	94.701
	Cu2+ (a)	65.599	66.072
	Cu+ (a)	50.020	35.533
	CuO22− (a)	−172.576	−77.598
	H3AsO3 (a)	−640.061	−574.856
	H2AsO3− (a)	−587.328	−506.519
	HAsO32− (a)	−524.171	−401.154
	AsO33− (a)	−447.577	−279.875
	H3AsO4 (a)	−766.515	−685.283
	H2AsO4− (a)	−753.620	−655.707
	HAsO42− (a)	−714.942	−588.019
	AsO43− (a)	−648.669	−482.181
	H2S (a)	−27.281	−25.083
	HS− (a)	12.087	35.496
	S2− (a)	86.026	129.087
	HSO4− (a)	−756.182	−672.731
	SO42− (a)	−744.865	−631.876
	(a) refers to aqueous

Additional Eh-pH stability diagrams for the Cu—S—H₂O, As—H₂O, and S—H₂O systems are shown individually in Appendices A and B. Appendix A shows how the diagrams change by increasing temperature in 25° C. increments. Appendix B shows how the diagrams change by increasing species molality in 0.1 mol/kg increments.

Padilla's diagrams were recreated using Stabcal as seen in FIGS. 5.3-5.4. The enargite data utilized is from Craig & Barton (Craig and Barton 1973).

The most important item to note from the above figures is that at the acidic conditions proposed by CSM for the pressure oxidation of enargite at positive oxidation potentials, enargite can be transformed to solid copper sulfide phase (stability region surrounding enargite region), which would stay in the solid concentrate, and a soluble arsenic species. Padilla focused on the upper left corner of the diagram, acidic oxidizing conditions, showing Cu²⁺ as stable. At pH<2, the species would be Cu²⁺, H₃AsO₄ and HSO₄⁻; at pH between 2 and 2.3, the species will be Cu²⁺, H₃AsO₄, and SO₄²⁻; and at a pH between 2.3 and 4.3, Cu²⁺, H₂AsO₄⁻ and SO₄²⁻ will be stable (Padilla, Rivas, and Ruiz 2008). Based on the diagrams, it appears that there is a region where Cu²⁺ is no longer the stable form of copper, but rather CuS or Cu₂S, while there is still a soluble arsenic phase. This is a metathesis-like reaction path.

It is important to keep in mind that a thermodynamic evaluation commonly predicts whether such reaction is possible, not whether the reaction kinetics are viable.

5.2 Metathesis Reaction Thermodynamics

A metathesis reaction is a double-replacement chemical reaction. Metathetic leaching may be represented by the reaction (Vignes 2011):

MeS(s)+CuSO₄→MeSO₄+CuS(s)↑  (5.7)

Metathesis is an exchange of bonds. The copper sulfide in Reaction 5.7 above is insoluble in the system and is precipitated.

Metathesis has long been used for copper cementation, as part of the nickel-copper matte leach (Hofirek and Kerfoot 1992), at Stillwater (Mular, Halbe, and Barratt 2002), and to transform sphalerite to copper sulfide particles (Vinals et al. 2004). For copper minerals, it has been used to convert chalcopyrite to digenite (Bartlett 1992). The chalcopyrite metathesis reaction is shown below.

3CuFeS₂+6CuSO₄+4H₂O=5Cu_1.8S+3FeSO₄+4H₂SO₄  (5.8)

Metathesis has also been successful for the purification and enrichment of Chilean copper concentrates using pressure oxidation. Bornite and covellite were successfully treated for impurities, including a moderate (20-40%) extraction of arsenic (Fuentes, Vinals, and Herreros 2009a; Fuentes, Vinals, and Herreros 2009b).

For our work, based on the enargite Eh-pH diagrams, an example metathesis reaction may be:

Cu₃AsS₄(s)+2.25O₂(g)+2.5H₂O(l)→3CuS(s)+H₃AsO₃(aq)+H₂SO₄  (5.9)

Chapter 6

Feed Sample Characterization

Two enargite samples were collected for experimentation. The samples consist of a Peruvian concentrate (Marca Punta) and a high enargite content mineral specimen.

6.1 Marca Punta Sample

The first sample analyzed was from Marca Punta, Peru. The feed concentrate was analyzed using various methods shown below.

This sample was analyzed both by The Center for Advanced Mineral and Metallurgical Processing (CAMP) at Montana Tech of the University of Montana in Butte and by Freeport's Mineralogy group.

Total sulfur and carbon were analyzed on the LECO analyzer. Arsenic, copper and iron were analyzed on the digested sampled by ICP-AES. Gold and silver values were determined by fire assay. These values are shown in the table below.

TABLE 6.1
Marca Punta CAMP Concentrate Analysis
Cu, %   20.64
Fe, %   28.3
As, %   5.89
Au, g/t 1.93
Ag, o/t 1.65
TS, %   40.1

The sample was examined by XRD to determine the major mineral phases present as shown in FIGS. 6.1 and 6.2. The MLA-determined particle size distribution for the sample is presented in FIGS. 6.2. The particle size was biased high due to agglomeration of the material from drying; the P80 was approximately 30 μm. The prepared sample was analyzed by the MLA X-ray Backscatter Electron (XBSE) method. The XBSE method uses the variation in the gray level of mineral phases based on the backscatter electron (BSE) image to differentiate (segment) the particles and mineral phases. After segmentation of the BSE image is complete, EDX spectra are collected at the “center” of each phase. The collected X-ray spectra are compared to a mineral X-ray database for identification. The phases present are shown in Table 6.2.

TABLE 6.2
Phase/Mineral Concentrations for the Marca Punta sample (wt %)
			Con
	Phase/Mineral	Formula	Feed
	Pyrite	FeS2	61.4
	Enargite	Cu3AsS4	38.0
	Quartz	SiO2	0.27
	Chalcocite	Cu2S	0.20
	Chalcopyrite	CuFeS2	0.04
	FeO	Fe2O3	0.03
	Sphalerite	ZnS	0.02
	Galena	PbS	0.01
	P—mineral present, found at less than 0.01%
	ND—mineral not detected

The MLA-calculated bulk elemental analysis is shown below.

TABLE 6.3
MLA-Calculated Bulk Elemental Analysis (wt %)
Element wt (%)
Sulfur  45.3
Iron    28.6
Copper  18.6
Arsenic 7.23
Oxygen  0.15
Silicon 0.12
Zinc    0.01
Lead    0.01
P—element present at less than 0.01%
ND—element not detected

FIG. 6.3 is a classified MLA image from a selected frame obtained during analysis of the sample. The image is of agglomerate that is mainly pyrite and enargite. Enargite (pink) constituted approximately one-third of the sample shown in the MLA image.

The BSE image shown in FIG. 6.4 is from the same analytical frame as the MLA image shown in the figure above. It is difficult to discern by casual observation, but the enargite (En) grain is slightly brighter than the pyrite (Py) in the BSE image in FIG. 6.4.

The BSE image in FIG. 6.5 is taken at a lower magnification than in the previous figure shows a relatively large enargite compared to those that are in the agglomerate and comprise the majority of the sample.

A comparison between the MLA calculated and analytical assays are shown below.

TABLE 6.4
Comparison
	Element	MLA Calculated	Head Assay
	Cu	18.6	20.64
	Fe	28.6	28.3
	As	7.23	5.89
	S	45.3	40.1

As mentioned above, Freeport also performed analysis on this sample. XRD bulk mineralogy is shown in the table below.

TABLE 6.5
Marca Punta FMIXRD Bulk Mineralogy
Quartz         2.50
Pyrite         52.96
Enargite       31.44
Poitevinite    5.02
Swelling Clays 8.09

ICP from Freeport shows a full elemental sweep.

TABLE 6.6
Marca Punta FMI ICP Elemental Analysis
	Ag	ppm	56.5
	Al	%	0.04
	As	%	5.9
	Ba	%	0.00155
	Bi	ppm	36.6
	Ca	%	0.25
	Cd	ppm	4
	Ce	ppm	2.6
	Co	%	0.00444
	Cr	%	0.0049
	Cs	ppm	0.5
	Cu	%	19.3
	Dy	ppm	<0.5
	Er	ppm	<0.5
	Eu	ppm	<0.5
	Fe	%	27.39
	Ga	ppm	6.9
	Gd	ppm	<0.5
	Hf	ppm	1.8
	Ho	ppm	<0.5
	K	%	<0.1
	La	ppm	1.3
	Li	ppm	<10.0
	Lu	ppm	<0.5
	Mg	%	<0.0
	Mn	%	0.00995
	Na	%	<0.1
	Nb	ppm	<5.0
	Nd	ppm	1
	Ni	ppm	34
	P	ppm	34.7
	Pb	%	0.05
	Pr	ppm	<0.5
	Rb	ppm	<0.5
	Re	ppm	<0.5
	S	%	40.31
	Sb	ppm	678.8
	Se	ppm	11.2
	Si		0.57
	Sm	ppm	<2.0
	Sn	ppm	284.9
	Sr	%	0.00244
	Tb	ppm	<0.5
	Te	ppm	166.5
	Th	ppm	0.7
	Ti	%	0.03
	Tl	ppm	14.1
	Tm	ppm	<0.5
	U	ppm	<1.0
	W	ppm	14.8
	Y	ppm	<2.0
	Yb	ppm	<0.5
	Zn	%	0.17
	Zr	ppm	97.1

FMI QEMSCAN bulk mineralogy compared to chemical analysis shows elements and minerals present in the table below followed by QEMSCAN liberation analysis based on copper sulfides and arsenic sulfides, in FIG. 6.6.

TABLE 6.7
Marca Punta FMI QEMSCAN Bulk Mineralogy
Particle Size    11.91
As (QEMSCAN)     6.51
As (Chemical)    5.90
Cu (QEMSCAN)     20.59
Cu (Chemical)    19.30
Fe (QEMSCAN)     26.52
Fe (Chemical)    27.39
Pb (QEMSCAN)     0.08
Pb (Chemical)    0.05
S (QEMSCAN)      42.45
S (Chemical)     40.31
Sb (QEMSCAN)     0.68
Sb (Chemical)    0.07
Zn (QEMSCAN)     0.19
Zn (Chemical)    0.17
Chalcopyrite     0.29
Chalcocite       0.94
Covellite        4.18
Bornite          1.45
Cu/As/SbGroup    4.78
Enargite         30.41
Cu bearing clays 1.96
Other (Cu)       0.06
Pyrite           54.27
Arsenopyrite     0.34
Galena           0.09
Sphalerite       0.30
Quartz           0.57
Other            0.35

TABLE 6.8
Marca Punta FMI QEMSCAN Liberation
	Cu Sulfides	As Sulfides
	Locked (0-30%)	39.45	19.73
	Middling (30-90%)	47.83	63.31
	Liberated (90-100%)	12.72	16.95

6.2 High Grade Enargite Sample

The second sample analyzed was a high grade enargite specimen from Butte, Mont. Photographs of the specimens before testing are shown in FIG. 6.7.

The feed sample was pulverized at CAMP and analyzed using various methods shown below.

Total sulfur and carbon were analyzed on the LECO analyzer. Arsenic, copper and iron were analyzed on the digested sampled by ICP-AES. Gold and silver values were determined by fire assay.

TABLE 6.9
High Grade Sample Analysis
Cu, %      29.7
Fe, %      9.97
As, %      10.7
Au, oz/ton 0.16
Ag, oz/ton 26.5
TS, %      34.1
TC, %      0.19

The enargite sampled was examined by XRD to confirm the presence of major mineral phases as shown in FIG. 6.8.

The acquired diffractogram for enargite is shown in red in FIG. 6.9 with the whole powder patter fitted (WPPF) calculated plot shown in blue. The residual graph, which is the difference between acquired and calculated, is shown in pink. The WPPF plot was calculated using the phases shown in the figure above. Qualitative observation of the peak positions on the diffractogram above and the candidate phases shows that enargite and quartz are responsible for the majority of observed peaks.

FIG. 6.10 is a classified MLA image from a selected frame obtained during analysis of the enargite sample. The highlighted particle shows the association of the three most abundant phases found in the sample, enargite (red), pyrite (sea foam green) and quartz (grey). A small grain of the copper arsenic-antimonide sulfide, watanabeite (pink) is located at the grain boundary between enargite and pyrite.

The BSE image in FIG. 6.11 is from the same analytical frame as the MLA image shown in the above figure. The watanabeite (Wtb) is seen as a small sliver, slightly brighter than enargite (En) which is brighter than pyrite (Py). Quartz is the darkest phase in the highlighted particle.

Enargite was the main phase in the sample at 65%. Pyrite was significant at 25% with minor quartz at 5% and bornite at 2%. Numerous other minor and trace phases were found and are listed in the table below. A trace, but noteable phase, was watanabeite that contained tellurium and bismuth.

	Mineral	Formula	Wt %
	Enargite	Cu3AsS4	65.4
	Pyrite	FeS2	24.9
	Quartz	SiO2	5.18
	Bornite	Cu5FeS4	2.04
	Chalcocite	Cu2S	0.90
	Mica	KAl2(AlSi3O10)(OH)2	0.58
	Chalcopyrite	CuFeS2	0.35
	Sphalerite	ZnS	0.33
	Hubnerite	MnWO4	0.05
	Berlinite	AlPO4	0.05
	Watanabeite	Cu4(As,Sb)2S5	0.04
	Hinsdalite	(Pb,Sr)Al3(PO4)(SO4)(OH)6	0.06
	Pyroxene	CaMgSi2O6	0.02
	Plagioclase	(Na,Ca)(Al,Si)4O8	0.02
	K_Feldspar	KAlSi3O8	0.11
	Biotite	K(Mg,Fe)3(AlSi3O10)(OH)2	0.01
	Rutile	TiO2	P
	Ilmenite	FeTiO3	P
	FeO	Fe2.5O3.5	P
	Vermiculite	(Mg,Fe,Al)3(Si,Al)4O10(OH)2•4H2O	P
	Galena	PbS	P
	Monazite	(La,Ce)PO4	P
	Calcite	CaCO3	P
	P—mineral present, found at less than 0.01%
	ND—mineral not detected

The MLA-calculated bulk elemental analysis is shown in the table below. Sulfur was 35.5%, copper was almost 33.8%, arsenic was 12.4% and iron was 11.9%.

TABLE 6.10
MLA-Calculated Bulk Elemental Analysis (wt %)
Element    wt (%)
Sulfur     35.5
Copper     33.8
Arsenic    12.4
Iron       11.9
Oxygen     3.18
Silicon    2.59
Aluminum   0.15
Zinc       0.22
Potassium  0.07
Tungsten   0.03
Phosphorus 0.02
Manganese  0.01
Antimony   0.01
Lead       0.01
Calcium    0.01
Titanium   P
Magnesium  P
Hydrogen   P
Strontium  P
Sodium     P
Cerium     P
Lanthanum  P
Carbon     P
P—element present at less than 0.01%
ND—element not detected

Arsenic was found in enargite and watanabeite. Due to the relatively large content of enargite, the input of arsenic from watanabeite was minimal, making enargite effectively responsible for all of the arsenic in the sample. Copper was found in several minerals in the sample. Enargite was responsible for 94% of the copper with bornite and chalcocite contributing slightly more than 5% to the overall copper balance as seen below.

TABLE 6.11
Copper Distribution in the Enargite Sample by Mineral
Mineral      Copper (wt %)
Bornite      3.8
Chalcocite   2.1
Chalcopyrite 0.4
Enargite     93.7
Watanabeite  0.0
Total        100.0

TABLE 6.12
Iron Distribution in the Enargite Sample by Mineral
Mineral      Iron (wt %)
Biotite      0.0
Borrrite     1.9
Chalcopyrite 0.9
FeO          0.0
Pyrite       97.2
Total        100.0

TABLE 6.13
Sulfur Distribution in the enargite sample by mineral
Mineral      Sulfur (wt %)
Bornite      1.5
Chalcocite   0.5
Chalcopyrite 0.3
Enargite     59.9
Hinsdalite   0.0
Pyrite       37.4
Sphalerite   0.3
Watanabeite  0.0
Total        100.0

A comparison between the MLA calculated and analytical assays are shown below.

TABLE 6.14
Comparison
	Element	MLA Calculated	Head Assay
	Cu	33.8	29.7
	Fe	12.4	9.97
	As	12.4	10.7
	S	35.5	34.1

Chapter 7

Research Program

The goal of this project is to develop a process to be integrated into an existing hydrometallurgical operation for the treatment of enargite concentrates and the operational parameters for this treatment. For this project, a rigorous experimental program was required to evaluate the processing technique. The experimental program is summarized in the following sections.

7.1 Sample Preparation

Sample preparation before testwork is very important to ensure that a representative sample is taken from the original feed sample. To do this, each solid sample was blended and split prior to testing.

7.2 Chemical Analysis Methods

In order to evaluate elemental distribution throughout experimentation, it is beneficial to establish accurate and precise quantitative analysis techniques. Liquid samples were sent to outside labs for assay by ICP for copper, iron and arsenic. Additional techniques are described in the following sections.

7.2.1 Copper Titration Procedure

To analyze PLS solutions for copper content as a check for the ICP results from the outside labs, the Short Iodide Method for Copper Ion Titration was used. Two titrations were performed on a pre-mixed known solution before each batch of samples to verify the accuracy of the results. The titration procedure is as follows:

• • 1. Pipette 1 or 2 ml of sample into an Erlenmeyer flask
  • 2. Dilute the sample to the 50 ml mark on the flask with distilled water
  • 3. Add 5 ml of 20 g/l ammonium bifluoride solution using a plastic syringe
  • 4. Pipette 5 ml of 30 wt % potassium iodide solution (solution will turn a reddish amber color)
  • 5. Titrate using 0.05 N sodium thiosulfate solution until a light yellow color is obtained (about the color of orange juice)
  • 6. Pipette 5 ml of 20 g/l thiodene indicator (solution will turn black)
  • 7. Titrate using 0.05 N sodium thiosulfate solution until solution changes from black to clear or milky-white
  • 8. The concentration of copper present is found by multiplying the number of ml's of sodium thiosulfate titrated by 3.177 and dividing by the volume of sample used

$\begin{array}{cc}\mathrm{Copper}\left(g\text{/}L\right)=\frac{\mathrm{ml}\mathrm{titrant}\times 3.177}{\mathrm{ml}\mathrm{sample}}& \left(7.1\right)\end{array}$

7.2.2 Free Acid Titration Procedure

To determine the free acid content in the solutions, the Determination of Free Acid in the Presence of Iron Titration was used. Two titrations were performed on a pre-mixed known solution before each batch of samples to verify the accuracy of the results. The titration procedure is as follows:

• • 1. Pipette 5 ml of sample into an Erlenmeyer flask
  • 2. Dilute the sample to the 50 ml mark on the flask with distilled water
  • 3. Add 2 drops of 20 wt % sodium thiosulfate solution
  • 4. Pipette 1 ml of 0.5 g/l methyl orange indicator solution (when acid is present, solution turns red)
  • 5. Titrate with 1.0 N sodium carbonate solution until a pH of 3.8 is reached or until the disappearance of all red color (solution will turn orange)
  • 6. The concentration of free acid present is found by multiplying the number of ml's of sodium carbonate titrated by 49 and dividing by the volume of sample used

$\begin{array}{cc}\mathrm{Free}H_2{\mathrm{SO}}_4\left(g\text{/}L\right)=\frac{\mathrm{Normality}\mathrm{of}\mathrm{titrant}\times 49\times \mathrm{ml}\mathrm{of}\mathrm{titrant}}{\mathrm{ml}\mathrm{sample}}& \left(7.2\right)\end{array}$

7.3 Data Analysis

Once assay results were received, all data was put into a mass balance and extractions were calculated. The mass balances are shown in Appendix C.

7.3.1 Analyzing Results Using Stat-Ease Design Expert

Stat-Ease Design Expert 8.0 software was used to perform statistical analyses including analysis of the variance (ANOVA). The Stat-Ease model fit summaries and ANOVA are shown in Appendix D.

Analysis consisted of the following:

• • 1. Compute effects. Use half-normal probability plot to select model. Click the biggest effect (point furthest to the right) and continue right-to-left until the line runs through points nearest zero. Alternatively, on the Pareto Chart pick effects from left to right, largest to smallest, until all other effects fall below the Bonferroni and/or t-value limit.
  • 2. Choose ANOVA and check the selected model:
    • a. Review the ANOVA results.
      • i. Model should be significant based on F-test:
        • 1. (Prob >F) is <0.05 is significant (good).
        • 2. (Prob >F) is >0.10 is not significant (bad).
      • ii. Curvature and Lack of Fit (if reported) should be insignificant:
        • 1. (Prob >F) is <0.05 is significant (bad).
        • 2. (Prob >F) is >0.10 is not significant (good).
    • b. Examine the F tests on the regression coefficients. Look for terms that can be eliminated, i.e., terms having (Prob >F) >0.10. Be sure to maintain hierarchy.
    • c. Check for “Adeq Precision” >4. This is a signal to noise ratio.
    • d. Verify the ANOVA assumptions by looking at the residual plots (Handbook for Experimenters, Version 08.1 2009).

Design Expert provides prediction equations in terms of actual units and coded units. In the case of mixture designs, the options are actual, pseudo and real units. The coded equations are determined first, and the actual equations are derived from the coded. Experimenters often wonder why the equations look so different, even to the point of having different signs on the coefficients.

To get the actual equation, replace each term in the coded equation with its coding formula:

$\begin{array}{cc}{X}_{\mathrm{Coded}}=\frac{X_{\mathrm{Actual}}-\stackrel{\_}{X}}{\left(X_{\mathrm{Hi}}-X_{\mathrm{Low}}\right)/2}& \left(7.3\right)\end{array}$

Substituting the formula into each linear term will result in a new linear coefficient and a correction to the intercept.

Substituting the formula into each quadratic term will result in a new quadratic coefficient and a correction to the intercept.

Substituting the formula into each interaction term will result in a new interaction coefficient, a correction to each main effect in the interaction, and a correction to the intercept.

These corrections from the interactions can be large and opposite in sign from the linear terms and can change the sign on the linear terms (“Stat-Ease Design Expert 8.0 Help” 2011).

Chapter 8

Atmospheric Pressure Leaching

Before starting experiments on the pressure oxidation of enargite, a series of atmospheric pressure leach tests were performed to evaluate whether there was a response in arsenic extraction. A Design of Experiments (DOE) matrix was generated using Stat-Ease Design Expert 8.0 software. This DOE matrix is shown below where −1 is the low, 0 is a center point, and 1 is the high.

TABLE 8.1
½ Factorial DOE for Atmospheric Pressure Leach Tests
		Factor 1	Factor 2	Factor 3	Factor 4	Factor 5
		A: Acid	B: Solids	C: Cu2+	D: Temperature	E: Time
Std	Run	g/L	g	g/L	deg C.	hrs
1	15	−1	−1	−1	−1	1
2	7	1	−1	−1	−1	−1
3	9	−1	1	−1	−1	−1
4	14	1	1	−1	−1	1
5	10	−1	−1	1	−1	−1
6	13	1	−1	1	−1	1
7	12	−1	1	1	−1	1
8	11	1	1	1	−1	−1
9	3	−1	−1	−1	1	−1
10	17	1	−1	−1	1	1
11	16	−1	1	−1	1	1
12	6	1	1	−1	1	−1
13	19	−1	−1	1	1	1
14	5	1	−1	1	1	−1
15	4	−1	1	1	1	−1
16	18	1	1	1	1	1
17	1	0	0	0	0	0
18	2	0	0	0	0	0
19	8	0	0	0	0	0

The experimental equipment setup can be seen in the FIG. 8.1.

The setup consisted of a 2 liter Pyrex resin kettle, constant temperature circulating water bath, agitator and a water cooled condenser to create a closed system.

8.1 Leaching Tests

The actual order in which these tests were performed differed slightly from the DOE so the following table shows the experimental order and also shows the actual numerical values of the test variables.

TABLE 8.2
Experimental Order of Atmospheric Leach Tests
	Factor 1	Factor 2	Factor 3	Factor 4	Factor 5
	Acid	Solids	Cu2+	Temperature	Time
Test #	g/L	g	g/L	deg C.	hrs
1	5	20	25	50	4
2	5	20	25	50	4
3	0	10	10	25	2
4	0	30	40	25	2
5	10	10	40	25	2
6	10	30	10	25	2
7	10	10	10	75	2
8	5	20	25	50	4
9	0	30	10	75	2
10	0	10	40	75	2
11	10	30	40	75	2
12	0	30	40	75	6
13	10	10	40	75	6
14	10	30	10	75	6
15	0	10	10	75	6
16	0	30	10	25	6
17	10	10	10	25	6
18	10	30	40	25	6
19	0	10	40	25	6

Two additional leach tests, 7-2 and 13-2 were performed to verify the results from the tests above. This will be discussed in more detail in the results section of this chapter below.

8.1.1 Leach Test Procedure

The procedure for the atmospheric pressure agitated leach tests was consistent throughout all 19 designed experiments.

• • 1. Mix 1 liter of leach feed solution according to acid and copper ion concentrations as specified in the DOE matrix
  • 2. Split and weigh out solid feed sample according to solids weight as specified in the DOE matrix
  • 3. Pour solids and leach solution into Pyrex resin kettle, set agitation at level 4 and record leaching start time
  • 4. Turn off agitator 5 minutes before taking hourly samples to allow solids to settle
  • 5. After each hour, take a sample using glass pipette (10 ml for 6 hour test or 20 ml for 2 and 4 hour tests), replace rubber stopper, and turn agitation back to level 4
  • 6. When samples return to room temperature, analyze for pH and ORP
  • 7. When leaching is complete, rinse contents of resin kettle into #40 Whatman filter paper in funnel with distilled water to drip filter (record weight of filter paper before filtering)
  • 8. Collect solution and record final volume
  • 9. Rinse solids with distilled water and allow to drip filter again
  • 10. Place filter paper containing solids in drying oven overnight at 90° C.
  • 11. Remove dry filter and solids from oven and record final weight
  • 12. Filter hourly samples according to above procedure and add dry solids to final weight from above

The two additional tests, 7-2 and 13-2 were performed following this procedure except no hourly samples were taken.

8.2 Analysis

The following sections discuss the results of analysis performed on both solids and liquids from the leach tests outlined above.

8.2.1 Pregnant Leach Solution Analysis

Hourly PLS samples were analyzed for pH and ORP using an Ag/AgCl electrode as shown in FIGS. 8.2 and 8.3.

A response is shown in the first hour in both of the above plots for leach tests 3, 4, 8, 9, 10, 12, 15, 16 and 19, which correspond to zero acid in the leach solution, except for test 8. Hourly readings were not taken for test #1. This is indicating some kind of response taking place at atmospheric pressure. This response is further investigated in the analysis continued on these samples below.

Copper and Free Acid were analyzed by titration and the results are shown in the tables below.

TABLE 8.3
Copper Titration Results on Final PLS
	Total ml	Copper
Test #	Added	(g/l)
1	14.4	22.87
2	14.5	23.03
3	6.1	9.69
4	22.1	35.11
5	22.5	35.74
6	6.7	10.64
7	6.3	10.01
8	14.9	23.67
9	6.3	10.01
10	24.5	38.92
11	23.8	37.81
12	22.9	36.38
13	24.0	38.12
14	6.2	9.85
15	6.0	9.53
16	6.0	9.53
17	6.1	9.69
18	22.9	36.38
19	23.5	37.33
7-2	4.7	7.47
13-2	18.7	29.70

TABLE 8.4
Free Acid Titration Results on Final PLS
	Total ml	Free Acid
Test #	Added	(g/l)
1	0.5	4.90
2	0.6	5.88
3	0.0	0.00
4	0.0	0.00
5	1.0	9.80
6	1.0	9.80
7	1.0	9.80
8	0.5	4.90
9	0.0	0.00
10	0.0	0.00
11	0.9	8.82
12	0.0	0.00
13	1.0	9.80
14	0.9	8.82
15	0.0	0.00
16	0.0	0.00
17	1.0	9.80
18	1.0	9.80
19	0.0	0.00
7-2	0.7	6.86
13-2	0.8	7.84

ICP was performed by Montana Tech/CAMP on leach solutions for copper, iron and arsenic. The results of this analysis are shown below. The copper numbers compare well to the copper titrations shown above.

TABLE 8.5
ICP by CAMP at Montana Tech
	Arsenic	Copper	Iron
	g/L	g/L	g/L
	1	0.117	23.120	0.608
	2	0.113	22.440	0.628
	3	0.002	8.942	0.101
	4	0.004	34.590	0.348
	5	0.055	35.040	0.252
	6	0.175	10.520	0.913
	7	0.078	10.040	0.389
	8	0.125	24.350	0.648
	9	0.017	10.310	0.560
	10	0.007	37.330	0.181
	11	0.204	38.600	1.262
	12	0.015	35.760	0.603
	13	0.073	37.440	0.434
	14	0.224	9.998	1.237
	15	0.003	9.531	0.227
	16	0.003	9.419	0.357
	17	0.064	9.085	0.321
	18	0.160	36.300	0.852
	19	0.007	37.640	0.134
	7-2	0.063	7.902	0.330
	13-2	0.061	29.960	0.332

8.2.2 Solid Leach Residue Analysis

Solid leach residues were sent to Idaho for assay by Chris Christopherson, Inc. for copper, iron and arsenic.

TABLE 8.6
Solid Leach Residue Assays Performed
by Chris Christopherson, Inc.
	Test #	Cu %	Fe %	As %
	1	17.33	29.48	6.78
	2	17.40	29.40	6.45
	3	16.64	30.65	6.84
	4	16.66	31.02	6.95
	5	17.18	29.56	6.34
	6	16.96	29.82	6.00
	7	17.52	28.86	5.67
	8	16.97	28.48	5.65
	9	17.12	29.42	5.80
	10	17.73	29.52	5.38
	11	17.77	29.12	6.70
	12	17.50	28.73	6.68
	13	17.49	28.28	6.64
	14	17.40	28.44	6.55
	15	16.86	28.25	6.69
	16	15.99	29.09	6.72
	17	17.07	29.11	6.39
	18	16.88	28.82	6.40
	19	16.62	29.28	6.50
	13-2	17.62	28.56	6.45
	7-2	16.92	29.25	6.24

8.2.3 Atmospheric Leach Results Summary

The Atmospheric Leach summary shown in the table below is the result of the mass balances performed based on the assays from above. The mass balance calculations are shown in Appendix C.

TABLE 8.7
Atmospheric Leach Results Summary
	Cu grams	Fe Extraction	As Extraction	Acid Consump.
Test ID	Diff Solids	%	%	g acid/g solid
1	0.51	11.48	12.12	0.022
2	0.55	12.34	13.88	−0.030
3	0.26	4.37	5.05	0.000
4	0.76	4.40	4.54	0.000
5	0.21	9.32	13.00	0.013
6	1.00	12.08	16.39	0.039
7	0.36	16.45	20.99	0.135
8	0.66	13.57	18.05	0.037
9	0.78	8.52	10.54	0.000
10	0.16	7.36	11.76	0.000
11	0.77	15.42	14.23	0.062
12	0.47	8.08	5.51	0.000
13	0.24	15.43	13.91	0.094
14	1.03	17.17	16.65	0.066
15	0.32	11.53	7.32	0.000
16	0.99	6.91	5.81	0.000
17	0.35	13.93	15.88	0.073
18	0.80	11.37	12.94	0.016
19	0.17	4.42	5.22	0.000
7-2	0.36	18.27	18.58	0.176
13-2	0.41	17.71	19.28	0.017

Test #7 resulted in about 21% arsenic extracted at 10 gpl sulfuric acid, 10 grams of solids, 10 gpl Cu²⁺, and 75° C. for 2 hours. This test also shows an apparent copper and arsenic separation with a 7% copper gain in the solid indicating the possibility of a copper-arsenic metathesis reaction occurring.

8.2.4 Stat-Ease Modeling

Stat-Ease Design Expert software was used for modeling of the atmospheric leach results to determine significant factors and to perform some optimization. Initial acid content was determined to be the most significant effect on PLS arsenic content. Temperature also had a slight positive effect. A 3-D surface plot of these effects on the arsenic response is shown in FIG. 8.4.

This modeling resulted in the following Final Equation in Terms of Actual Factors with an R-squared of 0.72935 and standard deviation of 2.73061:

$\begin{array}{cc}\mathrm{As}\mathrm{Extraction}=+4.75269+0.85291*\mathrm{Initial}\mathrm{Acid}+0.055236*\mathrm{Temperature}& \left(8.1\right)\end{array}$

Additional statistical data, including the 95% confidence intervals, for this model are shown in Appendix D.

8.3 Leach Residue Characterization

MLA was performed at Montana Tech/CAMP on the #7 leach residue sample. The sample was dried overnight and prepared by cold-mounting in epoxy resin.

The major phase in the residue sample was pyrite at 77% with the minor phase as enargite at 23%. Combined, the remaining minerals were less than 1% of the residue mineralogy as shown below.

TABLE 8.8
Phase/Mineral Concentrations for Leach Residue #7
	Mineral	Formula	Wt %
	Pyrite	FeS2	76.7
	Enargite	Cu3AsS4	23.0
	Quartz	SiO2	0.14
	Chalcocite	Cu2S	0.10
	Sphalerite	ZnS	0.03
	Chalcopyrite	CuFeS2	0.03
	Rutile	TiO2	0.01
	FeO	Fe2.5O3.5	P
	Molybdenite	MoS2	P
	P—mineral present, found at less than 0.01%
	ND—mineral not detected

Copper was 18%, arsenic 6.8% and iron was 30% according to the MLA-calculated bulk elemental analysis shown in the table below.

TABLE 8.9
MLA-Calculated Bulk Elemental Analysis
Element    Residue #7
Sulfur     45.8
Iron       29.7
Copper     17.5
Arsenic    6.83
Oxygen     0.08
Silicon    0.06
Zinc       0.02
Titanium   P
Molybdenum P
P—element present at less than 0.01%
ND—element not detected

The elemental distribution for arsenic, copper and iron is due to the distribution of essentially two minerals. Copper and arsenic in the sample are due to the enargite while the iron can be attributed to the pyrite.

FIG. 8.5 is a classified MLA image from the residue. Pyrite is shown as the green phase, the light blue is enargite, and the grayish-blue fines are a fine-grained mixture of pyrite and enargite that is composed of approximately 92% pyrite and 8% enargite by weight.

The backscatter electron image (BSE) image in FIG. 8.6 is from the same analytical frame as the MLA image shown in the above figure. Enargite (En) is the brightest phase and pyrite (Py) is slightly darker. It can be seen from the BSE image that much of the fine grained material is relatively bright and is classified as enargite. It is more difficult to discern the gray level of the fine particles as the background between the fine particles makes them appear darker.

Chapter 9

Autoclave Leaching

Before starting pressure oxidation experiments another Design of Experiments (DOE) matrix was generated using Stat-Ease Design Expert 8.0 software. This DOE matrix is shown below where −1 is the low, 0 is a center point, and 1 is the high.

TABLE 9.1
½ Factorial DOE for Pressure Oxidation Leach Tests
		Factor 1	Factor 2	Factor 3	Factor 4	Factor 5	Factor 6
		Time	Temp	Cu	Acid	Solids	O2 press
Std	Run	hr	deg C.	g/L	g/L	g	psi
1	5	−1	−1	−1	−1	−1	−1
2	8	1	−1	−1	−1	−1	1
3	25	−1	1	−1	−1	−1	1
4	35	1	1	−1	−1	−1	−1
5	6	−1	−1	1	−1	−1	1
6	21	1	−1	1	−1	−1	−1
7	24	−1	1	1	−1	−1	−1
8	16	1	1	1	−1	−1	1
9	26	−1	−1	−1	1	−1	1
10	2	1	−1	−1	1	−1	−1
11	11	−1	1	−1	1	−1	−1
12	12	1	1	−1	1	−1	1
13	23	−1	−1	1	1	−1	−1
14	32	1	−1	1	1	−1	1
15	28	−1	1	1	1	−1	1
16	17	1	1	1	1	−1	−1
17	34	−1	−1	−1	−1	1	1
18	22	1	−1	−1	−1	1	−1
19	4	−1	1	−1	−1	1	−1
20	30	1	1	−1	−1	1	1
21	7	−1	−1	1	−1	1	−1
22	10	1	−1	1	−1	1	1
23	33	−1	1	1	−1	1	1
24	9	1	1	1	−1	1	−1
25	1	−1	−1	−1	1	1	−1
26	20	1	−1	−1	1	1	1
27	29	−1	1	−1	1	1	1
28	13	1	1	−1	1	1	−1
29	27	−1	−1	1	1	1	1
30	15	1	−1	1	1	1	−1
31	3	−1	1	1	1	1	−1
32	31	1	1	1	1	1	1
33	14	0	0	0	0	0	0
34	19	0	0	0	0	0	0
35	18	0	0	0	0	0	0

The experimental equipment setup can be seen in the FIG. 9.1.

The equipment consisted of a 2-liter titanium Grade 2 autoclave from Autoclave Engineers with a Universal Reactor Controller which monitors Magnedrive agitation, reactor temperature, heating jacket over-temperature, and process pressure.

9.1 Autoclave/Pressure Oxidation Leaching Tests

Based on the results from the atmospheric pressure leach tests, it was decided to keep the initial leach solution copper concentration the same. The amount of solids was cut in half to conserve sample since the previous leach tests showed no effect of solids. The initial acid concentration was increased as it was the largest effect based on Stat-Ease modeling of the previous tests. Based on the literature, complete dissolution of enargite was achieved at a sulfuric acid content below 0.2 molar (but at higher temperature); higher concentration had a negligible effect on dissolution (Padilla, Rivas, and Ruiz 2008). A stoichiometric amount of oxygen without continuous flow was required for chalcopyrite to convert to digenite (Bartlett et al. 1986; Bartlett 1992).

The actual order in which these tests were performed differed slightly from the DOE so the following table shows the experimental order and also shows the actual numerical values of the test variables.

TABLE 9.2
Experimental Order of Pressure Oxidation Leach Tests
	Factor 1	Factor 2	Factor 3	Factor 4	Factor 5	Factor 6
	Time	Temp	Cu 2+	Acid	Solids	O2 press
Test #	Ins	deg C.	g/L	g/L	g	psi
1	0.5	100	10	30	15	0
2	0.5	100	10	10	5	0
3	0.5	100	40	30	5	0
4	0.5	100	40	10	15	0
5	0.5	160	40	10	5	0
6	0.5	160	10	30	5	0
7	1.0	100	10	10	15	0
8	1.0	100	40	30	15	0
9	1.0	100	40	10	5	0
10	1.0	100	10	30	5	0
11	0.5	160	10	10	15	0
12	0.5	160	40	30	15	0
13	1.0	160	10	10	5	0
14	1.0	160	40	30	5	0
15	1.0	160	40	10	15	0
16	1.0	160	10	30	15	0
17	0.75	130	25	20	10	50
18	0.75	130	25	20	10	50
19	0.75	130	25	20	10	50
20	0.5	100	40	10	5	100
21	0.5	100	10	30	5	100
22	0.5	100	10	10	15	100
23	0.5	100	40	30	15	100
24	0.5	160	10	10	5	100
25	0.5	160	40	30	5	100
26	0.5	160	40	10	15	100
27	0.5	160	10	30	15	100
28	1.0	100	10	30	15	100
29	1.0	100	10	10	5	100
30	1.0	100	40	30	5	100
31	1.0	100	40	10	15	100
32	1.0	160	40	10	5	100
33	1.0	160	10	30	5	100
34	1.0	160	10	10	15	100
35	1.0	160	40	30	15	100

9.1.1 Autoclave Leach Test Procedure

The procedure for the autoclave leach tests was consistent throughout all 35 designed experiments.

• • 1. Mix 1 liter of leach feed solution according to acid and copper ion concentrations as specified in the DOE matrix
  • 2. Split and weigh out solid feed sample according to solids weight as specified in the DOE matrix
  • 3. Charge the autoclave with liter of leach solution and preheat to 90° C.
  • 4. Once at this temperature, enargite concentrate sample is added and the autoclave is sealed
  • 5. Turn on and set agitator at 500 rpm
  • 6. The oxygen is admitted, if used, the pressure is then fixed to the desired value, and oxygen is turned off
  • 7. Record leaching start time and the system is allowed to react to the temperature and time specified in the DOE
  • 8. At the end of the experiment, the autoclave is rapidly cooled by circulating cold water through the cooling coil
  • 9. Rinse the contents of autoclave into #40 Whatman filter paper in funnel with distilled water to drip filter (record weight of filter paper before filtering)
  • 10. Collect solution and record final volume
  • 11. Rinse solids with distilled water and allow to drip filter again
  • 12. Place filter paper containing solids in drying oven overnight at 90° C.
  • 13. Remove dry filter and solids from oven and record final weight

9.2 Analysis

The following sections discuss the results of analysis performed on both solids and liquids from the leach tests outlined above.

9.2.1 Pregnant Leach Solution Analysis

Copper and Free Acid were analyzed by titration and the results are shown in the tables below.

TABLE 9.3
Copper Titration Results on Final PLS
	Total ml	Copper
Test #	Added	(g/l)
1	3.3	10.48
2	2.8	8.90
3	11.0	34.95
4	9.9	31.45
5	10.8	36.85
6	2.5	7.94
7	2.4	7.62
8	9.5	30.18
9	11.5	36.54
10	2.4	7.62
11	1.8	5.72
12	10.1	32.09
13	2.2	6.99
14	8.1	25.73
15	7.7	24.46
16	1.9	6.04
17	5.4	17.16
18	6.2	19.70
19	5.3	16.84
20	23.5	37.33
21	6.0	9.53
22	4.3	6.83
23	20.2	32.09
24	2.5	7.94
25	23.5	37.33
26	2.2	6.99
27	5.4	8.58
28	2.3	7.31
29	2.6	8.26
30	10.1	32.09
31	7.9	25.10
32	9.5	30.18
33	2.5	7.94
34	3.2	10.17
35	6.8	21.60

TABLE 9.4
Free Acid Titration Results on Final PLS
	Total ml	Free Acid
Test #	Added	(g/l)
1	3.3	31.85
2	0.9	8.82
3	2.8	27.44
4	0.8	7.84
5	0.9	9.02
6	2.4	23.52
7	0.9	8.82
8	2.2	21.56
9	0.9	8.82
10	2.3	22.54
11	0.8	7.64
12	2.4	23.52
13	0.7	6.86
14	0.9	8.82
15	1.5	14.70
16	2.3	22.54
17	1.5	14.21
18	1.5	14.70
19	1.6	15.68
20	4.6	45.08
21	3.5	34.30
22	0.9	8.82
23	3.1	30.38
24	1.0	9.80
25	3.8	37.24
26	0.7	6.86
27	2.9	28.42
28	2.1	20.58
29	0.9	8.33
30	2.4	23.52
31	0.7	6.86
32	0.8	7.84
33	2.5	24.50
34	0.8	7.84
35	2.1	20.58

ICP was performed by Montana Tech/CAMP and Hazen Research on leach solutions for copper, iron and arsenic. The results of this analysis are shown below. The copper numbers compare well to the copper titrations shown above.

TABLE 9.5
ICP results on PLS
	Arsenic	Copper	Iron
	g/L	g/L	g/L
	1	0.138	9.187	0.708
	2	0.038	7.031	0.203
	3	0.038	33.580	0.182
	4	0.094	29.860	0.521
	5	0.054	35.510	0.222
	6	0.045	6.296	0.180
	7	0.098	6.150	0.467
	8	0.098	30.840	0.475
	9	0.040	35.500	0.208
	10	0.037	5.761	0.180
	11	0.139	9.045	0.622
	12	0.139	32.770	0.566
	13	0.046	4.714	0.177
	14	0.046	25.560	0.166
	15	0.141	25.590	0.518
	16	0.131	8.296	0.536
	17	0.043	19.780	0.114
	18	0.037	20.260	0.088
	19	0.037	20.600	0.071
	20	0.012	40.50	0.106
	21	0.013	9.77	0.056
	22	0.012	7.10	0.169
	23	0.012	33.70	0.18
	24	0.064	6.800	0.071
	25	0.011	38.90	0.223
	26	0.134	8.565	0.185
	27	0.025	9.12	0.298
	28	0.056	5.848	0.215
	29	0.015	7.090	0.068
	30	0.032	31.860	0.095
	31	0.029	26.800	0.233
	32	0.069	25.540	0.298
	33	0.112	7.471	0.099
	34	0.249	7.846	0.264
	35	0.172	28.500	0.165

9.2.2 Solid Leach Residue Analysis

Solid leach residues were sent to Chris Christopherson, Inc. and Hazen Research for copper, iron and arsenic.

TABLE 9.6
Solid Leach Residue Assays
	Arsenic	Copper	Iron
	%	%	%
	1	5.77	17.76	30.67
	2	6.24	17.60	30.34
	3	5.90	16.56	30.35
	4	6.26	17.43	30.64
	5	3.16	11.61	16.15
	6	5.89	17.66	31.82
	7	6.28	17.59	31.02
	8	6.16	17.01	30.45
	9	5.64	16.03	28.98
	10	6.02	16.69	30.47
	11	5.58	19.59	29.03
	12	5.67	19.93	29.35
	13	5.37	20.95	28.01
	14	5.72	22.05	29.11
	15	4.94	25.71	26.86
	16	5.72	19.70	30.60
	17	5.52	14.46	31.60
	18	4.83	12.94	30.52
	19	5.12	14.14	30.80
	20	3.06	19.10	28.10
	21	2.75	17.90	29.10
	22	2.79	18.20	28.10
	23	3.05	18.00	28.60
	24	4.01	10.90	34.02
	25	3.56	19.70	26.70
	26	4.80	13.18	32.90
	27	2.62	18.10	28.30
	28	5.65	15.12	31.43
	29	5.30	15.11	29.93
	30	5.95	15.99	29.24
	31	6.25	16.38	29.40
	32	5.77	14.99	29.11
	33	4.39	11.53	34.15
	34	4.85	12.87	33.80
	35	4.67	12.38	32.81

Hazen also analyzed the sulfur species on the #33 composite solid residue as shown below.

TABLE 9.7
Sulfur Analysis on #33 POX Residue
Total Sulfur, % 44.2
SO4, %          <0.02
Elemental S, %  0.50
Sulfide, %      43.68

Most of the sulfur species are in the sulfide form in the solid residues and very little as elemental sulfur, which indicates the lack of a sulfur product layer surrounding the solid particles.

9.2.3 Pressure Oxidation Leach Results Summary

The PDX Leach summary shown in the table below is the result of the mass balances performed based on the assays from above. The mass balance calculations are shown in Appendix C.

TABLE 9.8
POX Leach Results Summary
	Cu grams	Fe Extraction	As Extraction	Acid Consump.
Test ID	Diff Solids	%	%	g acid/g solid
1	0.54	17.36	22.84	−0.059
2	0.17	16.87	19.63	0.108
3	0.20	15.49	20.99	−0.166
4	0.53	15.52	18.50	0.068
5	0.35	31.72	36.46	0.141
6	0.21	16.99	25.47	0.467
7	0.49	13.86	18.43	−0.027
8	0.55	14.62	19.05	0.328
9	0.20	16.74	21.32	0.160
10	0.24	18.22	22.67	0.702
11	0.51	21.54	27.08	0.139
12	0.23	17.55	24.65	0.176
13	0.13	23.64	30.94	0.188
14	0.05	19.25	26.94	4.668
15	−0.52	19.34	28.54	−0.689
16	0.40	18.66	26.40	0.093
17	0.42	3.80	16.14	0.295
18	0.55	4.12	18.47	0.263
19	0.50	4.62	17.97	0.169
20	0.04	10.41	24.95	−7.883
21	0.06	6.01	26.60	−1.203
22	0.16	7.58	23.37	−0.035
23	0.11	6.22	21.71	−0.438
24	0.46	9.82	39.93	−0.450
25	0.05	19.06	22.98	−1.725
26	0.95	6.07	28.70	0.092
27	0.17	9.63	25.91	−0.154
28	0.67	7.57	17.09	0.100
29	0.24	9.15	17.62	−0.023
30	0.18	10.19	17.98	0.507
31	0.39	7.87	9.85	0.068
32	0.46	35.73	39.90	0.169
33	0.44	10.62	47.19	0.443
34	1.15	10.21	39.96	0.018
35	1.07	6.61	34.65	0.031

Test #33 resulted in about 47% arsenic extracted at 30 gpl sulfuric acid, 5 grams of solids, 10 gpl Cu^2±, and 160° C. for 1 hour.

9.2.4 Stat-Ease Modeling

Stat-Ease Design Expert software was used for modeling of the PDX leach results to determine significant factors and to perform some optimization. Time appeared to have the most significant effect on PLS arsenic content. A 3-D surface plot of these effects on the arsenic response is shown in FIG. 9.2.

This modeling resulted in the following Final Equation in Terms of Actual Factors with an R-squared of 0.6049 and standard deviation of 0.018 after excluding points from Tests 12, 16, 17 and 18:

$\begin{array}{cc}1/\left(\mathrm{As}\mathrm{Extraction}\right)=& \left(9.1\right)\\ \begin{array}{cc}-0.021622& \\ +0.021050& *\mathrm{Time}\\ +5.56403E\text{-}004& *\mathrm{Temperature}\\ -5.28853E\text{-}004& *\mathrm{Cu}2+\\ +8.36188E\text{-}004& *\mathrm{Acid}\\ +6.52218E\text{-}003& *\mathrm{Solids}\\ -2.60371E\text{-}003& *\mathrm{Time}*\mathrm{Solids}\\ -1.33188E\text{-}005& *\mathrm{Temperature}*\mathrm{Acid}\\ -3.75247E\text{-}005& *\mathrm{Temperature}*\mathrm{Solids}\\ +1.81562E\text{-}005& *\mathrm{Cu}2+*\mathrm{Acid}\end{array}& \end{array}$

Additional statistical data, including the 95% confidence intervals, for this model are shown in Appendix D.

9.3 Verification Tests

Four pressure oxidation tests were performed at the test conditions that resulted in the highest arsenic extraction from above, which was Marca Punta PDX Test #33. The results of these tests are as follows.

Copper and Free Acid were analyzed by titration and the results are shown in the tables below.

TABLE 9.9
Copper Titration Results on Final PLS
		Total ml	Copper
	Test #	Added	(g/l)
	33-2	6.3	10.01
	33-3	6.1	9.69
	33-4	5.9	9.37
	33-5	5.9	9.37

TABLE 9.10
Free Acid Titration Results on Final PLS
		Total ml	Free
	Test #	Added	Acid
	33-2	4.6	45.08
	33-3	3.8	37.24
	33-4	3.5	34.30
	33-5	2.6	25.48

ICP was performed by Hazen Research on leach solutions for copper, iron and arsenic. The results of this analysis are shown below. The copper numbers compare well to the copper titrations shown above.

TABLE 9.11
ICP results on PLS
	Arsenic	Copper	Iron
	g/L	g/L	g/L
	33-2	0.043	10.70	0.263
	33-3	0.055	10.60	0.253
	33-4	0.066	9.63	0.228
	33-5	0.066	9.57	0.275

A composite solid leach residue was sent to Hazen Research for copper, iron and arsenic and results are shown below.

TABLE 9.12
Solid Leach Residue Assays
	Arsenic	Copper	Iron
	%	%	%
	33 Comp	2.38	14.4	30.9

The PDX Verification Leach summary shown in the table below is the result of the mass balances performed based on the assays from above.

TABLE 9.13
POX Verification Leach Results Summary
	Cu grams	Fe Extraction	As Extraction	Acid Consump.
Test ID	Diff Solids	%	%	g acid/g solid
33-2	0.43	26.66	44.32	0.906
33-3	0.40	24.55	46.67	2.337
33-4	0.40	22.91	49.39	0.749
33-5	0.39	24.87	49.31	2.681

9.4 Leach Residue Characterization

MLA was performed at Montana Tech/CAMP on the Test 33 composite sample. The sample was disaggregated by passing the sample though a 200 mesh sieve prior to cold-mounting in epoxy resin.

Pyrite was the most abundant phase. The enargite content was inversely related to the pyrite concentration. Covellite was present at minor levels. Quartz was present at trace levels and the sulfides sphalerite and chalcopyrite were found in the sample. The leach residue modal mineralogy as determined by MLA is shown below compared to the head sample.

TABLE 9.14
Mineral Grade for POX Head Sample
& Leach Residue #33 Composite
			Head	Residue
	Mineral	Formula	Wt %	Wt %
	Pyrite	FeS2	61.4	67.8
	Enargite	Cu3AsS4	38.0	31.2
	Covellite	CuS		0.46
	Quartz	SiO2	0.27	0.32
	Chalcocite	Cu2S	0.20
	Chalcopyrite	CuFeS2	0.04	0.08
	Sphalerite	ZnS	0.02	0.03
	Galena	PbS	0.01
	Zircon	ZrSiO4		0.03
	Chromferide	Fe3Cu0.4		0.02
	K_Feldspar	KAlSi3O8		0.01
	Sulfur	S		0.01
	Rutile	TiO2		0.01
	Almandine	Fe3Al2(SiO4)3		P
	Alunite	KAl3(SO4)2(OH)6		P
	Calcite	CaCO3		P
	Albite	NaAlSi3O8		P
	FeO	Fe2.5O3.5	0.03	P
	Andradite	Ca3Fe2(SiO4)3		ND
	Copper	Cu		ND
	Pyroxene	CaMgSi2O6		ND
	P—mineral present, found at less than 0.01%
	ND—mineral not detected

The MLA-calculated elemental values show in the table below are based on the MLA-determined modal mineralogy and assigned chemical formulas as presented above as well as the estimated mineral phase density. Enargite was identified as a mineral containing arsenic as shown in Table 9.16. Copper behaved similarly to arsenic as enargite was the main mineral source of copper with minor contribution from covellite. The primary source of iron in the samples was from the mineral pyrite, so the iron content was directly related to it.

Based on enargite being the source of arsenic, the MLA-based arsenic extraction comes out to 0.1559 grams of arsenic leached compared to the 0.13 grams of arsenic calculated in the mass balance, as seen in Appendix C.

Referring back to the postulated enargite metathesis reaction 5.9 from the Eh-pH thermodynamic study, the MLA mineralogical results of PDX Test #33 qualitatively confirm this has occurred. As seen, while the enargite mineral phase is decreasing the covellite phase is created in Table 9.14. As well, the overall test mass balance points to a gain of copper mass in the leached solids. However, more focused testing on a larger scale would be necessary to confirm this as the mass of sample treated in PDX Test #33 was 5 grams.

TABLE 9.15
MLA-Calculated Bulk Elemental Analysis
Element   wt %
Sulfur    46.6
Iron      31.6
Copper    15.4
Arsenic   5.94
Oxygen    0.19
Silicon   0.16
Zinc      0.02
Zirconium 0.02
Titanium  0.01
Aluminum  P
Chromium  P
Potassium P
Calcium   P
Carbon    P
Sodium    P
Hydrogen  P
Magnesium ND
P—element present at less than 0.01%
ND—element not detected

TABLE 9.16
Arsenic Distribution for #33 Composite
Mineral  wt %
Enargite 100.0
Total    100.0

TABLE 9.17
Copper Distribution for #33 Composite
Mineral      wt %
Enargite     97.8
Covellite    1.99
Chalcopyrite 0.17
Copper       0.00
Total        100.0

TABLE 9.18
Iron Distribution for #33 Composite
Mineral      wt %
Pyrite       99.9
Chalcopyrite 0.07
Chromferide  0.05
Almandine    0.00
FeO          0.00
Andradite    0.00
Total        100.0

FIG. 9.3 is a classified MLA image from a selected frame obtained during analysis of the #33 composite leach residue with an enargite particle highlighted. Note the appearance of a covellite phase after leaching.

The backscatter electron image (BSE) image in FIG. 9.4 is from the same analytical frame as the MLA image shown in the above figure with the particle highlighted in the MLA image, circled in the BSE image. Enargite (En) particles appear slightly brighter than the pyrite (Py) particles in the BSE image.

The particle size distribution and grain size distributions for pyrite and enargite are shown in FIG. 9.5. The particle size distribution P80 is 40 μm and the grain size P80's for both pyrite and enargite are near 40 also. This is because the grind size is smaller than the “true” grain size for the minerals and they are the major constituents of the samples. It follows that liberation should be good for both minerals as seen in FIG. 9.6 is 72 to 87% liberated, with enargite being less liberated, which is due to it being less abundant than pyrite.

9.5 Kinetic Tests

Based on the maximum arsenic extraction coupled with the evidence of a metathesis reaction, kinetic tests were performed using the same autoclave in 15 minute increments for PDX Test #33. The following table shows the experimental conditions at which the tests were performed.

TABLE 9.19
Leach Conditions for Kinetic Tests
	Time	Temp	Cu 2+	Acid	Solids	O2 press
Test ID	hrs	deg C.	g/L	g/L	g	psi
K-1	0.25	145	10	30	5	100
K-2	0.50	145	10	30	5	100
K-3	0.75	145	10	30	5	100
K-4	1.00	145	10	30	5	100
K-5	1.50	145	10	30	5	100

9.5.1 Kinetic Analysis

The kinetic leach tests were analyzed and the results are as follows. Copper and Free Acid were analyzed by titration and the results are shown in the tables below.

TABLE 9.20
Copper Titrations
		Total ml	Copper
	Test #	Added	(g/l)
	K-1	5.6	8.90
	K-2	5.9	9.37
	K-3	5.4	8.58
	K-4	5.8	9.21
	K-5	6.0	9.53

TABLE 9.21
Free Acid Titrations
		Total ml	Free Acid
	Test #	Added	(g/l)
	K-1	4.2	41.16
	K-2	4.3	42.14
	K-3	4.0	39.20
	K-4	5.1	49.98
	K-5	4.2	41.16

ICP was performed by Hazen Research on leach solutions for copper, iron and arsenic. The results of this analysis are shown below. The copper numbers compare well to the copper titrations shown above.

TABLE 9.22
ICP Results on PLS Performed by Hazen Research
	Arsenic	Copper	Iron
	g/L	g/L	g/L
	K-1	0.016	9.30	0.105
	K-2	0.031	9.33	0.185
	K-3	0.05	8.83	0.168
	K-4	0.083	9.70	0.404
	K-5	0.076	8.50	0.245

Solid leach residues were sent to Hazen Research for copper, iron and arsenic and results are shown below.

TABLE 9.23
Solid Leach Residue Assays Performed by Hazen Research
	Arsenic	Copper	Iron
	%	%	%
	K-1	3.16	18.3	28.3
	K-2	2.62	17.3	28.2
	K-3	2.41	15.1	30.9
	K-4	2.47	13.1	30.3
	K-5	2.27	12.7	31.5

TABLE 9.24
Kinetic Leach Results Summary
	Cu grams	Fe Extraction	As Extraction	Acid Consump.
Test ID	Diff Solids	%	%	g acid/g solid
K-1	0.08	10.82	26.19	1.459
K-2	0.17	16.88	34.91	2.040
K-3	0.31	17.02	44.39	−5.220
K-4	0.50	36.93	55.45	−2.891
K-5	0.47	25.86	54.33	−2.173

In general, the arsenic extraction increased as expected as time progressed, with the exception of Test K−5. These tests actually exceeded the recovery for Test #33 at about 47% by about 8% at the 1 hour point. These tests were all performed at 30 gpl sulfuric acid, 5 grams of solids, 10 gpl Cu²⁺, and 160° C.

9.5.2 Kinetic Leach Residue Characterization

MLA was performed on the solid residues from each kinetic test at Montana Tech/CAMP. The sample was disaggregated by passing the sample though a 200 mesh sieve prior to cold-mounting in epoxy resin.

Pyrite was the most abundant phase. The enargite content was inversely related to the pyrite concentration. Covellite was present at minor levels. Quartz was present at trace levels and the sulfides sphalerite and chalcopyrite were found in the sample. The modal mineralogy was determined by MLA is shown below.

TABLE 9.25
Phase/Mineral Concentrations for K-1 through K-5 Leach Residues in wt %
Mineral	Formula	Feed	K-1	K-2	K-3	K-4	K-5
Pyrite	FeS2	61.4	62.4	64.1	67.7	73.9	69.4
Enargite	Cu3AsS4	38.0	35.3	33.8	31.0	25.2	29.2
Covellite	CuS		1.73	1.33	0.76	0.24	0.56
Quartz	SiO2	0.27	0.26	0.49	0.27	0.41	0.58
Chalcocite	Cu2S	0.20	ND	ND	ND	ND	ND
Chalcopyrite	CuFeS2	0.04	0.09	0.13	0.12	0.07	0.14
Sphalerite	ZnS	0.02	0.20	0.13	0.07	0.03	0.02
Galena	PbS	0.01	ND	ND	ND	ND	ND
Zircon	ZrSiO4	ND	P	ND	ND	ND	ND
Chromferide	Fe3Cu0.4	ND	0.02	0.02	0.02	0.01	0.02
K_Feldspar	KAlSi3O8	ND	P	0.01	0.01	0.01	0.01
Sulfur	S	ND	ND	ND	ND	0.06	0.05
Rutile	TiO2	ND	0.02	0.02	0.02	0.03	0.03
Almandine	Fe3Al2(SiO4)3	ND	P	P	P	P	ND
Alunite	KAl3(SO4)2(OH)6	ND	P	P	P	P	P
Calcite	CaCO3	ND	ND	ND	P	P	P
Albite	NaAlSi3O8	ND	ND	0.01	ND	P	P
FeO	Fe2.5O3.5	0.03	ND	ND	P	P	P
Andradite	Ca3Fe2(SiO4)3	ND	ND	P	ND	0.01	ND
Copper	Cu	ND	ND	P	0.01	P	ND
Pyroxene	CaMgSi2O6	ND	P	0.01	P	ND	ND
P—mineral present, found at less than 0.01%
ND—mineral not detected

The MLA-calculated elemental values show in the table below are based on the MLA-determined modal mineralogy and assigned chemical formulas as presented above as well as the estimated mineral phase density. Enargite was identified as a mineral containing arsenic as shown in Table 9.27. Copper behaved similarly to arsenic as enargite was the main mineral source of copper with minor contribution from covellite. The primary source of iron in the samples was from the mineral pyrite, so the iron content was directly related to it. This deportment was not provided for the feed sample.

TABLE 9.2
MLA-Calculated Bulk Elemental Analysis
Element	Feed	K-1	K-2	K-3	K-4	K-5
Sulfur	45.3	45.5	45.8	46.6	47.9	46.9
Iron	28.6	29.1	29.9	31.6	34.5	32.4
Copper	18.6	18.3	17.3	15.6	12.4	14.5
Arsenic	7.23	6.71	6.43	5.9	4.79	5.55
Oxygen	0.15	0.15	0.28	0.16	0.24	0.33
Silicon	0.12	0.13	0.23	0.13	0.19	0.27
Zinc	0.01	0.14	0.08	0.05	0.02	0.01
Lead	0.01	ND	ND	ND	ND	ND
Zirconium	ND	P	ND	ND	ND	ND
Titanium	ND	0.01	0.01	0.01	0.02	0.02
Aluminum	ND	P	P	P	P	P
Chromium	ND	P	P	P	P	P
Potassium	ND	P	P	P	P	P
Calcium	ND	P	P	P	P	P
Carbon	ND	ND	ND	P	P	P
Sodium	ND	ND	P	ND	P	P
Hydrogen	ND	P	P	P	P	P
Magnesium	ND	P	P	P	ND	ND
P—element present at less than 0.01%
ND—element not detected

TABLE 9.27
Arsenic Distribution for #33 Composite
	Mineral	K-1	K-2	K-3	K-4	K-5
	Enargite	100.0	100.0	100.0	100.0	100.0
	Total	100.0	100.0	100.0	100.0	100.0

TABLE 9.28
Copper Distribution for #33 Composite
Mineral	K-1	K-2	K-3	K-4	K-5
Enargite	93.5	94.6	96.4	98.5	97.1
Covellite	6.31	5.13	3.25	1.29	2.55
Chalcopyrite	0.17	0.26	0.27	0.21	0.33
Copper	0.00	0.01	0.04	0.02	0.00
Total	100.0	100.0	100.0	100.0	100.0

TABLE 9.29
Iron Distribution for #33 Composite
Mineral	K-1	K-2	K-3	K-4	K-5
Pyrite	99.8	99.8	99.8	99.9	99.8
Chalcopyrite	0.09	0.13	0.12	0.07	0.13
Chromferide	0.07	0.05	0.04	0.03	0.04
Almandine	0.00	0.00	0.00	0.00	0.00
FeO	0.00	0.00	0.00	0.01	0.00
Andradite	0.00	0.00	0.00	0.01	0.00
Total	100.0	100.0	100.0	100.0	100.0

A pyrite particle is highlighted in the classified MLA image from the K−1 leach residue in FIG. 9.7.

The BSE image of the K−1 leach residue shows the circled pyrite particle that displays its crystalline form in FIG. 9.8.

The particle and grain size distributions and locking for pyrite and enargite are shown in FIG. 9.9 and FIG. 9.10, respectively. The particle and grain size is similar to the previous sample with a P80 of 38 μm. Liberation is 73 to 83% with pyrite being slightly more liberated than enargite, which is also similar to what was observed with the previous sample.

The highlighted particle in FIG. 9.11 shows the association between pyrite and enargite in the MLA image from the K−2 sample.

The contrast between enargite (En) and pyrite (Py) can be seen in the BSE image in FIG. 9.12.

The particle size, grain size and liberation data in FIG. 9.13 and FIG. 9.14 are similar to the previous samples. The particle size P80 was about 45 μm with the grain size P80's around 40 to 45 μm and liberation was 73 to 83%.

Covellite is highlighted in the leach residue from sample K−3 in FIG. 9.15.

The BSE image from the K−3 leach residue in FIG. 9.16 has a particle of covellite (Cov) circled. The mottled appearance is caused by the presence of some attached silicate.

Particle size and grain size data for the K−3 leach residue is shown in FIG. 9.17 with the P80's all being around 40 μm. Pyrite liberation was about 84% and the enargite, which was slightly less than seen in previous samples, at about 62% as seen in FIG. 9.18.

The MLA image in FIG. 9.19 highlights a pyrite particle with a quartz inclusion.

The BSE image shows the pyrite particle with a quartz inclusion in FIG. 9.20.

The particle size distribution for the K−4 residue P80 was 50 μm while the grain size P80 was 45 μm for enargite and about 50 μm for pyrite as seen in FIG. 9.21. Overall liberation was slightly lower in this sample than in the others with about 53% liberation for enargite and 77% liberation for pyrite as seen by the locking data in FIG. 9.22.

A classified MLA image from the K−5 leach residue is shown in FIG. 9.23.

Particles of quartz (Qtz), enargite (En), and pyrite (Py) are identified in the BSE image from the K−5 residue in FIG. 9.24.

Particle size and pyrite and enargite grain size P80's were all near 50 μm for the K−5 leach residue as seen in FIG. 9.25. Enargite liberation was 63% and pyrite liberation was 78% according to the liberation data in FIG. 9.26.

9.5.3 Kinetic Modeling

The Shrinking Core Model for spherical particles of unchanging size in a heterogeneous system can be applied to the system. The model suggests five steps that occur in succession during the reaction:

• • 1. Diffusion of reactant A through the film around the particle to the solid surface.
  • 2. Penetration and diffusion of A though the ash layer of the particle to the surface of the unreacted core.
  • 3. Reaction of A with the solid at this reaction surface.
  • 4. Diffusion of products through the ash back to the exterior surface of the solid.
  • 5. Diffusion of products through the film back into the main fluid.The step with the highest resistance, being the slowest, is considered the rate-controlling step. FIG. 9.27 below shows the shrinking core model and its associated concentration profile where the fluid is a gas, rather than a liquid.

When diffusion through the fluid film is controlling, the rate is controlled by the concentration gradient in the fluid as shown in the equation and FIG. 9.28. The gradient can be minimized by increasing agitation in the system.

$\begin{array}{cc}\begin{array}{c}-\frac{1}{S_{\mathrm{ex}}}\frac{N_B}{t}=-\frac{1}{4\pi R^2}\frac{N_B}{t}\\ =\frac{b}{4\pi R^2}\frac{N_B}{t}\\ ={\mathrm{bk}}_g\left(C_{\mathrm{Ag}}-C_{\mathrm{As}}\right)\\ =bk_gC_{\mathrm{Ag}}\\ =\mathrm{constant}\end{array}& \left(9.2\right)\end{array}$

When diffusion through the ash layer controls, particle size and surface area will determine the rate as shown in the equation and FIG. 9.29.

$\begin{array}{cc}-\frac{N_A}{t}=4\pi r^2Q_A=4\pi r^2Q_{\mathrm{As}}=4\pi r_c^2Q_{\mathrm{As}}=\mathrm{constant}& \left(9.3\right)\end{array}$

When the chemical reaction controls, the rate is as shown in Equation 9.4 and FIG. 9.30 below. Increasing the temperature will increase the rate of reaction according to the Arrhenius relationship as seen in Equation 9.5.

$\begin{array}{cc}-\frac{1}{4\pi r_c^2}\frac{N_A}{t}=-\frac{b}{4\pi r_c^2}\frac{N_A}{t}={\mathrm{bk}}^{″}C_{\mathrm{Ag}}& \left(9.4\right)\\ k=A{}^{-E_a/\left(\mathrm{RT}\right)}& \left(9.5\right)\end{array}$

The chemical step is usually much more temperature-sensitive than the physical steps so tests at varying temperatures with derivation of the activation energy should distinguish between ash or film diffusion as compared to chemical reaction as the controlling step. Physical processes tend to have low activation energy values vs. those of chemical reactions, i.e. E_a<5 kcal vs. 10-25 kcal, respectively (L. G. Twidwell, Huang, and Miller 1983).

Assuming the Shrinking-Core Model, the following are conversion-time expressions for spherical particles for the various controlling mechanisms, where X_B is conversion (Levenspiel 1999).

TABLE 9.30
Conversion-Time Expressions for Spherical Particles, Shrinking-Core
Model (Levenspiel 1999)
	Film Diffusion
	Controls	Ash Diffusion Controls	Reaction Controls
$\mathrm{Sphere}X_B=1-{\left(\frac{r_C}{R}\right)}^3$	$\frac{t}{\tau }=X_B$	$\frac{t}{\tau }=1-3{\left(1-X_B\right)}^{2/3}+2\left(1-X_B\right)$	$\frac{t}{\tau }=1-{\left(1-X_B\right)}^{1/3}$
	$\tau =\frac{{\rho }_BR}{3{\mathrm{bk}}_gC_{\mathrm{Ag}}}$	$\tau =\frac{{\rho }_BR^2}{6{\mathrm{bD}}_eC_{\mathrm{Ag}}}$	$\tau =\frac{{\rho }_BR}{{\mathrm{bk}}^{″}C_{\mathrm{Ag}}}$

FIGS. 9.31 and 9.32 show the conversion of spherical particles when chemical reaction, film diffusion, and ash diffusion control. By comparing the results of kinetic runs to these curves, the rate-controlling step could be determined. Unfortunately, there is not a considerable difference between ash diffusion and chemical reaction as controlling steps and may disappear in the scatter in experimental data (Levenspiel 1999).

The calculated arsenic extractions from each kinetic test were converted to a fractional conversion value, X_B, and substituted into the t/τ expressions in Table 9.30 for each of the possible controlling mechanisms as shown in Table 9.31 below.

TABLE 9.31
Kinetic Calculations
				Control Mechanism
Test		% As	Fractional	Fluid		Pore
ID	Time	Extraction	Conversion	Film	Chemical	Diffusion
K-1	0.25	26.19	0.2619	0.26	0.10	0.026
K-2	0.50	34.91	0.3491	0.35	0.13	0.049
K-3	0.75	44.39	0.4439	0.44	0.18	0.083
K-4	1.00	55.45	0.5545	0.55	0.24	0.141
K-5	1.50	54.33	0.5433	0.54	0.23	0.134

The data from Table 9.31 was plotted in FIG. 9.33, like FIG. 9.32, to compare mechanisms.

The K−5 point appears to be where no additional leaching occurs so to compare the mechanisms graphically another way, this point was excluded. The graphical comparisons are shown in FIGS. 9.34-.36.

Based on these kinetic results, it cannot be determined as of yet what the controlling mechanism is. There is also the possibility of a mechanism change as the process progresses. Additional studies at varying temperatures would need to be performed in order to calculate a rate constant, activation energies, etc.

9.6 High Grade Enargite Leaching

Leach tests were performed using the same autoclave on a prepared high grade enargite specimen sample to test reproducibility based on the pressure oxidation leach tests with the three highest recoveries, #24, 32 and 33 from section 9.1 above. The following table shows the experimental conditions at which the tests were performed.

TABLE 9.32
Leach Conditions for High Grade Enargite Tests
	Time	Temp	Cu 2+	Acid	Solids	O2 press
Test ID	hrs	deg C.	g/L	g/L	g	psi
HG-1	1.0	145	40	10	5	100
HG-2	1.0	145	10	30	5	100
HG-4	0.5	145	10	10	5	100

9.6.1 High Grade Leach Analysis

The high grade tests were analyzed and the results are as follows. Copper and Free Acid were analyzed by titration and the results are shown in the tables below.

TABLE 9.33
Copper Titrations
		Total ml	Copper
	Test #	Added	(g/l)
	HG-1	22.7	36.06
	HG-2	5.8	9.21
	HG-4	5.6	8.90

TABLE 9.34
Free Acid Titrations
		Total ml	Free Acid
	Test #	Added	(g/l)
	HG-1	1.6	15.68
	HG-2	4.2	41.16
	HG-4	1.4	13.72

ICP was performed by Hazen Research on leach solutions for copper, iron and arsenic. The results of this analysis are shown below. The copper numbers compare well to the copper titrations shown above.

TABLE 9.35
ICP Results on PLS Performed by Hazen Research
	Arsenic	Copper	Iron
	g/L	g/L	g/L
	HG-1	0.079	40.20	0.184
	HG-2	0.094	8.15	0.055
	HG-4	0.059	8.82	0.058

Solid leach residues were sent to Hazen Research for copper, iron and arsenic and results are shown below.

TABLE 9.36
Solid Leach Residue Assays Performed by Hazen Research
	Arsenic	Copper	Iron
	%	%	%
	HG-1	3.41	25.9	17.9
	HG-2	3.33	20.8	20.7
	HG-4	4.14	27.9	16.8

The high grade leach summary shown in the table below is the result of the mass balances performed based on the assays from above.

TABLE 9.37
High Grade Leach Results Summary
	Cu grams	Fe Extraction	As Extraction	Acid Consump.
Test ID	Diff Solids	%	%	g acid/g solid
HG-1	−0.03	32.27	45.24	0.689
HG-2	0.23	23.43	52.18	−4.592
HG-4	−0.32	20.96	32.36	−3.646

The summary leach results for the Marca Punta PDX tests compared to their corresponding high grade test are shown in the table below.

TABLE 9.38
Comparative Leach Summary for High Grade vs. POX tests
	Compare	Compare	Compare
	HG-1	POX 32	HG-2	POX 33	HG-4	POX 24
Cu Difference	−0.03	0.46	0.23	0.44	−0.32	0.46
in Solids (g)
Fe Extraction	32.27	35.73	23.43	10.62	20.96	9.82
(%)
As Extraction	45.24	39.90	52.18	47.19	32.36	39.93
(%)
Acid	0.69	0.17	−4.59	0.44	−3.65	−0.45
Consumption
(g/g)

This data shows some reproducibility but the copper increase is not as apparent. The arsenic extractions and acid consumptions have a reasonable correlation. The copper gain in the solids and iron extraction do not correlate well, which may be due to mineralogical effects or due to using a concentrate sample versus a high grade specimen.

Chapter 10

Proposed Process & Economic Evaluation

In an attempt to determine the preliminary scoping level economic feasibility of enargite pressure oxidation, a process flowsheet based on this research was developed as shown in FIG. 10.1 below. In some embodiments, the disclosed process entails pressure oxidation and leaching of the arsenic from the concentrate, performing solid/liquid separation by filtering, followed by arsenic precipitation by ferrihydrite or scorodite resulting in an upgraded copper concentrate to send to a smelting or copper concentrate leach operation.

In some embodiments the concentrate may be treated in a standard copper smelter used in the recovery of copper and precious metals. An apparent separation of arsenic from copper was achieved. For PDX Test #33 with the highest arsenic extraction, the copper gain in the solids was 0.44 grams, or about 12.5%, which would increase the amount paid for copper from the concentrate sent to the smelter.

Some assumptions used in the preliminary economics are as follows:

• • Used Freeport Miami smelter schedule
  • Used updated Bagdad capital costs
  • Low severity pressure oxidation
  • Operating costs do not include arsenic fixation
  • 157 tons/day concentrate feed as per Bagdad
  • Operating 350 days/year
  • Approximately 50% arsenic removal
  • 0.44 g acid/g concentrate acid consumption
  • 10 year cash flows used
  • 8% discount rate
  • No by-product credits were accounted for

10.1 Smelter Treatment

A Freeport Miami smelter schedule is shown in Table 10.1 below showing the smelter limits and penalties. It should be noted that an iron content above 15% results in an unknown increased treatment charge for more flux being needed in the process. A reduction in arsenic content from 5.89 wt % to 4.39% results in a penalty savings of approximately $2920/day for a plant treating 157 tons/day of concentrate.

TABLE 10.1
FMI Miami Smelter Limits & Penalties
Element	Symbol	Penalty Formula
Alumina	Al2O3	$0.50 ea 0.1% > 5%
Iron	Fe	>15% = increased treatment charge for
		more flux needed
Arsenic	As	$0.50/lb > 1% (20 lb) OR 2$/dt ea 0.1% > 0.1%
		Max 0.2%
Barium	Ba	0.5 to 1% limit
Beryllium	Be	<10 ppm limit
Bismuth	Bi	($1.10 to $7.50)/dt ea 0.1% > (0.1% to 0.4%)
		Max 0.4%
Cyanide	CN	<10 ppm !
Cadmium	Cd	($2.20 to $7.50)/dt ea 0.1% > (0.05% to 0.2%)
		Max 0.4%
Chloride	Cl	BAD PLAYER, DO NOT WANT ANY	5$/dt ea 0.1% > 2%
Cobalt	Co	0.5% limit
Chromium	Cr	$0.50 dt ea 0.1% > 3% no hex chrome,	NO Cu CHROMATE!
		5% max on tri v Cr
Fluoride	F	$5 dt ea 0.1% > 0.2% 0.5% max
Mercury	Hg	($1.85 to $2)/dt ea 10 ppm > 10 ppm
Magnesium	MgO	Normally 10% limit, desirable element
		in feed???
Ox
Manganese	Mn	2.0% limit
Sodium	Na	5.0% limit
Nickel	Ni	$2 dt ea 0.1% > 2%
Phosphorus	P	3.0% limit
Lead	Pb	$1 dt ea 0.1& > 1% OR $1/lb > 0.5%
		(more severe)
Antimony	Sb	BAD PLAYER, DO NOT WANT ANY	($2 to $2.20) dt ea
			0.1% > 0.3%
Selenium	Se	0.1% limit
Tin	Sn	($1.10 to $3) dt ea 0.1% >
		(0.2 to 3%) Max 3%
Tellurium	Te	0.01% limit
Thallium	Tl	0.01% limit
Zinc	Zn	$0.50 dt ea 0.1% > 3% 4.0% limit
Moisture	H2O	$2.50 wt ea 1% > (15% to 50%)what is
		the material?
Manifest		$30 ea
Bag		$20 ea
containers
Liners		? # & size?
Refining Fees Cu = 12¢ to	Recovery Rates	Cu = 96.5%
14¢ per pound paid
Au = $6.50 to $7.50 per oz paid		Au = 90%+
As = 50¢ per oz paid		As = 90%+
10,000 g or ppm = 1%
1,000 = 0.1%	ppm = opt	gmt = # ÷ 31.103481 = opt
100 = 0.01%	31.103481
10 = 0.001%	453 gr = 1 lb.
31.1035 gr = 1 troy oz	14.583 troy oz = 1 pound	Kg/Mt = # × 32.151 = opt

10.2 Capital Costs

Capital costs were estimated based on a 1999 Bagdad demonstration plant cost of $40 million brought to 2013 using Marshall & Swift Economic Indicators as $57 million (McElroy and Young 1999; “Economic Indicators” 2011; “Economic Indicators” 2013). Table 10.2 shows the Marshall & Swift Indices and Table 10.3 shows FMI's 2003 capital cost drivers updated using the Index to $US in 2013.

TABLE 10.2
Marshall & Swift Economic Indicators (“Economic Indicators”
2011; “Economic Indicators” 2013)
	Annual Index	Capital Cost
	2003	402.0	$40,000,000
	Prelim. ′13	571.4	$57,000,000

TABLE 10.3
FMI Pressure Oxidation Process Capital Costs (John O. Marsden and Brewer 2003)
Parameter	2003 Cost	2013 Cost
Concentrate Leaching	$0.90 per annual lb Cu	$1.28 per annual lb Cu
(including SX/EW)
Concentrate Leaching	<$0.45 per annual lb Cu	<$0.64 per annual lb Cu
(excluding SX/EW)
Smelting & Refining	$1.70-2.00 per annual lb Cu	$2.42-2.84 per annual lb Cu
(Greenfield)
Smelting & Refining	<$1.00 per annual lb Cu	<$1.42 per annual lb Cu
(Expansion)

10.3 Operating Costs

Shown below are the operating costs for the PDX process. The rate of inflation was considered using the Consumer Price Index from the Bureau of Labor Statistics (“Inflation Calculator: Bureau of Labor Statistics” 2013). Table 10.4 shows 1999 $US updated using the CPI to $US in 2013 by McElroy and Young.

TABLE 10.4
Pressure Oxidation Process Operating Costs
(McElroy and Young 1999)
	1999 $US/lb Copper	2013 $US/lb Copper
Oxygen	0.012	0.02
Neutralization (mill tailing)	0.006	0.01
Grinding & Autoclave	0.018	0.03
Agitation
Maintenance Supplies	0.019	0.03
Salaries/Labor	0.006	0.01
Total Leach	0.061	0.09
TOTAL	0.122	0.19

Oxygen costs shown above are based on chalcopyrite oxidation oxygen consumption. Equations 5.1 and 5.4 for enargite oxidation compared to Equations 2.18 and 2.19 for chalcopyrite oxidation show that the oxygen required would be lower for the enargite process, thus lowering oxygen costs. For chalcopyrite oxidation at lower temperatures (below 200° C.), five moles of oxygen are required vs 2.75 moles of oxygen for enargite. Table 10.5 shows 2003 operating costs by FMI updated using the CPI to SUS in 2013.

TABLE 10.5
FMI Pressure Oxidation Process Operating Costs (John O. Marsden and Brewer 2003)
Parameter	2003 Cost	2013 Cost
Smelting Cost (long term)	$80-90 per metric ton concentrate	$101-114 per metric ton concentrate
Refining Cost (long term)	$0.08-$0.09 per pound Cu	$0.10-$0.11 per pound Cu
Acid cost (delivered)	$10-50 per metric ton	$13-63 per metric ton
Freight rates (concentrate,	Depends on local situation $0.02-0.06	Depends on local situation $0.03-0.08
acid, cathode)	per ton-km by truck $25-30	per ton-km by truck $32-38 per
	per ton by sea	ton by sea
Gold and silver credits	Depends on grade in concentrate	Depends on grade in concentrate

TABLE 10.6
Operating Cost Assumptions
Copper in con           21%
Acid Consumption (g/g)  0.44
Tons of acid needed/ton 69.08
con/day
Appx distance Miami to  320
Bagdad (km)

The information in Table 10.5 was converted to dollars per ton of concentrate using the additional assumptions from Table 10.6 to calculate an average (midpoint) operating cost to be used in the NPV analysis in Section 10.4.

TABLE 10.7
FMI 2013 Estimated Pressure Oxidation Operating Costs
	Operating Costs per
	Ton of Concentrate
	Parameter	Low	High
	Smelting Cost (long term)	$101.00	$114.00
	Refining Cost (long term)	$46.28	$46.28
	Acid cost (delivered)	$898.04	$4,352.04
	Freight rates (concentrate,	$9.60	$25.60
	acid, 320 km by truck)
	TOTAL	$1,054.92	$4,537.92

10.4 NPV Analysis

Table 10.8 shows an NPV analysis for a project based on a pressure oxidation plant similar to Bagdad expected to process 157 tons per day (John O. Marsden and Brewer 2003). Operating costs were assumed to be at the low side, taken from Table 10.7 above. Table 10.9 shows the NPV sensitivity for each factor assuming $3/1b copper. The operating cost should be carefully monitored to keep the project feasible.

TABLE 10.8
Scoping Preliminary Economic Analysis
Year	Year	Year	Year	Year	Year
0	1	2	3	4	5
−$57,000,000	$18,328,072	$18,328,072	$18,328,072	$18,328,072	$18,328,072
Year	Year	Year	Year	Year
6	7	8	9	10
$18,328,072	$18,328,072	$18,328,072	$18,328,072	$18,328,072
	Plant Life, years	10
	Discount Rate	8.0%
	IRR	29.8%
	NPV	$65,982,856
	Payback Period, months	37.32
	Profitability Index	1.16
	Con	Days per year	Per Ton	Annual
	157.0	350.0	$1,388	$76,290,868	Revenue
	157.0	350.0	$1,055	$57,962,796	Cost
				$18,328,072	Before Tax Profit

TABLE 10.9
NPV Sensitivity
NPV, Sensitivity
	−20%	−10%	0	10%	20%
CAPEX	$77,382,856	$71,682,856	$65,982,856	$60,282,856	$54,582,856
OPEX	$143,769,872	$104,876,364	$65,982,856	$27,089,348	($11,804,160)
Discount Rate	$75,376,195	$70,546,991	$65,982,856	$61,665,883	$57,579,553
Revenue	($36,400,731)	$14,791,063	$65,982,856	$117,174,650	$168,366,444

Chapter 11

Results

• • A comprehensive survey of copper processing, arsenic chemistry and enargite technology was completed.
  • The thermodynamic study illustrated a region where a potential metathesis reaction of selective dissolution of arsenic could occur.
  • In one case, arsenic extraction during the atmospheric pressure leaching was Test #7 resulted in about 21% arsenic extracted at 10 gpl sulfuric acid, 10 grams of solids, 10 gpl Cu²⁺, and 75° C. for 2 hours. This test also shows an apparent copper and arsenic separation with a 7% copper gain in the solid indicating the possibility of a copper-arsenic metathesis reaction occurring.
  • With regard to mineralogy, the #7 atmospheric leach residue had an increase in pyrite content from 61.4 wt % to 76.7% and enargite decreased from 38% to 23%. Iron content went from 28.6% to 29.7%, copper decreased from 18.6% to 17.5% and arsenic from 7.23% to 6.83%. Mineralogical analysis did not show new copper phases appearing after leaching.
  • Atmospheric leach modeling using Stat-Ease Design Expert showed initial acid content as a factor on PLS arsenic content with temperature also showing a positive effect.
  • Pressure oxidation arsenic extraction for Test #33 resulted in about 47% arsenic extracted at 30 gpl sulfuric acid, 5 grams of solids, 10 gpl Cu^2±, and 160° C. for 1 hour.
  • Mineralogically, the #33 pressure oxidation composite sample increased in pyrite content from 61.4 wt % to 67.8%, enargite from 38% to 31.2%, and covellite, which was not detected in the feed appeared at 0.46% in the residue. Iron content increased from 28.6% to 31.6%, copper decreased from 18.6% to 15.4% and arsenic from 7.23% to 5.94%.
  • Stat-Ease was also used for modeling of the PDX leach results. Time had an effect on PLS arsenic content.
  • The preliminary kinetic results did not define what the controlling mechanism was and additional testing needs to be performed to derive this information.
  • High grade enargite mineral tests did show reproducibility to PDX work on enargite concentrates.
  • A scoping level preliminary assessment based on updated published cost data indicates positive economics for the proposed process.

Chapter 12

Conclusions

From the literature survey, the world's next major copper and gold orebodies will contain and increasing amount of enargite. There are limited industrial metallurgical technologies available to treat enargite on an industrial scale. The use of hydrometallurgical technologies for arsenic removal can also more directly produce stable forms of arsenic compounds such as ferrihydrite and scorodite.

The concentrate and pure mineral specimen characterizations performed were comprehensive and definitive.

Atmospheric leach testing was undertaken but did not confirm a desirable degree of arsenic from copper separation via a metathesis-like reaction.

Qualitatively, a pressure oxidation leach separation of arsenic from copper solids was achieved via a presumed metathesis-like reaction. Thermodynamically, a proposed metathesis reaction pathway was shown to be possible. Moreover, both the pressure oxidation positive mass balances along with the MLA mineralogical analysis showing the disappearance of enargite and the appearance of covellite confirmed that an apparent metathesis-like event was happening.

Both atmospheric and pressure oxidation testing were successfully modeled using Design-of-Experimentation testing coupled with Stat Ease software.

Focused kinetic and mineralogical testing of one embodiment of a pressure oxidation test confirmed testing reproducibility and a perceived metathesis arsenic separation reaction. Testing of a higher purity enargite sample showed good correlation with previous pressure oxidation work done on the complex enargite concentrate. Initial kinetic modeling was undertaken but additional work is needed for better definition now that a region of presumed metathesis-like arsenic separation has been found.

A preliminary scoping-level economic assessment was positive.

Chapter 13

SUGGESTIONS FOR FURTHER WORK

With the severe delays that equipment shipment, down-time, and malfunctioning components caused, there was a significant amount of research time that was lost. In outlining a thoroughly-researched pressure oxidation process, there are many areas for process design and optimization. Areas where further investigation should be conducted include:

• • 1. Sample. A complex enargite concentrate was examined initially. While some tests were performed with a high grade mineral sample, the focus of those tests was to determine if the same arsenic extractions could be achieved. Starting a new experimental program with a pure enargite sample could prove more valuable in determining the chemical reaction of enargite alone in this system before adding competing effects such as the role iron plays in leaching.
  • 2. System Chemistry. The actual chemical reactions occurring can be delineated further and stoichiometric oxygen requirements can be properly determined if work is done on a larger scale.
  • 3. Kinetics. Further kinetic evaluation at different temperatures would enable generation of an Arrhenius plot, determine k and activation energies to delineate controlling mechanisms.
  • 4. Separation. An apparent separation of arsenic from copper via a metathesis-like reaction was qualitatively achieved but not definitively confirmed or fully evaluated. More work needs to be performed on a larger scale to better define this positive separation phenomena.

APPENDIX A

Eh-pH Diagrams by Temperature

Figures A.1-A.21 are HSC 7.1 Eh-pH stability diagrams for the various systems at varying temperatures.

APPENDIX B

Eh-pH Diagrams by Molality

Figures B.1-B.12 are Eh-pH stability diagram at 25° C. for the various system.

APPENDIX C

Mass Balances

Mass balance calculations for the atmospheric pressure and pressure oxidation tests are shown below.

C.1 Atmospheric Pressure Leach Mass Balance

Tables C.1-C.8 show the mass balance calculations for the atmospheric pressure tests.

TABLE C.1
Atmospheric Pressure Final Volumes and Solid Weights
	VOLUME	SOLIDS
	ml	ml	ml	grams	grams	% Difference
Test ID	Initial Volume	Sample Vol	Final Volume	Initial Solids	Final Solids	Solids
MP Leach Test #1	1000	80	978	20.03	16.347	18.39
MP Leach Test #2	1000	80	975	20.02	16.050	19.82
MP Leach Test #3	1000	40	1038	10.08	8.560	15.08
MP Leach Test #4	1000	40	1053	29.99	25.480	15.05
MP Leach Test #5	1000	40	1046	10.02	8.499	15.14
MP Leach Test #6	1000	40	954	30.05	23.665	21.24
MP Leach Test #7	1000	40	939	10.03	7.497	25.27
MP Leach Test #8	1000	80	924	20.09	15.892	20.89
MP Leach Test #9	1000	40	975	30.08	24.787	17.58
MP Leach Test #10	1000	40	989	10.04	8.531	15.07
MP Leach Test #11	1000	40	990	30.03	23.885	20.45
MP Leach Test #12	1000	60	981	30.04	25.995	13.46
MP Leach Test #13	1000	60	971	10.03	8.230	17.92
MP Leach Test #14	1000	60	980	30.05	22.940	23.67
MP Leach Test #15	1000	60	980	10.00	8.037	19.65
MP Leach Test #16	1000	60	1045	30.02	25.195	16.08
MP Leach Test #17	1000	60	992	10.08	7.817	22.42
MP Leach Test #18	1000	60	1012	30.00	24.961	16.80
MP Leach Test #19	1000	60	979	10.00	9.055	9.50
MP Leach Test #7-2	1000	0	1291	10.00	7.462	25.37
MP Leach Test #13-2	1000	0	1303	10.01	7.455	25.51

TABLE C.2
Atmospheric Pressure Copper Mass Balance Calculations
	COPPER
	grams	grams	grams	grams	grams	grams	grams
Test ID	Cu In Solid	Cu In Soln	Cu Out Solid	Cu Out Soln	Diff Solids	Cu In	Cu Out
MP Leach Test #1	3.35	25.00	2.83	22.37	0.51	28.34	25.20
MP Leach Test #2	3.34	25.00	2.79	22.46	0.55	28.34	25.25
MP Leach Test #3	1.68	10.00	1.42	10.06	0.26	11.69	11.48
MP Leach Test #4	5.01	40.00	4.24	36.97	0.76	45.01	41.21
MP Leach Test #5	1.67	40.00	1.46	37.39	0.21	41.67	38.85
MP Leach Test #6	5.02	10.00	4.01	10.15	1.00	15.02	14.17
MP Leach Test #7	1.68	10.00	1.31	9.40	0.36	11.68	10.71
MP Leach Test #8	3.35	25.00	2.70	21.87	0.66	28.35	24.57
MP Leach Test #9	5.02	10.00	4.24	9.76	0.78	15.02	14.00
MP Leach Test #10	1.68	40.00	1.51	38.49	0.16	41.68	40.00
MP Leach Test #11	5.01	40.00	4.24	37.43	0.77	45.01	41.67
MP Leach Test #12	5.02	40.00	4.55	35.69	0.47	45.02	40.23
MP Leach Test #13	1.67	40.00	1.44	37.02	0.24	41.67	38.46
MP Leach Test #14	5.02	10.00	3.99	9.65	1.03	15.02	13.64
MP Leach Test #15	1.67	10.00	1.36	9.34	0.32	11.67	10.70
MP Leach Test #16	5.01	10.00	4.03	9.96	0.99	15.02	13.99
MP Leach Test #17	1.68	10.00	1.33	9.61	0.35	11.68	10.95
MP Leach Test #18	5.01	40.00	4.21	36.81	0.80	45.01	41.03
MP Leach Test #19	1.67	40.00	1.50	36.55	0.17	41.67	38.05
MP Leach Test #7-2	1.67	10.00	1.31	9.64	0.36	11.67	10.95
MP Leach Test #13-2	1.67	40.00	1.26	38.71	0.41	41.67	39.97
	Solid	g CuSO45H2O	Solid	Cu		Total	Total
	assay ×	added ×	assay ×	titration ×
	initial solids	63.55/249.68	final solids	final vol

TABLE C.3
Atmospheric Pressure Copper Mass Balance
Calculations Continued
	COPPER
	% Copper
	Lost in	% Cu Gain/	% Cu Gain/	Average
Test ID	soln	Initial Solid	Final Solid	Gain
MP Leach Test #1	10.50	13.11	16.06	14.59
MP Leach Test #2	10.17	12.70	15.84	14.27
MP Leach Test #3	−0.56	−0.55	−0.65	−0.60
MP Leach Test #4	7.58	10.11	11.90	11.00
MP Leach Test #5	6.54	26.13	30.79	28.46
MP Leach Test #6	−1.53	−0.51	−0.65	−0.58
MP Leach Test #7	6.03	6.01	8.04	7.03
MP Leach Test #8	12.52	15.58	19.69	17.64
MP Leach Test #9	2.45	0.81	0.99	0.90
MP Leach Test #10	3.77	15.03	17.69	16.36
MP Leach Test #11	6.43	8.56	10.76	9.66
MP Leach Test #12	10.79	14.37	16.60	15.48
MP Leach Test #13	7.45	29.73	36.22	32.98
MP Leach Test #14	3.49	1.16	1.52	1.34
MP Leach Test #15	6.61	6.61	8.22	7.41
MP Leach Test #16	0.41	0.14	0.16	0.15
MP Leach Test #17	3.89	3.86	4.97	4.41
MP Leach Test #18	7.97	10.62	12.76	11.69
MP Leach Test #19	8.63	34.51	38.13	36.32
MP Leach Test #7-2	3.63	3.63	4.86	4.25
MP Leach Test #13-2	3.23	12.93	17.35	15.14

TABLE C.4
Atmospheric Pressure Iron Mass Balance Calculations
	IRON
		grams	grams
	grams	Fe Out	Fe Out	grams	grams
Test ID	Fe In	Solid	Soln	Fe In	Fe Out
MP Leach Test #1	5.52	4.82	0.59	5.52	5.41
MP Leach Test #2	5.52	4.72	0.61	5.52	5.33
MP Leach Test #3	2.78	2.62	0.10	2.78	2.73
MP Leach Test #4	8.26	7.90	0.37	8.26	8.27
MP Leach Test #5	2.76	2.51	0.26	2.76	2.78
MP Leach Test #6	8.28	7.06	0.87	8.28	7.93
MP Leach Test #7	2.76	2.16	0.36	2.76	2.53
MP Leach Test #8	5.53	4.53	0.60	5.53	5.12
MP Leach Test #9	8.29	7.29	0.55	8.29	7.84
MP Leach Test #10	2.77	2.52	0.18	2.77	2.70
MP Leach Test #11	8.27	6.96	1.25	8.27	8.20
MP Leach Test #12	8.28	7.47	0.59	8.28	8.06
MP Leach Test #13	2.76	2.33	0.42	2.76	2.75
MP Leach Test #14	8.28	6.52	1.21	8.28	7.74
MP Leach Test #15	2.76	2.27	0.22	2.76	2.49
MP Leach Test #16	8.27	7.33	0.37	8.27	7.70
MP Leach Test #17	2.78	2.28	0.32	2.78	2.59
MP Leach Test #18	8.27	7.19	0.86	8.27	8.06
MP Leach Test #19	2.76	2.65	0.13	2.76	2.78
MP Leach Test #7-2	2.75	2.13	0.43	2.75	2.56
MP Leach Test #13-2	2.76	2.18	0.43	2.76	2.61
	Solid	Solid	CAMP	Total	Total
	assay ×	assay ×	ICP ×
	initial	final	final
	solids	solids	vol

TABLE C.5
Atmospheric Pressure Iron Mass Balance Calculations Continued
	IRON
			Final
		Liquid	Liquid	Average
	Solid Fe	Fe	Fe	Extraction	Calculated
Test ID	Extr %	Extr %	Extr %	%	Head
MP Leach	12.67	10.78	10.98	11.48	27.03
Test #1
MP Leach	14.44	11.10	11.49	12.34	26.63
Test #2
MP Leach	5.52	3.76	3.83	4.37	27.07
Test #3
MP Leach	4.35	4.43	4.43	4.40	27.57
Test #4
MP Leach	8.95	9.54	9.49	9.32	27.71
Test #5
MP Leach	14.75	10.52	10.98	12.08	26.38
Test #6
MP Leach	21.72	13.20	14.43	16.45	25.20
Test #7
MP Leach	18.22	10.81	11.68	13.57	25.51
Test #8
MP Leach	11.99	6.59	6.97	8.52	26.06
Test #9
MP Leach	8.99	6.46	6.63	7.36	26.85
Test #10
MP Leach	15.92	15.10	15.23	15.42	27.33
Test #11
MP Leach	9.76	7.14	7.33	8.08	26.83
Test #12
MP Leach	15.74	15.24	15.32	15.43	27.41
Test #13
MP Leach	21.21	14.64	15.67	17.17	25.74
Test #14
MP Leach	17.61	8.06	8.92	11.53	24.92
Test #15
MP Leach	11.39	4.51	4.84	6.91	25.65
Test #16
MP Leach	18.03	11.48	12.29	13.93	25.75
Test #17
MP Leach	12.97	10.43	10.70	11.37	26.85
Test #18
MP Leach	3.81	4.75	4.71	4.42	27.81
Test #19
MP Leach	22.64	15.48	16.68	18.27	25.58
Test #7-2
MP Leach	20.91	15.68	16.55	17.71	26.11
Test #13-2	(Mass	1 −	Soln		Total
	in −	(Mass in −	mass out/		g out/
	Solid	Soln mass	Mass out		g
	mass out)/	out)/			initial
	Mass in	Mass in			solids

TABLE C.6
Atmospheric Pressure Arsenic Mass Balance Calculations
	ARSENIC
		grams	grams
	grams	As Out	As Out	grams	grams
Test ID	As In	Solid	Soln	As In	As Out
MP Leach Test #1	1.36	1.11	0.11	1.36	1.22
MP Leach Test #2	1.36	1.04	0.11	1.36	1.15
MP Leach Test #3	0.69	0.59	0.00	0.69	0.59
MP Leach Test #4	2.04	1.77	0.00	2.04	1.78
MP Leach Test #5	0.68	0.54	0.06	0.68	0.60
MP Leach Test #6	2.04	1.42	0.17	2.04	1.59
MP Leach Test #7	0.68	0.43	0.07	0.68	0.50
MP Leach Test #8	1.37	0.90	0.12	1.37	1.01
MP Leach Test #9	2.05	1.44	0.02	2.05	1.45
MP Leach Test #10	0.68	0.46	0.01	0.68	0.47
MP Leach Test #11	2.04	1.60	0.20	2.04	1.80
MP Leach Test #12	2.04	1.74	0.01	2.04	1.75
MP Leach Test #13	0.68	0.55	0.07	0.68	0.62
MP Leach Test #14	2.04	1.50	0.22	2.04	1.72
MP Leach Test #15	0.68	0.54	0.00	0.68	0.54
MP Leach Test #16	2.04	1.69	0.00	2.04	1.70
MP Leach Test #17	0.69	0.50	0.06	0.69	0.56
MP Leach Test #18	2.04	1.60	0.16	2.04	1.76
MP Leach Test #19	0.68	0.59	0.01	0.68	0.60
MP Leach Test #7-2	0.68	0.48	0.08	0.68	0.56
MP Leach Test #13-2	0.68	0.47	0.08	0.68	0.54
	Solid	Solid	CAMP	Total	Total
	assay ×	assay ×	ICP ×
	initial	final	final
	solids	solids	vol

TABLE C.7
Atmospheric Pressure Arsenic Mass Balance
Calculations Continued
	ARSENIC
			Final
	Solid	Liquid	Liquid	Average
	As	As	As	Extraction	Calculated
Test ID	Extr %	Extr %	Extr %	%	Head
MP Leach	18.63	8.39	9.35	12.12	6.10
Test #1
MP Leach	23.95	8.08	9.60	13.88	5.72
Test #2
MP Leach	14.58	0.27	0.31	5.05	5.83
Test #3
MP Leach	13.18	0.21	0.24	4.54	5.92
Test #4
MP Leach	20.88	8.46	9.66	13.00	5.96
Test #5
MP Leach	30.51	8.15	10.50	16.39	5.28
Test #6
MP Leach	37.69	10.67	14.62	20.99	4.96
Test #7
MP Leach	34.27	8.46	11.41	18.05	5.05
Test #8
MP Leach	29.70	0.80	1.12	10.54	4.83
Test #9
MP Leach	32.80	1.00	1.47	11.76	4.64
Test #10
MP Leach	21.62	9.88	11.20	14.23	6.00
Test #11
MP Leach	14.99	0.71	0.83	5.51	5.83
Test #12
MP Leach	19.85	10.40	11.48	13.91	6.16
Test #13
MP Leach	26.48	10.74	12.74	16.65	5.73
Test #14
MP Leach	20.95	0.45	0.56	7.32	5.41
Test #15
MP Leach	17.07	0.16	0.20	5.81	5.65
Test #16
MP Leach	27.10	9.26	11.28	15.88	5.59
Test #17
MP Leach	21.70	7.93	9.19	12.94	5.86
Test #18
MP Leach	13.49	1.01	1.16	5.22	5.95
Test #19
MP Leach	29.21	12.02	14.52	18.58	5.63
Test #7-2
MP Leach	31.64	11.64	14.55	19.28	5.44
Test #13-2	(Mass	1 −	Soln		Total
	in −	(Mass	mass out/		g out/
	Solid	in −	Mass out		g
	mass out)/	Soln			initial
	Mass in	mass out)/			solids
		Mass in

TABLE C.8
Atmospheric Pressure Acid Consumption
Mass Balance Calculations
	ACID
			g Acid	g Acid
		grams	Consump/	Consump/
	grams	Acid	g Initial	g Final	Average
Test ID	Acid In	Out	Solids	Solids	Consumption
MP Leach	5.19	4.79	0.020	0.024	0.022
Test #1
MP Leach	5.20	5.73	−0.027	−0.034	−0.030
Test #2
MP Leach	0.00	0.00	0.000	0.000	0.000
Test #3
MP Leach	0.00	0.00	0.000	0.000	0.000
Test #4
MP Leach	10.37	10.25	0.012	0.014	0.013
Test #5
MP Leach	10.37	9.35	0.034	0.043	0.039
Test #6
MP Leach	10.36	9.20	0.116	0.155	0.135
Test #7
MP Leach	5.18	4.53	0.033	0.041	0.037
Test #8
MP Leach	0.00	0.00	0.000	0.000	0.000
Test #9
MP Leach	0.00	0.00	0.000	0.000	0.000
Test #10
MP Leach	10.37	8.73	0.055	0.069	0.062
Test #11
MP Leach	0.00	0.00	0.000	0.000	0.000
Test #12
MP Leach	10.37	9.52	0.085	0.103	0.094
Test #13
MP Leach	10.37	8.64	0.057	0.075	0.066
Test #14
MP Leach	0.00	0.00	0.000	0.000	0.000
Test #15
MP Leach	0.00	0.00	0.000	0.000	0.000
Test #16
MP Leach	10.37	9.72	0.064	0.083	0.073
Test #17
MP Leach	10.35	9.92	0.015	0.017	0.016
Test #18
MP Leach	0.00	0.00	0.000	0.000	0.000
Test #19
MP Leach	10.36	8.86	0.150	0.202	0.176
Test #7-2
MP Leach	10.36	10.22	0.015	0.020	0.017
Test #13-2	g of	g free
	96.5%	acid ×
	H2SO4	final
	added	vol

C.2 Pressure Oxidation Leach Mass Balance

Tables C.9-C.17 show the mass balance calculations for the pressure oxidation tests.

TABLE C.9
Pressure Oxidation Final Volumes
	VOLUME
		ml	ml
	Test ID	Initial Volume	Final Volume
	MP POX Test #1	1000	1000
	MP POX Test #2	1000	1123
	MP POX Test #3	1000	1159.5
	MP POX Test #4	1000	1210.5
	MP POX Test #5	1000	1080
	MP POX Test #6	1000	1240
	MP POX Test #7	1000	1215
	MP POX Test #8	1000	1244
	MP POX Test #9	1000	1095
	MP POX Test #10	1000	1250
	MP POX Test #11	1000	1135
	MP POX Test #12	1000	1226
	MP POX Test #13	1000	1404
	MP POX Test #14	1000	1321
	MP POX Test #15	1000	1324
	MP POX Test #16	1000	1328
	MP POX Test #17	1000	1267
	MP POX Test #18	1000	1245
	MP POX Test #19	1000	1225
	MP POX Test #20	1000	1026
	MP POX Test #21	1000	1069
	MP POX Test #22	1000	1230
	MP POX Test #23	1000	1227
	MP POX Test #24	1000	1244
	MP POX Test #25	1000	1041
	MP POX Test #26	1000	1333
	MP POX Test #27	1000	1169
	MP POX Test #28	1000	1446
	MP POX Test #29	1000	1257
	MP POX Test #30	1000	1225
	MP POX Test #31	1000	1372
	MP POX Test #32	1000	1250
	MP POX Test #33	1000	1195
	MP POX Test #34	1000	1293
	MP POX Test #35	1000	1491

TABLE C.10
Pressure Oxidation Final Solid Weights
	SOLIDS
	grams	grams	% Difference
Test ID	Initial Solids	Final Solids	Solids
MP POX Test #1	15.01	11.090	26.09
MP POX Test #2	5.00	3.753	24.97
MP POX Test #3	5.00	3.824	23.52
MP POX Test #4	15.00	11.338	24.41
MP POX Test #5	5.00	4.149	17.10
MP POX Test #6	5.00	3.536	29.22
MP POX Test #7	15.02	11.459	23.70
MP POX Test #8	15.01	11.524	23.22
MP POX Test #9	5.00	3.945	21.12
MP POX Test #10	5.00	3.564	28.78
MP POX Test #11	15.01	10.214	31.95
MP POX Test #12	15.05	11.468	23.79
MP POX Test #13	5.00	3.345	33.08
MP POX Test #14	5.00	3.575	28.53
MP POX Test #15	15.00	11.752	21.64
MP POX Test #16	15.00	10.686	28.77
MP POX Test #17	10.01	8.626	13.78
MP POX Test #18	10.01	8.643	13.67
MP POX Test #19	10.00	8.286	17.15
MP POX Test #20	5.00	4.177	16.52
MP POX Test #21	5.00	4.305	13.95
MP POX Test #22	15.00	12.900	14.01
MP POX Test #23	15.00	13.319	11.23
MP POX Test #24	5.01	3.409	31.94
MP POX Test #25	5.00	4.001	20.03
MP POX Test #26	15.00	11.774	21.53
MP POX Test #27	15.00	12.890	14.08
MP POX Test #28	15.01	12.151	19.06
MP POX Test #29	5.00	3.940	21.25
MP POX Test #30	5.01	4.090	18.29
MP POX Test #31	15.02	12.935	13.90
MP POX Test #32	5.01	2.530	49.48
MP POX Test #33	5.00	3.461	30.80
MP POX Test #34	15.01	10.559	29.65
MP POX Test #35	15.00	11.613	22.59

TABLE C.11
Pressure Oxidation Copper Mass Balance Calculations
	grams	grams	grams	grams	grams	grams	grams
Test ID	Cu In Solid	Cu In Soln	Cu Out Solid	Cu Out Soln	Diff Solids	Cu In	Cu Out
MP PDX Test #1	2.51	10.00	1.97	10.48	0.54	12.51	12.45
MP PDX Test #2	0.84	10.00	0.66	9.99	0.17	10.84	10.65
MP PDX Test #3	0.84	40.00	0.63	40.52	0.20	40.83	41.15
MP PDX Test #4	2.50	40.00	1.98	38.07	0.53	42.50	40.05
MP PDX Test #5	0.84	39.97	0.48	39.80	0.35	40.81	40.28
MP PDX Test #6	0.83	10.00	0.62	9.85	0.21	10.84	10.47
MP PDX Test #7	2.51	10.00	2.02	9.26	0.49	12.51	11.28
MP PDX Test #8	2.51	40.00	1.96	37.55	0.55	42.51	39.51
MP PDX Test #9	0.84	40.00	0.63	40.01	0.20	40.83	40.64
MP PDX Test #10	0.84	10.00	0.59	9.53	0.24	10.84	10.13
MP PDX Test #11	2.51	10.00	2.00	6.49	0.51	12.51	8.49
MP PDX Test #12	2.51	40.00	2.29	39.34	0.23	42.51	41.63
MP PDX Test #13	0.83	10.00	0.70	9.81	0.13	10.84	10.51
MP PDX Test #14	0.84	40.01	0.79	33.99	0.05	40.84	34.78
MP PDX Test #15	2.50	40.00	3.02	32.39	−0.52	42.51	35.41
MP PDX Test #16	2.51	10.00	2.11	8.02	0.40	12.50	10.12
MP PDX Test #17	1.67	25.00	1.25	21.74	0.42	26.67	22.98
MP PDX Test #18	1.67	25.00	1.12	24.52	0.55	26.67	25.64
MP PDX Test #19	1.67	25.00	1.17	20.63	0.50	26.67	21.80

TABLE C.12
Pressure Oxidation Copper Mass Balance Calculations
	grams	grams	grams	grams	grams	grams	grams
Test ID	Cu In Solid	Cu In Soln	Cu Out Solid	Cu Out Soln	Diff Solids	Cu In	Cu Out
MP PDX Test #20	0.84	40.00	0.80	38.30	0.04	40.83	39.10
MP PDX Test #21	0.84	10.00	0.77	10.19	0.06	10.84	10.96
MP PDX Test #22	2.51	10.00	2.35	8.40	0.16	12.51	10.75
MP PDX Test #23	2.51	40.00	2.40	39.37	0.11	42.50	41.77
MP PDX Test #24	0.84	10.00	0.37	9.88	0.46	10.84	10.25
MP PDX Test #25	0.84	40.00	0.79	38.86	0.05	40.84	39.65
MP PDX Test #26	2.51	10.00	1.55	9.32	0.95	12.51	10.87
MP PDX Test #27	2.51	10.00	2.33	10.03	0.17	12.51	12.36
MP PDX Test #28	2.51	10.00	1.84	10.57	0.67	12.51	12.40
MP PDX Test #29	0.84	10.00	0.60	10.38	0.24	10.84	10.98
MP PDX Test #30	0.84	40.00	0.65	39.31	0.18	40.84	39.96
MP PDX Test #31	2.51	40.00	2.12	34.43	0.39	42.51	36.55
MP PDX Test #32	0.84	40.00	0.38	37.73	0.46	40.84	38.11
MP PDX Test #33	0.84	10.00	0.40	9.49	0.44	10.84	9.89
MP PDX Test #34	2.51	10.00	1.36	13.15	1.15	12.51	14.50
MP PDX Test #35	2.51	40.00	1.44	32.21	1.07	42.51	33.65
	Feed	g CuSO45H2O	Residue	Cu		Total	Total
	assay ×	added ×	assay ×	titration ×
	initial solids	63.55/249.68	final solids	final vol

TABLE C.13
Pressure Oxidation Copper Mass Balance Calculations Continued
	COPPER
	% Copper	% Cu Gain/	% Cu Gain/	Average
Test ID	Lost in soln	Initial Solid	Final Solid	Gain
MP POX Test #1	−4.84	−3.22	−4.36	−3.79
MP POX Test #2	0.11	0.21	0.28	0.25
MP POX Test #3	−1.31	−10.45	−13.66	−12.05
MP POX Test #4	4.82	12.84	16.99	14.92
MP POX Test #5	0.43	3.44	4.15	3.80
MP POX Test #6	1.54	3.08	4.35	3.71
MP POX Test #7	7.36	4.90	6.43	5.66
MP POX Test #8	6.13	16.34	21.29	18.82
MP POX Test #9	−0.02	−0.15	−0.19	−0.17
MP POX Test #10	4.70	9.40	13.20	11.30
MP POX Test #11	35.10	23.38	34.36	28.87
MP POX Test #12	1.65	4.38	5.75	5.07
MP POX Test #13	1.87	3.75	5.60	4.68
MP POX Test #14	15.03	120.21	168.19	144.20
MP POX Test #15	19.03	50.76	64.78	57.77
MP POX Test #16	19.82	13.21	18.54	15.87
MP POX Test #17	13.05	32.62	37.83	35.22
MP POX Test #18	1.91	4.76	5.51	5.13
MP POX Test #19	17.49	43.73	52.78	48.25
MP POX Test #20	4.25	33.95	40.67	37.31
MP POX Test #21	−1.87	−3.74	−4.35	−4.05
MP POX Test #22	15.99	10.66	12.40	11.53
MP POX Test #23	1.56	4.17	4.70	4.43
MP POX Test #24	1.21	2.41	3.54	2.97
MP POX Test #25	2.85	22.79	28.50	25.64
MP POX Test #26	6.84	4.56	5.81	5.19
MP POX Test #27	−0.27	−0.18	−0.21	−0.20
MP POX Test #28	−5.64	−3.76	−4.64	−4.20
MP POX Test #29	−3.82	−7.64	−9.70	−8.67
MP POX Test #30	1.73	13.85	16.95	15.40
MP POX Test #31	13.92	37.06	43.04	40.05
MP POX Test #32	5.68	45.39	89.85	67.62
MP POX Test #33	5.09	10.19	14.72	12.45
MP POX Test #34	−31.43	−20.94	−29.77	−25.36
MP POX Test #35	19.47	51.93	67.08	59.50

TABLE C.14
Pressure Oxidation Iron Mass Balance Calculations
	IRON
			grams
	grams	grams	Fe Out	grams	grams
Test ID	Fe In	Fe Out Solid	Soln	Fe In	Fe Out
MP POX Test #1	4.13	3.40	0.71	4.13	4.11
MP POX Test #2	1.38	1.14	0.23	1.38	1.37
MP POX Test #3	1.38	1.16	0.21	1.38	1.37
MP POX Test #4	4.13	3.47	0.63	4.13	4.10
MP POX Test #5	1.38	0.67	0.24	1.38	0.91
MP POX Test #6	1.38	1.13	0.22	1.38	1.35
MP POX Test #7	4.14	3.55	0.57	4.14	4.12
MP POX Test #8	4.13	3.51	0.59	4.13	4.10
MP POX Test #9	1.38	1.14	0.23	1.38	1.37
MP POX Test #10	1.38	1.09	0.22	1.38	1.31
MP POX Test #11	4.14	2.97	0.71	4.14	3.67
MP POX Test #12	4.15	3.37	0.69	4.15	4.06
MP POX Test #13	1.38	0.94	0.25	1.38	1.19
MP POX Test #14	1.38	1.04	0.22	1.38	1.26
MP POX Test #15	4.13	3.16	0.69	4.13	3.84
MP POX Test #16	4.13	3.27	0.71	4.13	3.98
MP POX Test #17	2.76	2.73	0.14	2.76	2.87
MP POX Test #18	2.76	2.64	0.11	2.76	2.75
MP POX Test #19	2.76	2.55	0.09	2.76	2.64

TABLE C.15
Pressure Oxidation Iron Mass Balance Calculations
	IRON
	grams	grams	grams	grams	grams
Test ID	Fe In	Fe Out Solid	Fe Out Soln	Fe In	Fe Out
MP POX Test #20	1.38	1.17	0.11	1.38	1.28
MP POX Test #21	1.38	1.25	0.06	1.38	1.31
MP POX Test #22	4.13	3.62	0.21	4.13	3.83
MP POX Test #23	4.13	3.81	0.22	4.13	4.03
MP POX Test #24	1.38	1.16	0.09	1.38	1.25
MP POX Test #25	1.38	1.07	0.23	1.38	1.30
MP POX Test #26	4.13	3.87	0.25	4.13	4.12
MP POX Test #27	4.13	3.65	0.35	4.13	4.00
MP POX Test #28	4.14	3.82	0.31	4.14	4.13
MP POX Test #29	1.38	1.18	0.09	1.38	1.26
MP POX Test #30	1.38	1.20	0.12	1.38	1.31
MP POX Test #31	4.14	3.80	0.32	4.14	4.12
MP POX Test #32	1.38	0.74	0.37	1.38	1.11
MP POX Test #33	1.38	1.18	0.12	1.38	1.30
MP POX Test #34	4.13	3.57	0.34	4.13	3.91
MP POX Test #35	4.13	3.81	0.25	4.13	4.06
	Feed assay ×	Residue assay ×	ICP ×	Total	Total
	initial solids	final solids	final vol

TABLE C.16
Pressure Oxidation Iron Mass Balance Calculations Continued
	IRON
			Final
	Solid	Liquid	Liquid	Average
	Fe	Fe	Fe	Extraction	Calculated
Test ID	Extr %	Extr %	Extr %	%	Head
MP POX Test #1	17.72	17.13	17.23	17.36	27.39
MP POX Test #2	17.37	16.56	16.69	16.87	27.33
MP POX Test #3	15.75	15.33	15.39	15.49	27.43
MP POX Test #4	15.93	15.26	15.36	15.52	27.37
MP POX Test #5	51.40	17.40	26.36	31.72	18.18
MP POX Test #6	18.25	16.19	16.53	16.99	26.98
MP POX Test #7	14.09	13.72	13.77	13.86	27.45
MP POX Test #8	15.14	14.29	14.42	14.62	27.32
MP POX Test #9	17.03	16.55	16.63	16.74	27.42
MP POX Test #10	21.23	16.30	17.14	18.22	26.19
MP POX Test #11	28.30	17.08	19.24	21.54	24.46
MP POX Test #12	18.81	16.74	17.10	17.55	26.98
MP POX Test #13	31.97	18.01	20.94	23.64	23.71
MP POX Test #14	24.48	15.88	17.38	19.25	25.18
MP POX Test #15	23.61	16.59	17.84	19.34	25.62
MP POX Test #16	20.88	17.23	17.88	18.66	26.54
MP POX Test #17	1.11	5.24	5.04	3.80	28.69
MP POX Test #18	4.37	3.99	4.01	4.12	27.45
MP POX Test #19	7.38	3.17	3.31	4.62	26.39

TABLE C.17
Pressure Oxidation Iron Mass Balance Calculations Continued
	IRON
	Solid Fe	Liquid Fe	Final Liquid	Average	Calculated
Test ID	Extr %	Extr %	Fe Extr %	Extraction %	Head
MP POX Test #20	14.85	7.89	8.48	10.41	25.63
MP POX Test #21	9.11	4.34	4.56	6.01	26.24
MP POX Test #22	12.29	5.03	5.42	7.58	25.55
MP POX Test #23	7.85	5.34	5.48	6.22	26.86
MP POX Test #24	15.96	6.42	7.10	9.82	24.92
MP POX Test #25	22.50	16.84	17.85	19.06	25.99
MP POX Test #26	6.29	5.95	5.97	6.07	27.46
MP POX Test #27	11.74	8.43	8.72	9.63	26.64
MP POX Test #28	7.66	7.52	7.53	7.57	27.51
MP POX Test #29	14.44	6.23	6.79	9.15	25.29
MP POX Test #30	13.28	8.43	8.86	10.19	26.21
MP POX Test #31	8.11	7.73	7.76	7.87	27.44
MP POX Test #32	46.62	26.98	33.58	35.73	22.14
MP POX Test #33	14.22	8.56	9.07	10.62	25.99
MP POX Test #34	13.69	8.24	8.71	10.21	26.05
MP POX Test #35	7.81	5.95	6.07	6.61	27.04
	(Mass in-	1-(Mass in-	Soln mass out/		Total g out/
	Solid mass out)/	Soln mass out)/	Mass out		g initial solids
	Mass in	Mass in

TABLE C.18
Pressure Oxidation Arsenic Mass Balance Calculations
	ARSENIC
			grams
	grams	grams	As Out	grams	grams
Test ID	As In	As Out Solid	Soln	As In	As Out
MP POX Test #1	1.02	0.64	0.14	1.02	0.78
MP POX Test #2	0.34	0.23	0.04	0.34	0.28
MP POX Test #3	0.34	0.23	0.04	0.34	0.27
MP POX Test #4	1.02	0.71	0.11	1.02	0.82
MP POX Test #5	0.34	0.13	0.06	0.34	0.19
MP POX Test #6	0.34	0.21	0.06	0.34	0.26
MP POX Test #7	1.02	0.72	0.12	1.02	0.84
MP POX Test #8	1.02	0.71	0.12	1.02	0.83
MP POX Test #9	0.34	0.22	0.04	0.34	0.27
MP POX Test #10	0.34	0.21	0.05	0.34	0.26
MP POX Test #11	1.02	0.57	0.16	1.02	0.73
MP POX Test #12	1.02	0.65	0.17	1.02	0.82
MP POX Test #13	0.34	0.18	0.06	0.34	0.24
MP POX Test #14	0.34	0.20	0.06	0.34	0.27
MP POX Test #15	1.02	0.58	0.19	1.02	0.77
MP POX Test #16	1.02	0.61	0.17	1.02	0.78
MP POX Test #17	0.68	0.48	0.05	0.68	0.53
MP POX Test #18	0.68	0.42	0.05	0.68	0.46
MP POX Test #19	0.68	0.42	0.05	0.68	0.47

TABLE C.19
Pressure Oxidation Arsenic Mass Balance Calculations
	ARSENIC
	grams	grams	grams	grams	grams
Test ID	As In	As Out Solid	As Out Soln	As In	As Out
MP POX Test #20	0.34	0.13	0.01	0.34	0.14
MP POX Test #21	0.34	0.12	0.01	0.34	0.13
MP POX Test #22	1.02	0.36	0.01	1.02	0.37
MP POX Test #23	1.02	0.41	0.01	1.02	0.42
MP POX Test #24	0.34	0.14	0.08	0.34	0.22
MP POX Test #25	0.34	0.14	0.01	0.34	0.15
MP POX Test #26	1.02	0.57	0.18	1.02	0.74
MP POX Test #27	1.02	0.34	0.03	1.02	0.37
MP POX Test #28	1.02	0.69	0.08	1.02	0.77
MP POX Test #29	0.34	0.21	0.02	0.34	0.23
MP POX Test #30	0.34	0.24	0.04	0.34	0.28
MP POX Test #31	1.02	0.81	0.04	1.02	0.85
MP POX Test #32	0.34	0.15	0.09	0.34	0.23
MP POX Test #33	0.34	0.15	0.13	0.34	0.29
MP POX Test #34	1.02	0.51	0.32	1.02	0.83
MP POX Test #35	1.02	0.54	0.26	1.02	0.80
	Feed assay ×	Residue assay ×	ICP ×	Total	Total
	initial solids	final solids	final vol

TABLE C.20
Pressure Oxidation Arsenic Mass Balance Calculations Continued
	ARSENIC
		Liquid	Final
	Solid	As	Liquid	Average
	As	Extr	As	Extraction	Calculated
Test ID	Extr %	%	Extr %	%	Head
MP POX Test #1	37.29	13.51	17.73	22.84	5.18
MP POX Test #2	31.15	12.44	15.31	19.63	5.53
MP POX Test #3	33.64	12.97	16.35	20.99	5.39
MP POX Test #4	30.41	11.21	13.87	18.50	5.49
MP POX Test #5	61.48	17.13	30.78	36.46	3.78
MP POX Test #6	38.69	16.51	21.21	25.47	5.29
MP POX Test #7	29.54	11.62	14.15	18.43	5.58
MP POX Test #8	30.44	12.00	14.71	19.05	5.55
MP POX Test #9	34.58	12.90	16.47	21.32	5.33
MP POX Test #10	36.95	13.46	17.59	22.67	5.20
MP POX Test #11	44.16	15.42	21.64	27.08	4.85
MP POX Test #12	36.45	16.69	20.80	24.65	5.46
MP POX Test #13	47.15	19.11	26.56	30.94	4.89
MP POX Test #14	39.88	17.95	22.99	26.94	5.31
MP POX Test #15	43.08	18.25	24.28	28.54	5.11
MP POX Test #16	40.08	17.00	22.10	26.40	5.23
MP POX Test #17	30.01	8.07	10.34	16.14	5.31
MP POX Test #18	38.68	6.77	9.95	18.47	4.63
MP POX Test #19	37.62	6.65	9.63	17.97	4.69

TABLE C.21
Pressure Oxidation Arsenic Mass Balance Calculations Continued
	ARSENIC
	Solid As	Liquid As	Final Liquid	Average	Calculated
Test ID	Extr %	Extr %	As Extr %	Extraction %	Head
MP POX Test #20	62.43	3.62	8.79	24.95	2.80
MP POX Test #21	65.20	4.08	10.50	26.60	2.64
MP POX Test #22	64.72	1.45	3.94	23.37	2.50
MP POX Test #23	60.19	1.44	3.50	21.71	2.81
MP POX Test #24	59.86	23.25	36.68	39.93	4.31
MP POX Test #25	58.13	3.37	7.44	22.98	3.08
MP POX Test #26	44.61	17.49	24.00	28.70	4.96
MP POX Test #27	66.90	2.86	7.96	25.91	2.45
MP POX Test #28	32.75	7.95	10.58	17.09	5.11
MP POX Test #29	38.62	5.72	8.52	17.62	4.56
MP POX Test #30	28.50	11.54	13.90	17.98	5.65
MP POX Test #31	20.86	3.95	4.75	9.85	5.65
MP POX Test #32	57.13	25.38	37.19	39.90	4.64
MP POX Test #33	55.32	39.39	46.86	47.19	5.72
MP POX Test #34	49.82	31.50	38.56	39.96	5.55
MP POX Test #35	46.84	25.07	32.04	34.65	5.32
	(Mass in-	1-(Mass in-	Soln mass out/		Total g out/
	Solid mass out)/	Soln mass out)/	Mass out		g initial solids
	Mass in	Mass in

TABLE C.22
Pressure Oxidation Acid Consumption Mass Balance Calculations
	ACID
	grams	grams	g Acid Consump/	g Acid Consump/	Average
Test ID	Acid In	Acid Out	g Initial Solids	g Final Solids	Consumption
MP POX Test #1	31.09	31.85	−0.050	−0.068	−0.059
MP POX Test #2	10.37	9.90	0.092	0.123	0.108
MP POX Test #3	31.10	31.82	−0.144	−0.188	−0.166
MP POX Test #4	10.37	9.49	0.059	0.078	0.068
MP POX Test #5	10.38	9.74	0.128	0.154	0.141
MP POX Test #6	31.10	29.16	0.387	0.547	0.467
MP POX Test #7	10.37	10.72	−0.023	−0.030	−0.027
MP POX Test #8	31.10	26.82	0.285	0.371	0.328
MP POX Test #9	10.36	9.66	0.141	0.179	0.160
MP POX Test #10	31.10	28.18	0.584	0.820	0.702
MP POX Test #11	10.36	8.68	0.112	0.165	0.139
MP POX Test #12	31.12	28.84	0.152	0.200	0.176
MP POX Test #13	10.39	9.63	0.151	0.226	0.188
MP POX Test #14	31.12	11.65	3.892	5.445	4.668
MP POX Test #15	10.38	19.46	−0.605	−0.773	−0.689
MP POX Test #16	31.10	29.93	0.077	0.109	0.093
MP POX Test #17	20.74	18.00	0.273	0.317	0.295
MP POX Test #18	20.74	18.30	0.243	0.282	0.263
MP POX Test #19	20.74	19.21	0.153	0.185	0.169

TABLE C.23
Pressure Oxidation Acid Consumption Mass Balance Calculations
	ACID
	grams	grams	g Acid Consump/	g Acid Consump/	Average
Test ID	Acid In	Acid Out	g Initial Solids	g Final Solids	Consumption
MP POX Test #20	10.36	46.25	−7.173	−8.593	−7.883
MP POX Test #21	31.10	36.67	−1.113	−1.294	−1.203
MP POX Test #22	10.36	10.85	−0.032	−0.038	−0.035
MP POX Test #23	31.09	37.28	−0.412	−0.464	−0.438
MP POX Test #24	10.37	12.19	−0.364	−0.535	−0.450
MP POX Test #25	31.10	38.77	−1.533	−1.917	−1.725
MP POX Test #26	10.36	9.14	0.081	0.103	0.092
MP POX Test #27	31.09	33.22	−0.142	−0.165	−0.154
MP POX Test #28	31.10	29.76	0.089	0.110	0.100
MP POX Test #29	10.37	10.47	−0.020	−0.026	−0.023
MP POX Test #30	31.09	28.81	0.456	0.558	0.507
MP POX Test #31	10.36	9.41	0.063	0.074	0.068
MP POX Test #32	10.37	9.80	0.114	0.225	0.169
MP POX Test #33	31.09	29.28	0.363	0.524	0.443
MP POX Test #34	10.36	10.14	0.015	0.021	0.018
MP POX Test #35	31.09	30.68	0.027	0.035	0.031
	g of 96.5%	g free acid ×
	H2SO4	final vol
	added

TABLE C.24
Pressure Oxidation Oxygen Mass Balance Calculations
	OXYGEN
	Steam	Oxygen	Final	Oxygen	Oxygen
Test ID	Pressure	In	Pressure	Out	Consumed
MP POX Test #1	0	0	NM
MP POX Test #2	0	0	NM
MP POX Test #3	0	0	NM
MP POX Test #4	0	0	NM
MP POX Test #5	46	0	25	−21	−25
MP POX Test #6	46	0	NM
MP POX Test #7	0	0	NM
MP POX Test #8	0	0	NM
MP POX Test #9	0	0	NM
MP POX Test #10	0	0	NM
MP POX Test #11	46	0	NM
MP POX Test #12	46	0	20	−26	−20
MP POX Test #13	46	0	55	9	−55
MP POX Test #14	46	0	50	4	−50
MP POX Test #15	46	0	50	4	−50
MP POX Test #16	46	0	35	−11	−35
MP POX Test #17	16	50	60	44	−10
MP POX Test #18	16	50	60	44	−10
MP POX Test #19	16	50	60	44	−10

TABLE C.25
Pressure Oxidation Oxygen Mass Balance Calculations
	OXYGEN
	Steam	Oxygen	Final	Oxygen	Oxygen
Test ID	Pressure	In	Pressure	Out	Consumed
MP POX Test #20	0	100	65	65	35
MP POX Test #21	0	100	65	65	35
MP POX Test #22	0	100	60	60	40
MP POX Test #23	0	100	65	65	35
MP POX Test #24	46	100	130	84	−30
MP POX Test #25	46	100	110	64	−10
MP POX Test #26	46	100	130	84	−30
MP POX Test #27	46	100	90	44	10
MP POX Test #28	0	100	90	90	10
MP POX Test #29	0	100	85	85	15
MP POX Test #30	0	100	90	90	10
MP POX Test #31	0	100	85	85	15
MP POX Test #32	46	100	80	34	20
MP POX Test #33	46	100	125	79	−25
MP POX Test #34	46	100	110	64	−10
MP POX Test #35	46	100	125	79	−25
	psig	psig	psig	psig	psig
NM—not measured

APPENDIX D

Stat-Ease Statistical Data

Statistical data from Stat-Ease Design Expert 8.0 for the atmospheric pressure and pressure oxidation tests are shown below.

D.1 Atmospheric Leach Model ANOVA

A description of the Response Surface Model for the 0.5 Factorial, 3 center points DOE is shown in the following sections.

D.1.1 Response 1: Arsenic Extraction ANOVA & Diagnostic Data

The Analysis Of Variance and associated statistical data for Response Surface Reduced 2F1 Model for Response 1 Arsenic Extraction is shown below and in Figures D.1-D.11, which are State Ease graphs for arsenic extraction model.

TABLE D.1
Backward Elimination Regression with Alpha to Exit = 0.100; Forced Terms:
Intercept
Coefficient	t for H0
Removed	Estimate	Coeff = 0	Prob > |t|	R-Squared	MSE
AB	−0.039226989	−0.039007751	0.971334891	0.889820951	12.14142277
CE	0.08508036	0.0976685	0.926893835	0.889558198	9.736301949
CD	−0.16687118	−0.213916513	0.839061942	0.888547428	8.187840932
AE	0.174861055	0.244437812	0.815036263	0.887437549	7.088038259
BE	0.22966789	0.345062087	0.740183783	0.885522897	6.307528156
B-Solids	−0.407428387	−0.648905831	0.534579778	0.879497412	5.901799055
BC	−0.425438699	−0.700494572	0.501324643	0.872927441	5.601216088
AD	−0.43264109	−0.731217525	0.481428873	0.866133138	5.36427399
BD	−0.47299657	−0.816887982	0.431329047	0.858012214	5.215552164
E-Time	−0.828512307	−1.451138314	0.172376894	0.833095696	5.65919602
AC	−0.883415018	−1.485413617	0.161276689	0.804767496	6.146878699
DE	−0.93725219	−1.512130014	0.152742388	0.772881326	6.674091231
C-Initial [Cu2+]	−1.095108465	−1.695590825	0.110614156	0.729349819	7.456223079

TABLE D.2
Analysis of Variance Table [Partial sum of squares-Type III]
	Sum of		Mean	F	p- value
Source	Squares	df	Square	Value	Prob > F
Model	321.489	2	160.745	21.5585	<0.0001	significant
A-Initial Acid	290.979	1	290.979	39.025	<0.0001
D-Temperature	30.5098	1	30.5098	4.09186	0.0601
Residual	119.3	16	7.45622
Lack of Fit	100.799	14	7.19992	0.77834	0.6926	not significant
Pure Error	18.5007	2	9.25036
Cor Total	440.789	18

The Model F-value of 21.56 implies the model is significant. There is a 0.01% chance that a “Model F-Value” this large could occur due to noise.

Values of “Prob >F” less than 0.0500 indicate model terms are significant. In this case A are significant model terms. Values greater than 0.1000 indicate the model terms are not significant.

If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve your model.

The “Lack of Fit F-value” of 0.78 implies the Lack of Fit is not significant relative to the pure error. There is a 69.26% chance that a “Lack of Fit F-value” this large could occur due to noise. Non-significant lack of fit is good—we want the model to fit.

TABLE D.3
Trend Data
	Std. Dev.	2.73061	R-Squared	0.72935
	Mean	11.779	Adj R-Squared	0.69552
	C.V. %	23.182	Pred R-Squared	0.63601
	PRESS	160.441	Adeq Precision	10.406

The “Pred R-Squared” of 0.6360 is in reasonable agreement with the “Adj R-Squared” of 0.6955. “Adeq Precision” measures the signal to noise ratio. A ratio greater than 4 is desirable. Your ratio of 10.406 indicates an adequate signal. This model can be used to navigate the design pace.

TABLE D.4
Confidence Intervals
Coefficient	Standard	95% CI	95% CI
Factor	Estimate	df	Error	Low	High	VIF
Intercept	11.779	1	0.62644	10.451	13.107
A-Initial Acid	4.26453	1	0.68265	2.81737	5.71169	1
D-Temperature	1.38089	1	0.68265	−0.0663	2.82805	1

Final Equation in Terms of Coded Factors:

$\begin{array}{cc}\mathrm{As}\mathrm{Extraction}=+11.78+4.26*A+1.38*D& \left(D\mathrm{.1}\right)\end{array}$

Final Equation in Terms of Actual Factors:

$\begin{array}{cc}\mathrm{As}\mathrm{Extraction}=& \left(D\mathrm{.2}\right)\\ \begin{array}{cc}+4.75269& \\ +0.85291& *\mathrm{Initial}\mathrm{Acid}\\ +0.055236& *\mathrm{Temperature}\end{array}& \end{array}$

The Diagnostics Case Statistics Report for this response is shown below. Proceed to Diagnostic Plots (the next icon in progression). Be sure to look at the:

1) Normal probability plot of the studentized residuals to check for normality of residuals.

2) Studentized residuals versus predicted values to check for constant error.

3) Externally Studentized Residuals to look for outliers, i.e., influential values.

4) Box-Cox plot for power transformations.

TABLE D.5
Diagnostics Case Statistics
					Internally	Externally	Influence on
Standard	Actual	Predicted			Studentized	Studentized	Fitted Value	Cook's	Run
Order	Value	Value	Residual	Leverage	Residual	Residual	DFFITS	Distance	Order
1	7.3224844	8.89537	−1.5729	0.17763	−0.6351897	−0.6229239	−0.2895089	0.0290495	15
2	20.992571	17.4244	3.56815	0.17763	1.44095326	1.49561192	0.69509761	0.1494969	7
3	10.542378	8.89537	1.64701	0.17763	0.66512605	0.65309775	0.3035324	0.0318523	9
4	16.652177	17.4244	−0.7722	0.17763	−0.3118634	−0.3028825	−0.140767	0.0070026	14
5	11.756819	8.89537	2.86145	0.17763	1.15556395	1.16870107	0.54316317	0.0961436	10
6	13.911516	17.4244	−3.5129	0.17763	−1.4186467	−1.4690979	−0.682775	0.1449042	13
7	5.5124557	8.89537	−3.3829	0.17763	−1.3661483	−1.4073966	−0.6540988	0.134378	12
8	14.232981	17.4244	−3.1914	0.17763	−1.2888269	−1.3182019	−0.6126449	0.1195974	11
9	5.051925	6.13358	−1.0817	0.17763	−0.4368141	−0.4254881	−0.197749	0.0137381	3
10	15.879534	14.6626	1.21689	0.17763	0.49142788	0.47945517	0.22283062	0.0173881	17
11	5.8099897	6.13358	−0.3236	0.17763	−0.1306786	−0.1265966	−0.0588368	0.0012295	16
12	16.386052	14.6626	1.72341	0.17763	0.69597943	0.68431737	0.31804198	0.0348759	6
13	5.2215797	6.13358	−0.912	0.17763	−0.368301	−0.3581272	−0.1664425	0.0097665	19
14	12.99924	14.6626	−1.6634	0.17763	−0.6717444	−0.6597841	−0.3066399	0.0324893	5
15	4.5423743	6.13358	−1.5912	0.17763	−0.6425901	−0.6303725	−0.2929707	0.0297304	4
16	12.938408	14.6626	−1.7242	0.17763	−0.6963109	−0.6846535	−0.3181982	0.0349091	18
17	12.124663	11.779	0.34566	0.05263	0.13005567	0.12599247	0.02969671	0.0003132	1
18	13.878192	11.779	2.09919	0.05263	0.78982818	0.78010695	0.18387297	0.0115524	2
19	18.045724	11.779	6.26672	0.05263	2.35787842	2.82623503	0.66614998	0.1029554	8
Current Transform: None
Box-Cox Power Transformation
Constant	95% CI	95% CI	Best	Rec.
k	Low	High	Lambda	Transform
0	−0.35	1.54	0.6	None

Figures D.1-D.11 are State Ease graphs for arsenic extraction model.

D.1.2 Response 2: Copper Difference ANOVA & Diagnostic Data

The Analysis of Variance and associated statistical data for Response Surface Reduced 2F1 Model for Response 2 Copper Difference is shown below and in Figures D.12-D.22, which are State Ease graphs for copper difference model.

TABLE D.6
Backward Elimination Regression with Alpha to Exit = 0.100;
Forced Terms: Intercept
Coef-
ficient
Re-	t for H0
moved	Estimate	Coeff = 0	Prob > |t|	R-Squared	MSE
E-Time	0.00164	0.095629314	0.9298449	0.99102907	0.00353
AC	0.00303	0.203889035	0.8483933	0.99093583	0.00286
DE	−0.0054	−0.407325764	0.7006215	0.99063506	0.00246
AE	0.00576	0.464536345	0.658642	0.99029824	0.00218
BE	−0.0067	−0.573817966	0.5840488	0.98984189	0.002
CD	−0.0118	−1.058701184	0.3206523	0.98841868	0.00203
Hierarchical Terms Added after Backward Elimination Regression
E-Time
Transform: None
Constant: 0

TABLE D.7
Analysis of Variance Table [Partial sum of squares-Type III]
	Sum of		Mean	F	p-value
Source	Squares	df	Square	Value	Prob > F
Model	1.557659848	10	0.155766	68.4397299	<0.0001	significant
A-Initial Acid	0.045734577	1	0.0457346	20.0946445	0.002
B-Solids	1.283374317	1	1.2833743	563.883006	<0.0001
C-Initial [Cu2+]	0.141436193	1	0.1414362	62.1435729	<0.0001
D-Temperature	0.010770229	1	0.0107702	4.73217296	0.0613
E-Time	4.30E−05	1	4.30E−05	0.01887696	0.8941
AB	0.007664206	1	0.0076642	3.36746291	0.1038
AD	0.014381894	1	0.0143819	6.31904937	0.0362
BC	0.015081931	1	0.0150819	6.62662847	0.0329
BD	0.022385915	1	0.0223859	9.83581885	0.0139
CE	0.016787622	1	0.0167876	7.37606673	0.0264
Residual	0.018207668	8	0.002276
Lack of Fit	0.006773126	6	0.0011289	0.19744635	0.9485	not significant
Pure Error	0.011434542	2	0.0057173
Cor Total	1.575867516	18

The Model F-value of 68.44 implies the model is significant. There is a 0.01% chance that a “Model F-Value” this large could occur due to noise.

Values of “Prob >F” less than 0.0500 indicate model terms are significant. In this case A, B, C, AD, BC, BD, CE are significant model terms. Values greater than 0.1000 indicate the model terms are not significant.

If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve your model.

The “Lack of Fit F-value” of 0.20 implies the Lack of Fit is not significant relative to the pure error. There is a 94.85% chance that a “Lack of Fit F-value” this large could occur due to noise. Non-significant lack of fit is good—we want the model to fit.

TABLE D.8
Trend Data
Std. Dev.	0.047707007	R-Squared	0.9884459
Mean	0.546196201	Adj R-Squared	0.9740034
C.V. %	8.734408392	Pred R-Squared	0.9626489
PRESS	0.058860446	Adeq Precision	24.085464

The “Pred R-Squared” of 0.9626 is in reasonable agreement with the “Adj R-Squared” of 0.9740. “Adeq Precision” measures the signal to noise ratio. A ratio greater than 4 is desirable. Your ratio of 24.085 indicates an adequate signal. This model can be used to navigate the design space.

TABLE D.9
Confidence Intervals
Coefficient	Standard	95% CI	95% CI
Factor	Estimate	df	Error	Low	High	VIF
Intercept	0.546196201	1	0.0109447	0.52095759	0.57143
A-Initial Acid	0.05346411	1	0.0119268	0.02596097	0.08097	1
B-Solids	0.28321528	1	0.0119268	0.25571214	0.31072	1
C-Initial [Cu2+]	−0.09402001	1	0.0119268	−0.1215231	−0.0665	1
D-Temperature	−0.02594493	1	0.0119268	−0.0534481	0.00156	1
E-Time	0.001638658	1	0.0119268	−0.0258645	0.02914	1
AB	0.021886363	1	0.0119268	−0.0056168	0.04939	1
AD	0.029981134	1	0.0119268	0.002478	0.05748	1
BC	−0.03070213	1	0.0119268	−0.0582053	−0.0032	1
BD	−0.03740481	1	0.0119268	−0.0649079	−0.0099	1
CE	−0.03239176	1	0.0119268	−0.0598949	−0.0049	1

Final Equation in Terms of Coded Factors:

$\begin{array}{cc}\mathrm{Cu}\mathrm{Difference}=+0.546196201+0.05346411*A+0.28321528*B-0.094020009*C-0.025944929*D+0.001638658*E+0.021886363*A*B+0.029981134*A*D-0.030702129*B*C-0.037404809*B*D-0.032391764*C*E& \left(D\mathrm{.3}\right)\end{array}$

Final Equation in Terms of Actual Factors:

$\begin{array}{cc}\mathrm{Cu}\mathrm{Difference}=-0.12458313-0.010054177*\mathrm{Initial}\mathrm{Acid}+0.038730875*\mathrm{Solids}+0.002144518*\mathrm{Initial}\left[\mathrm{Cu}2+\right]+0.000755342*\mathrm{Temperature}+0.027812465*\mathrm{Time}+0.000437727*\mathrm{Initial}\mathrm{Acid}*\mathrm{Solids}+0.029981*\mathrm{Initial}\mathrm{Acid}*\mathrm{Temperature}-0.000204681*\mathrm{Solids}*\mathrm{Initial}\left[\mathrm{Cu}2+\right]-0.000149619*\mathrm{Solids}*\mathrm{Temperature}-0.001079725*\mathrm{Initial}\left[\mathrm{Cu}2+\right]*\mathrm{Time}& \left(D\mathrm{.4}\right)\end{array}$

The Diagnostics Case Statistics Report for this response is shown below. Proceed to Diagnostic Plots (the next icon in progression). Be sure to look at the:

1) Normal probability plot of the studentized residuals to check for normality of residuals.

2) Studentized residuals versus predicted values to check for constant error.

3) Externally Studentized Residuals to look for outliers, i.e., influential values.

4) Box-Cox plot for power transformations.

TABLE D.10
Diagnostics Case Statistics
					Internally	Externally	Influence on
Standard	Actual	Predicted			Studentized	Studentized	Fitted Value	Cook's	Run
Order	Value	Value	Residual	Leverage	Residual	Residual	DFFITS	Distance	Order
1	0.31547886	0.310230221	0.00525	0.67763	0.193770798	0.18168284	0.263411349	0.00718	15
2	0.36195228	0.365287141	−0.0033	0.67763	−0.12311735	−0.115274995	−0.16713049	0.0029	7
3	0.77907536	0.751421853	0.02765	0.67763	1.020920209	1.024017284	1.48466291	0.19917	9
4	1.0274448	1.030145908	−0.0027	0.67763	−0.099720291	−0.093337819	−0.135325058	0.0019	14
5	0.16482252	0.180317146	−0.0155	0.67763	−0.572035089	−0.546380805	−0.79216565	0.06253	10
6	0.23501757	0.241928696	−0.0069	0.67763	−0.255146941	−0.239645157	−0.34744753	0.01244	13
7	0.4673554	0.505254893	−0.0379	0.67763	−1.3991845	−1.50599484	* −2.18	0.37411	12
8	0.76987944	0.777424318	−0.0075	0.67763	−0.278544	−0.261826791	−0.379607387	0.01483	11
9	0.25889226	0.279211886	−0.0203	0.67763	−0.750165842	−0.727779938	−1.055165667	0.10754	3
10	0.34837983	0.350465956	−0.0021	0.67763	−0.077016189	−0.07206877	−0.104488304	0.00113	17
11	0.98519106	1.006144438	−0.021	0.67763	−0.773562901	−0.752284017	−1.090692702	0.11435	16
12	1.00433128	1.028822273	−0.0245	0.67763	−0.9041656	−0.892605686	−1.294136902	0.15622	6
13	0.16592708	0.155853441	0.01007	0.67763	0.37190155	0.350928849	0.508791263	0.02643	19
14	0.21239302	0.220552881	−0.0082	0.67763	−0.301248103	−0.28340382	−0.410890663	0.01734	5
15	0.76413024	0.753422848	0.01071	0.67763	0.395298609	0.373433039	0.541418775	0.02986	4
16	0.79690032	0.782655313	0.01425	0.67763	0.525901308	0.500666145	0.725886631	0.05285	18
17	0.5121584	0.546196201	−0.034	0.05263	−0.733026825	−0.709940121	−0.167334491	0.00271	1
18	0.5504083	0.546196201	0.00421	0.05263	0.090710382	0.084895464	0.020010053	4.16E−05	2
19	0.65798979	0.546196201	0.11179	0.05263	2.407549802	4.290892899	1.011373155	0.02927	8
* Exceeds limits

Figures D.12-D.22 are State Ease graphs for copper difference model.

D.1.3 Response 3: Iron Extraction ANOVA & Diagnostic Data

The Analysis of Variance and associated statistical data for Response Surface Reduced 2F1 Model Response 3 of Iron Extraction is shown below and in Figures D.23-D.33, which are State Ease graphs for iron extraction model.

TABLE D.11
Backward Elimination Regression with Alpha to Exit = 0.100; Forced Term: Intercept
Coefficient	t for H0
Removed	Estimate	Coeff = 0	Prob > |t|	R-Squared	MSE
CD	0.02472212	0.047993986	0.964737418	0.957889633	3.186488378
AB	0.041817972	0.093705868	0.929848867	0.957797192	2.55478668
AC	−0.064286059	−0.160879042	0.87848683	0.957578733	2.140009426
B-Solids	0.070438539	0.192602753	0.853623854	0.957316458	1.845634566
AE	−0.104189542	−0.306768853	0.767943502	0.956742626	1.636641166
DE	−0.123969776	−0.38761366	0.7084111	0.955930229	1.482113936
AD	0.149740642	0.491992958	0.634501455	0.954744962	1.369778158
BD	−0.269078348	−0.919631048	0.379414635	0.950917647	1.350566554
BC	0.270045443	0.92947743	0.372589722	0.947062771	1.335252063
BE	−0.294185332	−1.018355417	0.328601854	0.942487902	1.3390573
CE	−0.333041366	−1.1512207	0.270375734	0.936624724	1.370172124

TABLE D.12
Analysis of Variance Table [Partial sum of squares-Type III]
	Sum of		Mean	F	p-value
Source	Squares	df	Square	Value	Prob > F
Model	283.497	4	70.8743	51.7266	<0.0001	significant
A-Initial Acid	193.04	1	193.04	140.887	<0.0001
C-Initial [Cu2+]	14.3795	1	14.3795	10.4947	0.0059
D-Temperature	68.6212	1	68.6212	50.0822	<0.0001
E-Time	7.45676	1	7.45676	5.44221	0.0351
Residual	19.1824	14	1.37017
Lack of Fit	16.9661	12	1.41384	1.27587	0.5213	not significant
Pure Error	2.21628	2	1.10814
Cor Total	302.68	18

The Model F-value of 51.73 implies the model is significant. There is a 0.01% chance that a “Model F-Value” this large could occur due to noise.

Values of “Prob >F” less than 0.0500 indicate model terms are significant. In this case A, C, D, E are significant model terms. Values greater than 0.1000 indicate the model terms are not significant.

If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve your model.

The “Lack of Fit F-value” of 1.28 implies the Lack of Fit is not significant relative to the pure error. There is a 52.13% chance that a “Lack of Fit F-value” this large could occur due to noise. Non-significant lack of fit is good—we want the model to fit.

TABLE D.13
Trend Data
	Std. Dev.	1.1705435	R-Squared	0.93662
	Mean	10.74605	Adj R-Squared	0.91852
	C.V. %	10.89278	Pred R-Squared	0.90415
	PRESS	29.01045	Adeq Precision	23.898

The “Pred R-Squared” of 0.9042 is in reasonable agreement with the “Adj R-Squared” of 0.9185. “Adeq Precision” measures the signal to noise ratio. A ratio greater than 4 is desirable. Your ratio of 23.898 indicates an adequate signal. This model can be used to navigate the design space.

TABLE D.14
Confidence Intervals
Coefficient	Standard	95% CI	95% CI
Factor	Estimate	df	Error	Low	High	VIF
Intercept	10.74605	1	0.26854	10.1701	11.322
A-Initial Acid	3.4734694	1	0.29264	2.84583	4.10111	1
C-Initial [Cu2+]	−0.948009	1	0.29264	−1.5757	−0.3204	1
D-Temperature	2.0709474	1	0.29264	1.44331	2.69859	1
E-Time	0.6826768	1	0.29264	0.05504	1.31032	1

Final Equation in Terms of Coded Factors:

$\begin{array}{cc}\mathrm{Fe}\mathrm{Extraction}=+10.75+3.47*A-0.95*C+2.07*D+0.68*E& \left(D\mathrm{.5}\right)\end{array}$

Final Equation in Terms of Actual Factors:

$\begin{array}{cc}\mathrm{Fe}\mathrm{Extraction}=+3.34535+0.69469*\mathrm{Initial}\mathrm{Acid}-0.063201*\mathrm{Initial}\left[\mathrm{Cu}2+\right]+0.082838*\mathrm{Temperature}+0.34134*\mathrm{Time}& \left(D\mathrm{.6}\right)\end{array}$

The Diagnostics Case Statistics Report for this response is shown below. Proceed to Diagnostic Plots (the next icon in progression). Be sure to look at the:

1) Normal probability plot of the studentized residuals to check for normality of residuals.

2) Studentized residuals versus predicted values to check for constant error.

3) Externally Studentized Residuals to look for outliers, i.e., influential values.

4) Box-Cox plot for power transformations.

TABLE D.15
Diagnostics Case Statistics
					Internally	Externally	Influence on
Standard	Actual	Predicted			Studentized	Studentized	Fitted Value	Cook's	Run
Order	Value	Value	Residual	Leverage	Residual	Residual	DFFITS	Distance	Order
1	11.531211	10.97421	0.556998	0.30263	0.569816	0.555569	0.3659856	0.02818	15
2	16.4507	16.5558	−0.1051	0.30263	−0.10752	−0.1036489	−0.06828	0.001	7
3	8.5183291	9.60886	−1.09053	0.30263	−1.11563	−1.1262745	−0.741942	0.10802	9
4	17.172083	17.92115	−0.74907	0.30263	−0.76631	−0.7544239	−0.496983	0.05097	14
5	7.3589555	7.712842	−0.35389	0.30263	−0.36203	−0.3505062	−0.230899	0.01138	10
6	15.43287	16.02513	−0.59227	0.30263	−0.6059	−0.591664	−0.389763	0.03186	13
7	8.0778413	9.078196	−1.00035	0.30263	−1.02338	−1.0252429	−0.675387	0.0909	12
8	15.416364	14.65978	0.756583	0.30263	0.773995	0.7623288	0.5021903	0.05199	11
9	4.3718993	5.466965	−1.09507	0.30263	−1.12027	−1.1314183	−0.745331	0.10892	3
10	13.93204	13.77926	0.152782	0.30263	0.156298	0.1507443	0.099304	0.00212	17
11	6.9149613	6.832319	0.082643	0.30263	0.084545	0.0814899	0.0536822	0.00062	16
12	12.083622	12.4139	−0.33028	0.30263	−0.33788	−0.326928	−0.215366	0.00991	6
13	4.4249617	4.936301	−0.51134	0.30263	−0.52311	−0.5090783	−0.335359	0.02375	19
14	9.32463	10.51789	−1.19326	0.30263	−1.22072	−1.2444018	−0.81976	0.12933	5
15	4.4048609	3.570947	0.833913	0.30263	0.853105	0.8443107	0.5561965	0.06317	4
16	11.366222	11.88324	−0.51702	0.30263	−0.52892	−0.5148463	−0.339159	0.02428	18
17	11.477072	10.74605	0.731022	0.05263	0.641628	0.6275849	0.1479232	0.00457	1
18	12.344213	10.74605	1.598163	0.05263	1.40273	1.458044	0.3436643	0.02186	2
19	13.572111	10.74605	2.826061	0.05263	2.480473	3.1926206	0.7525079	0.06836	8
Current Transform: None
Box-Cox Power Transformation
Constant	95% CI	95% CI	Best	Rec.
k	Low	High	Lambda	Transform
0	0.41	1.84	1.1	None

Figures D.23-D.33 are State Ease graphs for iron extraction model.

D.1.4 Response 4: Acid Consumption ANOVA & Diagnostic Data

The Analysis of Variance and associated statistical data for Response Surface Reduced 2F1 Model for Response 4 Acid Consumption is shown below and in Figures D.34-D.44, which are State Ease graphs for acid consumption model.

TABLE D.16
Backward Elimination Regression with Alpha to Exit = 0.100; Forced Terms: Intercept
Coefficient	t for H0
Removed	Estimate	Coeff = 0	Prob > |t|	R-Squared	MSE
E-Time	0.015819091	−0.063562872	0.955099591	0.931536532	0.662004853
AE	0.015819091	−0.077769789	0.942907722	0.931398507	0.497504614
BD	−0.01950291	0.110601455	0.917259631	0.931188712	0.399220855
CE	0.01950291	−0.123467538	0.906546545	0.930978917	0.333698348
BC	0.031442378	−0.217720012	0.834862706	0.930433627	0.288286866
DE	−0.031442378	0.234241019	0.8215015	0.929888338	0.254228254
B-Solids	−0.04221945	0.334935094	0.746287085	0.928905184	0.229149527
AB	−0.04221945	0.352787412	0.732369054	0.927922029	0.209086545
BE	−0.059193051	0.517806711	0.615854159	0.925989448	0.195175139
CD	0.059193051	−0.535942835	0.602666491	0.924056866	0.1835823
C-Initial [Cu2+]	−0.082885378	0.773788924	0.454030355	0.920267624	0.177915952
AC	−0.082885378	0.786014338	0.445950269	0.916478383	0.173059082
D-Temperature	0.121688317	−1.170069547	0.261506763	0.908310787	0.17731706
AD	0.121688317	−1.155935533	0.265787809	0.900143192	0.18104279
Transform: Base 10 Log
Constant: 0.00013528
These Rows Were Ignored for this Analysis: 2

TABLE D.17
Analysis of Variance Table [Partial sum of squares-Type III]
	Sum of		Mean	F	p-value
Source	Squares	df	Square	Value	Prob >F
Model	26.1117	1	26.1117	144.229	<0.0001	significant
A-Initial Acid	26.1117	1	26.1117	144.229	<0.0001
Residual	2.89668	16	0.18104
Lack of Fit	2.87155	15	0.19144	7.61774	0.2778	not significant
Pure Error	0.02513	1	0.02513
Cor Total	29.0084	17

The Model F-value of 144.23 implies the model is significant. There is a 0.01% chance that a “Model F-Value” this large could occur due to noise.

Values of “Prob >F” less than 0.0500 indicate model terms are significant. In this case A are significant model terms. Values greater than 0.1000 indicate the model terms are not significant.

If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve your model.

The “Lack of Fit F-value” of 7.62 implies the Lack of Fit is not significant relative to the pure error. There is a 27.78% chance that a “Lack of Fit F-value” this large could occur due to noise. Non-significant lack of fit is good—we want the model to fit.

TABLE D.18
Trend Data
	Std. Dev.	0.42549	R-Squared	0.90014
	Mean	−2.4747	Adj R-Squared	0.8939
	C.V. %	17.1936	Pred R-Squared	0.88163
	PRESS	3.43376	Adeq Precision	18.0143

The “Pred R-Squared” of 0.8816 is in reasonable agreement with the “Adj R-Squared” of 0.8939. “Adeq Precision” measures the signal to noise ratio. A ratio greater than 4 is desirable. Your ratio of 18.014 indicates an adequate signal. This model can be used to navigate the design space.

TABLE D.19
Confidence Intervals
Co-		95%	95%
efficient	Standard	CI	CI
Factor	Estimate	df	Error	Low	High	VIF
Intercept	−2.4747	1	0.10029	−2.6873	−2.2621
A-Initial	1.27749	1	0.10637	1.05199	1.50299	1
Acid

Final Equation in Terms of Coded Factors:

$\begin{array}{cc}\mathrm{Log}10\left(\mathrm{Acid}\mathrm{Consumption}+0.00\right)=-2.47+1.28*A& \left(D\mathrm{.7}\right)\end{array}$

Final Equation in Terms of Actual Factors:

$\begin{array}{cc}\mathrm{Log}10\left(\mathrm{Acid}\mathrm{Consumption}+0.00\right)=-3.75219+0.25550*\mathrm{Initial}\mathrm{Acid}& \left(D\mathrm{.8}\right)\end{array}$

The Diagnostics Case Statistics Report for this response is shown below. Proceed to Diagnostic Plots (the next icon in progression). Be sure to look at the:

1) Normal probability plot of the studentized residuals to check for normality of residuals.

2) Studentized residuals versus predicted values to check for constant error.

3) Externally Studentized Residuals to look for outliers, i.e., influential values.

4) Box-Cox plot for power transformations.

TABLE D.20
Diagnostics Case Statistics
					Internally	Externally	Influence
Stan-					Stu-	Stu-	on Fitted
dard	Actual	Predicted			dentized	dentized	Value	Cook's	Run
Order	Value	Value	Residual	Leverage	Residual	Residual	DFFITS	Distance	Order
1	−3.868766	−3.7521926	−0.1166	0.118056	−0.291736	−0.283226	−0.103623	0.0057	15
2	−0.868333	−1.1972122	0.32888	0.118056	0.823047	0.814337	0.2979386	0.04534	7
3	−3.868766	−3.7521926	−0.1166	0.118056	−0.291736	−0.283226	−0.103623	0.0057	9
4	−1.177716	−1.1972122	0.0195	0.118056	0.0487909	0.047245	0.0172854	0.00016	14
5	−3.868766	−3.7521926	−0.1166	0.118056	−0.291736	−0.283226	−0.103623	0.0057	10
6	−1.025596	−1.1972122	0.17162	0.118056	0.4294844	0.418264	0.1530289	0.01235	13
7	−3.868766	−3.7521926	−0.1166	0.118056	−0.291736	−0.283226	−0.103623	0.0057	12
8	−1.209992	−1.1972122	−0.0128	0.118056	−0.031983	−0.030968	−0.01133	6.85E−05	11
9	−3.868766	−3.7521926	−0.1166	0.118056	−0.291736	−0.283226	−0.103623	0.0057	3
10	−1.13305	−1.1972122	0.06416	0.118056	0.160572	0.155599	0.0569283	0.00173	17
11	−3.868766	−3.7521926	−0.1166	0.118056	−0.291736	−0.283226	−0.103623	0.0057	16
12	−1.412962	−1.1972122	−0.2157	0.118056	−0.539932	−0.527615	−0.193037	0.01951	6
13	−3.868766	−3.7521926	−0.1166	0.118056	−0.291736	−0.283226	−0.103623	0.0057	19
14	−1.890409	−1.1972122	−0.6932	0.118056	−1.734784	−1.864137	−0.682025	0.20142	5
15	−3.868766	−3.7521926	−0.1166	0.118056	−0.291736	−0.283226	−0.103623	0.0057	4
16	−1.79223	−1.1972122	−0.595	0.118056	−1.489081	−1.553452	−0.568356	0.14841	18
17	−1.654207	−2.4747024	0.8205	0.055556	1.9842548	2.212688	0.5366557	0.1158	1
19	−1.430018	−2.4747024	1.04468	0.055556	2.5264254	3.155211	0.765251	0.18773	8
Current Transform: Base 10 Log Constant: 0.000135
Box-Cox Power Transformation
Constant	95% CI	95% CI	Best	Rec.
k	Low	High	Lambda	Transform
0.00014	−0.24	0.17	−0.04	Log

Figures D.34-D.44 are State Ease graphs for acid consumption model.

D.1.5 Model Graphs

The graphs in Figures D.45-D.50 show the preceding statistical data by varying the effects and their corresponding responses.

D.2 Pressure Oxidation Leach Model Fit Summaries & ANOVA

A description of the Response Surface Model for the 0.5 Factorial, 3 center points DOE is shown in the following sections.

D.2.1 Response 1: Arsenic Extraction ANOVA & Diagnostic Data

The Analysis of Variance and associated statistical data for Response Surface Reduced 2F1 Model for Response 1 Arsenic Extraction is shown below.

TABLE D.21
Backward Elimination Regression with Alpha to Exit = 0.100; Forced Terms: Intercept
Coefficient	t for H0
Removed	Estimate	Coeff = 0	Prob > |t|	R-Squared	MSE
AF	0.003873909	0.130343511	0.898290003	0.427632743	0.02628
B-Temperature	−0.004108757	−0.143373345	0.888038516	0.426792348	0.02457
CF	0.00433793	0.156564857	0.8776756	0.425855629	0.02307
BD	0.005637224	0.209960149	0.836349045	0.424273744	0.02177
D-Acid	0.007986792	0.306204071	0.763167557	0.421098412	0.02067
AD	0.008648594	0.340252673	0.737604828	0.41737505	0.01971
BC	−0.009676432	−0.389869865	0.700968707	0.412714096	0.01888
CE	−0.010208882	−0.420330149	0.678725908	0.407526088	0.01814
A-Time	0.017856587	0.750059325	0.461540393	0.39165374	0.01778
EF	0.017928752	0.760690731	0.454918151	0.37565284	0.01745
AC	0.018971721	0.812418313	0.424881162	0.357736153	0.0172
BE	0.019718299	0.850433696	0.403488944	0.338381599	0.01701
E-Solids	−0.020081704	−0.870941371	0.392072997	0.318307068	0.01685
F-O2 Pressure	0.022017182	0.959347947	0.346220495	0.294176489	0.0168
BF	0.023497317	1.025354967	0.314294952	0.266692433	0.01684
C-Cu2+	0.024916987	1.08630955	0.286605984	0.235786964	0.01694
DE	−0.026517577	−1.152518103	0.258520426	0.200783425	0.01713
DF	0.026864937	1.161278396	0.254685606	0.164856842	0.01732
AB	0.027074105	1.163795386	0.253386353	0.128368637	0.01751
CD	−0.02997355	−1.281353288	0.209277401	0.083646696	0.01785
Hierarchical Terms Added after Backward Elimination Regression
A-Time,
E-Solids

TABLE D.22
Analysis of Variance Table [Partial sum of squares-Type III]
					p-value
Source	Sum of Squares	df	Mean Square	F Value	Prob > F
Model	0.076880031	3	0.025626677	1.403670206	0.2603	not significant
A-Time	0.010203446	1	0.010203446	0.558881402	0.4603
E-Solids	0.012904795	1	0.012904795	0.706844524	0.4069
AE	0.05377179	1	0.05377179	2.945284691	0.0961
Residual	0.565964127	31	0.018256907
Lack of Fit	0.556946929	29	0.019205067	4.259652755	0.2078	not significant
Pure Error	0.009017198	2	0.004508599
Cor Total	0.642844157	34

The “Model F-value” of 1.40 implies the model is not significant relative to the noise. There is a 26.03% chance that a “Model F-value” this large could occur due to noise.

Values of “Prob >F” less than 0.0500 indicate model terms are significant. In this case there are no significant model terms. Values greater than 0.1000 indicate the model terms are not significant.

If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve your model.

The “Lack of Fit F-value” of 4.26 implies the Lack of Fit is not significant relative to the pure error. There is a 20.78% chance that a “Lack of Fit F-value” this large could occur due to noise. Non-significant lack of fit is good—we want the model to fit.

TABLE D.23
Trend Data
Std. Dev.	0.135118124	R-Squared	0.119593574
Mean	1.379820144	Adj R-Squared	0.034392953
C.V. %	9.792444629	Pred R-Squared	−0.083106026
PRESS	0.69626838	Adeq Precision	2.674094748

A negative “Pred R-Squared” implies that the overall mean is a better predictor of your response than the current model. “Adeq Precision” measures the signal to noise ratio. A ratio of 2.67 indicates an inadequate signal and we should not use this model to navigate the design space.

TABLE D.24
Confidence Intervals
Coefficient	Standard	95%	95% CI
Factor	Estimate	CI df	Error	Low	High	VIF
Intercept	1.379820144	1	0.022839131	1.333239428	1.4264
A-Time	0.017856587	1	0.023885735	−0.030858692	0.06657	1
E-Solids	−0.020081704	1	0.023885735	−0.068796983	0.02863	1
AE	0.040992297	1	0.023885735	−0.007722981	0.08971	1

Final Equation in Terms of Coded Factors:

$\begin{array}{cc}\mathrm{Log}10\left(\mathrm{As}\mathrm{Extraction}\right)=+1.38+0.018*A-0.020*E+0.041*A*E& \left(D\mathrm{.9}\right)\end{array}$

Final Equation in Terms of Actual Factors:

$\begin{array}{cc}\mathrm{Log}10\left(\mathrm{As}\mathrm{Extraction}\right)=+1.61237-0.25651*\mathrm{Time}-0.028612*\mathrm{Solids}+0.032794*\mathrm{Time}*\mathrm{Solids}& \left(D\mathrm{.10}\right)\end{array}$

The Diagnostics Case Statistics Report for this response is shown below. Proceed to Diagnostic Plots (the next icon in progression). Be sure to look at the:

1) Normal probability plot of the studentized residuals to check for normality of residuals.

2) Studentized residuals versus predicted values to check for constant error.

3) Externally Studentized Residuals to look for outliers, i.e., influential values.

4) Box-Cox plot for power transformations.

TABLE D.25
Diagnostics Case Statistics
					Internally	Externally	Influence
Stan-					Stu-	Stu-	on Fitted
dard	Actual	Predicted			dentized	dentized	Value	Cook's	Run
Order	Value	Value	Residual	Leverage	Residual	Residual	DFFITS	Distance	Order
1	1.35877	1.42303756	−0.0643	0.12232	−0.5076769	−0.501511	−0.1872249	0.00898	2
2	1.29297	1.37676614	−0.0838	0.12232	−0.6619887	−0.655876	−0.244853	0.01527	29
3	1.32194	1.42303756	−0.1011	0.12232	−0.7986868	−0.79391	−0.296384	0.02223	24
4	1.26712	1.37676614	−0.1096	0.12232	−0.8661892	−0.862607	−0.3220299	0.02614	13
5	1.56185	1.42303756	0.13881	0.12232	1.09656343	1.1002823	0.41075952	0.0419	20
6	1.40603	1.37676614	0.02927	0.12232	0.23121213	0.2276487	0.08498626	0.00186	9
7	1.26562	1.42303756	−0.1574	0.12232	−1.2435424	−1.255024	−0.468528	0.05388	5
8	1.27995	1.37676614	−0.0968	0.12232	−0.7648292	−0.759593	−0.2835727	0.02038	32
9	1.32871	1.42303756	−0.0943	0.12232	−0.7452087	−0.739747	−0.2761636	0.01935	21
10	1.35541	1.37676614	−0.0214	0.12232	−0.168688	−0.166021	−0.0619794	0.00099	10
11	1.43258	1.42303756	0.00954	0.12232	0.07537159	0.0741528	0.02768285	0.0002	6
12	1.39179	1.37676614	0.01502	0.12232	0.11865101	0.1167481	0.04358463	0.00049	33
13	1.49051	1.42303756	0.06748	0.12232	0.53304361	0.5267954	0.1966643	0.0099	3
14	1.43041	1.37676614	0.05364	0.12232	0.42374652	0.4180684	0.15607412	0.00626	30
15	1.4554	1.42303756	0.03236	0.12232	0.25563226	0.2517408	0.09398038	0.00228	25
16	1.42152	1.37676614	0.04476	0.12232	0.35358161	0.3485354	0.13011593	0.00436	14
17	1.20799	1.30088956	−0.0929	0.12232	−0.7339039	−0.728325	−0.2718996	0.01877	22
18	1.26639	1.41858732	−0.1522	0.12232	−1.2023099	−1.211339	−0.4522193	0.05037	7
19	1.25443	1.30088956	−0.0465	0.12232	−0.3670042	−0.361823	−0.1350765	0.00469	11
20	1.397	1.41858732	−0.0216	0.12232	−0.1705143	−0.16782	−0.062651	0.00101	34
21	1.42483	1.30088956	0.12394	0.12232	0.97914458	0.9784717	0.36528496	0.0334	4
22	1.36862	1.41858732	−0.05	0.12232	−0.3946995	−0.38926	−0.1453195	0.00543	31
23	1.33664	1.30088956	0.03575	0.12232	0.28242737	0.2781929	0.10385551	0.00278	26
24	1.60131	1.41858732	0.18272	0.12232	1.44347878	1.470277	0.54888666	0.0726	15
25	1.36136	1.30088956	0.06047	0.12232	0.47774281	0.4717138	0.17610112	0.00795	1
26	1.4579	1.41858732	0.03932	0.12232	0.31060282	0.3060286	0.11424719	0.00336	28
27	1.41344	1.30088956	0.11255	0.12232	0.88912862	0.886041	0.33077855	0.02754	27
28	1.23279	1.41858732	−0.1858	0.12232	−1.46778	−1.496862	−0.5588113	0.07506	16
29	1.24597	1.30088956	−0.0549	0.12232	−0.4338237	−0.428071	−0.1598081	0.00656	23
30	1.25477	1.41858732	−0.1638	0.12232	−1.2940944	−1.308896	−0.4886397	0.05835	8
31	0.99351	1.30088956	−0.3074	0.12232	−2.4282155	−2.654473	−0.9909732	0.20544	12
32	1.60097	1.41858732	0.18238	0.12232	1.44081255	1.4673661	0.54779998	0.07233	35
33	1.67385	1.37982014	0.29403	0.02857	2.20784805	2.3659103	0.40575027	0.03584	17
34	1.60164	1.37982014	0.22182	0.02857	1.66562289	1.7171765	0.29449335	0.0204	18
35	1.53969	1.37982014	0.15987	0.02857	1.20043182	1.2093542	0.20740254	0.0106	19
Current Transform Base 10 Log Constant: 0
Box-Cox Power Transformation
Constant k	95% CI Low	95% CI High	Best Lambda	Rec. Transform
0	−0.81	0.88	0	Log

Figures D.51-D.61 are State Ease graphs for arsenic extraction model.

D.2.2 Response 2: Copper Difference ANOVA & Diagnostic Data

The Analysis of Variance and associated statistical data for Response Surface Reduced 2F1 Model for Response 2 Copper Difference is shown below. Row 15 was ignored for this analysis.

TABLE D.26
Backward Elimination Regression with Alpha to Exit = 0.100; Forced Terms: Intercept
Coefficient	t for H0
Removed	Estimate	Coeff = 0	Prob > |t|	R- Squared	MSE
EF	−0.002106926	−0.099402147	0.922460256	0.904978602	0.012083987
AC	−0.003551447	−0.175035889	0.863748201	0.904754662	0.01124729
DE	−0.006018066	−0.30849684	0.762246949	0.904107195	0.010568831
F-O2 Pressure	0.008071341	0.428076144	0.674678496	0.90293571	0.010029325
AB	−0.007931878	−0.432937913	0.670839332	0.901798631	0.009549944
C-Cu2+	−0.009015318	−0.505384405	0.619778219	0.900323222	0.009154902
DF	−0.008937036	−0.512682256	0.61440767	0.898867703	0.008799712
CF	−0.011478949	−0.672812924	0.509167367	0.896458214	0.008558898
BE	0.013827771	0.823065287	0.420176999	0.892951065	0.008427432
BC	0.013377098	0.803529837	0.430670459	0.889659768	0.008291697
CD	−0.025913672	−1.571208047	0.130406568	0.877278116	0.008821174
CE	0.025941668	1.526686736	0.140474597	0.864841734	0.009310298
Hierarchical Terms Added after Backward Elimination Regression
F-O2 Pressure

TABLE D.27
Analysis of Variance Table [Partial sum of squares-Type III]
	Sum of		Mean	F	p-value
Source	Squares	df	Square	Value	Prob > F
Model	1.433346663	10	0.143334666	14.99322002	<0.0001	significant
A-Time	0.134010727	1	0.134010727	14.01790904	0.0011
B-Temperature	0.087173494	1	0.087173494	9.118599181	0.0061
D-Acid	0.065834797	1	0.065834797	6.886509886	0.0152
E-Solids	0.500426584	1	0.500426584	52.34606587	<0.0001
F-O2 Pressure	0.003567935	1	0.003567935	0.373216337	0.5472
AD	0.046619622	1	0.046619622	4.876547128	0.0375
AE	0.036296523	1	0.036296523	3.79672116	0.0637
AF	0.193808582	1	0.193808582	20.27293732	0.0002
BD	0.114632531	1	0.114632531	11.99089377	0.0021
BF	0.216533349	1	0.216533349	22.65001357	<0.0001
Residual	0.219879207	23	0.009559966
Lack of Fit	0.215478137	21	0.010260864	4.662895358	0.1913	not significant
Pure Error	0.00440107	2	0.002200535
Cor Total	1.65322587	33

The “Model F-value” of 14.99 implies the model is significant. There is a a 0.01% chance that a “Model F-value” this large could occur due to noise.

Values of “Prob >F” less than 0.0500 indicate model terms are significant. In this case A, B, D, E, AD, AF, BD, BF are significant model terms. Values greater than 0.1000 indicate the model terms are not significant.

If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve your model.

The “Lack of Fit F-value” of 4.66 implies the Lack of Fit is not significant relative to the pure error. There is a 19.13% chance that a “Lack of Fit F-value” this large could occur due to noise. Non-significant lack of fit is good—we want the model to fit.

TABLE D.28
Trend Data
Std. Dev.	0.097775076	R-Squared	0.8669999
Mean	0.574503525	Adj R-Squared	0.809173769
C.V. %	17.01905592	Pred R-Squared	0.724451032
PRESS	0.455544682	Adeq Precision	16.46633067

The “Pred R-Squared” of 0.7245 is in reasonable agreement with the “Adj R-Squared” of “Adeq Precision” measures the signal to noise ratio. A ratio greater than 4 is desirable. Your ratio of 16.466 indicates an adequate signal. This model can be used to navigate the design space.

TABLE D.29
Confidence Intervals
Coefficient	Standard	95% CI	95% CI
Factor	Estimate	df	Error	Low	High	VIF
Intercept	0.579577132	1	0.016880022	0.544658145	0.614496119
A-Time	0.066229971	1	0.017689394	0.029636672	0.10282327	1.013722346
B-Temperature	0.053410911	1	0.017687478	0.016821574	0.090000248	1.013675389
D-Acid	−0.046420791	1	0.017689394	−0.083014089	−0.009827492	1.013722346
E-Solids	0.127983791	1	0.017689394	0.091390492	0.164577089	1.013722346
F-O2 Pressure	0.010806704	1	0.017689394	−0.025786594	0.047400003	1.013722346
AD	0.039063321	1	0.017689394	0.002470022	0.075656619	1.013722346
AE	0.034468096	1	0.017689394	−0.002125202	0.071061395	1.013722346
AF	0.079647342	1	0.017689394	0.043054043	0.11624064	1.013722346
BD	−0.061254602	1	0.017689394	−0.097847901	−0.024661303	1.013722346
BF	0.084187416	1	0.017689394	0.047594117	0.120780715	1.013722346

Final Equation in Terms of Coded Factors:

$\begin{array}{cc}\mathrm{Sqrt}\left(\mathrm{Cu}\mathrm{Difference}\right)=+0.579577132+0.06622997*A+0.053410911*B-0.046420791*D+0.127983791*E+0.010806704*F+0.039063321*A*D+0.034468096*A*E+0.079647342*A*F-0.061254602*B*D+0.084187416*B*F& \left(D\mathrm{.11}\right)\end{array}$

Final Equation in Terms of Actual Factors:

$\begin{array}{cc}\mathrm{Sqrt}\left(\mathrm{Cu}\mathrm{Difference}\right)=+0.387651454-0.641920818*\mathrm{Time}\text{}0.004077009*\mathrm{Temperature}\text{}0.016988653*\mathrm{Acid}\text{}0.0049159*\mathrm{Solids}-0.013729781*O2\mathrm{Pressure}\text{}0.015625328*\mathrm{Time}*\mathrm{Acid}0.027574477*\mathrm{Time}*\mathrm{Solids}0.006371787*\mathrm{Time}*O2\mathrm{Pressure}-0.000272243*\mathrm{Temperature}*\mathrm{Acid}7.48E\text{-}05*\mathrm{Temperature}*O2\mathrm{Pressure}& \left(D\mathrm{.12}\right)\end{array}$

The Diagnostics Case Statistics Report for this response is shown below. Proceed to Diagnostic Plots (the next icon in progression). Be sure to look at the:

1) Normal probability plot of the studentized residuals to check for normality of residuals.

2) Studentized residuals versus predicted values to check for constant error.

3) Externally Studentized Residuals to look for outliers, i.e., influential values.

4) Box-Cox plot for power transformations.

TABLE D.30
Diagnostics Case Statistics
					Internally	Externally	Influence on
Standard	Actual	Predicted			Studentized	Studentized	Fitted Value	Cook's	Run
Order	Value	Value	Residual	Leverage	Residual	Residual	DFFITS	Distance	Order
1	0.41808	0.5436781	−0.1256	0.35529777	−1.599887	−1.6598026	−1.232177	0.12824	2
2	0.49004	0.3823138	0.10773	0.34293579	1.359259	1.3862245	1.001465699	0.08766	29
3	0.68185	0.6353279	0.04652	0.34217942	0.5866785	0.5781249	0.416960491	0.01628	24
4	0.36607	0.4307367	−0.0647	0.41171211	−0.862333	−0.8573513	−0.71723368	0.04731	13
5	0.19433	0.237622	−0.0433	0.34293579	−0.546183	−0.5376759	−0.3884392	0.01415	20
6	0.45039	0.3697805	0.08061	0.34242803	1.016635	1.017411	0.734191648	0.04893	9
7	0.59506	0.6046343	−0.0096	0.35350278	−0.121827	−0.1191878	−0.08813426	0.00074	5
8	0.67605	0.7800197	−0.104	0.34217942	−1.311126	−1.3330929	−0.9614653	0.08129	32
9	0.25483	0.189163	0.06566	0.34242803	0.8281607	0.8223104	0.593401676	0.03247	21
10	0.49075	0.4775748	0.01318	0.34293579	0.1662461	0.1626896	0.117533694	0.00131	10
11	0.45807	0.3111569	0.14691	0.34217942	1.8525478	1.9642955	1.41670694	0.16229	6
12	0.66041	0.6427955	0.01762	0.37933457	0.2287283	0.2239556	0.175083129	0.00291	33
13	0.44918	0.4952191	−0.046	0.34293579	−0.58089	−0.572336	−0.41347909	0.01601	3
14	0.42655	0.4901081	−0.0636	0.35529777	−0.809586	−0.8033193	−0.59635498	0.03284	30
15	0.21759	0.3418504	−0.1243	0.34271026	−1.567539	−1.6221822	−1.17134482	0.11647	25
16	0.21692	0.2935126	−0.0766	0.34217942	−0.965891	−0.9644226	−0.69556961	0.04412	14
17	0.3968	0.4246534	−0.0279	0.34293579	−0.351479	−0.3446806	−0.2490115	0.00586	22
18	0.70175	0.6946843	0.00707	0.37697512	0.0915625	0.0895662	0.069670298	0.00046	7
19	0.71113	0.7916657	−0.0805	0.35350278	−1.024468	−1.0256236	−0.7584048	0.05217	11
20	1.07123	1.1049234	−0.0337	0.37668034	−0.436537	−0.4287214	−0.33327764	0.01047	34
21	0.72711	0.7307095	−0.0036	0.35529777	−0.045878	−0.0448719	−0.03331129	0.00011	4
22	0.62449	0.7072176	−0.0827	0.35377447	−1.052529	−1.0551173	−0.780678	0.05513	31
23	0.97663	0.8223593	0.15427	0.34217942	1.9453978	2.0815878	1.501301611	0.17897	26
25	0.73238	0.6822505	0.05013	0.34293579	0.6325004	0.6240487	0.450838463	0.01898	1
26	0.81838	0.8150118	0.00336	0.34242803	0.0424313	0.0415003	0.029947724	8.52E−05	28
27	0.41516	0.5288818	−0.1137	0.34271026	−1.43466	−1.4704617	−1.06179051	0.09756	27
28	0.63258	0.6184164	0.01416	0.37668034	0.1834313	0.1795307	0.139562826	0.00185	16
29	0.32919	0.3761944	−0.047	0.34242803	−0.592789	−0.5842392	−0.42160299	0.01664	23
30	0.73907	0.8024786	−0.0634	0.35377447	−0.806753	−0.8004262	−0.59223281	0.03239	8
31	0.47684	0.4981883	−0.0213	0.34217942	−0.269198	−0.2636967	−0.19018574	0.00343	12
32	1.03328	0.9676993	0.06558	0.34271026	0.8272742	0.8214031	0.593118513	0.03244	35
33	0.65077	0.580764	0.07001	0.02987852	0.7269804	0.7193132	0.12623638	0.00148	17
34	0.74405	0.580764	0.16329	0.02987852	1.6955547	1.7727773	0.311114812	0.00805	18
35	0.70614	0.580764	0.12538	0.02987852	1.301892	1.322954	0.232172756	0.00475	19
Current Transform Square Root Constant: 0
Box-Cox Power Transformation
Constant	95% CI	95% CI	Best	Rec.
k	Low	High	Lambda	Transform
0	0.16	0.79	0.48	Square Root

Figures D.62-D.72 are State Ease graphs for copper difference model

D.2.3 Response 3: Iron Extraction ANOVA & Diagnostic Data

The Analysis of Variance and associated statistical data for Response Surface Reduced 2F1 Model for Response 3 Iron Extraction is shown below and Figures D.73-D.83, which are State Ease graphs for iron extraction model.

TABLE D.31
Backward Elimination Regression with Alpha to Exit = 0.100; Forced Terms: Intercept
Coefficient	t for H0
Removed	Estimate	Coeff = 0	Prob > |t|	R-Squared	MSE
CD	−0.003519684	−0.116338704	0.909162125	0.812027313	0.027225518
BD	0.005196502	0.178154999	0.861153432	0.811601163	0.025468091
BC	−0.006632222	−0.235090909	0.81731736	0.810907005	0.023964309
EF	0.011154147	0.407595035	0.688972666	0.808943585	0.022788836
B-Temperature	0.01147767	0.430107322	0.672520313	0.806864528	0.021756999
A-Time	0.011668143	0.447483704	0.659864302	0.804715985	0.020841191
DF	−0.015074657	−0.590692082	0.561688065	0.801129778	0.020162724
AD	−0.015095588	−0.601381986	0.554341585	0.797533605	0.019549835
F-O2 Pressure	0.01624186	0.657111718	0.518246722	0.79337055	0.019044912
CE	0.022402954	0.918313124	0.368413826	0.785450077	0.018915158
AF	0.027934622	1.148980891	0.262372816	0.773135312	0.019167484
AC	0.028972922	1.183817425	0.248078306	0.759888081	0.019475255
CF	0.029649586	1.20185492	0.240681256	0.746014844	0.019808173
AE	0.037695277	1.515094467	0.141812415	0.723590775	0.020758607
BF	0.037836069	1.485531603	0.148986666	0.700998886	0.021653306
C-Cu2+	0.043902786	1.687737726	0.102571805	0.670581303	0.023033487
BE	0.044128549	1.644806399	0.110807959	0.639850082	0.024342855
Hierarchical Terms Added after Backward Elimination Regression
A-Time,
B-Temperature

TABLE D.32
Analysis of Variance Table [Partial sum of squares−Type III]
	Sum of		Mean	F	p-value
Source	Squares	df	Square	Value	Prob > F
Model	1.306013583	6	0.21766893	8.444808578	<0.0001	significant
A-Time	0.004356658	1	0.004356658	0.169023386	0.6841
B-Temperature	0.004215759	1	0.004215759	0.163557018	0.689
D-Acid	0.182248848	1	0.182248848	7.070630755	0.0128
E-Solids	0.944579783	1	0.944579783	36.6464586	<0.0001
AB	0.087409324	1	0.087409324	3.391182234	0.0762
DE	0.083203211	1	0.083203211	3.227999468	0.0832
Residual	0.721713227	28	0.025775472
Lack of Fit	0.695596471	26	0.02675371	2.048777397	0.3807	not significant
Pure Error	0.026116757	2	0.013058378
Cor Total	2.02772681	34

The Model F-value of 8.44 implies the model is significant. There is a 0.01% chance that a “Model F-Value” this large could occur due to noise.

Values of “Prob >F” less than 0.0500 indicate model terms are significant. In this case D, E are significant model terms. Values greater than 0.1000 indicate the model terms are not significant.

If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve your model.

The “Lack of Fit F-value” of 2.05 implies the Lack of Fit is not significant relative to the pure error. There is a 38.07% chance that a “Lack of Fit F-value” this large could occur due to noise. Non-significant lack of fit is good—we want the model to fit.

TABLE D.33
Trend Data
Std. Dev.	0.160547415	R-Squared	0.644077682
Mean	1.076681654	Adj R-Squared	0.567808613
C.V. %	14.91131703	Pred R-Squared	0.441320042
PRESS	1.132850329	Adeq Precision	8.6688612

The “Pred R-Squared” of 0.4413 is in reasonable agreement with the “Adj R-Squared” of 0.5678. “Adeq Precision” measures the signal to noise ratio. A ratio greater than 4 is desirable. Your ratio of 8.669 indicates an adequate signal. This model can be used to navigate the design space.

TABLE D.34
Confidence Intervals
Coefficient	Standard	95%	95% CI
Factor	Estimate	CI df	Error	Low	High	VIF
Intercept	1.076659792	1	0.02713752	1.021071102	1.1322485
A-Time	0.011668143	1	0.028381041	−0.046467785	0.0698041	1
B-Temperature	0.01147767	1	0.028380441	−0.046657028	0.0696124	1
D-Acid	0.075467056	1	0.028381041	0.017331128	0.133603	1
E-Solids	−0.171808376	1	0.028381041	−0.229944304	−0.113672	1
AB	0.05226415	1	0.028381041	−0.005871778	0.1104001	1
DE	0.050991179	1	0.028381041	−0.007144749	0.1091271	1

Final Equation in Terms of Coded Factors:

$\begin{array}{cc}\mathrm{Log}10\left(\mathrm{Fe}\mathrm{Extraction}\right)=+1.08+0.012*A+0.011*B+0.075*D-0.17*E+0.052*A*B+0.051*D*E& \left(D\mathrm{.13}\right)\end{array}$

Final Equation in Terms of Actual Factors:

$\begin{array}{cc}\mathrm{Log}10\left(\mathrm{Fe}\mathrm{Extraction}\right)=+2.22946-1.09152*\mathrm{Time}-6.45843E\text{-}003*\mathrm{Temperature}-2.65153E\text{-}003*\mathrm{Acid}-0.054758*\mathrm{Solids}+9.29140E\text{-}003*\mathrm{Time}*\mathrm{Temperature}+1.0198E\text{-}003*\mathrm{Acid}*\mathrm{Solids}& \left(D\mathrm{.14}\right)\end{array}$

The Diagnostics Case Statistics Report for this response is shown below. Proceed to Diagnostic Plots (the next icon in progression). Be sure to look at the:

1) Normal probability plot of the studentized residuals to check for normality of residuals.

2) Studentized residuals versus predicted values to check for constant error.

3) Externally Studentized Residuals to look for outliers, i.e., influential values.

4) Box-Cox plot for power transformations.

TABLE D.35
Diagnostics Case Statistics
					Internally	Externally	Influence on
Standard	Actual	Predicted			Studentized	Studentized	Fitted Value	Cook's	Run
Order	Value	Value	Residual	Leverage	Residual	Residual	DFFITS	Distance	Order
1	1.239615	1.25311063	−0.0135	0.21619	−0.094949	−0.093253	−0.0489748	0.00036	2
2	1.227217	1.17191861	0.0553	0.21619	0.3890455	0.3830719	0.2011832	0.00596	29
3	1.190011	1.17153767	0.01847	0.21595	0.12995	0.1276468	0.066991	0.00066	24
4	1.190878	1.29940225	−0.1085	0.21595	−0.763403	−0.757572	−0.3975852	0.02293	13
5	1.501347	1.25311063	0.24824	0.21619	1.746448	1.8167827	0.9541451	0.12018	20
6	1.2302	1.17191861	0.05828	0.21619	0.4100354	0.4038611	0.2121014	0.00662	9
7	1.141721	1.17153767	−0.0298	0.21595	−0.209739	−0.206122	−0.1081759	0.00173	5
8	1.164804	1.29940225	−0.1346	0.21595	−0.946813	−0.945002	−0.4959513	0.03527	32
9	1.223741	1.30206238	−0.0783	0.21619	−0.551026	−0.544055	−0.2857289	0.01196	21
10	1.260612	1.22087037	0.03974	0.21619	0.2795997	0.2749456	0.144397	0.00308	10
11	1.333241	1.22048942	0.11275	0.21595	0.7931368	0.7877441	0.4134199	0.02475	6
12	1.244286	1.34835401	−0.1041	0.21595	−0.732049	−0.725838	−0.3809305	0.02109	33
13	1.373618	1.30206238	0.07156	0.21619	0.5034222	0.4966033	0.2608081	0.00999	3
14	1.284372	1.22087037	0.0635	0.21619	0.4467634	0.440285	0.2312306	0.00786	30
15	1.286523	1.22048942	0.06603	0.21595	0.4645041	0.4579017	0.2403137	0.00849	25
16	1.271013	1.34835401	−0.0773	0.21595	−0.544044	−0.537087	−0.2818712	0.01165	14
17	0.579323	0.80751152	−0.2282	0.21619	−1.605405	−1.654458	−0.8688948	0.10155	22
18	0.615056	0.7263195	−0.1113	0.21619	−0.782787	−0.777233	−0.4081905	0.02414	7
19	0.664586	0.72593856	−0.0614	0.21595	−0.431575	−0.425215	−0.2231591	0.00733	11
20	1.01733	0.85380314	0.16353	0.21595	1.150311	1.1572586	0.6073467	0.05206	34
21	0.778545	0.80751152	−0.029	0.21619	−0.203791	−0.200267	−0.105177	0.00164	4
22	0.879758	0.7263195	0.15344	0.21619	1.0795099	1.0828305	0.5686852	0.04592	31
23	0.794137	0.72593856	0.0682	0.21595	0.4797362	0.4730397	0.2482583	0.00906	26
24	0.992263	0.85380314	0.13846	0.21595	0.9739743	0.973049	0.5106707	0.03733	15
25	1.280237	1.06042799	0.21981	0.21619	1.5464491	1.5879086	0.8339441	0.09423	1
26	0.783145	0.97923597	−0.1961	0.21619	−1.379584	−1.403256	−0.7369675	0.07499	28
27	0.983594	0.97885503	0.00474	0.21595	0.0333375	0.0327374	0.0171811	4.37E−05	27
28	0.878948	1.10671961	−0.2278	0.21595	−1.602233	−1.650859	−0.8663954	0.10101	16
29	0.961569	1.06042799	−0.0989	0.21619	−0.695519	−0.688963	−0.3618325	0.01906	23
30	1.008097	0.97923597	0.02886	0.21619	0.2030481	0.1995362	0.1047932	0.00162	8
31	0.895766	0.97885503	−0.0831	0.21595	−0.584476	−0.577477	−0.3030687	0.01344	12
32	1.552976	1.10671961	0.44626	0.21595	* 3.139	** 3.83	* 2.01	0.38773	35
33	1.025921	1.07691485	−0.051	0.02858	−0.322263	−0.317044	−0.0543853	0.00044	17
34	1.00923	1.07691485	−0.0677	0.02858	−0.427745	−0.421416	−0.072289	0.00077	18
35	0.820177	1.07691485	−0.2567	0.02858	−1.622497	−1.67389	−0.2871364	0.01107	19
Current Transform: Base 10 Log Constant: 0
Box-Cox Power Transformation
Constant	95% CI	95% CI	Best	Rec.
k	Low	High	Lambda	Transform
0	−0.62	0.39	−0.12	Log
**Case(s) with |External Stud. Residuals| > 3.54
*Exceeds limits

Figures D.73-D.83 are State Ease graphs for iron extraction models.

D.2.4 Response 4: Acid Consumption ANOVA & Diagnostic Data

The Analysis of Variance and associated statistical data for Response Surface Reduced 2F1 Model for Response 4 Acid Consumption is shown below and in Figures D.84-D.94, which are State Ease plots for acid consumption models.

TABLE D.36
Backward Elimination Regression with Alpha to Exit = 0.100; Forced Terms: Intercept
Coefficient	t for H0
Removed	Estimate	Coeff = 0	Prob > |t|	R-Squared	MSE
DE	−0.138029101	−0.070693961	0.944717286	0.771446227	113.3206104
BD	−0.188863213	−0.100361677	0.92148026	0.771281792	105.8419975
CE	−0.283739077	−0.156014559	0.878101838	0.77091065	99.38788843
AF	−0.467499546	−0.265270802	0.794188232	0.769903107	93.95294125
F-O2 Pressure	0.469619972	0.274073066	0.787330876	0.768886402	89.1254097
BC	−0.777547625	−0.465909128	0.646868836	0.766099284	85.45283919
CD	1.156152343	0.707500587	0.487843753	0.759937144	83.31889841
BE	1.28498068	0.796342378	0.435184461	0.752325217	81.86740854
A-Time	2.236661589	1.39836243	0.176598571	0.72926295	85.42275188
EF	−2.306647554	−1.411787887	0.172000621	0.70473485	89.11132502
Hierarchical Terms Added after Backward Elimination Regression
A-Time,
F-O2 Pressure
Transform: Power
Lambda: 1.82
Constant: 8.67128

TABLE D.37
Analysis of Variance Table [Partial sum of squares-Type III]
	Sum of		Mean	F	p-value
Source	Squares	df	Square	Value	Prob > F
Model	5059.005436	13	389.1542643	4.34135189	0.0014	significant
A-Time	160.0849621	1	160.0849621	1.785886001	0.1957
B-Temperature	438.2434011	1	438.2434011	4.888983604	0.0383
C-Cu2+	306.979975	1	306.979975	3.424626728	0.0784
D-Acid	418.0938965	1	418.0938965	4.66419848	0.0425
E-Solids	719.3726862	1	719.3726862	8.025223562	0.01
F-O2 Pressure	7.057373393	1	7.057373393	0.078731095	0.7818
AB	601.6384995	1	601.6384995	6.711797034	0.0171
AC	405.2154028	1	405.2154028	4.520527761	0.0455
AD	526.9094815	1	526.9094815	5.878130303	0.0244
AE	301.7023474	1	301.7023474	3.365750234	0.0808
BF	569.8209578	1	569.8209578	6.356844879	0.0198
CF	317.6219748	1	317.6219748	3.543347426	0.0737
DF	286.2644781	1	286.2644781	3.19352747	0.0884
Residual	1882.41814	21	89.63895905
Lack of Fit	1868.444761	19	98.33919794	14.07522076	0.0683	not significant
Pure Error	13.97337912	2	6.986689561
Cor Total	6941.423576	34

The Model F-value of 4.34 implies the model is significant. There is a 0.14% chance that a “Model F-Value” this large could occur due to noise.

Values of “Prob >F” less than 0.0500 indicate model terms are significant. In this case B, D, E, AB, AC, AD, BF are significant model terms. Values greater than 0.1000 indicate the model terms are not significant.

If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve your model.

The “Lack of Fit F-value” of 14.08 implies there is a 6.83% chance that a “Lack of Fit F-value” this large could occur due to noise. Lack of fit is bad—we want the model to fit. This relatively low probability (<10%) is troubling.

TABLE D.38
Trend Data
Std. Dev.	9.46778533	R-Squared	0.72881382
Mean	51.292547	Adj R-Squared	0.560936662
C.V. %	18.45840358	Pred R-Squared	0.157267501
PRESS	5849.763238	Adeq Precision	13.53986235

The “Pred R-Squared” of 0.1573 is not as close to the “Adj R-Squared” of 0.5609 as one might normally expect. This may indicate a large block effect or a possible problem with your model and/or data. Things to consider are model reduction, response transformation, outliers, etc. “Adeq Precision” measures the signal to noise ratio. A ratio greater than 4 is desirable. Your ratio of 13.540 indicates an adequate signal. This model can be used to navigate the design space.

TABLE D.39
Confidence Intervals
Coefficient	Standard	95%	95% CI
Factor	Estimate	CI df	Error	Low	High	VIF
Intercept	51.29959579	1	1.600350986	47.97148372	54.627708
A-Time	2.236661589	1	1.673683802	−1.243954418	5.7172776	1
B-Temperature	−3.700611655	1	1.673648382	−7.181154	−0.220069	1
C-Cu2+	3.097276904	1	1.673683802	−0.383339103	6.5778929	1
D-Acid	3.614613986	1	1.673683802	0.133997979	7.09523	1
E-Solids	−4.741349644	1	1.673683802	−8.221965651	−1.260734	1
F-O2 Pressure	0.469619972	1	1.673683802	−3.010996034	3.950236	1
AB	−4.336035414	1	1.673683802	−7.81665142	−0.855419	1
AC	3.558508302	1	1.673683802	0.077892296	7.0391243	1
AD	4.057822236	1	1.673683802	0.577206229	7.5384382	1
AE	−3.070537145	1	1.673683802	−6.551153151	0.4100789	1
BF	−4.219822855	1	1.673683802	−7.700438862	−0.739207	1
CF	3.150505787	1	1.673683802	−0.33011022	6.6311218	1
DF	2.990947164	1	1.673683802	−0.489668842	6.4715632	1

Final Equation in Terms of Coded Factors:

$\begin{array}{cc}{\left(\mathrm{Acid}\mathrm{Consump}+8.67\right)}^{\bigwedge }1.82=+51.30+2.24*A-3.70*B+3.10*C+3.61*D-4.74*E+0.47*F-4.34*A*B+3.56*A*C+4.06*A*D-3.07*A*E-4.22*B*F+3.15*C*F+2.99*D*F& \left(D\mathrm{.15}\right)\end{array}$

Final Equation in Terms of Actual Factors:

$\begin{array}{cc}{\left(\mathrm{Acid}\mathrm{Consump}+8.67\right)}^{\bigwedge }1.82=+2.51160+71.75419*\mathrm{Time}+0.60121*\mathrm{Temperature}-0.71525*\mathrm{Cu}2+-1.15498*\mathrm{Acid}+0.89405*\mathrm{Solids}+0.24423*O2\mathrm{Pressure}-0.77085*\mathrm{Time}*\mathrm{Temperature}+0.94894*\mathrm{Time}*\mathrm{Cu}2++1.62313*\mathrm{Time}*\mathrm{Acid}-2.45643*\mathrm{Time}*\mathrm{Solids}-3.75095E\text{-}003*\mathrm{Temperature}*O2\mathrm{Pressure}+4.20067E\text{-}003*\mathrm{Cu}2+*O2\mathrm{Pressure}+5.98189E\text{-}003*\mathrm{Acid}*O2\mathrm{Pressure}& \left(D\mathrm{.16}\right)\end{array}$

The Diagnostics Case Statistics Report for this response is shown below. Proceed to Diagnostic Plots (the next icon in progression). Be sure to look at the:

1) Normal probability plot of the studentized residuals to check for normality of residuals.

2) Studentized residuals versus predicted values to check for constant error.

3) Externally Studentized Residuals to look for outliers, i.e., influential values.

4) Box-Cox plot for power transformations.

TABLE D.40
Diagnostics Case Statistics
					Internally	Externally	Influence on
Standard	Actual	Predicted			Studentized	Studentized	Fitted Value	Cook's	Run
Order	Value	Value	Residual	Leverage	Residual	Residual	DFFITS	Distance	Order
1	50.33589	52.4548	−2.1189	0.43494	−0.2977226	−0.2911626	−0.2554479	0.00487	2
2	52.1268	53.6046	−1.4778	0.43494	−0.2076386	−0.2028428	−0.1779616	0.00237	29
3	49.20739	42.382	6.82543	0.4347	0.9588322	0.95690504	0.8391222	0.0505	24
4	51.70001	48.8749	2.82508	0.4347	0.3968656	0.38876176	0.34091013	0.00865	13
5	52.48795	54.9293	−2.4414	0.43494	−0.3430316	−0.3357064	−0.2945278	0.00647	20
6	56.07582	63.5191	−7.4433	0.43494	−1.045853	−1.0483144	−0.9197256	0.06014	9
7	50.68302	54.9418	−4.2588	0.4347	−0.5982695	−0.5888914	−0.5164064	0.01966	5
8	54.53317	48.7042	5.82897	0.4347	0.8188498	0.81218706	0.71221716	0.03683	32
9	52.6948	54.6462	−1.9514	0.43494	−0.2741934	−0.2680657	−0.2351841	0.00413	21
10	58.73106	65.8716	−7.1405	0.43494	−1.0033041	−1.0034702	−0.8803821	0.05534	10
11	52.46141	55.297	−2.8356	0.4347	−0.3983363	−0.3902134	−0.3421831	0.00872	6
12	52.86571	50.4184	2.44733	0.4347	0.3437991	0.33646175	0.29504759	0.00649	33
13	53.00348	38.363	14.6405	0.43494	2.0571199	2.24662517	1.97104873	0.23266	3
14	111.6258	94.5439	17.0819	0.43494	2.4001636	2.74963178	* 2.41	0.31673	30
15	43.83968	52.856	−9.0163	0.4347	−1.2666049	−1.2861846	−1.1278716	0.08812	25
16	51.97037	65.2485	−13.278	0.4347	−1.8652989	−1.9929123	−1.7476102	0.19111	14
17	54.17289	46.2091	7.96377	0.43494	1.1189806	1.12610083	0.98797059	0.06884	22
18	53.81337	40.8848	12.9286	0.43494	1.8165791	1.93099961	1.69413855	0.18143	7
19	52.78954	58.8236	−6.0341	0.4347	−0.8476663	−0.8417639	−0.7381535	0.03947	11
20	0.648594	13.4678	−12.819	0.4347	−1.8008405	−1.9111984	−1.6759542	0.17813	34
21	38.83523	41.8897	−3.0544	0.43494	−0.4291765	−0.4206824	−0.3690805	0.01013	4
22	50.59521	57.5934	−6.9982	0.43494	−0.9833035	−0.9824905	−0.8619758	0.05316	31
23	46.38086	44.4189	1.96198	0.4347	0.2756173	0.26946281	0.23629536	0.00417	26
24	46.26122	40.2617	5.9995	0.4347	0.8428058	0.83676774	0.73377227	0.03902	15
25	34.03686	42.2448	−8.208	0.43494	−1.1532949	−1.1629316	−1.0202836	0.07313	1
26	51.96072	59.3076	−7.3468	0.43494	−1.0322957	−1.0339937	−0.9071615	0.05859	28
27	49.33818	44.1358	5.20237	0.4347	0.7308263	0.72246001	0.63353436	0.02934	27
28	52.04113	42.6141	9.427	0.4347	1.3242985	1.34998209	1.18381646	0.09633	16
29	50.72231	56.6832	−5.9608	0.43494	−0.8375517	−0.8313704	−0.7293925	0.03857	23
30	56.52374	57.2583	−0.7346	0.43494	−0.1032181	−0.1007561	−0.0883971	0.00059	8
31	51.70473	44.7319	6.97287	0.4347	0.9795445	0.9785544	0.8581068	0.0527	12
32	52.7946	54.4072	−1.6126	0.4347	−0.226536	−0.2213472	−0.1941021	0.00282	35
33	55.81027	51.2174	4.59291	0.02858	0.4921948	0.48312767	0.08287496	0.00051	17
34	51.16378	51.2174	−0.0536	0.02858	−0.0057422	−0.0056038	−0.0009613	6.93E−08	18
35	51.30353	51.2174	0.08617	0.02858	0.0092343	0.00901178	0.00154587	1.79E−07	19
Current Transform: Power Lambda: 1.82 Constant: 8.67128
Box−Cox Power Transformation
Constant	95% CI	95% CI	Best	Rec.
k	Low	High	Lambda	Transform
8.67128	1.3	2.45	1.82	Power
*Exceeds limits

Figures D.84-D.94 are State Ease plots for acid consumption models.

D.2.5 Model Graphs

The model graphs in Figures D.95-D.101 show the preceding statistical data by varying the effects and their corresponding responses.

Claims

1. A treated ore solid comprising: a percentage of at least one metal; anda percentage of an element;a percentage of enargite; anda percentage of covellite;wherein the percentage of enargite in the treated ore solid is less than the percentage of enargite in the treated ore solid is reduced compared to the ore solid prior to treatment; andwherein the percent is measure by chemical (for example acid titration), visual (for example mineral liberation analyzer), and/or spectral analysis (for example x-ray diffraction).

2. The treated ore solid of claim 1, wherein the percentage of covellite in the treated ore solid is increased compared to the ore solid prior to treatment.

3. The treated ore solid of claim 1, wherein the element is arsenic.

4. The treated ore solid of claim 3, wherein the percentage of arsenic in the treated ore solid is reduced compared to the ore solid prior to treatment.

5. The treated ore solid of claim 4, wherein the percentage of arsenic in the treated ore solid is reduced between about 30% and 80% compared to the ore solid prior to treatment.

6. The treated ore solid of claim 5, wherein the percentage of arsenic in the treated ore solid is reduced about 47%.

7. The treated ore solid of claim 1, wherein the percentage of enargite in the treated ore solid is reduced between about 10% and 30% compared to the ore solid prior to treatment.

8. The treated ore of claim 1, wherein the metal is selected from gold, silver, iron, and copper.

9. The treated ore solid of claim 8, wherein the metal is copper.

10. The treated ore solid of claim 9, wherein the percentage of copper in the treated ore solid is reduced between about 10% and 30% compared to the ore solid prior to treatment.

11. A method of lowering an amount of an element or compound in an ore comprising: mixing a solution comprising the ore and a liquid in a pressurized container, wherein the solution is at a temperature;allowing one or more element or compound to leave the ore and enter the liquid; and

12. The method of claim 11, wherein the temperature of the solution is between about 50 and 200 degrees Celsius.

13. The method of claim 12, wherein the temperature of the solution is about 160 degrees Celsius.

14. The method of claim 1, wherein the container is pressurized with oxygen.

15. The method of claim 11, wherein the pressure in the container is between about 50 and 150 psi.

16. The method of claim 15, wherein the pressure in the container is about 100 psi.

17. The method of claim 11, wherein the liquid comprises an acid.

18. The method of claim 17, wherein the acid is at a concentration of between about 1 and 50 g/L.

19. The method of claim 18, wherein the acid is at a concentration of about 30 g/L.

20. The method of claim 11, wherein the solution comprises solids at a concentration of between about 1 and 20 g/L.

21. The method of claim 20, wherein the solution comprises solids at a concentration of about 5 g/L.

22. The method of claim 11, wherein the element or compound is Arsenic.

23. The method of claim 11, wherein the concentration of arsenic is lowered by between about 15% and 90%.

24. The method of claim 11, wherein the concentration of arsenic is lowered by about 55%.

25. A method of lowering an amount of an element in an ore comprising: adding the ore to an airtight container;adding an acid-containing liquid to the container, wherein the ore and liquid create a solution;pressurizing the container to greater than 50 psi;maintaining the solution at a temperature greater than 100 degrees Celsius;agitating the solution;allowing the Arsenic to leave the ore and enter the liquid; and therebylowering the amount of at least one element or compound in the ore.

26. A system for treating an ore comprising; an airtight pressure oxidation container comprising; at least one opening in fluid communication with an interior of the container for adding or extracting a gas or liquid;at least one opening in fluid communication with the interior for adding or removing the ore;an agitator or mixer for mixing a solution placed within the container;a temperature control system for altering the temperature of the solution;a separator or thickener system for separating the solution into a solid part and a liquid part; anda liquid treatment system for filtering and treating the liquid.

27. The system of claim 26, further comprising a delivery system for adding a solution comprising ore and liquid to the container.