Monitoring a state of a shape memory material member

Information

  • Patent Grant
  • 12234811
  • Patent Number
    12,234,811
  • Date Filed
    Monday, August 21, 2023
    a year ago
  • Date Issued
    Tuesday, February 25, 2025
    16 hours ago
Abstract
A state of a shape memory material member in an actuator can be monitored and controlled to protect the shape memory material member. When activated, the actuator can be configured to morph into an activated configuration in which a dimension (e.g., the height) of the actuator increases. A sensor configured to acquire sensor data. A portion of the shape memory material member can operatively engaging the sensor. One or more processors can be operatively connected to monitor a state of the shape memory material member based on the sensor data.
Description
FIELD

The subject matter described herein relates in general to actuators and, more particularly, to shape memory material-based actuators.


BACKGROUND

Some motor vehicles have actuators in one or more portions of a vehicle seat. These actuators can provide a haptic effect to a seat occupant. Such an effect can provide support and/or comfort to a seat occupant.


SUMMARY

In one respect, the present disclosure is directed to a system. The system can include an actuator. When activated, the actuator can be configured to morph into an activated configuration in which a dimension of the actuator increases. The actuator can include a shape memory material member. The system can include a sensor configured to acquire sensor data. A portion of the shape memory material member can operatively engage the sensor. The system can include one or more processors operatively connected to monitor a state of the shape memory material member based on the sensor data.


In another respect, the present disclosure is directed to a method of monitoring a state of a shape memory material member used in an actuator. A portion of the shape memory material member can operatively engage a sensor. The method can include causing the actuator to morph into an activated configuration. The method can include monitoring a state of the shape memory material member using sensor data acquired by the sensor. The method can include controlling an activated state of the actuator based on the acquired sensor data.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 shows an example of a system for monitoring a state of a shape memory material member.



FIG. 2 is a close-up of a portion of the system of FIG. 1.



FIG. 3 is an example of a system for monitoring a state of a shape memory material member.



FIG. 4 is an example of a method of monitoring a state of a shape memory material member.



FIG. 5A-5C is a first example of an actuator.



FIGS. 6A-6B is a second example of an actuator.



FIGS. 7A-7B is a third example of an actuator.



FIG. 8 is a fourth example of an actuator.





DETAILED DESCRIPTION

Some actuators used in vehicles used shape memory alloys for actuation. Shape memory alloys can be prone to overstress and/or overheating, which can lead to a reduced life and/or effectiveness of the actuators. Accordingly, arrangements described herein are directed to monitoring the state of a shape memory material member. Such monitoring can be based on sensor data from a sensor that is operatively engaged by the shape memory material member. The state of the shape memory material member can be controlled based on the sensor data.


Detailed embodiments are disclosed herein; however, it is to be understood that the disclosed embodiments are intended only as examples. Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting, but merely as a basis for the claims and as a representative basis for teaching one skilled in the art to variously employ the aspects herein in virtually any appropriately detailed structure. Further, the terms and phrases used herein are not intended to be limiting but rather to provide an understandable description of possible implementations. Various embodiments are shown in FIGS. 1-8, but the embodiments are not limited to the illustrated structure or application.



FIG. 1 shows an example of a system 100 for monitoring a state of a shape memory material member. The system 100 can include an actuator 110. The actuator 110 is represented generally as there are various suitable actuators that can work with arrangements herein. When activated, the actuator is configured to morph into an activated configuration in which a dimension (e.g., a height) of the actuator increases.


The actuator 110 can be a shape memory material based actuator. Thus, the actuator 110 can include a shape memory material member 120. When an activation input is provided to the memory material member 120, the memory material member 120 can contract, thereby causing the actuator to morph into an activated configuration in which a dimension height of the actuator increases. In some arrangements, the contracting member can be a shape memory material member, which can include shape memory alloys and shape memory polymer. As an example, the contracting member can be a shape memory alloy wire. Various non-limiting examples of suitable actuators are shown in FIGS. 6-9, and they will be described in greater detail herein.


The phrase “shape memory material” includes materials that changes shape when an activation input is provided to the shape memory material and, when the activation input is discontinued, the material substantially returns to its original shape. Examples of shape memory materials include shape memory alloys (SMA) and shape memory polymers (SMP).


In one or more arrangements, the shape memory material members can be shape memory material wires. As an example, the shape memory material members can be shape memory alloy wires. Thus, when an activation input (i.e., heat) is provided to the shape memory alloy wire(s), the wire(s) can contract. Shape memory alloy wire(s) can be heated in any suitable manner, now known or later developed. For instance, shape memory alloy wire(s) can be heated by the Joule effect by passing electrical current through the wires. In some instances, arrangements can provide for cooling of the shape memory alloy wire(s), if desired, to facilitate the return of the wire(s) to a non-activated configuration. Of course, it will be appreciated that the activation input can be provided to the shape memory alloy wire(s) in other ways. For example, heated air can be blown on the shape memory alloy wire(s).


The wire(s) can have any suitable characteristics. For instance, the wire(s) can be high temperature wires with austenite finish temperatures from about 80 degrees Celsius to about 110 degrees Celsius. The wire(s) can have any suitable diameter. For instance, the wire(s) can be from about 0.2 millimeters (mm) to about 0.7 mm, from about 0.3 mm to about 0.5 mm, or from about 0.375 millimeters to about 0.5 millimeters in diameter. In some arrangements, the wire(s) can have a stiffness of up to about 70 gigapascals. The pulling force of SMA wire(s) can be from about 150 MPA to about 400 MPa. The wire(s) can be configured to provide an initial moment of from about 300 to about 600 N·mm, or greater than about 500 N·mm, where the unit of newton millimeter (N·mm) is a unit of torque (also called moment) in the SI system. One newton meter is equal to the torque resulting from a force of one newton applied perpendicularly to the end of a moment arm that is one meter long. In various aspects, the wire(s) can be configured to transform in phase, causing the shape memory material members to be moved from non-activated position to an activated position in about 3 seconds or less, about 2 seconds or less, about 1 second or less, or about 0.5 second or less.


The wire(s) can be made of any suitable shape memory material, now known or later developed. Different materials can be used to achieve various balances, characteristics, properties, and/or qualities. As an example, an SMA wire can include nickel-titanium (Ni—Ti, or nitinol). One example of a nickel-titanium shape memory alloy is FLEXINOL, which is available from Dynaolloy, Inc., Irvine, California. As a further example, the SMA wires can be made of Cu—Al—Ni, Fe—Mn—Si, or Cu—Zn—Al.


The SMA wire can be configured to increase or decrease in length upon changing phase, for example, by being heated to a phase transition temperature TSMA. Utilization of the intrinsic property of SMA wires can be accomplished by using heat, for example, via the passing of an electric current through the SMA wire in order provide heat generated by electrical resistance, in order to change a phase or crystal structure transformation (i.e., twinned martensite, detwinned martensite, and austenite) resulting in a lengthening or shortening the SMA wire. In some implementations, during the phase change, the SMA wire can experience a decrease in length of from about 2 to about 8 percent, or from about 3 percent to about 6 percent, and in certain aspects, about 3.5 percent, when heated from a temperature less than the TSMA to a temperature greater than the TSMA.


The SMA wire can have a critical temperature. Once the critical temperature is reached, the SMA wire cannot produce any more force. Thus, if the SMA wire is heated above the critical temperature, it cannot produce any more force. This inherent property of the SMA wire can be leveraged according to arrangements described herein.


Other active materials may be used in connection with the arrangements described herein. For example, other shape memory materials may be employed. Shape memory materials, a class of active materials, also sometimes referred to as smart materials, include materials or compositions that have the ability to remember their original shape, which can subsequently be recalled by applying an external stimulus, such as an activation signal.


While the shape memory material members are described, in some implementations, as being wires, it will be understood that the shape memory material members are not limited to being wires. Indeed, it is envisioned that suitable shape memory materials may be employed in a variety of other forms, such as sheets, plates, panels, strips, cables, tubes, or combinations thereof. In some arrangements, the shape memory material members may include an insulating coating.


In some arrangements, the actuator 110 can include a single shape memory material member 120. In some instances, one or more portions of the shape memory material member 120 can extend external to overall envelope of the actuator 110. For instance, the shape memory material member 120 can include a first external portion 121 and a second external portion 122. Further, a portion of the shape memory material member 120 can extend within the actuator 110. Thus, the shape memory material member 120 can include an internal portion 123.


One example of the routing of the shape memory material member 120 will now be described with respect to FIG. 1. Beginning of the left side of FIG. 1, there can be the first external portion 121 of the shape memory material member 120. The shape memory material member 120 can then be routed with respect to the actuator 110. For instance, in some arrangements, the shape memory material member 120 can extend substantially linearly within the actuator 110. In other arrangements, the shape memory material member 120 can extend in a non-linear manner, such as in a serpentine or a zig-zag arrangement. The shape memory material member 120 can exit the actuator 110. This portion is the second external portion 122. In the second external portion, the of the shape memory material member 120 can operatively engage a sensor 150, as will be described in more detail in FIG. 2.


The shape memory material member 120 can be activated and/or deactivated using any suitable form of energy and/or from any suitable source. For example, in some arrangements, the of the shape memory material member 120 can be operatively connected to a power source (e.g., the power source(s) 340 in FIG. 3). In one or more arrangements, the first external portion 121 can be operatively connected to receive electrical energy (e.g., power in). For instance, the shape memory material member 120 can be operatively connected to a power source at an electrical connection 140. In one or more arrangements, the second external portion 122 can be operatively connected for electrical energy to exit the system 100 (e.g., power out). For instance, the shape memory material member 120 can be operatively connected to a power source at electrical connection 141.


However, it will be appreciated that arrangements described herein are not limited to activating and/or deactivating the shape memory material member 120 based on electrical energy. Indeed, as an example, the shape memory material member 120 can be activated and/or by supplying hot air, such as from a heater or some other heat source, to the shape memory material member 120. The heater can be operatively positioned with respect to the shape memory material member 120.


The shape memory material member can have a plurality of mechanically isolated zones. Each of the mechanically isolated zones does not affect the other mechanically isolated zones. The shape memory material member can be electrically connected throughout its routing. However, if the shape memory material member contracts or expands, then such contraction or expansion occurs through all of the mechanically isolated zones.


The mechanically isolated zones can be defined by a plurality of isolation points. In the example shown in FIG. 1, there can be four isolation points, including a first isolation point 130, a second isolation point 131, a third isolation point 132, and a fourth isolation point 133. The isolation points 130, 131, 132, 133 can be defined in any suitable manner. For instance, the isolation points 130, 131, 132, 133 can be locations where the shape memory material member 120 is crimped.


The isolation points 130, 131, 132, 133 can create a plurality of mechanically isolated zones, including a first mechanically isolated zone 160, a second mechanically isolated zone 161, a third mechanically isolated zone 162, a fourth mechanically isolated zone 163, and a fifth mechanically isolated zone 164. Each of these mechanically isolated zones will be described in turn below.


The first mechanically isolated zone 160 can be defined by the first isolation point 130. The first mechanically isolated zone can include the first external portion 121 of the shape memory material member 120. The first isolation point 130 can be located at or near where the shape memory material member 120 enters the actuator.


The second mechanically isolated zone 161 can be defined between the first isolation point 130 and the second isolation point 131. The second mechanically isolated 161 zone can be largely, if not entirely, defined by the portion of the shape memory material member 120 routed within the actuator 110.


The third mechanically isolated zone 162 can be defined between the second isolation point 131 and the third isolation point 132. The third mechanically isolated zone 162 can be a free floating zone where the shape memory material member 120 does not engage another structure.


The fourth mechanically isolated zone 163 can be defined between the third isolation point 132 and the fourth isolation point 133. The fourth mechanically isolated zone 163 can be monitored by a sensors. The fourth mechanically isolated zone 163 can be where the shape memory material member 120 operatively engages the sensor 150. Additional details of this area will be described in greater detail with FIG. 2.


The fifth mechanically isolated zone 164 can be define by the fourth isolation point 133 and beyond. The fifth mechanically isolated zone 164 can include the second external portion 122 of the shape memory material member 120. The fourth isolation point 133 can be located at or near where the shape memory material member 120 exits the actuator 110.


Referring to FIG. 2, a close-up of a portion of the system 100 of FIG. 1 is shown. In particular, an example of the operative engagement between the sensor 150 and the shape memory material member 120 is shown. “Operative engagement” refers to an arrangement in which the activation and/or deactivation of the shape memory material member affects the sensor 150.


As noted above, the sensor 150 can be a force sensitive resistive sensor 155. The force sensitive resistive sensor 155 can be a relatively thin and/or substantially flat structure. In one or more arrangements, the shape memory material member can be wrapped around the sensor 150. Thus, when the shape memory material member 120 contracts in response to an activation input (e.g., electrical energy), it can exert a force on the sensor 150. The force sensitive resistive sensor 155 can be a resistor that changes its resistance when a force, pressure, or mechanical stress is applied. The resistance depends on how much force, pressure, or mechanical stress is applied. The resistance is proportional to the force, pressure, or mechanical stress is applied being applied to it.


The shape memory material member 120 can be wrapped around the sensor 150 one or more times. Thus, the shape memory material members 120 can be coiled about the sensor 150 to form one or more coils 125.


In some arrangements, one or more structures can be used in connection with the sensor 150 to provide protection thereto. As an example, a first protective member 170 can be operatively connected to one side of the sensor 150. Alternatively or additionally, a second protective member 175 can be operatively connected to an opposite side of the sensor 150. The first protective member 170 and the second protective member 175 can be sized, shaped, and configured to protect the sensor 150 while not interfering with its operation.


Referring to FIG. 3, an example of a system 300 for monitoring a state of a shape memory material member is shown. The system 300 can include various elements. Some of the possible elements of the system 300 are shown in FIG. 3 and will now be described. It will be understood that it is not necessary for the system 300 to have all of the elements shown in FIG. 3 or described herein. The system 300 can have any combination of the various elements shown in FIG. 3. Further, the system 300 can have additional elements to those shown in FIG. 3. In some arrangements, the system 300 may not include one or more of the elements shown in FIG. 3. Further, the elements shown may be physically separated by large distances. Indeed, one or more of the elements can be located remotely from the other elements, such an on a remote server or cloud-based server.


In addition to the actuator 110, the system 300 can include one or more processors 310, one or more data stores 320, one or more sensors 330, one or more power sources 340, one or more input interfaces 350, one or more output interfaces 360, and/or one or more control modules 370. Each of these elements will be described in turn below.


As noted above, the system 300 can include one or more processors 310. “Processor” means any component or group of components that are configured to execute any of the processes described herein or any form of instructions to carry out such processes or cause such processes to be performed. The processor(s) 310 may be implemented with one or more general-purpose and/or one or more special-purpose processors. Examples of suitable processors include microprocessors, microcontrollers, DSP processors, and other circuitry that can execute software. Further examples of suitable processors include, but are not limited to, a central processing unit (CPU), an array processor, a vector processor, a digital signal processor (DSP), a field-programmable gate array (FPGA), a programmable logic array (PLA), an application specific integrated circuit (ASIC), programmable logic circuitry, and a controller. The processor(s) 310 can include at least one hardware circuit (e.g., an integrated circuit) configured to carry out instructions contained in program code. In arrangements in which there is a plurality of processors 310, such processors can work independently from each other or one or more processors can work in combination with each other.


The system 300 can include one or more data stores 320 for storing one or more types of data. The data store(s) 320 can include volatile and/or non-volatile memory. Examples of suitable data stores 320 include RAM (Random Access Memory), flash memory, ROM (Read Only Memory), PROM (Programmable Read-Only Memory), EPROM (Erasable Programmable Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), registers, magnetic disks, optical disks, hard drives, or any other suitable storage medium, or any combination thereof. The data store(s) 320 can be a component of the processor(s) 310, or the data store(s) 320 can be operatively connected to the processor(s) 310 for use thereby. The term “operatively connected,” as used throughout this description, can include direct or indirect connections, including connections without direct physical contact.


The system 300 can include one or more sensors 330. “Sensor” means any device, component and/or system that can detect, determine, assess, monitor, measure, quantify, acquire, and/or sense something. The one or more sensors can detect, determine, assess, monitor, measure, quantify, acquire, and/or sense in real-time. As used herein, the term “real-time” means a level of processing responsiveness that a user or system senses as sufficiently immediate for a particular process or determination to be made, or that enables the processor to keep up with some external process.


In arrangements in which the system 300 includes a plurality of sensors 330, the sensors can work independently from each other. Alternatively, two or more of the sensors can work in combination with each other. In such case, the two or more sensors can form a sensor network. The sensor(s) 330 can be operatively connected to the processor(s) 310, the data store(s) 320, and/or other elements of the system 300 (including any of the elements shown in FIG. 1).


The sensor(s) 330 can include the sensor 150 (e.g., the force sensitive resistive sensor 155) described in connection with FIG. 1 above. In addition, the sensor(s) 330 can include any suitable type of sensor, now known or later developed, that can acquire information or data about the actuator 110, the shape memory material member 120, or any other portion or component of the system 100 of FIG. 1 or the system of FIG. 2.


As noted above, the system 300 can include one or more power sources 340. The power source(s) 340 can be any power source capable of and/or configured to energize the actuator 110, as will be described later. For example, the power source(s) 340 can include one or more batteries, one or more fuel cells, one or more generators, one or more alternators, one or more solar cells, and combinations thereof. The power source(s) 340 can be any suitable source of electrical energy.


The system 300 can include one or more input interfaces 350. An “input interface” includes any device, component, system, element or arrangement or groups thereof that enable information/data to be entered into a machine. The input interface(s) 350 can receive an input from a vehicle occupant (e.g., a driver or a passenger). Any suitable input interface 350 can be used, including, for example, a keypad, gesture recognition interface, voice recognition interface, display, touch screen, multi-touch screen, button, joystick, mouse, trackball, microphone and/or combinations thereof.


The system 300 can include one or more output interfaces 360. An “output interface” includes any device, component, system, element or arrangement or groups thereof that enable information/data to be presented to a vehicle occupant (e.g., a person, a vehicle occupant, etc.). The output interface(s) 360 can present information/data to a vehicle occupant. The output interface(s) 360 can include a display. Alternatively or in addition, the output interface(s) 360 may include an earphone and/or speaker. Some components of the system 300 may serve as both a component of the input interface(s) 350 and a component of the output interface(s) 360.


The system 300 can include one or more modules, at least some of which will be described herein. The modules can be implemented as computer readable program code that, when executed by a processor, implements one or more of the various processes described herein. One or more of the modules can be a component of the processor(s) 310, or one or more of the modules can be executed on and/or distributed among other processing systems to which the processor(s) 310 is operatively connected. The modules can include instructions (e.g., program logic) executable by one or more processor(s) 310. Alternatively or in addition, one or more data stores 320 may contain such instructions. In some arrangements, the module(s) can be located remote from the other elements of the system 300.


In one or more arrangements, the modules described herein can include artificial or computational intelligence elements, e.g., neural network, fuzzy logic or other machine learning algorithms. Further, in one or more arrangements, the modules can be distributed among a plurality of modules. In one or more arrangements, two or more of the modules described herein can be combined into a single module.


The system 300 can include one or more control modules 370. The control module(s) 370 can include profiles and logic for controlling the actuator 110. The control module(s) 370 can use profiles, parameters, or settings loaded into the control module(s) 370 and/or stored in the data store(s) 320, such as the actuation profiles. In some arrangements, the control module(s) 370 can be located remotely from the other elements of the system 300, such as on a remote server, a cloud-based server, or an edge server.


The control module(s) 370 can be configured to cause one or more of the actuators 110 to be activated or deactivated. As used herein, “cause” or “causing” means to make, force, compel, direct, command, instruct, and/or enable an event or action to occur or at least be in a state where such event or action may occur, either in a direct or indirect manner. For instance, the control module(s) 370 can cause the actuator 110 to be selectively activated or deactivated in any suitable manner. For instance, when the actuator 110 includes a shape memory material member 120, the shape memory material member 120 can be heated by the Joule effect by passing electrical current through the shape memory material member. To that end, the control module(s) 370 can be configured to selectively permit, restrict, adjust, alter, and/or prevent the flow of electrical energy from the power source(s) 340 to the shape memory material member 120 of the actuator 110. The control module(s) 370 can be configured to send control signals or commands over a communication network 390 to one or more elements of the system 300.


The control module(s) 370 can be configured to cause the actuator 110 to be activated or deactivated based on various events, conditions, inputs, or other factors. For instance, the control module(s) 370 can be configured to cause the actuator 110 to be activated or deactivated based on a user input. A user can provide an input on the input interface(s) 350.


In some arrangements, the control module(s) 370 can be configured to cause the actuator 110 to be activated or deactivated. In some instances, the control module(s) 370 can be configured to adjust the degree of activation of the actuator 110. For instance, the control module(s) 370 can be configured to cause the actuator 110 to be in an activated configuration that corresponds to its full activated position (e.g., extended to its maximum height). The control module(s) 370 can be configured to activate the actuator 110 to one or more activated configurations between the non-activated configuration and the full activated configuration, such as an extended position but less than its maximum height. The control module(s) 370 can be configured to maintain the activated configuration of the actuator 110. The control module(s) 370 can be configured to adjust the activated configuration of the actuator 110.


The control module(s) 370 can be configured to receive sensor data from the sensor 150. The control module(s) 370 can be configured to analyze the sensor data. For instance, when the sensor is a force sensitive resistive sensor 155, the control module(s) 370 can be configured to detect changes in the resistance of or measured by the force sensitive resistive sensor 155.


As noted above, the resistance of the force sensitive resistive sensor 155 will stop changing once the critical temperature is reached, even if the shape memory material member 120 is heated beyond the critical temperature. Thus, once the resistance of the force sensitive resistive sensor 155 stops changing, then the control module(s) 370 can recognize that the shape memory material member has reached its critical temperature and that the actuator 110 is at its maximum activated configuration.


The actual value of the resistance of the force sensitive resistive sensor 155 does not have to be known. Rather, the control module(s) 370 only needs to monitor the changes in electrical resistance. When the control module(s) 370 detect that the resistance is no longer changing, the control module(s) 370 can be configured to take one or more actions. For instance, the control module(s) 370 can discontinue the supply of electrical energy to the shape memory material member 120. Alternatively, the control module(s) 370 can maintain the current state of the actuator 110. Thus, additional power is not supplied to the shape memory material member 120. In this way, extra power is not supplied to the to the shape memory material member 120 and, therefore, is not wasted.


It will be appreciated that arrangements described herein are not limited to force sensitive resistive sensor or to monitoring changes in resistance. Indeed, arrangements described herein can be configured to monitor the state of the shape memory material member 120 based on any sensor data. Such monitoring can be based on any parameter, characteristic, or metric. The control module(s) 370 can be configured to determine when at least one metric is fulfilled based on feedback from one or more of the sensor(s) 150.


The various elements of the system 300 can be communicatively linked to one another or one or more other elements through one or more communication networks 390. As used herein, the term “communicatively linked” can include direct or indirect connections through a communication channel, bus, pathway or another component or system. A “communication network” means one or more components designed to transmit and/or receive information from one source to another. The data store(s) 320 and/or one or more other elements of the system 300 can include and/or execute suitable communication software, which enables the various elements to communicate with each other through the communication network and perform the functions disclosed herein.


The one or more communication networks 390 can be implemented as, or include, without limitation, a wide area network (WAN), a local area network (LAN), the Public Switched Telephone Network (PSTN), a wireless network, a mobile network, a Virtual Private Network (VPN), the Internet, a hardwired communication bus, and/or one or more intranets. The communication network 390 further can be implemented as or include one or more wireless networks, whether short range (e.g., a local wireless network built using a Bluetooth or one of the IEEE 802 wireless communication protocols, e.g., 802.11a/b/g/i, 802.15, 802.16, 802.20, Wi-Fi Protected Access (WPA), or WPA2) or long range (e.g., a mobile, cellular, and/or satellite-based wireless network; GSM, TDMA, CDMA, WCDMA networks or the like). The communication network 390 can include wired communication links and/or wireless communication links. The communication network 390 can include any combination of the above networks and/or other types of networks.


Now that the various potential systems, devices, elements and/or components of the system 300 have been described, various methods will now be described. Various possible steps of such methods will now be described. The methods described may be applicable to the arrangements described above, but it is understood that the methods can be carried out with other suitable systems and arrangements. Moreover, the methods may include other steps that are not shown here, and in fact, the methods are not limited to including every step shown. The blocks that are illustrated here as part of the methods are not limited to the particular chronological order. Indeed, some of the blocks may be performed in a different order than what is shown and/or at least some of the blocks shown can occur simultaneously.


Turning to FIG. 4, an example of a method 400 of monitoring a state of a shape memory material member. is shown. At block 410, the actuator 110 can be caused to morph into an activated configuration. Such causing can be performed by the processor(s) 310 and/or the control module(s) 370. For instance, the processor(s) 310 and/or the control module(s) 370 can cause electrical energy from the power source(s) 340 to be supplied to the plurality of actuators 110. More particularly, the processor(s) 310 and/or the control module(s) 370 can cause electrical energy from the power source(s) 340 to be supplied to the shape memory material member 120 of the actuator 110. As a result, the shape memory material member 120 can contract, which morphs the actuator 110 into the activated configuration where a height of the actuator 110 can increase. The causing can be performed automatically, in response to a user input (e.g., provided on the input interface(s) 350), or in any other suitable way. The method 400 can continue to block 420.


At block 420, a state of the shape memory material member 120 can be monitored. The monitoring can be performed by the control module(s) 370 and/or the processor(s) 310 based on sensor data acquired by the sensor 150 (e.g., the force sensitive resistive sensor 155). In one or more arrangements, the control module(s) 370 and/or the processor(s) 310 can monitor for changes in the resistance of and/or measured by the sensor 150. In one particular arrangement, the control module(s) 370 and/or the processor(s) 310 can monitor when the resistance of and/or measured by the sensor 150 stops changing. The method 400 can continue to block 430.


At block 430, the activated configuration of the actuator 110 can be controlled based on the monitored state of the shape memory material member 120. The controlling can be performed by the control module(s) 370 and/or the processor(s) 310. As an example, when the resistance of and/or measured by the sensor 150 stops changing, the control module(s) 370 and/or the processor(s) 310 can cause the supply of electrical energy to the shape memory material member 120 to be discontinued. As another example, when the resistance of and/or measured by the sensor 150 stops changing, the control module(s) 370 can maintain the current state of the actuator 110. Thus, the control module(s) 370 and/or the processor(s) 310 can cause the supply of electrical energy to the shape memory material member 120 to be maintained at the current level.


As noted above, the resistance of the force sensitive resistive sensor 155 will stop changing once the critical temperature is reached, even if the shape memory material member 120 is heated beyond the critical temperature. Thus, once the resistance of the force sensitive resistive sensor 155 stops changing, then the control module(s) 370 can recognize that the shape memory material member has reached its critical temperature and that the actuator 110 is at its maximum activated configuration.


The actual value of the resistance of the force sensitive resistive sensor 155 does not have to be known. Rather, the control module(s) 370 only needs to monitor the changes in electrical resistance. When the control module(s) 370 detects that the resistance is no longer changing, the control module(s) 370 can be configured to take one or more actions. For instance, the control module(s) 370 can discontinue the supply of electrical energy to the shape memory material member 120. Alternatively, the control module(s) 370 can maintain the current state of the actuator 110. Thus, additional power is not supplied to the shape memory material member 120. In this way, extra power is not supplied to the to the shape memory material member 120 and, therefore, is not wasted.


The method 400 can end. Alternatively, the method 400 can return to block 410 or to some other block. The method 400 can be repeated at any suitable point, such as at a suitable time or upon the occurrence of any suitable event or condition.


As noted above, arrangements described herein can be used in connection there can be a plurality of actuators. The actuators can be substantially identical to each other. Alternatively, one or more of the actuators can be different from the other actuators in one or more respects. FIGS. 5-8 show some non-limiting examples of suitable actuators.



FIGS. 5A-5C show one example of an actuator 500 suitable for use in connection with arrangements described herein. The basic details of the actuator 500 will now be described. Additional details of the actuator 500 are described in U.S. Pat. No. 10,960,793, which is incorporated herein by reference in its entirety.


The actuator 500 is depicted here with an outer skin 510, hinge assemblies 520, and an input-responsive element 530. The actuator 600 can have a first dimension 540 and a second dimension 550.


The input-responsive element 530 can include one or more elements capable of transitioning from a first configuration to a second configuration. The transition of the input-responsive element 530 from the first configuration to the second configuration displaces the hinge assemblies 520 with respect to the outer skin 510 and causes a change in confirmation of the outer skin 510. In some implementations, the input-responsive element 530 can include a SMM wire 532. The SMM wire 532 can be a shape memory alloy.



FIG. 5A shows an example of the actuator 500 in a non-activated configuration. When heated, the SMM wire 532 can contract, causing the hinge assemblies 520 to move toward one another. As a result, the actuator 500 can morph from a non-activated configuration to an activated configuration as shown in FIG. 5C. In the activated configuration, the second dimension 550 of the actuator can increase, and the first dimension 540 of the actuator 500 can decrease.



FIGS. 6A-6B show another example of an actuator 600 suitable for use in connection with arrangements described herein. The basic details of the actuator 600 will now be described. Additional details of the actuator 600 are described in U.S. patent application Ser. No. 17/729,522, which is incorporated herein by reference. FIG. 6A shows an example of the actuator 600 in a non-activated condition, and FIG. 6B shows an example of the actuator 600 in an activated condition.


The actuator 600 can include a first endcap 610 and a second endcap 620. The first endcap 610 and the second endcap 620 can be spaced apart. The actuator 600 can include a first outer member 640 and a second outer member 650. The first outer member 640 and the second outer member 650 can have a bowed shape.


The actuator 600 can include one or more shape memory material members 680. The shape memory material members 680 can be operatively connected to the first endcap 610 and the second endcap 620. The phrase “shape memory material” includes materials that changes shape when an activation input is provided to the shape memory material and, when the activation input is discontinued, the material substantially returns to its original shape. Examples of shape memory materials include shape memory alloys (SMA) and shape memory polymers (SMP).


In one or more arrangements, the shape memory material members 680 can be shape memory material wires. As an example, the shape memory material members 680 can be shape memory alloy wires. Thus, when an activation input (i.e., heat) is provided to the shape memory alloy wire(s), the wire(s) can contract. Shape memory alloy wire(s) can be heated in any suitable manner, now known or later developed. For instance, shape memory alloy wire(s) can be heated by the Joule effect by passing electrical current through the wires. In some instances, arrangements can provide for cooling of the shape memory alloy wire(s), if desired, to facilitate the return of the wire(s) to a non-activated configuration.


As noted above, FIG. 6B is an example of the actuator 600 in an activated condition. When an activation input (e.g., electrical energy) is provided to the shape memory material member(s) 680, the shape memory material member(s) 680 can contract. This contraction causes the shape memory material member(s) 680 to pull the first endcap 610 and the second endcap 620 toward each other in a direction that corresponds to the first dimension 690.


Consequently, the ends of the first outer member 640 can be drawn toward each other in a direction that corresponds to the first dimension 690, and the ends of the second outer member 650 can be drawn toward each other in a direction that corresponds to the first dimension 690. As a result, the first outer member 640 and the second outer member 650 can bow outward and away from each other in a direction that corresponds to the second dimension 695. It will be appreciated that the first dimension 690 (i.e., the width) of the actuator 600 can decrease, and the second dimension 695 (i.e., the height) of the actuator 600 can increase.



FIGS. 7A-7B show one example of an actuator 700 suitable for use according to arrangements herein. The basic details of the actuator 700 will now be described. Additional details of the actuator 700 are described in U.S. patent application Ser. No. 18/329,217, which is incorporated herein by reference.


The actuator 700 can include a first outer body member 710, a second outer body member 730, a first endcap 760, a second endcap 770, and a shape memory material member 780. The first outer body member 710 can include a first portion 712 and a second portion 714. The first portion 712 and the second portion 714 can be operatively connected to each other such that the first portion 712 and the second portion 714 can move relative to each other. In one or more arrangements, the first portion 712 and the second portion 714 can be pivotably connected to each other. For example, the first portion 712 and the second portion 714 can be pivotably connected to each other by one or more hinges. The first portion 712 and the second portion 714 can be angled relative to each other. As a result, the first outer body member 710 can have a generally V-shape.


The second outer body member 730 can include a first portion 732, a second portion 734, and a base 736. In one or more arrangements, each of the first portion 732 and the second portion 734 can be pivotably connected to the base 736. For example, the first portion 732 can be pivotably connected to the base 736 by one or more hinges, and the second portion 734 can be pivotably connected to the base 736 by one or more hinges. The first portion 732 and the second portion 734 can be located on opposite sides of the base 736.


The actuator 700 can include a first endcap 760 and a second endcap 770. The first endcap 760 and the second endcap 770 can be spaced apart. The actuator 700 can include one or more shape memory material members 780. The shape memory material member(s) 780 can extend between the first endcap 760 and the second endcap 770 in any suitable manner. The shape memory material member(s) 780 can be operatively connected to the first endcap 760 and the second endcap 770.



FIG. 7A shows an example of the actuator 700 in a non-activated configuration. Here, the shape memory material member(s) 780 are not activated. FIG. 7B shows an example of the actuator 700 in an activated configuration. When an activation input (e.g., electrical energy) is provided to the shape memory material member(s) 780, the shape memory material member(s) 780 can contract. This contraction causes the shape memory material member(s) 780 to pull the first endcap 760 and the second endcap 770 toward each other in a direction that corresponds to a first dimension 790. As a result, the first outer body member 710 and the second outer body member 730 can extend outward and away from each other in a direction that corresponds to a second dimension 795. It will be appreciated that, in going from the non-activated condition to the activated condition, the first dimension 790 (i.e., the width) of the actuator 700 can decrease and/or the second dimension 795 (i.e., the height) of the actuator 700 can increase. Further, it will be appreciated that the actuator 700 can deliver a force in a direction that is out of plane or otherwise different from the direction of contraction of the shape memory material member(s) 780.



FIG. 8 shows one example of an actuator 800 suitable for use according to arrangements herein. The basic details of the actuator 800 will now be described. Additional details of the actuator 800 are described in U.S. patent application Ser. No. 18/329,217, which is incorporated herein by reference.


The actuator 800 can include a first outer body member 810, a second outer body member 830, and one or more shape memory material members 880. The actuator 800 includes a first endcap 860 and a second endcap 870. The first endcap 860 and the second endcap 870 shown in FIG. 8 are different than the first endcap 760 and the second endcap 770 shown in FIGS. 7A-7B.



FIG. 8 shows an example of the actuator 800 in a non-activated configuration. Here, the shape memory material member(s) 880 are not activated. When an activation input (e.g., electrical energy) is provided to the shape memory material member(s) 880, the shape memory material member(s) 880 can contract. This contraction causes the shape memory material member(s) 880 to pull the first endcap 860 and the second endcap 870 toward each other in a direction that corresponds to the first dimension 890. As a result, the first outer body member 810 and the second outer body member 830 can extend outward and away from each other in a direction that corresponds to the second dimension 895. It will be appreciated that, in going from the non-activated condition to the activated condition, the first dimension 890 (i.e., the width) of the actuator 800 can decrease and/or the second dimension 895 (i.e., the height) of the actuator 800 can increase.


The various examples of actuators shown in FIGS. 5-8 are merely examples and are not intended to be limiting. Other actuators are described in U.S. Patent Publication Nos. 2023/0191953 and 2023/0136197 as well as U.S. Pat. Nos. 11,370,330; 11,285,844; and 11,091,060, which are incorporated herein by reference in their entireties.


Arrangements described herein can be used in any application in which shape memory material-based actuators are used. For instance, arrangements described herein can be used in connection with seat actuators or other actuators in a vehicle. “Vehicle” means any form of transport, including motorized or powered transport. In one or more implementations, the vehicle can be an automobile. While arrangements will be described herein with respect to automobiles, it will be understood that embodiments are not limited to automobiles. In some implementations, the vehicle may be a watercraft, an aircraft, spacecraft, or any other form of transport. However, it will be appreciated that arrangements described herein are not limited to vehicular applications. For instance, arrangements described herein can be used in connection with an office chair, a chair, a massage chair, a gaming chair, a recliner, or any other seat structure, now known or later developed. Of course, arrangements are not limited to seat applications.


It will be appreciated that arrangements described herein can provide numerous benefits, including one or more of the benefits mentioned herein. For example, arrangements described herein can enable indirect measurement of the maximum actuated state of a shape memory material member. Arrangements described herein can enable such indirect measurement using inexpensive sensors. Arrangements described herein do not require calibration. Arrangements described herein can protect shape memory material members from overheating and/or overstressing. Arrangements described herein can help to maximize the useful life of a shape memory material member. Arrangements described herein can facilitate improved actuator performance.


The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments. In this regard, each block in the flowcharts or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved.


The systems, components and/or processes described above can be realized in hardware or a combination of hardware and software and can be realized in a centralized fashion in one processing system or in a distributed fashion where different elements are spread across several interconnected processing systems. Any kind of processing system or other apparatus adapted for carrying out the methods described herein is suited. A typical combination of hardware and software can be a processing system with computer-usable program code that, when being loaded and executed, controls the processing system such that it carries out the methods described herein. The systems, components and/or processes also can be embedded in a computer-readable storage, such as a computer program product or other data programs storage device, readable by a machine, tangibly embodying a program of instructions executable by the machine to perform methods and processes described herein. These elements also can be embedded in an application product which comprises all the features enabling the implementation of the methods described herein and, which when loaded in a processing system, is able to carry out these methods.


Furthermore, arrangements described herein may take the form of a computer program product embodied in one or more computer-readable media having computer-readable program code embodied, e.g., stored, thereon. Any combination of one or more computer-readable media may be utilized. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The phrase “computer-readable storage medium” means a non-transitory storage medium. A computer-readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk drive (HDD), a solid state drive (SSD), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), a digital versatile disc (DVD), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer-readable storage medium may be any tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device.


The terms “a” and “an,” as used herein, are defined as one or more than one. The term “plurality,” as used herein, is defined as two or more than two. The term “another,” as used herein, is defined as at least a second or more. The terms “including” and/or “having,” as used herein, are defined as comprising (i.e., open language). The term “or” is intended to mean an inclusive “or” rather than an exclusive “or.” The phrase “at least one of . . . and . . . ” as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items. As an example, the phrase “at least one of A, B and C” includes A only, B only, C only, or any combination thereof (e.g., AB, AC, BC or ABC). As used herein, the term “substantially” or “about” includes exactly the term it modifies and slight variations therefrom. Thus, the term “substantially parallel” means exactly parallel and slight variations therefrom. “Slight variations therefrom” can include within 15 degrees/percent/units or less, within 14 degrees/percent/units or less, within 13 degrees/percent/units or less, within 12 degrees/percent/units or less, within 11 degrees/percent/units or less, within 10 degrees/percent/units or less, within 9 degrees/percent/units or less, within 8 degrees/percent/units or less, within 7 degrees/percent/units or less, within 6 degrees/percent/units or less, within 5 degrees/percent/units or less, within 4 degrees/percent/units or less, within 3 degrees/percent/units or less, within 2 degrees/percent/units or less, or within 1 degree/percent/unit or less. In some instances, “substantially” can include being within normal manufacturing tolerances.


Aspects herein can be embodied in other forms without departing from the spirit or essential attributes thereof. Accordingly, reference should be made to the following claims, rather than to the foregoing specification, as indicating the scope hereof.

Claims
  • 1. A system, comprising: an actuator configured to morph, when activated, into an activated configuration in which a dimension of the actuator increases, the actuator including a shape memory material member;a sensor configured to acquire sensor data, a portion of the shape memory material member operatively engaging the sensor, the shape memory material member including an external portion that extends external to the actuator; andone or more processors operatively connected to monitor a state of the shape memory material member based on the sensor data.
  • 2. The system of claim 1, wherein the portion of the shape memory material member that extends external to the actuator operatively engages the sensor.
  • 3. The system of claim 2, wherein the external portion of the shape memory material member is wrapped around the sensor, whereby, when the shape memory material member contracts, a characteristic of the sensor changes.
  • 4. The system of claim 3, wherein the sensor is a force sensitive resistive sensor.
  • 5. The system of claim 3, further including one or more protective members operatively connected to the sensor, whereby the protective members protect the sensor from the shape memory material member.
  • 6. The system of claim 1, wherein the shape memory material member is a shape memory alloy.
  • 7. The system of claim 1, wherein the shape memory material member is a wire.
  • 8. The system of claim 1, wherein the one or more processors are configured to: control the state of the shape memory material member using the sensor data.
  • 9. A system, comprising: an actuator configured to morph, when activated, into an activated configuration in which a dimension of the actuator increases, the actuator including a shape memory material member;a sensor configured to acquire sensor data, a portion of the shape memory material member operatively engaging the sensor; andone or more processors operatively connected to monitor a state of the shape memory material member based on the sensor data by monitoring changes in a resistance of the sensor.
  • 10. A system, comprising: an actuator configured to morph, when activated, into an activated configuration in which a dimension of the actuator increases, the actuator including a shape memory material member;a sensor configured to acquire sensor data, a portion of the shape memory material member operatively engaging the sensor; andone or more processors operatively connected to monitor a state of the shape memory material member based on the sensor data,when at least one metric is fulfilled based on the sensor data, the one or more processors being configured to discontinue a supply of energy to the shape memory material member.
  • 11. A system, comprising: an actuator configured to morph, when activated, into an activated configuration in which a dimension of the actuator increases, the actuator including a shape memory material member;a sensor configured to acquire sensor data, a portion of the shape memory material member operatively engaging the sensor; andone or more processors operatively connected to monitor a state of the shape memory material member based on the sensor data,when at least one metric is fulfilled based on the sensor data, the one or more processors being configured to substantially maintain a supply of energy to the shape memory material member at a current level.
  • 12. A system, comprising: an actuator configured to morph, when activated, into an activated configuration in which a dimension of the actuator increases, the actuator including a shape memory material member, the shape memory material member includes including a plurality of mechanically isolated zones defined by a plurality of isolation points along the shape memory material member;a sensor configured to acquire sensor data, a portion of the shape memory material member operatively engaging the sensor in one of the plurality of mechanically isolated zones that is external to the actuator; andone or more processors operatively connected to monitor a state of the shape memory material member based on the sensor data.
  • 13. The system of claim 12, wherein the plurality of isolation points are areas where the shape memory material member is crimped.
  • 14. A method of monitoring a state of a shape memory material member used in an actuator, a portion of the shape memory material member being wrapped around a sensor to operatively engage the sensor, the method comprising: causing the actuator to morph into an activated configuration;monitoring a state of the shape memory material member using sensor data from the sensor; andcontrolling an activated state of the actuator based on the sensor data.
  • 15. A method of monitoring a state of a shape memory material member used in an actuator, a portion of the shape memory material member operatively engaging a force sensitive resistive sensor, the method comprising: causing the actuator to morph into an activated configuration;monitoring a state of the shape memory material member using sensor data from the force sensitive resistive sensor, the monitoring including monitoring changes in a resistance of the force sensitive resistive sensor; andcontrolling an activated state of the actuator based on the sensor data.
  • 16. The method of claim 14, wherein controlling an activated state of the actuator based on the sensor data includes: discontinuing a supply of energy to the shape memory material member when at least one metric is fulfilled based on the sensor data.
  • 17. The method of claim 14, wherein controlling an activated state of the actuator based on the sensor data includes: substantially maintaining a supply of electrical energy to the shape memory material member when at least one metric is fulfilled based on the sensor data.
  • 18. A method of monitoring a state of a shape memory material member used in an actuator, a portion of the shape memory material member operatively engaging a sensor, the method comprising: causing the actuator to morph into an activated configuration by activating the shape memory material member;monitoring a state of the shape memory material member using sensor data from the sensor; andwhen at least one metric is fulfilled based on the sensor data, one of: discontinuing a supply of energy to the shape memory material member; ormaintaining a supply of energy to the shape memory material member at a current level.
US Referenced Citations (551)
Number Name Date Kind
1658669 Cohn et al. Feb 1928 A
2322755 Voorhies Jun 1943 A
2588706 Davis Mar 1952 A
3394631 Thompson Jul 1968 A
3706102 Grenier Dec 1972 A
4063826 Riepe Dec 1977 A
4244140 Kim Jan 1981 A
4396220 Dieckmann et al. Aug 1983 A
4498851 Kolm et al. Feb 1985 A
4522447 Snyder et al. Jun 1985 A
4541885 Caudill, Jr. Sep 1985 A
4544988 Hochstein Oct 1985 A
4553393 Ruoff Nov 1985 A
4595338 Kolm et al. Jun 1986 A
4779852 Wassell Oct 1988 A
4780062 Yamada et al. Oct 1988 A
4806815 Homma Feb 1989 A
4811564 Palmer Mar 1989 A
4834619 Walton May 1989 A
4898426 Schulz et al. Feb 1990 A
4923000 Nelson May 1990 A
4944755 Hennequin et al. Jul 1990 A
4955196 Lin et al. Sep 1990 A
4964402 Grim et al. Oct 1990 A
5069219 Knoblich Dec 1991 A
5088115 Napolitano Feb 1992 A
5129753 Wesley et al. Jul 1992 A
5250167 Adolf et al. Oct 1993 A
5255390 Gross et al. Oct 1993 A
5279123 Wechsler et al. Jan 1994 A
5482351 Young et al. Jan 1996 A
5488255 Sato et al. Jan 1996 A
5522712 Winn Jun 1996 A
5583844 Wolf et al. Dec 1996 A
5619177 Johnson et al. Apr 1997 A
5622482 Lee Apr 1997 A
5662376 Breuer et al. Sep 1997 A
5678247 Vickers Oct 1997 A
5686003 Ingram et al. Nov 1997 A
5747140 Heerklotz May 1998 A
5771742 Bokaie et al. Jun 1998 A
5846629 Gwinn Dec 1998 A
5853005 Scanlon Dec 1998 A
5861703 Losinski Jan 1999 A
6043978 Mody et al. Mar 2000 A
6053553 Hespelt Apr 2000 A
6093910 McClintock et al. Jul 2000 A
6116257 Yokota et al. Sep 2000 A
6142563 Townsend et al. Nov 2000 A
6155716 Okamura Dec 2000 A
6186047 Baruffaldi Feb 2001 B1
6227515 Broyles May 2001 B1
6379393 Mavroidis et al. Apr 2002 B1
6394001 Giesey et al. May 2002 B1
6404098 Kayama et al. Jun 2002 B1
6422010 Julien Jul 2002 B1
6443524 Yu Sep 2002 B1
6481799 Whalen Nov 2002 B1
6508437 Davis et al. Jan 2003 B1
6530217 Yokota et al. Mar 2003 B1
6546806 Varma Apr 2003 B1
6591188 Ohler Jul 2003 B1
6628522 Trautman et al. Sep 2003 B2
6664718 Perline et al. Dec 2003 B2
6719694 Weng et al. Apr 2004 B2
6740994 Lee et al. May 2004 B2
6773535 Wetzel Aug 2004 B1
6809462 Pelrine et al. Oct 2004 B2
6896324 Kull et al. May 2005 B1
6910714 Browne et al. Jun 2005 B2
6912748 VanSickle Jul 2005 B2
6943653 Hanke et al. Sep 2005 B2
6972659 von Behrens et al. Dec 2005 B2
6998546 Schmidt et al. Feb 2006 B1
7017345 Von Behrens et al. Mar 2006 B2
7086322 Schulz Aug 2006 B2
7093903 O'Connor et al. Aug 2006 B2
7100990 Kimura et al. Sep 2006 B2
7108316 Barvosa-Carter et al. Sep 2006 B2
7117673 Szilagyi Oct 2006 B2
7125077 Frank Oct 2006 B2
7204472 Jones et al. Apr 2007 B2
7237847 Hancock et al. Jul 2007 B2
7256518 Gummin Aug 2007 B2
7293836 Browne et al. Nov 2007 B2
7306187 Lavan Dec 2007 B2
7309104 Browne et al. Dec 2007 B2
7331616 Brei et al. Feb 2008 B2
7336486 Mongia Feb 2008 B2
7350851 Barvosa-Carter et al. Apr 2008 B2
7364211 Niskanen et al. Apr 2008 B2
7371052 Koeneman May 2008 B2
7446450 Boland et al. Nov 2008 B2
7448678 Browne et al. Nov 2008 B2
7476224 Petrakis Jan 2009 B2
7478845 Mankame et al. Jan 2009 B2
7484735 Verbrugge et al. Feb 2009 B2
7501607 Camm et al. Mar 2009 B2
7506937 Bequet Mar 2009 B2
7511402 Ito et al. Mar 2009 B2
7527312 Cucknell et al. May 2009 B1
7556313 Browne et al. Jul 2009 B2
7578661 Koeneman Aug 2009 B2
7594697 Browne et al. Sep 2009 B2
7619894 Wang et al. Nov 2009 B2
7661764 Ali et al. Feb 2010 B2
7709995 Hanlon et al. May 2010 B2
7717520 Boren et al. May 2010 B2
7729828 Gandhi Jun 2010 B2
7731279 Asada et al. Jun 2010 B2
7735940 Chiu Jun 2010 B2
7756246 Mikami et al. Jul 2010 B2
7758121 Browne et al. Jul 2010 B2
7766423 Alexander et al. Aug 2010 B2
7770391 Melz et al. Aug 2010 B2
7814810 Mitteer Oct 2010 B2
7823382 Ukpai et al. Nov 2010 B2
7823972 Browne Nov 2010 B2
7834527 Rivera et al. Nov 2010 B2
7878459 Mabe et al. Feb 2011 B2
7883148 Alexander et al. Feb 2011 B2
7892630 McKnight et al. Feb 2011 B1
7901524 McKnight et al. Mar 2011 B1
7905538 Ukpai et al. Mar 2011 B2
7905547 Lawall et al. Mar 2011 B2
7909403 Lawall et al. Mar 2011 B2
7964290 Mullner et al. Jun 2011 B2
7965509 Campbell et al. Jun 2011 B2
7971296 Jansen Jul 2011 B2
7971939 Fujita et al. Jul 2011 B2
8016952 Ishida et al. Sep 2011 B2
8038215 Di Giusto et al. Oct 2011 B2
8052112 Lawall et al. Nov 2011 B2
8056335 Brown Nov 2011 B1
8100471 Lawall et al. Jan 2012 B2
8109567 Alexander et al. Feb 2012 B2
8126615 McMillen et al. Feb 2012 B2
8172458 Petrakis May 2012 B2
8240677 Browne et al. Aug 2012 B2
8313108 Ac et al. Nov 2012 B2
8362882 Heubel et al. Jan 2013 B2
8366057 Vos et al. Feb 2013 B2
8414366 Browne et al. Apr 2013 B2
8446475 Topliss et al. May 2013 B2
8448435 Gregory et al. May 2013 B2
8510924 Mankame et al. Aug 2013 B2
8584456 McKnight Nov 2013 B1
8585456 Canon Nov 2013 B2
8593568 Topliss et al. Nov 2013 B2
8649242 Martin et al. Feb 2014 B2
8681496 Dede Mar 2014 B2
8695334 Lewis et al. Apr 2014 B2
8702120 Kalisz et al. Apr 2014 B2
8721557 Chen et al. May 2014 B2
8741076 Gao et al. Jun 2014 B2
8756933 Topliss Jun 2014 B2
8793821 Fowkes et al. Aug 2014 B2
8827709 Gurule et al. Sep 2014 B1
8830335 Topliss et al. Sep 2014 B2
8853916 Browne et al. Oct 2014 B2
8880141 Chen Nov 2014 B2
8881347 Feinstein Nov 2014 B2
8894142 Alexander et al. Nov 2014 B2
8912709 Pollock et al. Dec 2014 B2
8991769 Gandhi Mar 2015 B2
8998320 Mankame et al. Apr 2015 B2
9068561 Gondo Jun 2015 B2
9086069 Dede Jul 2015 B2
9140243 Gandhi et al. Sep 2015 B2
9168814 Gandhi Oct 2015 B2
9171686 Alacqua et al. Oct 2015 B2
9180525 Park et al. Nov 2015 B2
9267495 Kopfer et al. Feb 2016 B2
9298207 Li Mar 2016 B2
9347609 Pinto, IV et al. May 2016 B2
9428088 Rajasingham Aug 2016 B1
9457813 Hoerwick et al. Oct 2016 B2
9457887 Roe et al. Oct 2016 B2
9495875 Dowdall et al. Nov 2016 B2
9512829 Alacqua et al. Dec 2016 B2
9550466 Gandhi Jan 2017 B2
9588020 Browne et al. Mar 2017 B2
9662197 Yun et al. May 2017 B2
9664182 Nicolini et al. May 2017 B2
9664210 Ou et al. May 2017 B2
9684183 Brown et al. Jun 2017 B2
9696175 Hansen et al. Jul 2017 B2
9697708 Adrezin et al. Jul 2017 B2
9714460 Merideth Jul 2017 B2
9719534 Shevchenko et al. Aug 2017 B2
9731828 Lichota Aug 2017 B2
9764220 Keating et al. Sep 2017 B2
9784249 Li et al. Oct 2017 B2
9784590 Englehardt et al. Oct 2017 B2
9827888 Patrick et al. Nov 2017 B2
9848814 Benson et al. Dec 2017 B2
9943437 Lowe et al. Apr 2018 B2
9945490 Dankbaar et al. Apr 2018 B2
9981421 Macroe et al. May 2018 B2
9994136 Nakada Jun 2018 B2
10007263 Fields et al. Jun 2018 B1
10029618 Perez Astudillo et al. Jul 2018 B2
10059334 Zhu et al. Aug 2018 B1
10061350 Magi Aug 2018 B2
10066829 Wong et al. Sep 2018 B2
10168782 Tchon et al. Jan 2019 B1
10191550 Nussbaum et al. Jan 2019 B1
10208823 Kashani Feb 2019 B2
10299520 Shaffer et al. May 2019 B1
10302586 Sun et al. May 2019 B2
10315771 Rao et al. Jun 2019 B1
10330144 Alqasimi et al. Jun 2019 B1
10330400 Dede Jun 2019 B2
10335044 Banet et al. Jul 2019 B2
10349543 Sreetharan et al. Jul 2019 B2
10355624 Majdi et al. Jul 2019 B2
10371229 Gandhi et al. Aug 2019 B2
10371299 Leffler Aug 2019 B2
10377278 Ketels et al. Aug 2019 B2
10427634 Gandhi et al. Oct 2019 B2
10434973 Gandhi et al. Oct 2019 B2
10441491 Wyatt et al. Oct 2019 B2
10459475 Gandhi et al. Oct 2019 B2
10479246 Meingast et al. Nov 2019 B2
10532672 Pinkelman et al. Jan 2020 B1
10583757 Ketels et al. Mar 2020 B2
10591078 Oehler et al. Mar 2020 B2
10647237 Song May 2020 B2
10677310 Gandhi et al. Jun 2020 B2
10682931 Rowe et al. Jun 2020 B2
10759320 Mochizuki Sep 2020 B2
10773487 Frigerio et al. Sep 2020 B2
10781800 Brown et al. Sep 2020 B2
10814514 Aihara Oct 2020 B2
10843611 Caruss et al. Nov 2020 B2
10933974 Tsuruta et al. Mar 2021 B2
10960793 Gandhi et al. Mar 2021 B2
10965172 Dede et al. Mar 2021 B2
10993526 Vandewall et al. May 2021 B2
10995779 Keplinger et al. May 2021 B2
11048329 Lee et al. Jun 2021 B1
11091060 Pinkelman et al. Aug 2021 B2
11125248 Joshi et al. Sep 2021 B2
11137045 Gandhi et al. Oct 2021 B2
11180052 Severgnini et al. Nov 2021 B2
11241842 Gandhi et al. Feb 2022 B2
11247584 Breitweg et al. Feb 2022 B2
11248592 Tsuruta et al. Feb 2022 B1
11269891 Frank et al. Mar 2022 B2
11285844 Gandhi et al. Mar 2022 B2
11353009 Rowe et al. Jun 2022 B1
11356255 Emelyanov et al. Jun 2022 B1
11370330 Gandhi et al. Jun 2022 B2
11372481 Leroy et al. Jun 2022 B2
11377007 Samain et al. Jul 2022 B2
11458874 Nagai et al. Oct 2022 B2
11460009 Tsuruta et al. Oct 2022 B1
11460010 Tsuruta et al. Oct 2022 B1
11467669 Liu et al. Oct 2022 B2
11472325 Tsuruta et al. Oct 2022 B1
11486421 Keplinger et al. Nov 2022 B2
11536255 Rowe Dec 2022 B1
11542925 Rowe et al. Jan 2023 B1
11577471 Gandhi et al. Feb 2023 B2
11591076 Song et al. Feb 2023 B2
11592010 Panwar et al. Feb 2023 B1
11592037 Rowe et al. Feb 2023 B1
11603153 Trager et al. Mar 2023 B1
11603828 Gummin et al. Mar 2023 B2
11624376 Rowe et al. Apr 2023 B2
11628898 Trager et al. Apr 2023 B1
11642083 Severgnini et al. May 2023 B2
11649808 Tsuruta et al. May 2023 B2
11668287 Naly et al. Jun 2023 B2
11702015 Pinkelman et al. Jul 2023 B2
11732735 Song et al. Aug 2023 B2
11750115 Saneyoshi et al. Sep 2023 B2
11752901 Gandhi et al. Sep 2023 B2
11795924 Rowe Oct 2023 B2
11840161 Schmalenberg et al. Dec 2023 B2
11841008 Panwar et al. Dec 2023 B1
11885428 Panwar et al. Jan 2024 B2
11897379 Tsuruta et al. Feb 2024 B2
11913436 Easton et al. Feb 2024 B2
11927206 Rowe et al. Mar 2024 B2
20020130754 Alacqua et al. Sep 2002 A1
20020179663 Moore et al. Dec 2002 A1
20030000605 Homma Jan 2003 A1
20030182041 Watson Sep 2003 A1
20040035108 Szilagyi Feb 2004 A1
20040041998 Haddad Mar 2004 A1
20040104580 Spiessl et al. Jun 2004 A1
20040118854 Kutun Jun 2004 A1
20040145230 Fujita et al. Jul 2004 A1
20040195888 Frye Oct 2004 A1
20040256920 Gummin et al. Dec 2004 A1
20040261411 MacGregor Dec 2004 A1
20050023086 Szilagyi Feb 2005 A1
20050082897 Ropp et al. Apr 2005 A1
20050066810 Schulz May 2005 A1
20050111177 Kwitek May 2005 A1
20050146147 Niskanen et al. Jul 2005 A1
20050198904 Browne et al. Sep 2005 A1
20050199455 Browne et al. Sep 2005 A1
20050199845 Jones et al. Sep 2005 A1
20050206096 Browne et al. Sep 2005 A1
20050210874 Browne et al. Sep 2005 A1
20050211198 Froeschle et al. Sep 2005 A1
20050227607 Stevenson et al. Oct 2005 A1
20050253425 Asada et al. Nov 2005 A1
20060033312 Barvosa-Carter et al. Feb 2006 A1
20060038643 Xu et al. Feb 2006 A1
20060038745 Naksen et al. Feb 2006 A1
20060074325 Karo et al. Apr 2006 A1
20060201149 Biggs et al. Sep 2006 A1
20060223637 Rosenberg Oct 2006 A1
20060226013 Decre et al. Oct 2006 A1
20060244293 Buffa Nov 2006 A1
20060265965 Butera et al. Nov 2006 A1
20070025575 Oser et al. Feb 2007 A1
20070046074 Satta et al. Mar 2007 A1
20070063566 Browne et al. Mar 2007 A1
20070084220 Asada et al. Apr 2007 A1
20070188004 Browne et al. Aug 2007 A1
20070205853 Taya et al. Sep 2007 A1
20070236071 Fujita et al. Oct 2007 A1
20070246285 Browne et al. Oct 2007 A1
20070246898 Keefe et al. Oct 2007 A1
20070246979 Browne et al. Oct 2007 A1
20070271939 Ichigaya Nov 2007 A1
20070277877 Ghorbal et al. Dec 2007 A1
20080006353 Elzey et al. Jan 2008 A1
20080018198 Sohn et al. Jan 2008 A1
20080085436 Langan et al. Apr 2008 A1
20080100118 Young et al. May 2008 A1
20080114218 Suyama et al. May 2008 A1
20080219501 Matsumoto Sep 2008 A1
20080267770 Webster et al. Oct 2008 A1
20080271559 Garscha et al. Nov 2008 A1
20080272259 Zavattieri et al. Nov 2008 A1
20080307786 Hafez et al. Dec 2008 A1
20090008973 Browne Jan 2009 A1
20090009656 Honda et al. Jan 2009 A1
20090030576 Periot et al. Jan 2009 A1
20090041085 Petrakis Feb 2009 A1
20090108607 Browne et al. Apr 2009 A1
20090115284 Liang et al. May 2009 A1
20090131752 Park May 2009 A1
20090143730 De Polo et al. Jun 2009 A1
20090173305 Alexander et al. Jul 2009 A1
20090212158 Mabe et al. Aug 2009 A1
20090218858 Lawall et al. Sep 2009 A1
20090224584 Lawall et al. Sep 2009 A1
20090224587 Lawall et al. Sep 2009 A1
20090241537 Browne et al. Oct 2009 A1
20090242285 Whetstone, Jr. Oct 2009 A1
20090283643 Sar et al. Nov 2009 A1
20090284059 Gupta et al. Nov 2009 A1
20100001568 Trybus et al. Jan 2010 A1
20100027119 Kollar et al. Feb 2010 A1
20100031525 Allezy et al. Feb 2010 A1
20100036567 Gandhi Feb 2010 A1
20100066142 Gross et al. Mar 2010 A1
20100117663 Herrera et al. May 2010 A1
20100192567 Butera Aug 2010 A1
20100212312 Rudduck Aug 2010 A1
20100221124 Ikushima et al. Sep 2010 A1
20100244505 Demick et al. Sep 2010 A1
20100275592 Topliss et al. Nov 2010 A1
20100282902 Rajasingham Nov 2010 A1
20100287965 Bryant Nov 2010 A1
20100294476 Gomi et al. Nov 2010 A1
20100308689 Rahman et al. Dec 2010 A1
20100326070 Hao et al. Dec 2010 A1
20110021932 Kim et al. Jan 2011 A1
20110030380 Widdle, Jr. et al. Feb 2011 A1
20110038727 Vos et al. Feb 2011 A1
20110111839 Lesley et al. May 2011 A1
20110120119 Alexander et al. May 2011 A1
20110150669 Frayne et al. Jun 2011 A1
20110179790 Pretorius Jul 2011 A1
20110217031 Eromaki Sep 2011 A1
20110300358 Blohowiak et al. Dec 2011 A1
20120019216 Lewis et al. Jan 2012 A1
20120049095 Yamasaki Mar 2012 A1
20120056459 Harden Mar 2012 A1
20120081337 Camp, Jr. et al. Apr 2012 A1
20120109025 Weinberg et al. May 2012 A1
20120136126 Rousseau May 2012 A1
20120181896 Kornbluh et al. Jul 2012 A1
20120232783 Calkins et al. Sep 2012 A1
20120237309 Park et al. Sep 2012 A1
20120239183 Mankame et al. Sep 2012 A1
20120267928 Mankame et al. Oct 2012 A1
20120276807 Cabrera Nov 2012 A1
20120292155 Gunter Nov 2012 A1
20120297763 Mankame et al. Nov 2012 A1
20120319445 Zolno et al. Dec 2012 A1
20130005442 Erickson et al. Jan 2013 A1
20130011806 Gao et al. Jan 2013 A1
20130043354 Shome et al. Feb 2013 A1
20130075210 Langbein et al. Mar 2013 A1
20130098029 Pinto, IV et al. Apr 2013 A1
20130188313 Dede Jul 2013 A1
20130205770 Browne et al. Aug 2013 A1
20130227943 Mance et al. Sep 2013 A1
20140130491 Gandhi et al. May 2014 A1
20140168894 Dede Jun 2014 A1
20140196633 Shaw Jul 2014 A1
20140207333 Vandivier et al. Jul 2014 A1
20140217792 Meyer Aug 2014 A1
20140239677 Laib et al. Aug 2014 A1
20140243939 Lowe Aug 2014 A1
20140250881 Yamamoto Sep 2014 A1
20140265468 Greenhill et al. Sep 2014 A1
20140265479 Bennett Sep 2014 A1
20140277739 Kornbluh et al. Sep 2014 A1
20140298794 Flaschentrager et al. Oct 2014 A1
20140314976 Niiyama et al. Oct 2014 A1
20140316269 Zhang et al. Oct 2014 A1
20140333088 Lang et al. Nov 2014 A1
20140338324 Jasklowski Nov 2014 A1
20150016968 Grabowska et al. Jan 2015 A1
20150130220 Preisler et al. May 2015 A1
20150185764 Magi Jul 2015 A1
20150197173 Hulway Jul 2015 A1
20150202993 Mankame Jul 2015 A1
20150274078 Alacqua et al. Oct 2015 A1
20150289994 Engeberg et al. Oct 2015 A1
20150290015 Elahinia et al. Oct 2015 A1
20150331488 Grant et al. Nov 2015 A1
20150366350 DiCenso et al. Dec 2015 A1
20160004298 Mazed et al. Jan 2016 A1
20160032997 Seepersad et al. Feb 2016 A1
20160061345 Jackson, Jr. Mar 2016 A1
20160082984 Schmidt Mar 2016 A1
20160084665 Englehardt et al. Mar 2016 A1
20160123793 Kolich et al. May 2016 A1
20160221475 Sugiyama Aug 2016 A1
20160246374 Carter et al. Aug 2016 A1
20160278459 Hilty Sep 2016 A1
20160325837 Erhel et al. Nov 2016 A1
20160345088 Vilermo et al. Nov 2016 A1
20160375835 Murray et al. Dec 2016 A1
20170116792 Jelinek et al. Apr 2017 A1
20170121068 Foshansky et al. May 2017 A1
20170123499 Eid May 2017 A1
20170148102 Franke et al. May 2017 A1
20170153707 Subramanian et al. Jun 2017 A1
20170158104 Le et al. Jun 2017 A1
20170166222 James Jun 2017 A1
20170174236 Worden et al. Jun 2017 A1
20170203432 Andrianesis Jul 2017 A1
20170240075 McCoy et al. Aug 2017 A1
20170252260 Gummin et al. Sep 2017 A1
20170328384 Goto et al. Nov 2017 A1
20170355288 Barbat et al. Dec 2017 A1
20180001113 Streeter Jan 2018 A1
20180012433 Ricci Jan 2018 A1
20180036198 Mergl et al. Feb 2018 A1
20180073491 Gissen et al. Mar 2018 A1
20180084915 Norman et al. Mar 2018 A1
20180115260 Chiba et al. Apr 2018 A1
20180130347 Ricci et al. May 2018 A1
20180132825 Tachibana May 2018 A1
20180134191 Ketels et al. May 2018 A1
20180141562 Singhal May 2018 A1
20180149141 Cullen et al. May 2018 A1
20180151035 Maalouf et al. May 2018 A1
20180178808 Zhao et al. Jun 2018 A1
20180249772 Koo et al. Sep 2018 A1
20180251234 Wang Sep 2018 A1
20180264975 Bonk et al. Sep 2018 A1
20180281621 Kaku et al. Oct 2018 A1
20180286189 Motamedi et al. Oct 2018 A1
20180321703 Gandhi et al. Nov 2018 A1
20180345841 Prokhorov et al. Dec 2018 A1
20180348759 Freeman et al. Dec 2018 A1
20180355991 Pfahler Dec 2018 A1
20190005272 Gault et al. Jan 2019 A1
20190023161 Sullivan et al. Jan 2019 A1
20190039525 Hu Feb 2019 A1
20190041986 Rihn et al. Feb 2019 A1
20190042857 Endo et al. Feb 2019 A1
20190059608 Yan et al. Feb 2019 A1
20190061307 Chen et al. Feb 2019 A1
20190083022 Huang Mar 2019 A1
20190135150 Gao et al. May 2019 A1
20190143869 Sequi et al. May 2019 A1
20190154122 Lima et al. May 2019 A1
20190197842 Long et al. Jun 2019 A1
20190232842 Boccuccia et al. Aug 2019 A1
20190291649 Ito Sep 2019 A1
20200010001 Pinkelman et al. Jan 2020 A1
20200015493 Ergun et al. Jan 2020 A1
20200015593 Norman et al. Jan 2020 A1
20200032822 Keplinger et al. Jan 2020 A1
20200088175 Li et al. Mar 2020 A1
20200112269 Taghavi et al. Apr 2020 A1
20200179168 Kelleher et al. Jun 2020 A1
20200197250 Wyatt et al. Jun 2020 A1
20200223325 Pinkelman et al. Jul 2020 A1
20200238854 Gandhi et al. Jul 2020 A1
20200247274 Gandhi Aug 2020 A1
20200276971 Takeda et al. Sep 2020 A1
20200282878 Gandhi et al. Sep 2020 A1
20200298732 Gandhi et al. Sep 2020 A1
20200307416 Gandhi et al. Oct 2020 A1
20200309102 Henderson et al. Oct 2020 A1
20200339242 Tsuruta et al. Oct 2020 A1
20200377036 Lee et al. Dec 2020 A1
20200378370 Kopfer et al. Dec 2020 A1
20210095646 Blecha et al. Apr 2021 A1
20210118597 Pinkelman et al. Apr 2021 A1
20210132396 Shin et al. May 2021 A1
20210153754 Ozawa et al. May 2021 A1
20210162457 Eberfors Jun 2021 A1
20210221269 Baranowski et al. Jul 2021 A1
20210236061 Severgnini et al. Aug 2021 A1
20210237809 Rowe et al. Aug 2021 A1
20210265922 Nakagawa Aug 2021 A1
20220001530 Sameoto et al. Jan 2022 A1
20220012458 Uetabira Jan 2022 A1
20220031178 Brulet et al. Feb 2022 A1
20220106941 Easton Apr 2022 A1
20220119202 Morrissey et al. Apr 2022 A1
20220154703 Shin et al. May 2022 A1
20220164079 Severgnini et al. May 2022 A1
20220196109 Gandhi et al. Jun 2022 A1
20220242328 Pinkelman et al. Aug 2022 A1
20220258656 Little Aug 2022 A1
20220299016 Tsuruta et al. Sep 2022 A1
20220307485 Gummin et al. Sep 2022 A1
20220314857 Tsuruta et al. Oct 2022 A1
20220316458 Tsuruta et al. Oct 2022 A1
20220412325 Kopfer et al. Dec 2022 A1
20230078040 Rowe et al. Mar 2023 A1
20230088911 Song et al. Mar 2023 A1
20230119407 Sugiyama et al. Apr 2023 A1
20230120436 Tsuruta et al. Apr 2023 A1
20230124526 Tsuruta et al. Apr 2023 A1
20230136197 Gilmore et al. May 2023 A1
20230179122 Palaniswamy et al. Jun 2023 A1
20230191953 Panwar et al. Jun 2023 A1
20230193929 Rowe et al. Jun 2023 A1
20230287871 Rowe Sep 2023 A1
20230312109 Joshi et al. Oct 2023 A1
20230331371 Gupta et al. Oct 2023 A1
20230331372 Gupta et al. Oct 2023 A1
20230337827 Pinkelman et al. Oct 2023 A1
20240060480 Panwar et al. Feb 2024 A1
Foreign Referenced Citations (94)
Number Date Country
201037277 Mar 2008 CN
101367433 Feb 2009 CN
101417152 Apr 2009 CN
102333504 Jan 2012 CN
102152309 Nov 2012 CN
103038094 Apr 2013 CN
103147511 Jun 2013 CN
102026842 Jul 2013 CN
103935495 Jul 2014 CN
102765354 Nov 2014 CN
104290617 Jan 2015 CN
204774820 Nov 2015 CN
105517664 Apr 2016 CN
106168523 Nov 2016 CN
107111473 Jan 2017 CN
206029888 Mar 2017 CN
105946515 Apr 2018 CN
108100228 Jun 2018 CN
108819806 Nov 2018 CN
106014897 Dec 2018 CN
106956254 Mar 2019 CN
109572966 Apr 2019 CN
209010975 Jun 2019 CN
105003405 Jul 2019 CN
107485536 Jan 2020 CN
112411375 Feb 2021 CN
115706489 Feb 2023 CN
10155119 May 2003 DE
20309196 Nov 2003 DE
10222022 Dec 2003 DE
102010021902 Dec 2011 DE
102016210214 Dec 2017 DE
102019204866 Oct 2020 DE
102008021679 Jan 2021 DE
1420094 May 2004 EP
1519055 Mar 2005 EP
1904337 Oct 2010 EP
2723069 Apr 2014 EP
3196484 Jul 2017 EP
3058108 May 2018 FR
S5870892 May 1983 JP
S61277898 Dec 1986 JP
H03276698 Dec 1991 JP
H06033895 Jun 1994 JP
09-133069 May 1997 JP
H09168285 Jun 1997 JP
H10337061 Dec 1998 JP
2003276698 Oct 2003 JP
3706899 Oct 2005 JP
2006000347 Jan 2006 JP
2006006581 Jan 2006 JP
2006248456 Sep 2006 JP
2008014470 Jan 2008 JP
2008138558 Jun 2008 JP
2008154447 Jul 2008 JP
4273902 Jun 2009 JP
2009162233 Jul 2009 JP
2010117457 May 2010 JP
4576281 Nov 2010 JP
5760241 Aug 2015 JP
2017175155 Sep 2017 JP
2018188035 Nov 2018 JP
2019094789 Jun 2019 JP
2019101988 Jun 2019 JP
20200090181 Jun 2020 JP
2021107221 Jul 2021 JP
19980044089 Sep 1998 KR
20050056526 Jun 2005 KR
1020130005989 Jan 2013 KR
101395364 May 2014 KR
101861620 Apr 2018 KR
1020180074003 Jul 2018 KR
101931791 Dec 2018 KR
20210052091 May 2021 KR
20210086518 Jul 2021 KR
102298464 Sep 2021 KR
02011648 Feb 2002 WO
2005004321 Jan 2005 WO
2009079668 Jun 2009 WO
2009111362 Sep 2009 WO
2011017071 Feb 2011 WO
2011111769 Sep 2011 WO
2014145018 Sep 2014 WO
2014172320 Oct 2014 WO
2015037600 Mar 2015 WO
2016017057 Feb 2016 WO
2016130719 Aug 2016 WO
2017077541 May 2017 WO
2019043599 Mar 2019 WO
2019097437 May 2019 WO
2019173227 Sep 2019 WO
2020110091 Jun 2020 WO
2020183360 Sep 2020 WO
2021118185 Jun 2021 WO
Non-Patent Literature Citations (71)
Entry
Zhu et al., U.S. Appl. No. 18/172,637, filed Feb. 22, 2023.
Rowe et al., U.S. Appl. No. 18/329,217, filed Jun. 5, 2023.
Pinkelman et al., U.S. Appl. No. 18/452,343, filed Aug. 18, 2023.
Pinkelman et al., U.S. Appl. No. 18/452,376, filed Aug. 18, 2023.
Rowe et al., U.S. Appl. No. 18/453,395, filed Aug. 22, 2023.
Rowe et al., U.S. Appl. No. 18/452,734, filed Aug. 21, 2023.
Jani et al., “A review of shape memory alloy research, applications, and opportunities”, Elsevier, 2014, pp. 1078-1113 (36 pages).
Tiseo et al., “A Shape Memory Alloy Based Tuneable Dynamic Vibration Absorber for Vibration Tonal Control”, Journal of Theoretical and Applied Mechanics, 2010, pp. 135-153 (19 pages).
Williams et al., “Dynamic modelling of a shape memory alloy adaptive tuned vibration absorber”, Elsevier, Journal of Vibration and Sound, 2005, pp. 211-234 (24 pages).
Araki et al., “Integrated mechanical and material design of quasi-zero-stiffness vibration isolator with superelastic Cu—Al—Mn shape memory alloy bars”, Journal of Sound and Vibration, 2015 (34 pages).
Casciati et al., “Performance of a base isolator with shape memory alloy bars”, Earthquake Engineering and Engineering Vibration, Dec. 2007 (8 pages).
Correa et al., “Mechanical Design of Negative Stiffness Honeycomb Materials”, Integrating Materials and Manufacturing Innovation, 4:10, pp. 1-11, 2015 (11 pages).
Ferguson-Pell, “Seat Cushion Selection”, J. Rehab. Res. Dev., Special Supplement #2, 23(3), pp. 49-73, 1986 (25 pages).
Miga Motor Company, “Miga Adrenaline—A Space Age Wire,” retrieved from the Internet: <https://migamotors.com/index.php?main_page=product_info&cPath=1&products_id=37>, [retrieved Mar. 26, 2021] (1 page).
Furukawa Techno Material, “Shape Memory Alloys & Super-elastic Alloys,” retrieved from the Internet: <https://www.furukawa-ftm.com/english/nt-e/product.htm>, [retrieved Mar. 26, 2021] (3 pages).
Endragon Technology Corporation, “What is Electrostatic Chuck?” retrieved from the Internet: <https://edragoncorp.weebly.com/what-is-electrostatic-chuck.html>, 2014 (8 pages).
Strittmatter et al., “Intelligent materials in modern production—Current trends for thermal shape memory alloys,” Procedia Manufacturing, vol. 30, pp. 347-356, 2019 (10 pages).
Shunk, “GM awarded DOE money to research Shape Memory Alloy heat engines,” dated Nov. 2, 2009, retrieved from the Internet: <https://www.autoblog.com/2009/11/02/gm-awarded-doe-money-to-research-shape-memory-alloy-heat-engines/>, [retrieved Mar. 26, 2021] (2 pages).
Gummin, “Shape Memory Alloy Massage for Seating Surfaces,” dated Jun. 15, 2018, retrieved from the Internet: <https://contest.techbriefs.com/2018/entries/consumer-products/8871> (3 pages).
Stoeckel, “Shape Memory Actuators for Automotive Applications,” Materials & Design. Vol. 11, No. 6, pp. 302-307, Dec. 1990 (6 pages).
Katayama et al., “Shape Memory Alloy Wire Actuated Hinge Mechanism for Deploying Segmented Plates,” Bulletin of Osaka Prefecture University, Series A, vol. 45, No. 2, 1996, pp. 119-124 (8 pages).
Rowe et al., U.S. Appl. No. 63/485,398, filed Feb. 16, 2023.
Pinkelman et al., U.S. Appl. No. 17/729,522, filed Apr. 26, 2022.
Barbarino et al., “A review on shape memory alloys with applications to morphing aircraft”, Smart Materials and Structures, Apr. 2014 (19 pages).
“HapWRAP: Soft Growing Wearable Haptic Device”, retrieved from the Internet: <https://smartdevicess.createdsites.com>, dated May 27, 2019 (18 pages).
Yilmaz et al., “Detecting Vital Signs with Wearable Wireless Sensors”, Sensors, Dec. 2010 (26 pages).
Choi et al. “Highly conductive, stretchable, and biocompatible Ag—Au core-sheath nanowire composite for wearable and implantable bioelectronics”, Nature Nanotechnology 13, No. 11, 2018 (36 pages).
Gao et al., “Wearable Microfluidic Diaphragm Pressure Sensor for Health and Tactile Touch Monitoring”, Advanced Materials, Oct. 2017 (15 pages).
Kweon et al., “Wearable high-performance pressure sensors based on three-dimensional electrospun conductive nanofibers”, NPG Asia Materials 2018 (12 pages).
Wang et al. “Monitoring of the central blood pressure waveform via a conformal ultrasonic device”, Nat Biomed Eng, Sep. 2018 (22 pages).
Agharese et al. “hapWRAP: Soft Growing Wearable Haptic Device”, 2018 IEEE International Conference on Robotics and Automation (ICRA), May 2018 (7 pages).
Gao et al., “Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis”, Nature, Jan. 2016 (30 pages).
Jitosho et al. “Exploiting Bistability for High Force Density Reflexive Gripping”, 2019 International Conference on Robotics and Automation (ICRA), May 2019 (7 pages).
Wikipedia, “Slap bracelet”, retrieved from the Internet: <https://en.wikipedia.org/wiki/Slap_bracelet>, [retrieved Mar. 12, 2021] (2 pages).
Maffiodo et al. “Three-Fingered Gripper with Flexure Hinges Actuated by Shape Memory Alloy Wires”, Int. J. of Automation Technology, vol. 11, No. 3, pp. 355-360, 2017 (6 pages).
Buckner et al. “Roboticizing fabric by integrating functional fibers”, Proceedings of the National Academy of Sciences, Oct. 2020 (10 pages).
Blain, “Refrigerants not required: Flexible metal cooling prototype demonstrates extreme efficiency”, retrieved from the Internet: <https://newatlas.com/shape-memory-alloy-nitinol-heating-cooling/58837/> [retrieved Apr. 1, 2024], dated Mar. 13, 2019 (13 pages).
Taniguchi, “Flexible Artificial Muscle Actuator Using Coiled Shape Memory Alloy Wires”, APCBEE Procedia 7, pp. 54-59, May 2013 (6 pages).
Acome et al., “Hydraulically amplified self-healing electrostatic actuators with muscle-like performance”, Science 359, pp. 61-65, 2018 (5 pages).
Wang et al., “Recent Progress in Artificial Muscles for Interactive Soft Robotics”, Advanced Materials, vol. 33, Issue 19, published Oct. 27, 2020 (48 pages).
Liang et al., “Comparative study of robotic artificial actuators and biological muscle”, Advances in Mechanical Engineering, 2020 (25 pages).
El-Atab et al., “Soft Actuators for Soft Robotic Applications: A Review”, Advanced Intelligent Systems 2020 (37 pages).
Pagoli et al., “Review of soft fluidic actuators: classification and materials modeling analysis”, Smart Materials and Structures, vol. 31, 2021 (31 pages).
Park et al., “A Novel Fabric Muscle Based on Shape Memory Alloy Springs”, Soft Robotics, vol. 7, No. 3, 2020 (11 pages).
Ebay, “Cardboard Dividers 5 Sets 7.5″ X 10.5″ X 4″ High 12 cell”, retrieved from the Internet: <https://www.ebay.comitm/175101454003var=0&mkevt=1&mkcid=1&mkrid=711-53200-19255-0&campid=5337076261&toolid=10049&customid=ACF63RFK9J675c23041e8b13f9c32042ed51988cf3> [retrieved Jan. 20, 2022](1 page).
Cazottes et al., “Bistable Buckled Beam: Modeling of Actuating Force and Experimental Validations”, Journal of Mechanical Design, 2009 (10 pages).
Cazottes et al., “Design of Actuation for Bistable Structures Using Smart Materials,” Advances in Science and Technology, vol. 54, pp. 287-292, 2008 (1st Page/Abstract only).
Cazottes et al., “Actuation of bistable buckled beams with Macro-Fiber Composites,” IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 564-569, 2008 (7 pages).
Haines et al., “New Twist on Artificial Muscles,” Proceedings of the National Academy of Sciences, vol. 113, No. 42, pp. 11709-11716, Oct. 18, 2016 (9 pages).
Inoue et al., “High-performance structure of a coil-shaped soft-actuator consisting of polymer threads and carbon nanotube yarns,” AIP Advances 8, 2018, (8 pages).
Abbas et al., “A Physics Based Model for Twisted and Coiled Actuator” 2017 IEEE International Conference on Robotics and Automation (ICRA), pp. 6121-6126, 2017 (6 pages).
Haines et al., “Artificial Muscles from Fishing Line and Sewing Thread” (Supplementary Materials) Science 343, 868, 2014 (36 pages).
Yip et al., “On the Control and Properties of Supercoiled Polymer Artificial Muscles,” IEEE Transactions on Robotics 2017 (11 pages).
alibaba.com, “Hangzhou Phase Change Technology Co., Ltd”, Retrieved from the Internet: <https://hzfeijie.en.alibaba.com/product/1448845650-220286736/phase_change_material_PCM_balls.html#!>, [Retrieved May 2, 2017] (3 pages).
Goodfellow Corporation, “New to Our Range: A Magnetic Shape Memory Alloy that Converts Magnetic Field Energy into Kinetic Energy,” <retrieved from the Internet: http://www.goodfellowusa.com/corporate/news/US/June-2011/us.htm> [retrieved Jan. 23, 2012] (2 pages).
Goodfellow Corporation, “Magnetic Shape Memory Material”, <retrieved from the Internet: http://www.goodfellowusa.com/larger-quantities/alloys/magnetic-shape-memory-material/> [retrieved Jan. 23, 2012] (3 pages).
Sherrit et al., “Planar Rotary Motor using Ultrasonic Horns”, Proc. SPIE 7981, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2011, 79810O, Apr. 13, 2011 (8 pages).
Henry, “Dynamic Actuation Properties of Ni—Mn—Ga Ferromagnetic Shape Memory Alloys”, submitted to the Massachusetts Institute of Technology Department of Materials Science and Engineering on May 22, 2002, images on pp. 64-66 (202 pages).
Zhu et al., U.S. Appl. No. 18/433,896, filed Feb. 6, 2024.
Rowe et al., U.S. Appl. No. 18/468,029, filed Sep. 15, 2023.
Zhu et al., U.S. Appl. No. 18/399,075, filed Dec. 28, 2023.
Rowe et al., U.S. Appl. No. 18/178,302, filed Mar. 3, 2023.
Rowe et al., U.S. Appl. No. 18/399,026, filed Dec. 28, 2023.
Ou et al., “jamSheets: Thin Interfaces with Tunable Stiffness Enabled by Layer Jamming,” Proceedings of the 8th International Conference on Tangible, Embedded, and Embodied Interaction, 2014 (8 pages).
Ou et al., “aeroMorph—Heat-sealing Inflatable Shape-change Materials for Interaction Design,” Proceedings of the 29th Annual Symposium on User Interface Software and Technology (2016) pp. 121-132 (10 pages).
Song et al., “Resistance Modelling of SMA Wire Actuators”, Canadian Institute for NDE, International Workshop: Smart Materials, Structures & NDT in Aerospace Conference, Nov. 2011 (10 pages).
Rowe et al., U.S. Appl. No. 18/452,602, filed Aug. 21, 2023.
Motzki, “Efficient SMA Actuation—Design and Control Concepts”, Proceedings, vol. 64, No. 1, MDPI, 2020 (9 pages).
Arduino Documentation, “Secrets of Arduino PWM”, last revision May 27, 2024, retrieved from the Internet: <https://docs.arduino.cc/tutorials/generic/secrets-of-arduino-pwm/>, [retrieved Jun. 1, 2024] (13 pages).
Spiess, “#321 7 Sensors tested: Measuring Current with Microcontrollers (Arduino, ESP32, ESP8266)”, uploaded on Apr. 5, 2020 by user “Andreas Spiess” accessible via the Internet: <https://www.youtube.com/watch?v=cG8moaufmQs>.
International Search Authorithy, International Search Report and Written Opinion for International Application No. PCT/US2024/042739 mailed on Nov. 28, 2024, 2024 (12 pages).