STTR Phase I: Nanoscale Transport Processes Prediction/Design/Analysis Tool for NEMS Applications

Information

  • NSF Award
  • 0232640
Owner
  • Award Id
    0232640
  • Award Effective Date
    1/1/2003 - 21 years ago
  • Award Expiration Date
    12/31/2003 - 20 years ago
  • Award Amount
    $ 100,000.00
  • Award Instrument
    Standard Grant

STTR Phase I: Nanoscale Transport Processes Prediction/Design/Analysis Tool for NEMS Applications

This Small Business Technology Transfer Phase I project will produce a unique computational tool for predicting transport in nanoscale systems. The novel approach to be used here is based on Lattice Boltzmann Methods (LBM) which will enable virtual prototyping of nanodevices using grids of up to a hundred million computational cells thus opening the way for computer aided design and analysis of NEMS devices in the data storage industry. Existing LBM codes will be extended to handle the high Knudsen number range applicable for the head disk interface in computer disk drive system. This new analytical model will then be implemented in a commercial software package, PowerFLOW, which is now used for automotive applications worldwide and has early applications in the data storage industry. With this platform, the highest standards of numerical accuracy, parallel efficiency, and geometric flexibility (including full integration with commercial CAD tools), will be obtained. Upon benchmarking this algorithm against simplistic flow data, a nanoscale transport problem of industrial level complexity will be simulated, with the goal to resolve all the relevant geometric details of the slider and to obtain detailed pressure and shear (head) stress distributions. <br/> Commercially, this nanoscale transport prediction tool will open new simulation markets, especially at the engineering design level. Secondly, this new technology should open broad new markets for computer aided engineering (CAE), especially in NEMS and related industries, by enabling nanoscale transport prediction in devices of real world complexity which are now designed/optimized using either experimentation or semi-empirical rules. Market analysis shows that the existing CAE market of about $150 MM per year should increase 10- to 100-fold by introducing new prediction technologies at the engineering design level.

  • Program Officer
    Cheryl F. Albus
  • Min Amd Letter Date
    12/11/2002 - 21 years ago
  • Max Amd Letter Date
    12/11/2002 - 21 years ago
  • ARRA Amount

Institutions

  • Name
    Exa Corporation
  • City
    Burlington
  • State
    MA
  • Country
    United States
  • Address
    55 Network Drive
  • Postal Code
    018030000
  • Phone Number
    7815640287

Investigators

  • First Name
    Ilya
  • Last Name
    Staroselsky
  • Email Address
    ilya@exa.com
  • Start Date
    12/11/2002 12:00:00 AM

FOA Information

  • Name
    Industrial Technology
  • Code
    308000