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

这个小型企业技术转移第一阶段项目将产生一种独特的计算工具，用于预测纳米系统中的传输。这里使用的新方法是基于格子Boltzmann方法(LBM)，该方法将使用多达1亿个计算单元的网格来实现纳米设备的虚拟原型，从而为数据存储行业的NEMS设备的计算机辅助设计和分析开辟了道路。现有的LBM代码将被扩展以处理适用于计算机磁盘驱动系统中的磁头磁盘接口的高Knudsen数范围。这一新的分析模型随后将在商业软件包PowerFlow中实施，该软件包现已用于全球汽车应用，并已在数据存储行业得到早期应用。有了这个平台，将获得最高标准的数值精度、并行效率和几何灵活性(包括与商业CAD工具的完全集成)。在将该算法与简单的流动数据进行比较后，将模拟工业级复杂的纳米级传输问题，目标是解决滑块的所有相关几何细节，并获得详细的压力和剪切(头部)应力分布。在商业上，这种纳米尺度的传输预测工具将打开新的模拟市场，特别是在工程设计层面。其次，这项新技术将为计算机辅助工程(CAE)打开广阔的新市场，特别是在NEMS和相关行业，因为它能够在现实世界中复杂的设备中进行纳米级的传输预测，这些设备现在使用实验或半经验规则进行设计/优化。市场分析表明，通过在工程设计层面引入新的预测技术，现有的每年约1.5亿美元的CAE市场将增长10-100倍。

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. 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.