SST: Predicting and Optimizing Nano/Micro Sensor Material Behavior in Extreme Environments

SST：预测和优化极端环境中纳米/微米传感器材料的行为

• 批准号: 0428419
• 负责人: Youping Chen
• 金额: --
• 依托单位: George Washington University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-01 至 2006-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0428419&HistoricalAwards=false
• 关键词: SST; Predicting; Optimizing; Nano; Micro

Abstract0428419James LeeGeorge Washington UniversityThe need of ever decreasing feature size on sensors and the need of sensor applications in extreme conditions have posed severe requirements on sensor materials, leading to the need for new materials. Development of such materials is an extraordinary challenge. Response to this challenge can be significantly aided by accurately predicting material behavior at nano/micro scale and under extreme conditions. The objective of this research is to provide a theoretical and computational basis for sensor developments, with the emphasis on nano/micro sensor materials in extreme conditions. It consists of two parts: (1) developing a multiscale field theory that exactly represents atomic N-body dynamics and can work as an alternative to, but computationally more efficient than atomic-level molecular dynamics simulation in studying statistical and high temperature properties of materials; (2) performing multiscale modeling to understand, predict and optimize complex material behavior of nano/micro sensors in extreme conditions. This is a project supported under the Sensors Initiative NSF 04-522.

Abstract0428419James Leegeorge Washington University的需求降低了传感器的功能大小，并且在极端条件下对传感器应用的需求对传感器材料提出了严重的要求，从而导致需要新材料。这种材料的开发是一个非凡的挑战。通过在纳米/微尺度和极端条件下准确预测材料行为，可以显着帮助对这一挑战的反应。这项研究的目的是为传感器开发提供理论和计算基础，重点是在极端条件下纳米/微传感器材料。 它由两个部分组成：（1）开发一个多尺度场理论，该理论准确代表原子N体动力学，并且可以作为替代方案的替代方法，但在研究材料的统计和高温特性中，计算比原子级分子动力学模拟更有效； （2）在极端条件下进行多尺度建模以理解，预测和优化纳米/微传感器的复杂材料行为。这是传感器计划NSF 04-522支持的项目。