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.

摘要0428419詹姆斯李乔治华盛顿大学传感器上不断减小的特征尺寸的需要和传感器在极端条件下应用的需要对传感器材料提出了严格的要求，导致对新材料的需求。开发这种材料是一个巨大的挑战。通过准确预测纳米/微米尺度和极端条件下的材料行为，可以显著帮助应对这一挑战。本研究的目的是为传感器的发展提供理论和计算基础，重点是极端条件下的纳米/微米传感器材料。 它由两部分组成：（1）发展多尺度场论，精确地表示原子N体动力学，可以作为替代，但在研究材料的统计和高温性质方面比原子级分子动力学模拟更有效;（2）执行多尺度建模，以理解，预测和优化极端条件下纳米/微米传感器的复杂材料行为。这是一个由传感器倡议NSF 04-522支持的项目。