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

传感器特征尺寸的不断减小和极端条件下传感器应用的需要对传感器材料提出了严格的要求，导致了对新材料的需求。这种材料的开发是一个非同寻常的挑战。通过准确预测材料在纳米/微米尺度和极端条件下的行为，可以极大地帮助应对这一挑战。本研究的目的是为传感器的发展提供理论和计算基础，重点研究极端条件下的纳米/微米传感器材料。它由两部分组成：(1)发展多尺度场论，准确地表示原子N体动力学，在研究材料的统计和高温性质方面可以替代原子水平的分子动力学模拟，但在计算上比原子水平的分子动力学模拟更有效；(2)进行多尺度建模，以了解、预测和优化极端条件下纳米/微传感器的复杂材料行为。这是一个由传感器计划NSF 04-522支持的项目。

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.