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

点击翻译按钮获取中文摘要

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.