University - Industry Cooperative Research Programs in the Mathematical Sciences: Novel Parallel Molecular Dynamics Algorithms for Simulating Thin-film Depositions

数学科学领域的产学合作研究项目：用于模拟薄膜沉积的新型并行分子动力学算法

• 批准号: 9626859
• 负责人: Yuefan Deng
• 金额: $ 7.1万
• 依托单位: SUNY at Stony Brook
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-09-01 至 1999-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9626859&HistoricalAwards=false
• 关键词: University; Industry; Cooperative; Research; Programs

9626859 Deng The University-Industry Cooperative Research Programs in the Mathematical Sciences are programs designed to establish a mechanism for exchange of mathematical scientists between academia and industry at different stages of their careers. These programs will strengthen the links between industry and academia and identify and encourage new avenues of research in the mathematical sciences. The University-Industry Postdoctoral Research Fellowships provide two years of support for recent recipients of doctoral degrees in the mathematical sciences. These awards are a means of contributing to the future vitality of the scientific effort of the nation. The postdoctoral fellow will work closely with scientific advisors from both academia and industry. The postdoctoral fellow will work under the direction of Satoshi Hamaguchi at IBM and Yuefan Deng at the State University of New York at Stony Brook. The research concerns the study of deposition and etching of thin films, focusing on atomic scale phenomena. This activity involves modeling and simulation. The use of parallel computation is expected to improve the number and length of simulations to provide a better understanding of the phenomena.

[9626859]邓数学科学校企合作研究项目是建立学术界与产业界在数学科学家职业生涯不同阶段的交流机制的项目。这些项目将加强工业界和学术界之间的联系，并确定和鼓励数学科学研究的新途径。大学-行业博士后研究奖学金为最近获得数学科学博士学位的人提供两年的支持。这些奖项是为国家科学事业的未来活力作出贡献的一种手段。该博士后将与来自学术界和工业界的科学顾问密切合作。这位博士后将在IBM的滨口聪（Satoshi Hamaguchi）和纽约州立大学石溪分校的邓岳凡（yuvan Deng）的指导下工作。本研究主要关注薄膜的沉积和蚀刻，重点关注原子尺度现象。这个活动包括建模和模拟。使用并行计算有望增加模拟的次数和长度，从而更好地理解这些现象。