Collaborative Research: CDI-Type I: Meta-Codes for Computational Kinetics

合作研究：CDI-Type I：计算动力学元代码

• 批准号: 1027765
• 负责人: Michael Falk
• 金额: $ 28万
• 依托单位: Johns Hopkins University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-15 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1027765&HistoricalAwards=false
• 关键词: Collaborative; Research; CDI; Type; Meta

This award is part of the Cyber-enabled Discovery and Innovation CDI-Type I and the recipients are Michael Falk of Johns Hopkins University and Krishnakumar Garikipati of University of Michigan Ann Arbor.Materials are increasingly being applied in devices that derive their function from small-scale, and even nanometer-scale, features. Examples include advanced battery materials and quantum wires proposed for use in next generation opto-electronics. Features on these scales are subject to profound changes over time due to the thermally induced motion of atoms. The focus of this project is to develop the computational tools that are required for predicting the way these features evolve with time by developing computer programs referred to as "meta-codes." These meta-codes allow researchers to consider these problems by integrating knowledge obtained from the smallest scales, on which electrons control atomic interactions, to the largest scales, on which elastic interactions drive features to form or dissolve with time. The expected result is an automated, top-down working paradigm that naturally integrates tools from quantum mechanics, statistical physics and continuum elasticity. The intellectual impact comes both from an increased understanding of how to develop meta- codes to undertake multi-scale modeling and from a deeper understanding of the energy storage and electronic materials studied with these novel tools. The broader impact of this work arise from the development of an approach that integrates chemistry, physics and mechanics, and that can be used to refine our understanding of how a wide variety of materials systems evolve when there exist large spatial variations in composition and stress. The project includes active participation of students at the undergraduate, graduate and postdoctoral level, and incorporates a series of outreach activities that leverage those ongoing in the involved institutions.

该奖项是网络发现与创新cdi - I的一部分，获奖者是约翰霍普金斯大学的Michael Falk和密歇根大学安娜堡分校的Krishnakumar Garikipati。材料越来越多地应用于从小尺度甚至纳米尺度特征中获得功能的设备中。例子包括用于下一代光电子技术的先进电池材料和量子线。随着时间的推移，由于原子的热诱导运动，这些尺度上的特征会发生深刻的变化。这个项目的重点是开发计算工具，通过开发被称为“元代码”的计算机程序来预测这些特征随时间演变的方式。这些元代码允许研究人员通过整合从最小尺度（电子控制原子相互作用）到最大尺度（弹性相互作用驱动特征随时间形成或溶解）获得的知识来考虑这些问题。预期的结果是一个自动化的、自上而下的工作范式，它自然地集成了量子力学、统计物理和连续介质弹性的工具。智力上的影响来自于对如何开发元代码进行多尺度建模的理解的增加，以及对使用这些新工具研究的能量存储和电子材料的更深入理解。这项工作的更广泛的影响来自于一种整合化学、物理和力学的方法的发展，它可以用来完善我们对各种材料系统在成分和应力存在较大空间变化时如何演变的理解。该项目包括本科生、研究生和博士后学生的积极参与，并结合了一系列利用相关机构正在进行的外展活动。