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.

该奖项是基于网络的发现和创新CDI-Type I的一部分，获奖者是约翰·霍普金斯大学的迈克尔·福克（Michael Falk）和密歇根大学Ann Arbor的Krishnakumar Garikipati。材料越来越多地应用于设备中，这些设备可从小规模的小规模，甚至Nannomer-Scale-Scale-Scale-Scale，功能中得出功能。示例包括提议在下一代光电子学中使用的高级电池材料和量子线。 由于原子的热诱导运动，这些量表上的特征会随着时间的推移而发生深刻的变化。 该项目的重点是开发通过开发称为“元编码”的计算机程序来预测这些功能随时间发展所需的计算工具。 这些元编码使研究人员可以通过整合从最小的量表中获得的知识来考虑这些问题，电子相互作用控制原子相互作用到最大的尺度，弹性相互作用会驱动特征以随着时间的推移形成或溶解。预期的结果是自动自上而下的工作范式，该范式自然地整合了量子力学，统计物理学和连续弹性的工具。 智力上的影响既来自对如何开发元代码进行多尺度建模的了解，又来自对使用这些新型工具研究的能源存储和电子材料的更深入了解。这项工作的更广泛影响是源于整合化学，物理和力学的方法的发展，并且可以用来完善我们对各种材料系统在组成和压力中存在很大空间变化时如何发展的理解。该项目包括学生在本科，研究生和博士后级别的积极参与，并纳入了一系列外展活动，以利用参与机构中正在进行的人们。