Collaborative Research: ITR/AP: Novel Scalable Simulation Techniques for Chemistry, Materials Science and Biology
Collaborative Research: ITR/AP: Novel Scalable Simulation Techniques for Chemistry, Materials Science and Biology
批准号:
0121357
负责人:
Josep Torrellas
金额:
$124.1万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2001
资助国家:
美国
项目状态:
已结题
起止时间:
2001-10-01 至 2007-09-30
中文摘要
普林斯顿大学的Roberto Car和Annabella Selloni在信息技术研究计划(ITR)下得到化学系、材料研究部和高级计算基础设施与研究部的支持,使从头算分子动力学模拟更有效,更容易在高性能计算平台上实现。共同负责人包括伊利诺伊大学的Josep Torrellas和Laxmikant Kale,宾夕法尼亚大学的Michael Klein,纽约大学的Mark Tuckerman,印第安纳大学的Glenn Martyna和卡内基梅隆大学的Nicholas Nystrom(分别通过合作提案CHE-0121357, CHE-0121302, CHE-0121375, CHE-0121367和CHE-0121273)。这个由计算化学家和计算机科学家组成的团队将开发新的高效和高精度的方法,具有理想缩放特性的可扩展开源软件模块,以及新颖的硬件设计,这些设计将使化学、材料科学和工程、地球科学和生物学感兴趣的复杂事件和环境建模成为可能。信息技术(IT)已经改变了计算科学,在某种程度上,化学、纳米科学、工程和生物学的关键过程的现实的、基于原子的模拟现在可以使用高度精确的模拟来解决。这项研究可能对聚合物生成催化剂、纳米级电子器件和人工仿生催化剂的设计产生潜在的影响。
英文摘要
Roberto Car and Annabella Selloni of Princeton University are supported under the Information Technology Research Program (ITR) by the Division of Chemistry, the Division of Materials Research, and the Division of Advanced Computational Infrastructure and Research to make ab initio molecular dynamics simulations more effective and more accessible on high performance computing platforms. Co-PI's include Josep Torrellas and Laxmikant Kale of University of Illinois, Michael Klein of the University of Pennsylvania, Mark Tuckerman of New York University, Glenn Martyna of Indiana University, and Nicholas Nystrom of Carnegie Mellon University (via collaborative proposals CHE-0121357, CHE-0121302, CHE-0121375, CHE-0121367, and CHE-0121273, respectively). This team of computational chemists and computer scientists will develop new efficient and high accuracy methods, extensible open source software modules with desirable scaling properties, and novel hardware designs that will enable modeling of complex events and environments of interest to chemistry, materials science and engineering, geoscience, and biology.Information technology (IT) has transformed computational science to the extent that realistic, atom-based simulations of key processes in chemistry, nanoscience and engineering, and biology can now be addressed using highly accurate simulations. This research can potentially impact the design of polymer-generating catalysts, nanoscale electronic devices, and artificial biomimetic catalysts.
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