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SI2-SSI: Collaborative Research: Scalable, Extensible, and Open Framework for Ground and Excited State Properties of Complex Systems

SI2-SSI: Collaborative Research: Scalable, Extensible, and Open Framework for Ground and Excited State Properties of Complex Systems
SI2-SSI:协作研究:复杂系统基态和激发态属性的可扩展、可扩展和开放框架
批准号:
1339715
负责人:
Laxmikant Kale
金额:
$238.32万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-10-01 至 2019-09-30

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中文摘要
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英文摘要
Computer simulation plays a central role in helping us understand, predict, and engineer the physical and chemical properties of technological materials systems such as semiconductor devices, photovoltaic systems, chemical reactions and catalytic behavior. Despite significant progress in performing realistic simulations in full microscopic detail, some problems are currently out of reach: two examples are the modeling of electronic devices with multiple functional parts based on new materials such as novel low power computer switches that would revolutionize the Information Technology industry, and the photovoltaic activity of complex interfaces between polymers and inorganic nanostructures that would enhance US energy self-reliance. The research program of this collaborative software institute aims to create an open and effective scientific software package that can make efficient use of cutting-edge high performance computers (HPC) to solve challenging problems involving the physics and chemistry of materials. By having such software available, this software initiative will have multiple broad impacts. First, the community of materials scientists will be able to study next-generation problems in materials physics and chemistry, and computer science advances that enable the software will be demonstrated and made accessible for both communities which will help cross-fertilize further such collaborative efforts. Second, the capability of simulating and engineering more complex materials systems and technological devices could play a role in helping the US continue is competitive edge in science, technology, and education. Third, through training of young scientists, direct outreach to the broader scientific community through workshops and conferences, and educational programs ranging from secondary to graduate levels, the power, importance, and capabilities of computational modeling, materials science, and computer science methodologies that enable the science will be communicated to a broad audience. Finally, by enabling the refinement of existing materials systems as well as discovery of new materials systems, the resulting scientific advances can help broadly impact society via technological improvements: in terms of the two examples provided above, (a) the successful design of new electronic device paradigms helps significantly advance the digital revolution by permitting the introduction of smaller, more efficient, and more capable electronic circuits and information processing systems, and (b) successful creation of inexpensive, easy-to-fabricate, and durable photovoltaic materials and devices can lead to cleaner forms of energy production while reducing reliance on fossil fuels.The technical goal is to greatly enhance the open software tool OPENATOM to advance discovery in nanoscience and technology. OPENATOM will be delivered as a open, robust and validated software package capable of utilizing HPC architectures efficiently to describe the electronic structure of complex materials systems from first principles. In terms of describing electronic ground-states, OPENATOM will be enhanced by features such as improved configurational sampling methods, hybrid density functionals, and incorporation of fast super-soft pseudopotential techniques. In addition, the team will incorporate the many-body GW-BSE approach for electronic excitations that permits accurate computation of electronic energy levels, optical absorption and emission, and luminescence. Ultimately, such an extensible software framework will permit accurate electronic structure computations to employ effectively future HPC platforms with 10,000,000 cores.
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