SOLAR: Of Randomness and Disorder: A New Paradigm for Solar Materials Simulation

太阳能：随机性和无序性：太阳能材料模拟的新范式

• 批准号: 1035400
• 负责人: Troy Van Voorhis
• 金额: $ 155.2万
• 依托单位: Massachusetts Institute of Technology
• 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: 2010-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1035400&HistoricalAwards=false
• 关键词: SOLAR; Randomness; Disorder; New; Paradigm

This project entails the development and application of transformative tools for the design and modeling of imperfect and amorphous materials for photovoltaic (PV) applications. In particular, the work will focus on the fundamental connections between random matrix theory (RMT) and electronic structure theory, using the resulting links to leverage large scale simulations of disordered PV materials. Specifically, since one is in the end most interested in the distribution of eigenvalues, the question naturally arises if it is possible to calculate these distributions directly from the ensemble of structures. Surprisingly, in many cases, RMT allows the calculation of universal eigenvalue distributions from an apparently random distribution of matrices, without ever actually doing any matrix algebra. The work will be organized around four specific aims: 1) The construction of large data sets on amorphous silicon and organic bulk heterojunction PV that can be used to test the predictions of RMT; 2) Exploring the range of RMT models in the context of PV, pushing the fundamental limits of this technique; 3) Using RMT to constrain reduced models of extended systems, focusing on variables that rapidly approach the asymptotic predictions of RMT; 4) Leveraging DFT and RMT to describe amorphous group IV, III/V and II/VI semiconductors. One of the grand scientific challenges of the 21st century is the development of a technology that can convert sunlight to electricity on a large scale at reasonable cost. Most of the proposed developments toward this end rely heavily on materials containing defects or inherently disordered materials as the active element. These materials have lower manufacturing costs, but typically also lower energy efficiency, which offsets their value in the solar marketplace. This work will develop mathematical and computational tools that will yield a deeper understanding of new solar technologies and accelerate the design of better conversion devices. The project will contribute to reducing our national carbon footprint and minimizing our dependence on foreign sources of fossil fuels. The work will also bring novel high-performance computing tools to bear on solar energy problems. Finally, through the training of students and postdocs, the project will help foster the next generation of scientists and engineers, ready to address problems relevant to society.

该项目需要开发和应用变革性工具，用于用于光伏（PV）应用的不完美和无定形材料的设计和建模。 特别是，这项工作将着重于随机矩阵理论（RMT）与电子结构理论之间的基本联系，使用结果链接来利用无序的PV材料的大规模模拟。具体而言，由于最终对特征值的分布最感兴趣，因此如果可以直接从结构的集合中计算这些分布，则自然会出现这个问题。令人惊讶的是，在许多情况下，RMT允许从矩阵的明显随机分布中计算通用特征值分布，而无需实际执行任何矩阵代数。 这项工作将围绕四个特定目的组织：1）在无定形硅和有机散装异质结PV上建造大型数据集，可用于测试RMT的预测； 2）在PV的背景下探索RMT模型的范围，从而推动了该技术的基本限制； 3）使用RMT来限制扩展系统的减少模型，重点是快速接近RMT的渐近预测的变量； 4）利用DFT和RMT来描述IV，III/V和II/VI半导体的无定形组。 21世纪的宏伟科学挑战之一是开发一种技术，该技术可以以合理的成本大规模将阳光转化为电力。 大多数拟议的开发项目都严重依赖于包含缺陷或固有无序材料作为活动元素的材料。这些材料的制造成本较低，但通常也降低了能源效率，从而抵消了其在太阳能市场中的价值。这项工作将开发数学和计算工具，这些工具将对新的太阳能技术产生更深入的了解，并加速更好的转换设备的设计。 该项目将有助于减少我们的国家碳足迹，并最大程度地减少我们对外国化石燃料来源的依赖。 这项工作还将带来新颖的高性能计算工具，以解决太阳能问题。 最后，通过对学生和博士后的培训，该项目将有助于培养下一代的科学家和工程师，并准备解决与社会相关的问题。