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，用于光伏（PV）应用的不完美和非晶材料的设计和建模。特别是，这项工作将集中在随机矩阵理论（RMT）和电子结构理论之间的基本联系上，利用由此产生的联系来利用无序PV材料的大规模模拟。具体地说，由于人们最终对特征值的分布最感兴趣，如果有可能直接从结构的集合计算这些分布，自然会产生问题。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计算普遍特征值分布，而无需实际进行任何矩阵代数。这项工作将围绕四个具体目标进行组织：1)构建非晶硅和有机体异质结PV的大型数据集，可用于测试RMT的预测；2)探索PV背景下RMT模型的范围，突破该技术的基本极限；3)使用RMT约束扩展系统的简化模型，重点关注快速接近RMT渐近预测的变量；4)利用DFT和RMT描述非晶族IV、III/V和II/VI半导体。21世纪最大的科学挑战之一是开发一种技术，能够以合理的成本大规模地将太阳光转化为电能。大多数提出的这方面的发展在很大程度上依赖于含有缺陷或固有无序的材料作为活性元素。这些材料的制造成本较低，但通常也较低的能源效率，这抵消了它们在太阳能市场上的价值。这项工作将开发数学和计算工具，从而更深入地了解新的太阳能技术，并加速设计更好的转换设备。该项目将有助于减少我们国家的碳足迹，并最大限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的高性能计算工具来解决太阳能问题。最后，通过培养学生和博士后，该项目将有助于培养下一代科学家和工程师，准备好解决与社会相关的问题。