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

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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.