Computational Modeling and the Design of Perovskite Solar Cells
Materials modeling of solar cell absorbers has been developing rapidly in the last few decades, thanks to the capability of density functional theory to calculate total energies and electronic structures and the development of computational algorithms to determine optical properties, band offsets, and defects in semiconductors. We give a brief introduction to the materials systems and the computation of key parameters for photovoltaic application such as the bandgap, effective mass, and optical absorption. Then we take perovskite solar cells as an example, to show how one can understand and engineer real materials through high-throughput first-principles calculations. This is followed by a short perspective.
- Inorganic Crystal Structure Database (ICSD). https://icsd.fizkarlsruhe.de. Accessed in January 2019
- Pilania G, Balachandran P, Kim C, Lookman T (2016) Finding new perovskite halides via machine learning. Front Mater 3:19Google Scholar
- Wang LW (2012) High Chalcocite: A Solid-liquid hybrid phase. Phys Rev Lett 108:085703Google Scholar
- Xiao Z, Meng W, Wang J, Mitzi DB, Yan Y (2017) Searching for promising new perovskite-based photovoltaic absorbers: The importance of electronic dimensionality. 4:206Google Scholar