Phase behavior and electronic properties of mixed halide perovskites from atomic scale simulations
Halide perovskites have seen a surge in activity over the last years thanks to their potential for applications in light harvesting and emission technologies. Compositional engineering through mixing on different sublattices is essential for achieving optimal performance. While new halide perovskite composition are being developed largely through systematic optimization and trial-and-error approaches, we contend that this situation can be substantially improved by computational modeling.
Here, we therefore propose a comprehensive research project that involves (1) model construction and development of associated tools, (2) analyzing phase behavior and predicting phase diagrams, and (3) mapping associated electronic properties, including those of polarons and defects, as a function of composition and temperature. In this context, we will consider subsystems of CsPb1-xSnxI3-y-zBryClz following a gradual increase in complexity during the course of the project. The project is based on the systematic construction of atomic scale models, referred to as graph potentials, which are intermediate between complex machine learning models such as Gaussian approximation potentials and lattice models such as cluster and force constant expansions. By involving both computational/theoretical and experimental researchers, the goal of the present project is to lead to better understanding and a more allow rational design of new materials.
Paul Erhart (contact)
Professor at Chalmers, Physics, Condensed Matter and Materials Theory
Assistant Professor at Chalmers, Physics, Condensed Matter and Materials Theory
Technische Universität Darmstadt
University of Cambridge
Cambridge, United Kingdom
Swedish Research Council (VR)
Project ID: 2020-04935
Funding Chalmers participation during 2020–2024