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HL: Fachverband Halbleiterphysik
HL 45: Hybrid Perovskite and Photovoltaics I (joint session CPP/HL)
HL 45.4: Vortrag
Mittwoch, 18. März 2020, 10:15–10:30, ZEU 260
Phase transitions of hybrid and inorganic perovskites simulated by machine-learning force fields — Ryosuke Jinnouchi1,2, Jonathan Lahnsteiner1, Ferenc Karsai3, Georg Kresse1, and •Menno Bokdam1 — 1University of Vienna, Vienna, Austria — 2Toyota Central R&D Labs, Aichi, Japan — 3VASP Software GmbH, Vienna, Austria
Finite-temperature simulations of complex dynamic solids are a formidable challenge for first-principles methods. Long simulation times and large length scales under isothermal-isobaric (NPT) conditions are required, demanding years of compute time. We applied the recently developed on-the-fly Machine-Learning Force Field (MLFF) scheme[1] to generate force fields for several hybrid and inorganic perovskites (APbX3, A={MA,Cs},X={I,Br,Cl}). The MLFFs open up the required time and length scales, while retaining the distinctive chemical precision of first principles methods. We study the entropy driven phase transitions of hybrid perovskites, which have never been accurately described in simulations. Simulations using machine learned potentials give direct insight into the underlying microscopic mechanisms. The ordering of the Methylammonium (MA) molecules as function of temperature is obtained. Furthermore, we relate the phase transition temperatures of different perovskites to the radii of the involved species, and we determine the order of the transitions in Landau theory.
[1] R. Jinnouchi et al., Phys. Rev. Lett. 122, 225701 (2019)