Proceedings of International Conference on Perovskite Thin Film Photovoltaics and Perovskite Photonics and Optoelectronics (NIPHO24)
Publication date: 25th April 2024
Hybrid perovskites are well known for their excellent optoelectronic and transport properties and to the high tolerance to electronic defects. These crystalline semiconductors also show intriguing properties (e.g. electrocaloric response, resistive switching, ferroelectric/electret states, etc.) involving the ionic dynamics at several timescales from picoseconds to micro/milli seconds (e.g. the reorientation of molecular cations, the diffusion and trapping/detrapping of charged defects, etc.) that are typically activated by temperature or external bias. The microscopic study of such phenomena is typically out-of-reach of ab initio methods due to the associated computational cost and requires alternative approaches such as classical molecular dynamics whose numerical cost scales linearly with the number of atoms.
In this lecture, it will be discussed the progress on physics-based models1 as well as advanced machine learning approaches2 for the large scale molecular dynamics simulations. Showcase applications will be presented based on the MYP potential related to the mobility of ionic defects and their interaction with surfaces3 or boundaries4 in lead and tin based systems. Finally, recent improvements for the study of crystallization and complex 2D/3D interfaces will be discussed.
A.M acknowledges financial support from ICSC – Centro Nazionale di Ricerca in High Performance Computing, Big Data and Quantum Computing, and MUR for projects PRIN 2022 NEWATOMISTS and PRIN PNRR 2022 ORIENTING, funded by European Union – NextGenerationEU
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