Proceedings of MATSUS Spring 2025 Conference (MATSUSSpring25)
DOI: https://doi.org/10.29363/nanoge.matsusspring.2025.231
Publication date: 16th December 2024
Chalcogenide perovskites, in particular BaZrS3, have gained a lot of popularity in the last few years due to its great potential as an alternative lead-free photovoltaic absorber material. This is due to promising optoelectronic properties such as defect tolerance, strong dielectric screening, and light absorption [1]. However some of the fundamental material physics, in particular polymorphic phase transitions, have not been explored in detail. Experimental studies have given conflicting results with Raman spectroscopy showing no signs of a phase transition[2], whilst XRD studies show an orthorhombic-to-tetragonal phase transition at 800K [3].
In this talk, we will introduce our machine learning potential model trained on perovskite structures with the neuroevolution potential method [4]. Through molecular dynamics calculations, we heat the experimentally reported orthorhombic Pnma phase and observe a first-order phase transition to a tetragonal I4/mcm phase at 610K. Upon further heating, we observe a second-order phase transition from the tetragonal phase to the cubic Pm-3m phase at 880K. We explain the order of these phase transitions through group-subgroup relationships and Landau theory.
Further analysis shows that the phase transitions are mediated through the M and R phonon modes associated with octahedral tilting, as is typically found in perovskite structures [5]. We analyze all possible Glazer tiltings to show that for the BaZrS3 perovskite only the Pnma --> I4/mcm --> Pm-3m phase transition route is accessible through heating. We also show temperature-dependent static structure factors and compare them to published experimental work[3]. To end, we highlight the dependence of stability of different polymorphs of the perovskite across various pressures and temperatures through a phase diagram.