Ab-Initio Computational Design of Halide Perovskites and Related Materials
George Volonakis a
a Univ Rennes, ENSCR, INSA Rennes, CNRS, ISCR - UMR 6226, F-35000 Rennes, France.
Proceedings of Emerging Light Emitting Materials 2024 (EMLEM24)
La Canea, Greece, 2024 October 16th - 18th
Organizers: Grigorios Itskos, Sohee Jeong and Jacky Even
Invited Speaker, George Volonakis, presentation 045
DOI: https://doi.org/10.29363/nanoge.emlem.2024.045
Publication date: 13th July 2024

Ab initio calculations are becoming more and more efficient and have emerged as an indispensable tool to model, characterise and understand complex systems like halide perovskites and perovskite-like materials. In particular, over the last decade, such computational approaches have been extensively employed and successfully unveiled the underlying atomic-scale physical mechanisms of these exciting materials. In this talk, I will overview our most recent results on the electronic structure of prototypical structures of layered halide perovskites, vacancy ordered double perovskites, and low dimensional halide perovskite-like materials [1-2]. I will present the key details of their electronic structure for each type of system that define their experimentally observed optical properties and achieved performances. Our results show how well (or how bad) these different types of materials can perform for different opto-electronic applications ranging from indoors and outdoors PV, light emitters. Finally, in the last part of my talk, I will focus on our latest state-of-the-art ab initio calculations of the charge carrier transport properties when comparing three-dimensional ABX3 and layered halide perovskites. Our results explore directly the effects of structural dimensionality on the carrier mobilities of a selection of prototypical layered perovskites and identify the importance of the intrinsic carrier density in layered compounds to the exhibited transport properties [3].

The research leading to these results was supported by the Agence Nationale pour la Recherche through the CPJ program and the SURFIN project (Grant No. ANR-23-CE09-0001). This work was granted access to the High Performance Computing (HPC) resources of Trés Grand Centre de Calcul (TGCC) under the Allocation Grant No. 2022-A0130907682 made by Grand Equipement National de Calcul Intensif (GENCI). 

 

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