Computational Modeling of Perovskite for Photovoltaic Applications
Edoardo Mosconi a
a Computational Laboratory for Hybrid/Organic Photovoltaics (CLHYO), Istituto CNR di Scienze e Tecnologie Chimiche “Giulio Natta” (CNR-SCITEC), Perugia, 06123 Italy
NIPHO
Proceedings of International Conference on Perovskite Thin Film Photovoltaics and Perovskite Photonics and Optoelectronics (NIPHO22)
Online, Spain, 2022 February 14th - 15th
Organizers: Giulia Grancini, Mónica Lira-Cantú and Silvia Colella
Invited Speaker, Edoardo Mosconi, presentation 016
DOI: https://doi.org/10.29363/nanoge.nipho.2022.016
Publication date: 11th November 2021

Hybrid AMX3 perovskites (A=Cs, CH3NH3; M=Sn, Pb; X=halide) have in the last years revolutionized the scenario of emerging photovoltaic technologies. Despite the extremely fast progress, the materials electronic properties which are key to the photovoltaic performance are relatively little understood. Density Functional Theory electronic structure methods have so far delivered an unbalanced description of Pb- and Sn-based perovskites. We developed an effective GW method incorporating spin-orbit coupling[1] which allows us to accurately model the electronic, optical and transport properties of halide perovskites, opening the way to new materials design. In particular, the different CH3NH3SnI3 and CH3NH3PbI3 electronic properties are discussed in light of their exploitation for solar cells and found to be dominantly due to relativistic effects. By applying our computational approach, we moved to investigate the effect of the chlorine doping for the mixed halide perovskites (MAPbI3-xClx)[2] and the role of the different A cation.[3] In parallel, a series of computational simulation carried out using Car-Parrinello molecular dynamics have been performed investigating the nature of the perovskites/TiO2 interface,[4] the role of moisture in the perovskite degradation[5] process and the effect of the defect on the device working mechanism.[6] Finally, a series of different strategies will be reported to increase the device stability and efficiency.[7] The overall picture of our theoretical investigations underlines a crucial role of computational investigation, casting the possibility of performing predictive modeling simulations, in which the properties of a given system are simulated even before the materials laboratory synthesis and characterization. At the same time, computer simulations are shown to offer the required atomistic insight into hitherto inaccessible experimental observables.

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