Proceedings of MATSUS Spring 2024 Conference (MATSUS24)
DOI: https://doi.org/10.29363/nanoge.matsus.2024.144
Publication date: 18th December 2023
Halide perovskites have garnered significant attention due to their unique properties and potential applications in optoelectronics and energy-related fields. However, the reduction in crystal dimension of perovskite from 3D to low dimensional structures introduces challenges, particularly regarding quantum and dielectric confinements, resulting in larger band gaps and exciton-binding energies. The low dimensional structures imply intrinsically bigger unit cells which makes challenging the application of standard density functional theory (DFT) calculation in terms of computational cost. Furthermore, DFT tends to significantly underestimate band gaps, which is extremely problematic for optoelectronic materials. Density Functional Tight-Binding (DFTB) is a flexible, semi-empirical method based on DFT which capable of simulating large system sizes and offers the possibility of accurate band gap prediction with low computational cost.1,2
In this work, we highlight the application of DFTB methodology for studying the electronic structure, effective masses, and charge density localization in low-dimensional perovskite materials. By employing empirical fitting and parameterization, the DFTB method captures the electronic band structures of model 2D halide perovskites (e.g., Cs2PbI4, BA2PbI4, PEA2PbI4, and BA2PbBr4). We show good agreement between DFTB results and experimental electronic band gaps, as well as reduced effective masses. This first attempt is promising for further applications to other low-dimensional (1D, 0D, hollow) perovskite nanostructures or 2D/3D perovskite heterostructures with large sizes and complexity, which demonstrated excellent operational stability in solar cell architectures.
The work at institute FOTON acknowledges funding from the M-ERA.NET project PHANTASTIC (R.8003.22), and the European Union's Horizon 2020 program, through an Innovation Action under Grant Agreement No. 861985 (PeroCUBE) and through a FET Open research and innovation action under the Grant Agreement No. 899141 (PoLLoC). M.Z. acknowledges funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 899546. J.E. acknowledges financial support from the Institut Universitaire de France. This work was granted access to the HPC resources of TGCC under the allocations 2022-A0120911434 made by GENCI.
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