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Article

Investigation of Opto-Electronic Properties and Stability of Mixed-Cation Mixed-Halide Perovskite Materials with Machine-Learning Implementation

1
Horia Hulubei National Institute for Physics and Nuclear Engineering, 077126 Magurele, Ilfov, Romania
2
Research Institute of the University of Bucharest (ICUB), Mihail Kogalniceanu Blvd 36-46, 050107 Bucharest, Romania
3
National Institute of Materials Physics, 077125 Magurele, Ilfov, Romania
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Department of Engineering, Reykjavik University, Menntavegur 1, IS-102 Reykjavik, Iceland
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Faculty of Physics, Materials and Devices for Electronics and Optoelectronics Research Center, University of Bucharest, 077125 Magurele, Ilfov, Romania
*
Author to whom correspondence should be addressed.
Academic Editor: Dhruba B. Khadka
Energies 2021, 14(17), 5431; https://doi.org/10.3390/en14175431
Received: 29 July 2021 / Revised: 24 August 2021 / Accepted: 26 August 2021 / Published: 1 September 2021
The feasibility of mixed-cation mixed-halogen perovskites of formula AxA’1xPbXyX’zX”3yz is analyzed from the perspective of structural stability, opto-electronic properties and possible degradation mechanisms. Using density functional theory (DFT) calculations aided by machine-learning (ML) methods, the structurally stable compositions are further evaluated for the highest absorption and optimal stability. Here, the role of the halogen mixtures is demonstrated in tuning the contrasting trends of optical absorption and stability. Similarly, binary organic cation mixtures are found to significantly influence the degradation, while they have a lesser, but still visible effect on the opto-electronic properties. The combined framework of high-throughput calculations and ML techniques such as the linear regression methods, random forests and artificial neural networks offers the necessary grounds for an efficient exploration of multi-dimensional compositional spaces. View Full-Text
Keywords: mixed-cation; mixed-halide; perovskite; optical absorption; degradation mechanisms; machine-learning techniques mixed-cation; mixed-halide; perovskite; optical absorption; degradation mechanisms; machine-learning techniques
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MDPI and ACS Style

Filipoiu, N.; Mitran, T.L.; Anghel, D.V.; Florea, M.; Pintilie, I.; Manolescu, A.; Nemnes, G.A. Investigation of Opto-Electronic Properties and Stability of Mixed-Cation Mixed-Halide Perovskite Materials with Machine-Learning Implementation. Energies 2021, 14, 5431. https://doi.org/10.3390/en14175431

AMA Style

Filipoiu N, Mitran TL, Anghel DV, Florea M, Pintilie I, Manolescu A, Nemnes GA. Investigation of Opto-Electronic Properties and Stability of Mixed-Cation Mixed-Halide Perovskite Materials with Machine-Learning Implementation. Energies. 2021; 14(17):5431. https://doi.org/10.3390/en14175431

Chicago/Turabian Style

Filipoiu, Nicolae, Tudor Luca Mitran, Dragos Victor Anghel, Mihaela Florea, Ioana Pintilie, Andrei Manolescu, and George Alexandru Nemnes. 2021. "Investigation of Opto-Electronic Properties and Stability of Mixed-Cation Mixed-Halide Perovskite Materials with Machine-Learning Implementation" Energies 14, no. 17: 5431. https://doi.org/10.3390/en14175431

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