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WIREs Comput Mol Sci
Impact Factor: 16.778

High‐throughput computational design of halide perovskites and beyond for optoelectronics

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Abstract Halide perovskites have attracted great interest as promising next‐generation materials in optoelectronics, ranging from solar cells to light‐emitting diodes. Despite their exceptional optoelectronic properties and low cost, the prototypical organic–inorganic hybrid lead halide perovskites suffer from toxicity and low stability. Therefore, it is of high demand to search for stable and nontoxic alternatives to the hybrid lead halide perovskites. Recently, high‐throughput computational materials design has emerged as a powerful approach to accelerate the discovery of new halide perovskite compositions or even novel compounds beyond perovskites. In this review, we discuss how this approach discovers halide perovskites and beyond for optoelectronics. We first overview the background of halide perovskites and methodologies in high‐throughput computational design. Then, we focus on materials properties for different optoelectronic applications, and how they are assessed with materials descriptors. Finally, we review different studies in terms of specific materials types to discuss their design principles, screening results, and experimental verification. This article is categorized under: Structure and Mechanism > Computational Materials Science Electronic Structure Theory > Density Functional Theory
(Left) Constitution space, step‐by‐step screening process, and (right) calculated decomposition enthalpies. (Reprinted with permission from Reference 50 Copyright 2017 American Chemical Society)
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(Left) Input dataset of hybrid perovskites for training and testing and (right) importance and correlation of the selected features. (Reprinted from Reference 77)
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Schematic diagram of the high‐throughput screening process. (Reprinted from Reference 69)
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(Left) Structure of ideal rock‐salt double perovskite where, range of ionic radii for the B site and B′ site, heat map of the occurrence of the 43 elements considered, and (right) map of Cs2BB'Cl6 properties. (Reprinted with permission from Reference 61. Copyright 2017 American Chemical Society)
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(Left) Design principles and (right) phase stability diagram analysis results sliced at several Ag/Cu‐varied growth conditions. (Reprinted with permission from Reference 107. Copyright 2017 American Chemical Society)
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(Left) Space of candidate perovskites for materials screening and materials screening process by considering gradually the properties relevant to photovoltaic performance, (right) energies of different motifs arrangements, distribution mapping of double perovskites with effective tolerance factor and octahedral factor as variables, decomposition enthalpy, and decomposition enthalpy corresponding to different decomposition pathways. (Reprinted with permission from Reference 70. Copyright 2017 American Chemical Society)
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(Left) Schematic representation of the computational screening process, (right) scalar relativistic bandgaps calculated for each structure, plot of the difference between the maximum and minimum metal‐halide bond length, bandgaps calculated for the remaining structures. (Reprinted with permission from Reference 78 Copyright 2016 American Chemical Society)
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Electronic Structure Theory > Density Functional Theory
Structure and Mechanism > Computational Materials Science

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