Bulk and surface DFT investigations of inorganic halide perovskites screened using machine learning and materials property databases

Abstract

An integrated ML-DFT methodology enables screening of inorganic halide perovskites for photovoltaic applications and thorough characterization of their surface structures. Glazer tilts make (110) the most stable surface.

Machine learning for perovskite materials design and discovery

“…In 2019, Jain et al 66 constructed an ML classification model based on SVM with 189 ABX 3 inorganic samples to predict the perovskite formability of 454 ABX 3 compositions, among which the formation probability of 45 compounds is equal to or higher than 0.8. After comparing the thermodynamic stability information of perovskite in MP, AFLOW, and OQMD, 18 compounds were subject to carry out the DFT-based bulk structural optimizations and electronic structure predictions.…”

Water-Dispersible CsPbBr3 Perovskite Nanocrystals with Ultra-Stability and its Application in Electrochemical CO2 Reduction

“…Changes in the crystal structure can be directly obtained from the structure distortion after structural relaxations, and changes in electronic structure are usually reflected in the charge redistributions (known as charge transfer). Such crystal structure distortion and charge redistributions have been widely used to check the stability of perovskites in a specific environment using DFT calculations [50][51][52]. Here, we calculated the crystal structure distortions and charge redistributions of the CsPbBr 3 after the adsorption of H 2 O molecules to elucidate the mechanism of CsBr-induced water-stability of w-CsPbBr 3 NCs.…”

Computational high throughput screening of inorganic cation based halide perovskites for perovskite only tandem solar cells

“…The respective ionic radii are provided in table 1. A previous study performed by us on hybrid perovskites [23], showed that among 10 metals used in combination with methylammonium and the 3 halogens, only 5 metals, (Cd, Hg, Pb, Sn, and Ge) resulted in perovskites that gave band gaps in the range desired for application in tandem solar cells. Therefore, in this study, we consider only these 5 metals for simulation of the perovskites.…”

“…There are, however, a number of theoretical publications available, that concentrated in high-throughput screening of perovskite materials, in terms of their energy band gaps using density functional theory calculations [11][12][13][14][15][16][17][18][19][20][21][22]. In 2018, we performed a high-throughput study on hybrid perovskite materials based on DFT calculations that aimed in finding novel perovskite materials for hybrid perovskite-only tandem solar cells [23]. We came up with 8 hybrid perovskites, 5 of which are in the lower band gap range and 3 in the higher band gap range.…”