Segregation of anion (Cl−) impurities at transparent polycrystalline α-alumina interfaces

Tewari, Amit; Nabiei, Farhang; Cantoni, Marco; Bowen, Paul; Hébert, C.

doi:10.1016/j.jeurceramsoc.2014.04.018

Cited by 5 publications

(1 citation statement)

References 22 publications

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“…Various studies have shown the dynamic correlation between methylammonium molecules in lead iodide-based perovskites. 111,112 Although ab initio MD has tackled a broad range of problems, one major benefit of classical MD is the large system size, which provides a strong motivation to develop classical force fields to study large time length scales phenomena such as grain boundary segregation [113][114][115][116][117] and diffusion, 118 interfacial adsorption, 119 and so forth. The first such interatomic potential for molecular dynamics was developed by Mattoni et al, 112 which was used to study the relaxation times in methylammonium lead halide.…”

Section: Molecular Vibrations and Lattice Dynamicsmentioning

confidence: 99%

A review on computational modeling of instability and degradation issues of halide perovskite photovoltaic materials

Bhatt

Pandey

Rajput

et al. 2023

WIREs Comput Mol Sci

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Hybrid halide perovskite solar cells have been recognized as one of the most promising future photovoltaic technologies due to their demonstrated high‐power conversion efficiency, versatile stoichiometry and low cost. However, degradation caused by environmental exposure and structural instability due to ionic defect migration hinders the commercialization of this technology. While the experimental studies try to understand the phenomenology of the degradation mechanisms and devise practical measures to improve the stability of these materials, theoretical studies have attempted to bridge the gaps in our understanding of the fundamental degradation mechanisms at different time and length scales. A deeper understanding of the physical and chemical phenomena at an atomic level through multiscale materials modeling is going to be crucial for the knowledge‐based prognosis and design of future halide perovskites. There have been increased efforts in this direction in the last few years. However, the instability fundamentals explored through atomistic modeling and simulation methods have not been reviewed comprehensively in the literature yet. Therefore, this paper is an attempt to present a critical review, while identifying the existing gaps and opportunities in the investigation of the degradation and instability issues of the halide perovskites using computational methods. The review will primarily focus on the instability caused due to the intrinsic ionic defect migration and degradation due to thermal, moisture and light exposure. The findings from the simulation studies conducted primarily using density functional theory, ab initio molecular dynamics, classical molecular dynamics and machine learning methods will be presented.This article is categorized under: Software > Molecular Modeling Structure and Mechanism > Computational Materials Science Data Science > Artificial Intelligence/Machine Learning

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