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

IF 16.8 2区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY Wiley Interdisciplinary Reviews: Computational Molecular Science Pub Date : 2023-06-21 DOI:10.1002/wcms.1677
Pranjul Bhatt, Ayush Kumar Pandey, Ashutosh Rajput, Kshitij Kumar Sharma, Abdul Moyez, Abhishek Tewari
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引用次数: 1

Abstract

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.

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卤化物钙钛矿光伏材料不稳定性和降解问题的计算模型综述
混合卤化物钙钛矿太阳能电池因其高功率转换效率、多功能化学计量和低成本而被公认为未来最有前途的光伏技术之一。然而,环境暴露引起的降解和离子缺陷迁移引起的结构不稳定阻碍了该技术的商业化。虽然实验研究试图理解降解机制的现象学,并制定切实可行的措施来提高这些材料的稳定性,但理论研究试图弥合我们在不同时间和长度尺度上对基本降解机制的理解差距。通过多尺度材料建模,更深入地了解原子水平上的物理和化学现象,对于基于知识的预测和设计未来的卤化物钙钛矿至关重要。在过去几年中,朝着这个方向作出了更大的努力。然而,通过原子建模和模拟方法探索的不稳定性基本原理在文献中尚未得到全面的综述。因此,本文试图提出一个批判性的综述,同时确定在使用计算方法研究卤化物钙钛矿的降解和不稳定性问题方面存在的差距和机会。综述将主要集中在由于热、湿气和光暴露导致的固有离子缺陷迁移和降解引起的不稳定性上。将介绍主要使用密度泛函理论、从头算分子动力学、经典分子动力学和机器学习方法进行的模拟研究的结果。本文分类如下:
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Wiley Interdisciplinary Reviews: Computational Molecular Science
Wiley Interdisciplinary Reviews: Computational Molecular Science CHEMISTRY, MULTIDISCIPLINARY-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
28.90
自引率
1.80%
发文量
52
审稿时长
6-12 weeks
期刊介绍: Computational molecular sciences harness the power of rigorous chemical and physical theories, employing computer-based modeling, specialized hardware, software development, algorithm design, and database management to explore and illuminate every facet of molecular sciences. These interdisciplinary approaches form a bridge between chemistry, biology, and materials sciences, establishing connections with adjacent application-driven fields in both chemistry and biology. WIREs Computational Molecular Science stands as a platform to comprehensively review and spotlight research from these dynamic and interconnected fields.
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