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<jats:title>Abstract</jats:title><jats:p>The polarizable continuum model (PCM) is a computational method originally formulated 30 years ago but still today it represents one of the most successful examples among continuum solvation models. Such a success is mainly because of the continuous improvements, both in terms of computational efficiency and generality, made by all the people involved in the PCM project. The result of these efforts is that nowadays, PCM, with all its different variants, is the default choice in many computational codes to couple a quantum–mechanical (QM) description of a molecular system with a continuum description of the environment. In this review, a brief presentation of the main methodological and computational aspects of the method will be given together with an analysis of strengths and critical issues of its coupling with different QM methods. Finally, some examples of applications will be presented and discussed to show the potentialities of PCM in describing the effects of environments of increasing complexity. © 2012 John Wiley &amp; Sons, Ltd.</jats:p><jats:p>This article is categorized under: <jats:list list-type="explicit-label"> <jats:list-item><jats:p>Electronic Structure Theory &gt; Ab Initio Electronic Structure Methods</jats:p></jats:list-item> </jats:list></jats:p>

<jats:title>Abstract</jats:title><jats:p>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.</jats:p><jats:p>This article is categorized under:<jats:list list-type="simple"> <jats:list-item><jats:p>Software &gt; Molecular Modeling</jats:p></jats:list-item> <jats:list-item><jats:p>Structure and Mechanism &gt; Computational Materials Science</jats:p></jats:list-item> <jats:list-item><jats:p>Data Science &gt; Artificial Intelligence/Machine Learning</jats:p></jats:list-item> </jats:list></jats:p>