AbstractThe commercialization of perovskite solar cells (PSCs), as an emerging industry, still faces competition from other renewable energy technologies in the market. It is essential to ensure that PSCs are durable and stable in high‐temperature environments in order to meet the varied market demands of hot regions or seasons. The influence of high temperatures on the PSCs is complex, encompassing factors such as lattice strain, crystal phase changes, the creation of defects, and ion movement. Furthermore, it intensifies lattice vibrations and phonon scattering, which in turn impacts the migration rate of charge carriers. This review focuses on the durability of organic–inorganic hybrid PSCs under high temperatures. It begins by analyzing the impact of external temperature variations on the internal energy dynamics of PSCs. Subsequently, it outlines the various mechanisms provided by different functional molecules, applied to interface stabilization, grain boundary passivation, crystal growth control, electrode protection, and the development of new hole transport layers, to enhance the thermal stability of PSCs. Additionally, machine learning (ML) is discussed for predicting crystal structure stability, PSCs operational stability, and material screening, with a focus on the potential of deep learning and explainable artifical intelligence (AI) techniques in the commercialization of PSCs.
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