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RESEARCH PAPER · Materials Today Energy · 2024

A comprehensive review of machine learning applications in perovskite solar cells: Materials discovery, device performance, process optimization and systems integration

Ling Mao, Changying Xiang

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A comprehensive review of machine learning applications in perovskite solar cells: Materials discovery, device performance, process optimization and systems integrationOriginalA group improvised PSO-random forest-based intelligent hybrid approach for advancing perovskite solar cell efficiency0Advancements in perovskite/CIGS tandem solar cells: Material synergies, device configurations, and economic viability for sustainable energy9Machine learning for predicting and improving perovskite properties0Structural colors for building-integrated photovoltaics (BIPV): Multidisciplinary perspectives towards sustainable design8Machine learning optimization of KOH treatment parameters for enhanced tensile strength and cellulose content in sisal fibers: A synergistic approach5AI Applications for Optimizing Performance and Longevity in Solar Energy Systems0Transforming Near-Infrared Photodetectors with Perovskites: Materials, Strategies, and Future Outlook11Comprehensive harvesting of solar energy via tandem solar cells coupled with an absorption heat transformer4Improving the performance of AgCdF3-based perovskite solar cells using machine learning-driven adjustment of active layer and charge transport materials with SCAPS-1D19Computational Insights into Perovskite Materials: Classical Molecular Dynamics and Ab Initio Approaches1Leveraging Generative AI and Large Language Model for Process Systems Engineering: A State-of-the-Art Review17Advancements in AgBiS2 thin film solar cells: strategies, challenges, and perspectives6Machine Learning‐Driven Perovskite Research from Experimental Exploration to Industrial Development6Dual-model machine learning for collaborative optimization of efficiency and stability in perovskite solar cells2Predicting photovoltaic efficiency of two-dimensional Janus materials for applications in solar energy harvesting: A combined first-principles and machine learning study4Comparative analysis of machine learning techniques for modeling irradiance-dependent J–V characteristics of perovskite solar cells1High-accuracy machine learning approach for predicting J–V characteristics of perovskite solar cells under variable irradiance5Spatial‐Uniformity–Driven Bayesian Optimization for Rapid Development of Printed Perovskite Solar Cells1Chalcogenide perovskites for next-generation solar cells: Progress, challenges, and future perspectives5Comparative Study on Prediction of Bandgaps Using Machine Learning Techniques with Regression Analysis0From first principles to machine learning: accelerating the design and discovery of hybrid organic–inorganic perovskites0Machine learning force fields for inorganic crystalline materials: principles, advances, and emerging applications8Machine-learning–driven exploration of HTL effects in Mg 3 SbBr 3 perovskite solar cells for ultra-high efficiency1Multifunctional roles and future prospects of metal oxides in perovskite solar cells0Perovskite solar cells towards industrialization: overcoming challenges with data-driven strategies8Data-driven AI approaches for screening high-efficiency, stable, and lead-free perovskite photovoltaic materials: a review2Design and analysis of the electro-optical characteristics of super-lattice structure based ZnO/MGRL PIN photodetector using random-forest-regression model for detection of photon in UV wavelength0Recent advances in data‐driven and artificial intelligence‐integrated perovskite solar cells: From design to self‐driving laboratories7Machine Learning for Designing Perovskites and Perovskite‐Inspired Solar Materials: Emerging Opportunities and Challenges7Machine learning applications in the design, optimization, and manufacturing of perovskite solar cells3Machine Learning-Guided SCAPS-1D Optimization of Lead-Free Cs2TiI4Br2 Perovskite Solar Cells for High-Efficiency and Sustainability0PerovskiteOpt-AI: A Machine Learning-Driven Multi-Parameter Optimization Framework for Lead-Free Perovskite Solar Cell Device Architecture Using SCAPS-1D Simulation and Gaussian Process Surrogate Modeling3From record efficiency to commercially viable modules: A commercialization framework for stability-driven translation of perovskite solar cells1Robust Multi-Output Prediction of Perovskite Solar Cell Parameters via Multi-Task Learning0Multiscale Computational Study of Perovskite Materials Using Classical Molecular Dynamics and Ab Initio Approaches0Quantifying hybrid lead halide perovskites from multiple viewpoints: a human-guided machine learning approach1Surrogate-assisted rolling-horizon multi-objective HVAC setpoint optimization for office buildings with BIPV systems0Beyond Exact Current Matching: Fabrication‐Tolerant Design of All‐Perovskite Tandem Solar Cells via Surrogate Modeling and Diode‐Based J – V Reconstruction0B-Site Engineering in Terbium-Based Perovskites: Unveiling TbRuO3 and TbOsO3 for High-Performance Optoelectronics—A DFT Study0A systematic review of AI assisted SCAPS 1D modeling for hydrophilic degradation analysis and efficiency retention in perovskite solar cells0

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  1. A group improvised PSO-random forest-based intelligent hybrid approach for advancing perovskite solar cell efficiency

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  2. Advancements in perovskite/CIGS tandem solar cells: Material synergies, device configurations, and economic viability for sustainable energy

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  4. Structural colors for building-integrated photovoltaics (BIPV): Multidisciplinary perspectives towards sustainable design

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  6. AI Applications for Optimizing Performance and Longevity in Solar Energy Systems

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  8. Comprehensive harvesting of solar energy via tandem solar cells coupled with an absorption heat transformer

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  9. Improving the performance of AgCdF3-based perovskite solar cells using machine learning-driven adjustment of active layer and charge transport materials with SCAPS-1D

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  10. Computational Insights into Perovskite Materials: Classical Molecular Dynamics and Ab Initio Approaches

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  13. Machine Learning‐Driven Perovskite Research from Experimental Exploration to Industrial Development

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  15. Predicting photovoltaic efficiency of two-dimensional Janus materials for applications in solar energy harvesting: A combined first-principles and machine learning study

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  16. Comparative analysis of machine learning techniques for modeling irradiance-dependent J–V characteristics of perovskite solar cells

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  17. High-accuracy machine learning approach for predicting J–V characteristics of perovskite solar cells under variable irradiance

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  18. Spatial‐Uniformity–Driven Bayesian Optimization for Rapid Development of Printed Perovskite Solar Cells

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    Julia Elizabeth Huddy, Yanan Li, Mariia Klymenko, Danielle L. Hedvig, William Joseph Scheideler

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  19. Chalcogenide perovskites for next-generation solar cells: Progress, challenges, and future perspectives

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  20. Comparative Study on Prediction of Bandgaps Using Machine Learning Techniques with Regression Analysis

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  21. From first principles to machine learning: accelerating the design and discovery of hybrid organic–inorganic perovskites

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  22. Machine learning force fields for inorganic crystalline materials: principles, advances, and emerging applications

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  23. Machine-learning–driven exploration of HTL effects in Mg 3 SbBr 3 perovskite solar cells for ultra-high efficiency

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  24. Multifunctional roles and future prospects of metal oxides in perovskite solar cells

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  28. Recent advances in data‐driven and artificial intelligence‐integrated perovskite solar cells: From design to self‐driving laboratories

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  34. Robust Multi-Output Prediction of Perovskite Solar Cell Parameters via Multi-Task Learning

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  36. Quantifying hybrid lead halide perovskites from multiple viewpoints: a human-guided machine learning approach

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  39. B-Site Engineering in Terbium-Based Perovskites: Unveiling TbRuO3 and TbOsO3 for High-Performance Optoelectronics—A DFT Study

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  40. A systematic review of AI assisted SCAPS 1D modeling for hydrophilic degradation analysis and efficiency retention in perovskite solar cells

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