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RESEARCH PAPER · Advanced Functional Materials · 2023

Machine Learning for Perovskite Solar Cells and Component Materials: Key Technologies and Prospects

Yiming Liu, Xinyu Tan, Jie Liang, Hongwei Han, Peng Xiang, Wensheng Yan

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Machine Learning for Perovskite Solar Cells and Component Materials: Key Technologies and ProspectsOriginalComparative Study of Five Classifiers for Predicting Power Conversion Efficiency in Perovskite Solar Cells0Lead-free perovskite-inspired semiconductors for indoor light-harvesting – the present and the future53Leveraging machine learning to consolidate the diversity in experimental results of perovskite solar cells20The role of machine learning in perovskite solar cell research42A review on computational modeling of instability and degradation issues of halide perovskite photovoltaic materials24Automatic Screen‐out of Ir(III) Complex Emitters by Combined Machine Learning and Computational Analysis25Auxiliary guidance manufacture and revealing potential mechanism of perovskite solar cell using machine learning18Comprehensive Machine Learning Pipeline for Prediction of Power Conversion Efficiency in Perovskite Solar Cells6Interfacial Tuning of Polymeric Composite Materials for High-Performance Energy Devices18Accelerated discovery of perovskite materials guided by machine learning techniques11Machine‐Learning Accelerating the Development of Perovskite Photovoltaics12Exploration of Solution-Processed Bi/Sb Solar Cells by Automated Robotic Experiments Equipped with Microwave Conductivity18Recent studies on small molecular and polymeric hole‐transporting materials for high‐performance perovskite solar cells27Parametric estimation of photovoltaic systems using a new multi-hybrid evolutionary algorithm18Bayesian parameter estimation for characterising mobile ion vacancies in perovskite solar cells14Unraveling the Effect of Compositional Ratios on the Kesterite Thin-Film Solar Cells Using Machine Learning Techniques17Transfer Learning for Material Parameter Extraction from Current-Voltage Characteristics of Solar Cells2Experimental demonstration of SnO₂ nanofiber-based memristors and their data-driven modeling for nanoelectronic applications10A machine learning approach for in silico prediction of the photovoltaic properties of perovskite solar cells based on dopant-free hole-transport materials8Exploring the Impact of Guanidinium Ion Doping on Perovskite Performance Through Surface Photovoltage Characterization0Highly Reliable Anti-Reflection Radiative Cooling Glass Applicable to Thermal Management of Solar Cells24Surface matrix regulation of perovskite quantum dots for efficient solar cells26Toward high-quality colloidal metal halide perovskite nanocrystals4Towards scalability for metal halide perovskites photovoltaics1Utilizing machine learning to enhance performance of thin-film solar cells based on Sb 2 (S x Se 1− x ) 3 : investigating the influence of material properties28Advancing perovskite solar cell commercialization: Bridging materials, vacuum deposition, and AI-assisted automation32Machine Learning in Soft Matter: From Simulations to Experiments34Machine learning as a characterization method for analysis and design of perovskite solar cells26Unveiling dominant recombination loss in perovskite solar cells with a XGBoost-based machine learning approach38Materials genome engineering accelerates the research and development of organic and perovskite photovoltaics64Methods and applications of machine learning in computational design of optoelectronic semiconductors22Machine Learning Aided Design and Optimization of Thermal Metamaterials195Encapsulating perovskite solar cells for long-term stability and prevention of lead toxicity66Predictive machine learning approaches for perovskites properties using their chemical formula: towards the discovery of stable solar cells materials21Data-driven strategy for bandgap database construction of perovskites and the potential segregation study11Predicting photovoltaic parameters of perovskite solar cells using machine learning9Artificial intelligence applications in solar energy16Machine learning-based screening of two-dimensional perovskite organic spacers13Machine Learning for Perovskite Solar Cells: An Open‐Source Pipeline11Geometric data analysis-based machine learning for two-dimensional perovskite design12Artificial neural network assisted numerical analysis on performance enhancement of Sb2(S,Se)3 solar cell with SnS as HTL20Machine Learning-Driven Exploration of Cesium-Based All-Inorganic Mixed-Halide Perovskite Solar Cells with a Double Absorber Layer Architecture18Investigating the Performance of FASnI3‐Based Perovskite Solar Cells with Various Electron and Hole Transport Layers: Machine Learning Approach and SCAPS‐1D Analysis49Exploring the impact of guanidinium ion doping on perovskite performance through surface photovoltage characterization3Self-supervised generative models for crystal structures6Adapting Explainable Machine Learning to Study Mechanical Properties of 2D Hybrid Halide Perovskites16MolPackL: Quantification and Interpretation of Intermolecular Interactions Driven by Molecular Packing10Machine learning for perovskite optoelectronics: a review24Perovskite solar cells: Organic-based molecules for electron and hole transport materials with machine learning insights11Predicting battery applications for complex materials based on chemical composition and machine learning14Machine learning driven performance for hole transport layer free carbon-based perovskite solar cells32A scalable and aging-resistant film for radiative cooling29Digital manufacturing of perovskite materials and solar cells12Superhydrophobic photothermal coatings based on polyurea for durable anti-icing and deicing21A UV-resistant porous composite film for radiative cooling and enhanced hydrophobicity7All-Season Dual-Mode Thermolator Based on Radiative Cooling and Solar Heating Technology10Exploration of highly stable and highly efficient new lead-free halide perovskite solar cells by machine learning19Machine learning prediction of materials properties from chemical composition: Status and prospects29Machine-learning-assisted exploration of new non-fullerene acceptors for high-efficiency organic solar cells12Machine learning-assisted design of high-performance perovskite photodetectors: a review22Property Prediction for Complex Compounds Using Structure-Free Mendeleev Encoding and Machine Learning9Advanced Photovoltaic Degradation Analysis using Physics Modeling and Bayesian Machine Learning0Perovskite Solar Cell Design Revolution: A Machine Learning Perspective0Enhancing Power Conversion Efficiency of Perovskite Solar Cells Through Machine Learning Guided Experimental Strategies26Thermodynamic stability descriptor of A2BX6-type perovskite materials18Accelerating materials property discovery in uncharted domains through the integration of high-throughput computation and machine learning2An explainable “family bucket” model for simultaneous prediction of K-edge XANES for multiple light transition metals3Data-driven modelling for electrolyte optimisation in dye-sensitised solar cells and photochromic solar cells10Data-guided design of double-atom catalysts for enhanced electrocatalytic performance7Decoding recombination dynamics in perovskite solar cells: an in-depth critical review76Deep learning for augmented process monitoring of scalable perovskite thin-film fabrication36From synthesis to properties: expanding the horizons of machine learning in nanomaterials research39Gray-Box Identification of a Photovoltaic Power Generation System0Introducing a Novel Figure of Merit for Evaluating Stability of Perovskite Solar Cells: Utilizing Long Short-Term Memory Neural Networks14Machine learning for predicting and improving perovskite properties0Simulation and machine learning driven optimization of Rb 2 SnBr 6 -based lead-free perovskite solar cells using diverse ETLs for enhanced photovoltaic performance17Machine learning strategies for small sample size in materials science41Unlocking new horizons, challenges of integrating machine learning to energy conversion and storage research9Machine Learning-Assisted Accelerated Research of Energy Storage Properties of BaTiO3–BiMeO3 Ceramics10Applications of machine learning in surfaces and interfaces30Electricity Driven Behavior and Self-Cleaning Property of Droplets on Superhydrophobic Anti-pollution Flashover Coating3Accelerating ionic liquid research in perovskite solar cells through machine learning:Opportunities and challenges5Machine Learning-Assisted Prediction and Control of Bandgap for Organic–Inorganic Metal Halide Perovskites31Machine Learning Prediction of Organic–Inorganic Halide Perovskite Solar Cell Performance from Optical Properties42Freeze resistant hydroxypropyl cellulose hydrogel with passive radiative cooling performance for thermochromic smart window30A composite photonic structure with periodic array of SiO2 particles for solar cell radiative cooling2Integration of Microstructural Image Data into Machine Learning Models for Advancing High-Performance Perovskite Solar Cell Design28Flux‐Regulated Crystallization of Perovskites Using Machine Learning‐Predicted Solvent Evaporation Rates for X‐Ray Detectors4Predictive modeling of CsFABiCuI6-based PSC with Nd-doped ZnO as ETL using machine learning and numerical simulation7A guided review of machine learning in the design and application for pore nanoarchitectonics of carbon materials85Machine learning screening and DFT calculations for exploring Cs2Ag0.75X0.25BiCl6 (X=Na, K, Rb) double perovskites as underwater photovoltaic materials6Machine Learning-Assisted Analysis of Perovskite Solar Cell Long-Term Stability under Multiple Environmental Factors18Accelerating the Discovery of Efficient Phosphorescent Iridium(III) Complex Emitters with Targeted Color Gamuts Through Interpretable Machine Learning Models and Virtual Screening2Unlocking a self-driving research workflow for perovskite photovoltaics12Machine learning perspective: Revealing deep mechanisms and new advances in adsorption and catalysis of gaseous molecules18Multi-Model Deep Learning Framework for Defect Detection in Mixed-Dimensionality FAPbI₃ Perovskite Films0Integration of Geoscientific Data Mining and GBM Hyperparameter Optimization to Improve the Accuracy of Landslide Hazard Prediction1Prediction of ABX3 Perovskite Formation Energy Using Machine Learning3Unraveling the thermodynamic origins and kinetic pathways of intermediate phase engineering in perovskite solar cells11Accelerated Multi‐Property Screening of Lead‐Free Halide Double Perovskite via Transfer Learning13Machine learning aided optoelectric characterization modelling and prediction of the IV parameters of perovskite solar cells with > 90% accuracy4Machine Learning‐Driven Perovskite Research from Experimental Exploration to Industrial Development6Machine learning in X-ray diffraction for materials discovery and characterization19Thermodynamic stability prediction of organic–inorganic hybrid perovskites using machine learning2Data-Driven Optimization and Mechanical Assessment of Perovskite Solar Cells via Stacking Ensemble and SHAP Interpretability5Enhanced optoelectronic behavior of eco-friendly Cs2BiCuI6 double perovskite solar cells via terbium-doped FTO and graphene oxide interface engineering3Multiscale Coupling Between Macroscopic Mechanics and Atomic Assembly (MM–AA) of Soft‐Lattice Halide Perovskites6An innovative machine learning based approach for predicting the efficiency of a chalcogenide perovskite semiconductor photovoltaic cell4From Data‐Driven to Intelligence‐Driven: Innovating Research Paradigms of Perovskite Solar Cells4Investigations and optimizations of lead-free CsGeI 2 Br perovskite solar cell using numerical simulations and machine learning4Machine Learning for Accelerating Energy Materials Discovery: Bridging Quantum Accuracy with Computational Efficiency44Accelerated Data‐Driven Discovery of Dual‐Functional Ionic Liquid Passivation for FAPbI 3 Perovskite Solar Cells Using Graph Neural Network4Machine learning facilitates the development of interconnecting layers for perovskite/silicon heterojunction tandem solar cells with proof-of-concept efficiency > 38%0Comparative analysis of machine learning techniques for modeling irradiance-dependent J–V characteristics of perovskite solar cells1Predicting solar cell efficiencies using historical data from a manufacturing process0Inorganic Charge Transport Layers for High‐Performance p‐i‐n Perovskite Solar Cells6Robust Perovskite Solar Cells for Extreme and Emerging Applications8A multi-model deep learning framework for SEM-based defect detection in $\textrm{FAPbI}_3$ Perovskite thin films7Mechanical stability of flexible perovskite solar cells: challenges, strategies, and prospects23Accelerating perovskite solar cell design using machine learning: a comparative study on Pb and Sn compositions0Thermal Management of Perovskite Solar Cells5Ionotronics‐Enabled Emerging Halide Perovskite Optoelectronic Devices10Machine Learning-Assisted Optimization of $\text{Rb}_{2} \text{LiGaI}_{6}$-Based Perovskite Solar Cells: Insights from SCAPS-1D Simulation0Based on machine learning prediction and experimental verification: The optimization of NH3-SCR performance on Ce/Co-modified MnNi catalysts8A Study on Efficiency Prediction of Perovskite Solar Cell Using Random Forest0Multi-axis quality evaluation of data augmentation for perovskite solar cell datasets0Perovskite solar cells towards industrialization: overcoming challenges with data-driven strategies8ResViT-Solar: A Hybrid Residual-Transformer for Photovoltaic Panel Fault and Cleanliness Detection2Strategic engineering of perovskite solar cells: revolutionary developments from interfacial stabilization to copper-based semiconductor innovations1VO2-based dynamic infrared modulation: properties and applications7Machine Learning-Assisted Optimization of Rb2LiGaI6-Based Perovskite Solar Cells: Insights from SCAPS-1D Simulation1Recent advances in data‐driven and artificial intelligence‐integrated perovskite solar cells: From design to self‐driving laboratories7Physics-informed weakly supervised learning for in-situ photoluminescence dynamics analysis in perovskite solar cells0Predicting photovoltaic output parameters of perovskite solar cells using explainable machine learning with physics-informed and simulation-derived descriptors4Machine Learning Accelerated Design of Self-Assembled Monolayers for High-Performance Perovskite Solar Cells5Multiscale computational and machine learning insights into rare-earth-doped front electrode and La2NiMnO6 double perovskite material for photovoltaic applications and proposed fabrication pathways1Machine learning–guided SCAPS-1D design of lead-free CH₃NH₃SnI₃ perovskite solar cells with 40.17% simulated PCE4Efficient Discovery of Lead-Free A 3 BX 6 Halide Perovskites via Machine Learning2Functional Superhydrophobic PDMS Composite Films for Passive Radiative Cooling2Machine Learning Potentials for Inorganic and Hybrid Lead Halide Perovskites: From Phase Stability to Defects and Interfaces2Rapid Parameter Prediction in Perovskite Solar Cells via AI-Assisted Performance Analysis1Machine Learning for Designing Perovskites and Perovskite‐Inspired Solar Materials: Emerging Opportunities and Challenges7Solution-Processed Perovskite/Polymer Nanocomposites for Advanced Optoelectronic Devices0Recent Progress in CH 3 NH 3 PbX 3 (X = Cl, Br, I) Organic–Inorganic Hybrid Perovskite Optoelectronic Devices2Mechanical stability in flexible perovskite solar cells: Interface engineering and device design6Bioinspired Strain-Engineered Perovskite–Organic Tandem Solar Cells: Advances in Organic Semiconductors for Wearable Photovoltaics2Hole transporting materials in inverted flexible perovskite solar cells: Challenges, progress, and perspectives2From record efficiency to commercially viable modules: A commercialization framework for stability-driven translation of perovskite solar cells1A weighted ensemble model for screening passivation materials in high-efficiency perovskite solar cells0Machine Learning for Superconductor Discovery: From Data-Driven Insights to Accelerated Design1

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