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RESEARCH PAPER · Advanced Energy Materials · 2023

Optimizing Perovskite Thin‐Film Parameter Spaces with Machine Learning‐Guided Robotic Platform for High‐Performance Perovskite Solar Cells

Jiyun Zhang, Bowen Liu, Ziyi Liu, Jianchang Wu, Simon Arnold, Hongyang Shi, Tobias Osterrieder, Jens Hauch, Zhenni Wu, Junsheng Luo, Jerrit Wagner, Christian G. Berger, Tobias Stubhan, Frederik Schmitt, Kaicheng Zhang, Mykhailo Sytnyk, Thomas Heumueller, Carolin M. Sutter‐Fella, Ian Marius Peters, Yicheng Zhao, Christoph Josef Brabec

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Optimizing Perovskite Thin‐Film Parameter Spaces with Machine Learning‐Guided Robotic Platform for High‐Performance Perovskite Solar CellsOriginalEmpowering research in chemistry and materials science through intelligent algorithms15Machine Learning-Based Prediction and Influencing Factors on the Performance of Perovskite Solar Cells1Precise control of process parameters for >23% efficiency perovskite solar cells in ambient air using an automated device acceleration platform42Accelerating Photostability Evaluation of Perovskite Films through Intelligent Spectral Learning-Based Early Diagnosis20Materials genome engineering accelerates the research and development of organic and perovskite photovoltaics64Machine Learning Approach for Predicting the Hole Mobility of the Perovskite Solar Cells8Wide‐Gap Perovskites for Indoor Photovoltaics23Toward Self-Driven Autonomous Material and Device Acceleration Platforms (AMADAP) for Emerging Photovoltaics Technologies54Optimizing the performance of vapor-deposited perovskite solar cells through advanced predictive modeling21Exploring the influence of crystallization fouling on microscale heat exchangers through machine learning analysis12Temporal Decoupling-Based Machine Learning Framework for Precise Efficiency Prediction in Perovskite Solar Cells2Machine learning driven performance for hole transport layer free carbon-based perovskite solar cells32Construction frontier molecular orbital prediction model with transfer learning for organic materials36Digital manufacturing of perovskite materials and solar cells12Repeatable Perovskite Solar Cells through Fully Automated Spin-Coating and Quenching21A comprehensive review of machine learning applications in perovskite solar cells: Materials discovery, device performance, process optimization and systems integration41Enhancing Durability of Organic–Inorganic Hybrid Perovskite Solar Cells in High‐Temperature Environments: Exploring Thermal Stability, Molecular Structures, and AI Applications18Bayesian optimization and prediction of the durability of triple-halide perovskite thin films under light and heat stressors17Self-driving AMADAP laboratory: Accelerating the discovery and optimization of emerging perovskite photovoltaics16Inverse design workflow discovers hole-transport materials tailored for perovskite solar cells183Accelerating the design and manufacturing of perovskite solar cells using a one-shot automated machine learning framework10Accelerating optimization of halide perovskites: two blueprints for automation2An AI-accelerated pathway for reproducible and stable halide perovskites17Deep learning for augmented process monitoring of scalable perovskite thin-film fabrication36Machine learning for predicting and improving perovskite properties0Mass-customization of organic photovoltaics and data production for machine learning models precisely predicting device behavior8Performance optimization of perovskite solar cells with an automated spin coating system and artificial intelligence technologies17Autonomous Optimization of Air‐Processed Perovskite Solar Cell in a Multidimensional Parameter Space23Perovskite solar cells304Recent Advances in 3D Printed Electrodes – Bridging the Nano to Mesoscale47Effect of precursor concentration and annealing temperature on the optical properties of Cs2AgBiBr6 perovskite thin film1Advancing perovskite photovoltaic technology through machine learning‐driven automation49Machine Learning Prediction of Organic–Inorganic Halide Perovskite Solar Cell Performance from Optical Properties42Enhanced Efficiency of CZTS Solar Cells with Reduced Graphene Oxide and Titanium Dioxide Layers: A SCAPS Simulation Study9Preparation of sulfur group compounds and perovskite quantum dot films and optimization strategies for efficient light utilization: Recent advances and perspectives7Solar‐to‐Hydrogen Conversion Efficiency for Photovoltaic Water Electrolysis to Produce Green Hydrogen37Fabrication of SERS Substrates Using Silver-Coated Gold Nanostars for Chemical Sensing: A Multiobjective Bayesian Optimization Approach8Unlocking a self-driving research workflow for perovskite photovoltaics12A full-process artificial intelligence framework for perovskite solar cells6Feature Selection for Machine Learning‐Driven Accelerated Discovery and Optimization in Emerging Photovoltaics: A Review9Towards Machine-Learning Enabled Automated Analysis of Heterogeneous Nanomaterials1The Necessity of Dynamic Workflow Managers for Advancing Self‐Driving Labs and Optimizers6Prediction and Fine Screening of Small Molecular Passivation Materials for High‐Efficiency Perovskite Solar Cells Via an Enhanced Machine Learning Workflow9Explainable Artificial Intelligence Driven Methodology for Accelerated Research of Complex Systems: Case Study of Thin‐Film Photovoltaic Kesterite‐Based Technology7Optimizing the efficiency of perovskite solar cells for improved performance and energy conversion using temporal dynamic graph neural network2Machine-Learning-Driven in-Device Optimization of All-Printed Perovskite Solar Cells8Fine-Tuning Donor Material Deposition with Ultrasonic Aerosol Jet Printing to Balance Efficiency and Stability in Inverted Organic Photovoltaic Devices5Advancements in AgBiS2 thin film solar cells: strategies, challenges, and perspectives6Low-toxicity solvent processing in ambient air for perovskite solar cells via two-step Bayesian machine learning12Machine Learning‐Driven Perovskite Research from Experimental Exploration to Industrial Development6Digital Twin for Chemical Science: a case study on water interactions on the Ag(111) surface13Machine learning in X-ray diffraction for materials discovery and characterization19Prospects of AI in advancing green hydrogen production: From materials to applications9Advancement of technology towards developing perovskite-based solar cells for renewable energy harvesting and energy transformation applications30Process Parameter Specification and Control in Solution Processing of Hybrid Perovskite Photovoltaics: From Domain‐Specific Jargon to Evidence‐Based, Unambiguous Description of Experimental Workflows4Enhancing RbSnBr3 perovskite solar cells performances: machine learning-driven optimization of active layers and electron transport materials using SCAPS-1D4Solution ALD of (CH 3 NH 3 )(PbI 3 ) Perovskite Thin Films Yields Functional Quality and Stability Superior to Classical Processing2Algorithm-Guided Experimentation for Optimization of High-Performance Perovskite Solar Cells3AI‐Assisted Design of Advanced Polymeric Materials: Challenges and Solutions25Hybrid Learning Enables Reproducible >24% Efficiency in Autonomously Fabricated Perovskites Solar Cells7Spatial‐Uniformity–Driven Bayesian Optimization for Rapid Development of Printed Perovskite Solar Cells1Automation of the Antisolvent Method via an Automated Spin‐Coating System and the Effects of Reduced Surface Roughness and Depth Distribution of Residual PbI 2 on Reproducibility1Thermal Management of Perovskite Solar Cells5Lösungs‐ALD von (CH 3 NH 3 )(PbI 3 )‐Perowskit‐Dünnfilmen liefert der klassischen Verarbeitung überlegene funktionale Qualität und Stabilität0Data‐Driven Design of Scalable Perovskite Film Fabrication via Machine Learning–Guided Processing3A review of lead leakage monitoring in perovskite solar cells: emerging detection technologies, just transition to clean energy and perspectives5Advancements and challenges of self-assembled monolayers as buried interfaces in inverted perovskite solar cells: from molecular design to automation-enabled data-driven optimization1Machine-learning prediction accelerates the discovery of phase-stable formamidinium-based perovskites0Manufacture of metal halide perovskite devices by thermal evaporation: fundamentals, progress and prospects0Physics-interpreted closed-loop optimization and interpretable process insight in perovskite photovoltaics0Qubots: open-source modular laboratory robots as building blocks for flexible assembly of self-driving labs0Supramolecular hosts for high-performance and sustainable perovskite optoelectronics7Disentangling Environmental Effects on Perovskite Solar Cell Performance via Interpretable Machine Learning8Organic–Inorganic Metal Halide Perovskites: Toward Stability, Chirality, and AI-Guided Discovery1Research progress on the application of machine learning in perovskite solar cells0Accelerated Emergence of Self-Driving Laboratories for Accelerating Materials Discovery1Recent advances in data‐driven and artificial intelligence‐integrated perovskite solar cells: From design to self‐driving laboratories7Boosting the efficiency of Cs2BiAgI6 perovskite solar cells: Device modeling and machine learning prediction3Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories1Recent Advances in Artificial Intelligence in Organic Electronic Research1Accelerating Perovskite Solar Cell Development Through High‐Throughput Technologies: Computational Simulation, Automated Experimentation, and Intelligent Integration0A Self‐Driving Lab for Solution‐Processed Electrochromic Thin Films0In Situ Contact Angle Measurement for Autonomous Spin Coating in Self‐Driving Labs0Innovations in functional layers of flexible perovskite solar cells: Progress toward efficient and commercially viable photovoltaics1Surface Modification of Perovskite Solar Cells Using Organic Dyes for Enhanced Efficiency and Moisture Stability0Red, White & Blue: Identifying Recombination Loss Mechanisms in Perovskite Solar Cells0Ink Design for Printing Perovskite Solar Cells and Modules0Robot-Assisted Study of a Near-Infrared Dye in Perovskite Solar Cells0Towards system-level artificial intelligence in perovskite photovoltaics0

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