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RESEARCH PAPER · Nature Reviews Materials · 2022

Machine learning for a sustainable energy future

Zhenpeng Yao, Yanwei Lum, Andrew K. Johnston, L.M. Mejía-Mendoza, Xin Zhou, Yonggang Wen, Alán Aspuru‐Guzik, Edward Hartley Sargent, Zhi Wei Seh

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Machine learning for a sustainable energy futureOriginalHow machine learning can accelerate electrocatalysis discovery and optimization125A Review on Data-Driven Security Assessment of Power Systems: Trends and Applications of Artificial Intelligence51Machine learning-inspired battery material innovation49Which molecular properties determine the impact sensitivity of an explosive? A machine learning quantitative investigation of nitroaromatic explosives34Next-generation intelligent laboratories for materials design and manufacturing25Data-Driven Battery Aging Mechanism Analysis and Degradation Pathway Prediction22Reshaping the material research paradigm of electrochemical energy storage and conversion by machine learning34Predicting Chronic Kidney Disease Using Machine Learning Algorithms70Prediction of concrete compressive strength employing machine learning techniques19A Survey on Large Language Models: Applications, Challenges, Limitations, and Practical Usage370Large Language Models: A Comprehensive Survey of its Applications, Challenges, Limitations, and Future Prospects83Large Language Models: A Comprehensive Survey of its Applications, Challenges, Limitations, and Future Prospects44Health monitoring by optical fiber sensing technology for rechargeable batteries83Ultrahigh‐Speed Aqueous Copper Electrodes Stabilized by Phosphorylated Interphase23Discovery of Unconventional Proton‐Conducting Inorganic Solids via Defect‐Chemistry‐Trained, Interpretable Machine Learning31Ni-rich layered cathodes for lithium-ion batteries: From challenges to the future243Artificial intelligence-driven rechargeable batteries in multiple fields of development and application towards energy storage34Large Language Models: A Comprehensive Survey of its Applications, Challenges, Limitations, and Future Prospects53Modeling Single‐Atom Catalysis86Accordion-like Co-MOF derived heterostructured Co/CoP@PNC as highly efficient electrocatalyst for alkaline hydrogen evolution reaction25Machine Learning: Models, Challenges, and Research Directions87Machine Learning-Assisted Low-Dimensional Electrocatalysts Design for Hydrogen Evolution Reaction207Application of Digital Methods in Polymer Science and Engineering28Anion optimization for bifunctional surface passivation in perovskite solar cells175Prediction modeling using deep learning for the classification of grape-type dried fruits30Hierarchical FeS2 cathode with suppressed shuttle effect for high performance magnesium-ion batteries74Smart Dope: A Self‐Driving Fluidic Lab for Accelerated Development of Doped Perovskite Quantum Dots47Large Language Models: A Comprehensive Survey of its Applications, Challenges, Limitations, and Future Prospects103Machine learning in metal-ion battery research: Advancing material prediction, characterization, and status evaluation49Explainable AI for Material Property Prediction Based on Energy Cloud: A Shapley-Driven Approach38Artificial intelligence for the understanding of electrolyte chemistry and electrode interface in lithium battery20Accelerated chemical science with AI86Autonomous nanomanufacturing of lead-free metal halide perovskite nanocrystals using a self-driving fluidic lab29Navigating the unknown with AI: multiobjective Bayesian optimization of non-noble acidic OER catalysts59Artificial Intelligence for Management of Variable Renewable Energy Systems: A Review of Current Status and Future Directions103Advancing next-generation proton-exchange membrane fuel cell development in multi-physics transfer204The developments, challenges, and prospects of solid-state Li-Se batteries30A Fast Forward Prediction Framework for Energy Materials Design Based on Machine Learning Methods25Advanced Functional Optical Fiber Sensors for Smart Battery Monitoring35Advancements in nanomaterials for nanosensors: a comprehensive review334Advancing State of Charge Management in Electric Vehicles With Machine Learning: A Technological Review104AI and ML for selecting viable electrocatalysts: progress and perspectives51Artificial Intelligence and machine learning in renewable and sustainable energy strategies: a critical review and future perspectives24Computational chemistry for water-splitting electrocatalysis239Enhancing the performance of platinum group metal-based electrocatalysts through nonmetallic element doping29Heterogeneous catalysis for the environment92Sapiential battery systems: beyond traditional electrochemical energy81Unlocking the potential: machine learning applications in electrocatalyst design for electrochemical hydrogen energy transformation239Toward Next-Generation Heterogeneous Catalysts: Empowering Surface Reactivity Prediction with Machine Learning24Roadmap to Human–Machine Interaction through Triboelectric Nanogenerator and Machine Learning Convergence31Sustainable moisture energy184Artificial intelligence-based methods for renewable power system operation142Advancement in Supercapacitors for IoT Applications by Using Machine Learning: Current Trends and Future Technology53Insights into Nano- and Micro-Structured Scaffolds for Advanced Electrochemical Energy Storage54Recent advances of polyoxometalate-based materials applied for electron-related devices53Development of Polymethine Dyes for NIR‐II Fluorescence Imaging and Therapy46Harnessing a Better Future: Exploring AI and ML Applications in Renewable Energy25Nature-inspired interfacial engineering for energy harvesting139Recent progress, challenges and prospects of electrolytes for fluoride-ion batteries59Indium Nitride Nanowires: Low Redox Potential Anodes for Lithium‐Ion Batteries20Heterojunction structure of cobalt sulfide cathodes for high-performance magnesium-ion batteries70A mini review on the applications of artificial intelligence (AI) in surface chemistry and catalysis27Attention towards chemistry agnostic and explainable battery lifetime prediction24An artificial intelligence study on energy, exergy, and environmental aspects of upcycling face mask waste to a hydrogen-rich syngas through a thermal conversion process45Interpretable machine learning prediction for li-ion battery's state of health based on electrochemical impedance spectroscopy and temporal features53Machine learning in energy storage material discovery and performance prediction77Integral 2D/3D structured CoSnO3@MXene/NF as a highly active and stable bifunctional electrocatalyst for alkaline water splitting22Renewable energy role in low-carbon economy and net-zero goal: Perspectives and prospects47Recent advances in fabricating high-performance triboelectric nanogenerators via modulating surface charge density31Solar–Hydrogen Storage System: Architecture and Integration Design of University Energy Management Systems26Shaping Sustainable Futures: Public Policies and Renewable Energy Insights Based on Global Bibliometric Analysis23New Engineering Science Insights into the Electrode Materials Pairing of Electrochemical Energy Storage Devices20Digital twin-driven architecture for AIoT-based energy service provision and optimal energy trading between smart nanogrids35Single Atom Catalysts Based on Earth-Abundant Metals for Energy-Related Applications311Non-destructive characterization techniques for battery performance and life-cycle assessment93Machine Learning in Lithium-Ion Battery: Applications, Challenges, and Future Trends56Aided design and molecular regulatory mechanism of non-fused ring acceptors in the framework of A-D1-D2-A molecular systems27Direct operational data-driven workflow for dynamic voltage prediction of commercial alkaline water electrolyzers based on artificial neural network (ANN)26Engineering a Sustainable Future: Harnessing Automation, Robotics, and Artificial Intelligence with Self-Driving Laboratories42Self-Driving Laboratories for Chemistry and Materials Science674Integrative CFD and AI/ML-based modeling for enhanced alkaline water electrolysis cell performance for hydrogen production32Catalysis in the digital age: Unlocking the power of data with machine learning75Deep learning-enabled integration of renewable energy sources through photovoltaics in buildings60Plasma‐Induced Oxygen Defect Engineering in Perovskite Oxide for Boosting Oxygen Evolution Reaction42The Design of Transition Metal Sulfide Cathodes for High-Performance Magnesium-Ion Batteries59Comprehensive review of advances in machine-learning-driven optimization and characterization of perovskite materials for photovoltaic devices37An affordable platform for automated synthesis and electrochemical characterization23Differentiable modeling and optimization of non-aqueous Li-based battery electrolyte solutions using geometric deep learning40Advanced porous MOF materials and technologies for high-efficiency ppm-level toxic gas separation32Enhancing Power Conversion Efficiency of Perovskite Solar Cells Through Machine Learning Guided Experimental Strategies26Forecasting global sustainable energy from renewable sources using random forest algorithm82Generative diffusion model for surface structure discovery29The Effects of Artificial Intelligence on the Fashion Industry—Opportunities and Challenges for Sustainable Transformation31A comprehensive understanding on the anionic redox chemistry of high-voltage cathode materials for high-energy-density lithium-ion batteries115A mechanism review of metal phthalocyanines as single-atomic catalysts in electrochemical energy conversion31A review of machine learning applications in polymer composites: advancements, challenges, and future prospects135Enabling high-performance multivalent metal-ion batteries: current advances and future prospects146Integrating artificial intelligence in energy transition: A comprehensive review248Modern organic transformations: heterogeneous thermocatalysis or photocatalysis?62Molecular representation learning: cross-domain foundations and future Frontiers27Rapid synthesis of metastable materials for electrocatalysis46Solar Energy Forecasting Using Machine Learning Techniques for Enhanced Grid Stability39Predicting thermodynamic stability of inorganic compounds using ensemble machine learning based on electron configuration36Approximate homomorphic encryption based privacy-preserving machine learning: a survey61Battery lifetime prediction across diverse ageing conditions with inter-cell deep learning140Advancements and future outlook of Artificial Intelligence in energy and climate change modeling76Exploring big data applications in sustainable urban infrastructure: A review34Molecular Engineering of Organic Electrode Materials for Beyond Lithium‐Ion Batteries36Advancing perovskite photovoltaic technology through machine learning‐driven automation49Amorphous/Crystalline Heterostructured Nanomaterials: An Emerging Platform for Electrochemical Energy Storage44Enhancing Robustness and Charge Transfer Kinetics of Sodium-Ion Batteries through Introduction of Anionic Anchoring Separators80Advancing organic photovoltaic cells for a sustainable future: The role of artificial intelligence (AI) and deep learning (DL) in enhancing performance and innovation48The Energy Hunger Paradox of Artificial Intelligence: End of Clean Energy or Magic Wand for Sustainability?28Assessing the impact of artificial intelligence on the transition to renewable energy? Analysis of U.S. states under policy uncertainty20Bioinspired electrocatalysts for water splitting21Bimetallic Organic Framework‐Derived 3D Hierarchical Ni–Cu/MWCNTs as Anode Catalysts for High‐Performance, Durable Direct Urea Fuel Cells20Applications of density functional theory and machine learning in nanomaterials: A review51A review of enhancing wind power with AI: applications, economic implications, and green innovations20Language models for materials discovery and sustainability: Progress, challenges, and opportunities26AI‐Generated Ammonium Ligands for High‐Efficiency and Stable 2D/3D Heterojunction Perovskite Solar Cells32Machine learning applications in energy systems: current trends, challenges, and research directions91Empowering Generalist Material Intelligence with Large Language Models29AI in power systems: a systematic review of key matters of concern30In Situ Light‐Modulation of Capacity and Impedance in Lithium‐Ion Batteries24Carbon Emission Quantification of Machine Learning: A Review23Machine Learning Force Fields in Electrochemistry: From Fundamentals to Applications25Artificial Intelligence‐Driven Approaches in Semiconductor Research44AI‐Driven Defect Engineering for Advanced Thermoelectric Materials37Understanding solid-state battery electrolytes using atomistic modelling and machine learning107Machine learning in photocatalysis: accelerating design, understanding, and environmental applications20Design Strategies, Challenges, and Prospects of Nanomaterials for Aqueous Zn–Iodine Batteries72A comprehensive review on data-level methods for imbalanced data classification32Progressive Learning‐Guided Discovery of Single‐Atom Metal Oxide Catalysts for Acidic Oxygen Evolution Reaction37Hollow structures derived from metal-glycerates toward efficient electrochemical energy storage and conversion25Large language models for batteries31Bio-hydrovoltaic technology: advancing from non-living to living hydrovoltaic systems25Oxygen Spillover: Revolutionizing Catalytic Performance and Disrupting Mechanistic Paradigms in Sustainable Chemistry43Machine learning-assisted Ru-N bond regulation for ammonia synthesis22AI‐Driven Advances in Sustainable Materials for Green Energy: From Innovation to Lifecycle Management3133 Unresolved Questions in Nanoscience and Nanotechnology58Machine learning as a catalyst for PEMFC optimization: A comprehensive review from flow fields to system integration with a multiscale perspective on research and applications29Recent progress in the synthesis, scaling, processing and technoeconomic analysis of metal-organic frameworks towards industrial applications30Prussian blue analogues and their derivatives for electrochemical energy conversion21Uncovering battery electrochemical mechanisms by artificial intelligence22Dynamics in electrochemical organic oxidation reactions from in situ and operando techniques48Overcoming the integration bottleneck: a global review of renewable energy and grid adaptation strategies22Early prediction of lithium-ion battery degradation with a generative pre-trained transformer37Stable acidic oxygen-evolving catalyst discovery through mixed accelerations33AI-driven control and optimization for renewable energy integration in smart grids: Challenges, applications, and future research directions23AI-powered open-source infrastructure for accelerating materials discovery and advanced manufacturing27

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