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RESEARCH PAPER · Journal of Materials Chemistry A · 2023

Data-driven design of electrocatalysts: principle, progress, and perspective

Shan Zhu, Kezhu Jiang, Biao Chen, Shijian Zheng

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Data-driven design of electrocatalysts: principle, progress, and perspectiveOriginalEfficiently predicting and synthesizing intrinsic highly fire-safe polycarbonates with processability10Interfacial engineering of transition metal dichalcogenide/carbon heterostructures for electrochemical energy applications135Recent Advances in Multifunctional Reticular Framework Nanoparticles: A Paradigm Shift in Materials Science Road to a Structured Future47Metal-based electrocatalysts with data-driven designed particle size for hydrogen evolution5Navigating the unknown with AI: multiobjective Bayesian optimization of non-noble acidic OER catalysts59Accelerating materials research with a comprehensive data management tool: a case study on an electrochemical laboratory13Efficient design and synthesis of an amorphous conjugated polymer network for a metal-free electrocatalyst of hydrogen evolution reaction16Machine Learning Assisted Prediction of the Mass Activity of Platinum-Based Anode Catalysts Supported on a Variety of Carbon Nanostructures for Direct Methanol Fuel Cells0The Efficient and Directional Electrocatalytic Depolymerization of Α-O-4 Bond in Lgnin by Auxiliary Electrolyte0Decoding intrinsic features of carbons from their capacitive performance5Computational Modeling of CO 2 Reduction and Conversion via Heterogeneous and Homogeneous Catalysis1CatEmbed: A Machine-Learned Representation Obtained via Categorical Entity Embedding for Predicting Adsorption and Reaction Energies on Bimetallic Alloy Surfaces3The efficient and directional electrocatalytic depolymerization of α-O-4 bond in lignin by auxiliary electrolyte8Study on the efficient electrocatalytic depolymerization of α-O-4 bond in lignin assisted by simple electrolyte4Routes to Bidirectional Cathodes for Reversible Aprotic Alkali Metal–CO 2 Batteries44Recent Advances in Salt‐Template Assisted Synthesis of 3D Porous Carbon Materials for Electrochemical Energy Storage19Advanced hard carbon materials for practical applications of sodium-ion batteries developed by combined experimental, computational, and data analysis approaches80Spherical Ru/FeOx composite as a bifunctional electrocatalyst for overall water splitting in neutral media5Forecasting the Mass Activity of Platinum Anode Catalysts on Various Carbon Nanostructures in Direct Methanol Fuel Cells Using Machine Learning1A brief overview of deep generative models and how they can be used to discover new electrode materials8Insights into infrared crystal phase characteristics based on deep learning holography with attention residual network37Machine learning in electrocatalysis–Living up to the hype?7Machine-Learning-Enabled Quantification of Metal-Based Nanoparticle Sizes Using Linear Sweep Voltammetry5A Machine Learning Approach for Prediction of Faradaic Efficiency in Electrochemical CO2 Reduction on Nitrogen‐Doped Carbon4Rational Design of Carbon‐Based Electrocatalysts for H 2 O 2 Production by Machine Learning and Structural Engineering26Guided electrocatalyst design through in-situ techniques and data mining approaches8Data-driven design of metal oxide electrocatalysts with low tafel slope in oxygen evolution reaction12MOF-templated synthesis of Co4S3-Co9S8 heterojunctions embedded in N-doped carbon for enhanced hydrogen evolution1AI-Enhanced Electrochemical Sensing Systems: A Paradigm Shift for Intelligent Food Safety Monitoring50AI-Accelerated Discovery of Electrocatalyst Materials26Convergence of Computational Materials Science and AI for Next-Generation Energy Storage Materials6AILD: An Interpretable AI Framework for Designing Logical Descriptors in Predicting CO Adsorption on Catalysts0Predicting the HER activity of SACs on MXenes with simple features and interpretable machine learning models9Multi-staged machine learning-driven investigation of biomass-derived hard carbon anodes for sodium-ion batteries: Connecting precursor, structure, and performance19Bubble evolution dynamics and interfacial management strategies for high-flux water electrolysis: a review1Machine learning-driven high-throughput screening of electrocatalysts and electrolytes for electrochemical surfaces and interfaces5Methodological Frameworks for Computational Electrocatalysis: From Theory to Practice8Discerning the underlying trends in electrocatalytic hydrogen evolution activity of MOF/MOF-derived materials using data-driven approach4Design, characterization, and dynamic behavior of atomically dispersed Pt catalysts for water splitting and oxygen reduction: From experimental insights to machine-learning-assisted analysis3Machine Learning and Domain Adaptation for Material Generalization in Electrocatalyst Evaluation: A Comprehensive Review2Explainable AI in Electrocatalysis and Photocatalysis: From Catalyst Design to Mechanistic Insights7Recent Development in Boride‐Based Electrodes and Their Water‐Splitting Potential by Electrocatalysts0Reaction kinetics in electrochemical precision synthesis of high-value-added chemicals: from mechanisms to tuning strategies0Crystallographic insights into tetrahedral coordination for advanced electrocatalysis0Machine Learning‐Driven Rational Design of Organic Electro‐Oxidation Catalysts: A Mechanism‐Embedded Approach to Selectivity Engineering0Data-driven framework with interpretable machine learning of sputter-deposited electrocatalysts for hydrogen evolution reaction in alkaline water electrolysis and anion exchange membrane water electrolysis0

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