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RESEARCH PAPER · iScience · 2021

Machine learning-accelerated prediction of overpotential of oxygen evolution reaction of single-atom catalysts

Lianping Wu, Tian Guo, Teng Li

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Machine learning-accelerated prediction of overpotential of oxygen evolution reaction of single-atom catalystsOriginalApplying Machine Learning to Rechargeable Batteries: From the Microscale to the Macroscale166Applying Machine Learning to Rechargeable Batteries: From the Microscale to the Macroscale56In Silico Design of Covalent Organic Framework-Based Electrocatalysts73Graphene‐Supported Atomically Dispersed Metals as Bifunctional Catalysts for Next‐Generation Batteries Based on Conversion Reactions212Analysis and modeling of high-performance polymer electrolyte membrane electrolyzers by machine learning56Electronic structure engineering for electrochemical water oxidation151Machine learning for design principles for single atom catalysts towards electrochemical reactions116Machine Learning Utilized for the Development of Proton Exchange Membrane Electrolyzers51Toward Excellence of Electrocatalyst Design by Emerging Descriptor‐Oriented Machine Learning127Tuning the Polarity of a Fibrous Poly(vinylidene fluoride-co-hexafluoropropylene)-Based Support for Efficient Water Electrolysis8A review on the electrocatalytic dissociation of water over stainless steel: Hydrogen and oxygen evolution reactions80Prediction of Oxygen Evolution Activity for NiCoFe Oxide Catalysts via Machine Learning31Data‐Driven High‐Throughput Rational Design of Double‐Atom Catalysts for Oxygen Evolution and Reduction115Inferring potential landscapes from noisy trajectories of particles within an optical feedback trap7Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery552A Synthesis Strategy of Double-Atom Catalysts on a Carbon Surface5Using Machine Learning to Predict Oxygen Evolution Activity for Transition Metal Hydroxide Electrocatalysts39Computational Approaches to Alkaline Anion-Exchange Membranes for Fuel Cell Applications17Machine Learning Captures Synthetic Intuitions for Hollow Nanostructures4Optimal design and flow-field pattern selection of proton exchange membrane electrolyzers using artificial intelligence60Rational design of carbon-supported single and dual atom catalysts for bifunctional oxygen electrocatalysis19Bilayer MN4-O-MN4 by bridge-bonded oxygen ligands: Machine learning to accelerate the design of bifunctional electrocatalysts42Advanced zeolite and ordered mesoporous silica-based catalysts for the conversion of CO 2 to chemicals and fuels379Machine learning enabled rational design of atomic catalysts for electrochemical reactions19The Defect Chemistry Study of Single Transition-Metal Atoms Anchored on Ptse2 Monolayer for the Rational Design of Bifunctional Oer/Orr Electrocatalysts0Understanding the hydrogen evolution reaction activity of doped single-atom catalysts on two-dimensional GaPS4 by DFT and machine learning93Review of Carbon Support Coordination Environments for Single Metal Atom Electrocatalysts (SACS)373M-N 4 -Gr/MXene Heterojunction Nanosheets as Oxygen Reduction and Evolution Reaction Catalysts: Machine Learning and Density Functional Theory Insights52Data mining from a hierarchical dataset for mechanical metamaterials composed of curved-sides triangles10A Surrogate Machine Learning Model for the Design of Single-Atom Catalyst on Carbon and Porphyrin Supports towards Electrochemistry56Can Artificial Intelligence Boost Developing Electrocatalysts for Efficient Water Splitting to Produce Green Hydrogen?12State-of-the-art single-atom catalysts in electrocatalysis: From fundamentals to applications103Single Pd-doped arsenene coordinated with nitrogen atoms as an electrocatalyst for effective chlorine evolution reaction: DFT and machine learning studies5Intrinsic and external active sites of single-atom catalysts13Artificial Photosynthesis: Current Advancements and Future Prospects68Prefactibilidad tecno-económica para la producción de etanol a partir de la electroreducción de CO20Metal-Doped C 3 B Monolayer as the Promising Electrocatalyst for Hydrogen/Oxygen Evolution Reaction: A Combined Density Functional Theory and Machine Learning Study37Machine-Learning-Accelerated Screening of Double-Atom/Cluster Electrocatalysts for the Oxygen Reduction Reaction27WCx-Supported RuNi Single Atoms for Electrocatalytic Oxygen Evolution4Machine Learning-Assisted Low-Dimensional Electrocatalysts Design for Hydrogen Evolution Reaction207Single‐Atom Heterogeneous Catalysts: Human‐ and AI‐Driven Platform for Augmented Designs, Analytics and Reality‐Enabled Manufacturing22Single‐Atom Heterogeneous Catalysts: Human‐ and AI‐Driven Platform for Augmented Designs, Analytics and Reality‐Enabled Manufacturing1Active learning guides discovery of a champion four-metal perovskite oxide for oxygen evolution electrocatalysis161Predicting the Stability of Single-Atom Catalysts in Electrochemical Reactions161Intelligent design and synthesis of energy catalytic materials25Complimentary Computational Cues for Water Electrocatalysis: A DFT and ML Perspective76Unraveling the effect of single atom catalysts on the charging behavior of nonaqueous Mg–CO 2 batteries: a combined density functional theory and machine learning approach20Active site switching on high entropy phosphides as bifunctional oxygen electrocatalysts for rechargeable/robust Zn–air battery111Computational chemistry for water-splitting electrocatalysis239Machine Learning Prediction of Oer Activity for Pnma Perovskite Via Minimal Structure Relaxation1Rational design of single transition-metal atoms anchored on a PtSe 2 monolayer as bifunctional OER/ORR electrocatalysts: a defect chemistry and machine learning study62Unlocking the potential: machine learning applications in electrocatalyst design for electrochemical hydrogen energy transformation239Machine Learning Guides the Discovery of High-Performance HEA Catalysts1From Single Metals to High‐Entropy Alloys: How Machine Learning Accelerates the Development of Metal Electrocatalysts69Machine-Learning-Assisted Descriptors Identification for Indoor Formaldehyde Oxidation Catalysts36Recent Advancements in Scalable Hydrogen Generation: An Integrated Approach of Experiments, Computation, and Machine Learning1A review of advancements in theoretical simulation of oxygen reduction reaction and oxygen evolution reaction single-atom catalysts10Recent advances in the development of single atom catalysts for oxygen evolution reaction72Insights into the Single Atom and Support Interaction in Electrocatalytic Oxygen Evolution Reaction6Structure–Activity Relationships in Oxygen Electrocatalysis103Using Machine Learning to Forecast the Conductive Substrate-Supported Heteroatom-Doped Metal Compound Electrocatalysts for Hydrogen Evolution Reaction5Precise Synthesis of Single‐Atom Catalysts for Boosting Next‐Generation Advanced Oxidation and Reduction Processes in Sustainable Energy Applications17Machine learning applications on proton exchange membrane water electrolyzers: A component-level overview14A review on research progress of double perovskite oxides for oxygen evolution reaction electrocatalysts and supercapacitors46Enhancing Export Competitiveness of SMEs in Sfax: A Machine Learning Approach Using Principal Component Analysis0Strategies for enhancing catalytic performance of single-atom catalysts in 2e- oxygen reduction reaction: A review9Study of the growth kinetic effects of graphene in copper catalysts0Accelerating the green hydrogen revolution: The synergy of PEMWE and AI10Expanding the frontiers of electrocatalysis: advanced theoretical methods for water splitting77Machine Learning-Assisted High-Throughput Screening for Electrocatalytic Hydrogen Evolution Reaction33Theoretical insights into performance descriptors and their impact on activity optimization strategies for cobalt-based electrocatalysts44The Future of Catalysis: Applying Graph Neural Networks for Intelligent Catalyst Design28Unlocking CO2 conversion potential with single atom catalysts and machine learning in energy application24Parametric Optimization of Transition Metal-Based Nanocomposite Electrocatalysts for Oxygen Evolution Reaction in Alkaline Media4SPOCK Tool for Constructing Empirical Volcano Diagrams from Catalytic Data5TM-N4-Gra/XS2 (X= Mo, Sn, W) heterojunction catalysts for oxygen reduction reaction and oxygen evolution reaction: Density function theory and machine learning insights7Single Atom Engineering for Electrocatalysis: Fundamentals and Applications68Identifying Adsorption States of OER Intermediates on Single-Atom Catalysts via a Spectral Machine Learning Framework12Pathways to Low-Iridium Loading in Proton Exchange Membrane Water Electrolyzer Anodes: From Catalyst Design to Catalyst Layer Integration24High-Efficiency Catalyst Screening Driven by Machine Learning for the Oxidation of 5-Hydroxymethylfurfural to 2, 5-Furandicarboxylic Acid5Prospects of AI in advancing green hydrogen production: From materials to applications9Bridging Laboratory Catalysts with Industrial Proton Exchange Membrane Water Electrolyzers31Recent development and challenges in TMD-based 2D materials towards OER/ORR electrocatalysis6AI-Accelerated Discovery of Electrocatalyst Materials26Accelerated discovery of OER catalysts in Pnma perovskites via machine learning with minimal DFT structure relaxation5Industrial robust 2D multimetallic high-entropy oxides for water splitting1Data-driven optimisation of more sustainable high-to-medium entropy Perovskites for oxygen evolution catalysts0Designing single-atom catalysts: bridging metal–support interaction and adsorption energy optimization27Electrocatalytic hydrogen generation from seawater: advances, opportunities, challenges and future roadmap8Nanostructured high-entropy oxides for catalysis: linking entropy to function21Site surgery in single atom catalysis: machine learning assisted precise regulation of coordination environment and decoding of structure-activity relationships4Commercialization path of data-driven green catalytic technology: the application of machine learning in technology lifecycle management5From density functional theory to machine learning: Emerging paradigms in energy materials discovery8Design, characterization, and dynamic behavior of atomically dispersed Pt catalysts for water splitting and oxygen reduction: From experimental insights to machine-learning-assisted analysis3Machine learning-guided design of energy-related catalysts from nanoparticles to single-atom sites7Machine learning assisted directed conversion of waste plastics into high-performance single-atom catalysts: Progress, challenges and future opportunities0Crystallographic insights into LDH-based electrocatalysts for efficient oxygen evolution reaction3Tailoring single-atom catalysts for proton-exchange-membrane water electrolysis: From descriptors and design to optimization4Combining DFT calculations and machine learning for rational design of hydrogen electrocatalysts2Artificial intelligence–driven decoupling structure–activity relationship for lithium‐ion batteries0Rational Design and Multi-Scale Engineering of Iridium-Based Catalysts for Acidic Oxygen Evolution: From Atomic-Level Insights to Industrialization2From Data to Discovery: Crafting Data‐Driven Frameworks for Advancing OER Electrocatalysts0New Frontiers in Single-Atom Catalysis: Active-Site Dynamics and AI-Enabled Design12D semiconductors at the energy nexus: A comprehensive view of conversion and storage technologies0Biomass-derived carbon electrocatalysts for zinc-air Batteries: A review of design strategies, machine learning acceleration, and future perspectives0

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