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RESEARCH PAPER · ACS Catalysis · 2024

From Characterization to Discovery: Artificial Intelligence, Machine Learning and High-Throughput Experiments for Heterogeneous Catalyst Design

Jorge Benavides-Hernández, Franck Dumeignil

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From Characterization to Discovery: Artificial Intelligence, Machine Learning and High-Throughput Experiments for Heterogeneous Catalyst DesignOriginalChemGenX: AI in the Chemistry Classroom2A review of chalcogenide-based perovskites as the next novel materials: Solar cell and optoelectronic applications, catalysis and future perspectives111Machine Learning in 3D and 4D Printing of Polymer Composites: A Review48Advances in Aerosol Nanostructuring: Functions and Control of Next-Generation Particles28A review of machine learning methods for imbalanced data challenges in chemistry70Atomic-level insights for engineering interfacial hydrogen microenvironments of metal-based catalysts for alkaline hydrogen electrocatalysis36Behavior, mechanisms, and applications of low-concentration CO 2 in energy media36Digitalisation of catalytic processes for sustainable production of biobased chemicals and exploration of wider chemical space8Green Chemistry in Industrial Catalysis: Enhancements and Innovations1Heterojunction photocatalysts: where are they headed?115High-Throughput Methods for Accelerated Catalyst Discovery3Interactions of CO and/or H 2 O with mesoporous oxide-supported metal catalysts: the role of MSI effects3Low-temperature plasma-enabled CO 2 dissociation: a critical analysis of plasma setups and conversion mechanisms toward scale-up valorization17Metal–organic framework-based catalysts toward the electrosynthesis of urea8Opportunities and challenges in the ethylene value chain4Recent Progress on Utilising Visible Light to Better Catalyst Stability for the Dry Reforming of Methane3Synergistic effects of atomically precise Au-based bimetallic nanocluster on energy-related small molecule catalysis29The structure–property relationship of metallocene-based ethylene oligomerization catalysts using DFT and graph neural networks4Atomically Dispersed Cu Active Centers: Local Structure and Mechanism Modulation for Carbon Dioxide Reduction23Machine learning in electrocatalysis–Living up to the hype?7Atomic-level magnetism modulation of nanocrystals for biomedical imaging5Innovative Catalysis Approaches for Methane Utilization8AI in single-atom catalysts: a review of design and applications28Recent Advances in Membrane Electrode Assembly Based Nitrate Reduction Electrolyzers for Sustainable Ammonia Synthesis18Artificial Intelligence‐Assisted Experimental Optimization of Water Oxidation Catalysts0Recent developments in the use of machine learning in catalysis: A broad perspective with applications in kinetics69Zinc-air battery-H2O2 generation system: Current progress, key challenges, optimization strategies and future developments3Applications of machine learning in surfaces and interfaces30Catalytic Properties and Structural Optimization of Solid Transesterification Catalysts to Enhance the Efficiency of Biodiesel Synthesis32Catalyst design for efficient water splitting: A comprehensive review of challenges and opportunities39Active Learning‐Driven Discovery of Sub‐2 Nm High‐Entropy Nanocatalysts for Alkaline Water Splitting28Iron: From Basic Chemistry to Modern C∙H Bond Functionalization Catalysts1Transformative approaches in photocatalytic CO2 conversion: The impact of AI and computational chemistry4Guided electrocatalyst design through in-situ techniques and data mining approaches8Machine Learning for Developing Sustainable Polymers12Design and Application of Electrocatalyst Based on Machine Learning33Precision, intelligence, and a new paradigm for chemical research4A Data-Science Approach to Experimental Catalyst Discovery: Integrating Exploration, Exploitation, and Serendipity5AI-Driven Chemical Design: Transforming the Sustainability of the Pharmaceutical Industry18Machine learning perspective: Revealing deep mechanisms and new advances in adsorption and catalysis of gaseous molecules18Synergistic catalytic mechanism and performance regulation strategies between nanoparticles/clusters and single-atom sites18Recent Advances in Carbon-Based Catalysts for Heterogeneous Asymmetric Catalysis10Role of Machine Learning in Inorganic and Coordination Chemistry: Applications and Challenges0A Scoring Model for Catalyst Informatics Based on Real-Time High-Throughput Fluorogenic Assay for Catalyst Discovery and Kinetic Profiling1Aluminum Nanoparticles, a New Approach in Sustainable Chemistry and Usage in Medicine7Streamlining Catalyst Development through Machine Learning: Insights from Heterogeneous Catalysis and Photocatalysis0STM imaging on catalytic surfaces: from atomic-scale characterization of active sites to operando visualization of surface reactions5Advancing chemical engineering technology with artificial intelligence21Machine learning for catalyst optimization: Outlier detection and material innovation6Electrosynthesis of Chemicals from Biomass Glycerol17Supply Chain Optimization-based Drug Polymer Analysis Using AI Model for Synthesis and Characterization0Electrifying nitrate 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adsorption and catalytic degradation for excellent performance in persistent environmental contaminants14Probing All‐Solid‐State Batteries with Real‐Time Synchrotron and Neutron Techniques14Multi-feature deep learning framework for predicting CO adsorption mechanisms at metal oxide interfaces: a transformer-based approach1Advances in nanocatalysts for biofuel production: Mechanisms, performance, and future perspectives7Inverse ligand design: a generative data-driven model for optimizing vanadyl-based epoxidation catalysts5Convergence of Computational Materials Science and AI for Next-Generation Energy Storage Materials6Artificial intelligence-assisted design of molecularly imprinted polymers for enriching C-reactive protein6Building Catalyst Exploration Highways by Integrating High‐Throughput and Machine Learning Technologies11A review on the role of artificial intelligence and data science in green and sustainable chemistry: current trends and futuristic pathways6Machine learning-guided optimization of iron-based catalysts toward minimal-resource and efficient peroxymonosulfate activation for hazardous organic pollutants degradation8Based on machine learning prediction and experimental verification: The optimization of NH3-SCR performance on Ce/Co-modified MnNi catalysts8Development of Machine Learning and Chemical Language Model‐Based QSAR Models for Predicting Drug Residue Depletion Half‐Lives in Plasma and Tissues of Cattle Across Various Administration Routes3Fully automated and high-fidelity robotic platform enabling accelerated discovery of nanocatalysts2Accelerating catalytic advancements through the precision of high-throughput experiments & calculations4AI-driven electrocatalysis: reinforcement learning-based control and theoretical modeling of the glycerol oxidation reaction0Artificial Intelligence, Machine Learning, and High-Throughput Material Discovery Tools0Catalysts screening and optimization0Catalytic CO 2 hydrogenation toward net-zero 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wastewater treatment applications0Modulating the reaction pathway of tricobalt tetraoxide-based catalysts for advanced oxygen evolution2Machine Learning for Catalytic Reaction Systems: A Framework for Complex Chemical Processes7Earth-abundant nanomaterials for electrolytic hydrogen production: Advances, mechanistic insights, and industrial prospects10Energy-efficient machine learning approaches for enhanced biofuel (Biodiesel) production: A review5Hitchhikers Guide To Training More General Machine Learning Potentials in Heterogeneous Catalysis2Review on Carbonaceous Catalysts for Transesterification of Feedstock Toward Biodiesel Production: Advances, Challenges, and AI Perspectives2Metal-organic frameworks and their derivatives for green energy fuel: Hydrogen production2Computational Modeling of Catalysis by MXenes: Key Aspects2Chain Flexibility as a Fundamental Descriptor for Mild Depolymerization of Polyesters and Polycarbonates3Discerning 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 analysis3Unlocking the Potential of Heterogeneous Single‐Atom Catalysts for Renewable Energy Systems: From Foundation to Application2Learning catalytic kinetic models from data: current and emerging methods1High-Throughput Electrochemistry Using Scanning Electrochemical Cells4Tailoring Materials Design for Aqueous Energy Storage and Conversion through Electrochemical Reconstruction20Accelerating single-atom ORR catalyst discovery through theory and machine learning: a critical review13Integration of sustainable nanotechnology with artificial intelligence of things (AIoT) for environmental applications1Electronic and Structural Determinants of Activity and Stability in Noble Metal OER Catalysis6Decoding CO 2 ‐to‐Methanol Catalysis With Interpretable ML and Multi‐Objective Optimization4Self-regenerating catalysts for sustainable industrial applications4Machine learning and multi−scale descriptor frameworks for accelerated discovery of CO2 electrocatalysts2Catalytic strategies for the hydrogen evolution reaction in sustainable energy and environmental remediation11AI-Driven Catalyst Optimization in Methane Steam Reforming: A Hybrid HGBO–VIKOR and ConvLSTM Framework for Sustainable Hydrogen Production0Integration of artificial intelligence and machine learning in the optimization of clay-based catalysts for organic pollutant oxidation: A review1Electrifying catalysis: Joule heating-driven advanced materials for volatile organic compound oxidation0AI-driven framework for enhancing water quality engineering experimentation0Transformational Catalytic Innovation Supports CO 2 Resource Utilization: Bridging Sustainability and Industrial Applications0Mechanistic and Data-Guided Design of Biochar Adsorbents for Gas Phase Pollution Control: A State-of-the-Art Review2Theoretical Insights into Reaction-Induced Transformation and Tuning of Catalytic Behavior in Heterogenous Catalysis0Breaking the Boundaries of Bayesian Optimization Utilizing Continuous Chemistry Digital Twins0A data-driven perspective on CO₂ conversion: Machine learning for catalytic hydrogenation to methanol2Development of a High-Throughput Experimentation Workflow for Photochemical Reaction Screening0Machine learning as a mechanism-informed design paradigm for photocatalytic solar hydrogen evolution1Rational design of heterogeneous single-site catalysts via surface organometallic chemistry0Green organic synthesis in drug discovery: emerging roles of artificial intelligence and quantum chemical approaches0Thermal and Photocatalytic Conversion of CO 2 to Ethanol: Advances in Catalyst Design, Challenges, and Opportunities0

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