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RESEARCH PAPER · Chem Catalysis · 2024

Accelerated exploration of heterogeneous CO2 hydrogenation catalysts by Bayesian-optimized high-throughput and automated experimentation

Adrián Ramírez, Erwin Lam, Daniel Pacheco Gutiérrez, Yuhui Hou, Hermann Tribukait, Loı̈c M. Roch, Christophe Copéret, Paco V. Laveille

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Accelerated exploration of heterogeneous CO2 hydrogenation catalysts by Bayesian-optimized high-throughput and automated experimentationOriginalAccelerated design of nickel-cobalt based catalysts for CO 2 hydrogenation with human-in-the-loop active machine learning17Balancing computational chemistry's potential with its environmental impact21Chemspyd : an open-source python interface for Chemspeed robotic chemistry and materials platforms29Combining Bayesian optimization and automation to simultaneously optimize reaction conditions and routes29Cost-informed Bayesian reaction optimization17Modern Automation in Organic Synthesis Laboratories5Systematic Exploration of a Multi-Promoter Catalyst Composition Space with Limited Experiments: Non-Oxidative Propane Dehydrogenation to Propylene16Active learning streamlines development of high performance catalysts for higher alcohol synthesis75From Characterization to Discovery: Artificial Intelligence, Machine Learning and High-Throughput Experiments for Heterogeneous Catalyst Design190Self-Driving Laboratories for Chemistry and Materials Science674Process Modeling and Optimal Evaluation Analysis for Direct CO2 Conversion to Methanol0Material Engineering Solutions toward Selective Redox Catalysts for Chemical-Looping-Based Olefin Production Schemes: A Review24Design Principles of Catalytic Materials for CO 2 Hydrogenation to Methanol70The Changing Landscape of Materials Discovery0A revolutionary paradigm in chemistry and materials science research: self-driving laboratories8Active learning high coverage sets of complementary reaction conditions4Adaptive representation of molecules and materials in Bayesian optimization16General data management workflow to process tabular data in automated and high-throughput heterogeneous catalysis research6Role of the human-in-the-loop in emerging self-driving laboratories for heterogeneous catalysis48High-Throughput Optimization of a High-Pressure Catalytic Reaction5Effect of adsorbent loading on NaNiRu-DFMs' CO 2 capture and methanation: finding optimal Na-loading using Bayesian optimisation guided experiments9The integration of artificial intelligence and high-throughput experiments: An innovative driving force in catalyst design24Tellurium-Induced Noble-Metal Reactivity in CO2 Hydrogenation Catalysts8Artificial Intelligence‐assisted Heterogeneous Catalyst Design, Discovery, and Synthesis Utilizing Experimental Data1ENHANCING SOCIAL MEDIA AD CAMPAIGNS THROUGH ENSEMBLE-BASED OPTIMIZATION0Polycondensation as a Universal Method for Preparing High‐Density Single‐Atom Catalyst Libraries12Artificial Intelligence for Materials Discovery, Development, and Optimization171Machine learning application in thermal CO2 hydrogenation: catalyst design, process optimization, and mechanism insights13Synergy of Machine Learning and High‐Throughput Experimentation: A Road Toward Autonomous Synthesis8Recent advances of multicomponent VOCs catalytic oxidation: Insights into mechanism, mixing effect, and catalyst design13Selectivity control of CO2 hydrogenation at atmospheric pressure: Insights from selectivity overturning phenomena7Machine Learning for Accelerating Energy Materials Discovery: Bridging Quantum Accuracy with Computational Efficiency44Bayesian Optimization for Resource-Efficient Hydroformylation0Bayesian Optimization of Hierarchical ZSM-5 for High-Efficiency Polyolefin Waste Recycling to Light Olefins7Process parameters’ influence on integrated CO 2 capture and methanation: finding optimal conditions by Bayesian optimisation1Material Agnostic-Implicit Deep Adaptive Design for Experimental Design and Parameter Estimation in Chemical Engineering0Material Agnostic-Implicit Deep Adaptive Design for Experimental Design and Parameter Estimation in Chemical Engineering0Material Agnostic-Implicit Deep Adaptive Design for Experimental Design and Parameter Estimation in Chemical Engineering0Data Science-Assisted Workflow for Reaction Optimization in Process Chemistry2Adaptive Experiment Planning for Inverse Design and Understanding: Synergistic Interactions as Key to Optimized Multi-Promoter Formulations1Machine-Learning-Guided Discovery of CH 4 Combustion Catalysts Operating in the Presence of SO 22AI ‐Guided Design of Polymer‐Supported Metal Catalysts: From Predictive Machine Learning to Bayesian Optimization1Potential, challenges and opportunities of machine learning model for plasma-based gas conversion: a critical review0AI‐Driven Synthesis in Medicinal Chemistry: Integrating Large Language Models, Robotic Automation, and Sustainability Metrics to Accelerate Drug Discovery0Enhancing experimental heterogeneous catalysis via high-throughput workflows0Harnessing Selectivity in CO2 Hydrogenation: Mechanistic Descriptors, Data-Driven Catalyst Design, and Sustainability Constraints0Catalyst and Catalysis Co-Exploration in Methane Utilization0From Chatbots to Chemists: Autonomous Agents for Heterogeneous Catalysis0Machine Learning-Assisted Development of High-Performance Ethanol Synthesis Catalysts via CO2 Hydrogenation0Artificial intelligence-driven inverse design of catalytic materials0Trendbericht Technische Chemie 20260Dynamic Reconstruction of Atomically Dispersed Copper Catalysts for CO 2 Reduction: From In Situ Observations to Rational Design0Case Study of Bayesian Batch Optimization Strategies for Heterogeneous Catalysts in CO2 Hydrogenation0Taming Complexity: Structural and Electronic Evolution of Copper Indium Oxide Under CO2 Hydrogenation Via Multi-Method X-ray Characterization0Optimizing NiMo Electrocatalyst Coatings for Hydrogen Evolution in Alkaline Electrolysis With The Machine Learning‐Guided Autonomous Platform CatBot0

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  4. Combining Bayesian optimization and automation to simultaneously optimize reaction conditions and routes

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  6. Modern Automation in Organic Synthesis Laboratories

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  7. Systematic Exploration of a Multi-Promoter Catalyst Composition Space with Limited Experiments: Non-Oxidative Propane Dehydrogenation to Propylene

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  8. Active learning streamlines development of high performance catalysts for higher alcohol synthesis

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  11. Process Modeling and Optimal Evaluation Analysis for Direct CO2 Conversion to Methanol

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  12. Material Engineering Solutions toward Selective Redox Catalysts for Chemical-Looping-Based Olefin Production Schemes: A Review

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  13. Design Principles of Catalytic Materials for CO 2 Hydrogenation to Methanol

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  14. The Changing Landscape of Materials Discovery

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  19. Role of the human-in-the-loop in emerging self-driving laboratories for heterogeneous catalysis

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  20. High-Throughput Optimization of a High-Pressure Catalytic Reaction

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  23. Tellurium-Induced Noble-Metal Reactivity in CO2 Hydrogenation Catalysts

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