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RESEARCH PAPER · Chemical Science · 2024

Automation and machine learning augmented by large language models in a catalysis study

Yuming Su, Xue Wang, Yubo Ye, Yibo Xie, Yujing Xu, Yibin Jiang, Cheng Wang

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Automation and machine learning augmented by large language models in a catalysis studyOriginalA risk-based model for human-artificial intelligence conflict resolution in process systems6Application of graph neural network in computational heterogeneous catalysis29A Well‐Advanced High‐Throughput Test System for Electrocatalytic Screening Applications Under Industrial Relevant Conditions – A Perspective to Accelerate Electrolysis Research and Development4Engineering the Invisible2AI and automation: democratizing automation and the evolution towards true AI-autonomous robotics11Artificial intelligence-driven advances in photocatalytic hydrogen production19Digitalisation of catalytic processes for sustainable production of biobased chemicals and exploration of wider chemical space8Generative AI in Spectroscopy2Large Language Model-Driven Knowledge Discovery for Designing Advanced Micro/Nano Electrocatalyst Materials4Material design accelerated by large language models: end-to-end empowerment from knowledge mining to intelligent design1A new era in catalysis: Combining Al, DFT, single atom catalysis, and comprehensive characterizations applied to catalytic oxidation of C1-C4 volatile organic compounds24Large language models for reticular chemistry133AI in single-atom catalysts: a review of design and applications28Modeling the impact of structure and coverage on the reactivity of realistic heterogeneous catalysts39Recent developments in the use of machine learning in catalysis: A broad perspective with applications in kinetics69Interpretable physics-informed machine learning approaches to accelerate electrocatalyst development13Solvent Screening for Separation Processes Using Machine Learning and High-Throughput Technologies34Leveraging Prompt Engineering in Large Language Models for Accelerating Chemical Research29Machine learning-based design of electrocatalysts and catalytic mechanism research4Intelligent Systems for Inorganic Nanomaterial Synthesis38Machine Learning for Developing Sustainable Polymers12Using machine learning to guide the synthesis of supported palladium catalysts with desired palladium dispersion6Language models for materials discovery and sustainability: Progress, challenges, and opportunities26A Helping Hand: A Survey About AI-Driven Experimental Design for Accelerating Scientific Research5Empowering Generalist Material Intelligence with Large Language Models29AI in Mental Health: A Review of Technological Advancements and Ethical Issues in Psychiatry47From lab to fab: A large language model for chemical engineering12Natural-Language-Interfaced Robotic Synthesis for AI-Copilot-Assisted Exploration of Inorganic Materials23Synergizing a knowledge graph and large language model for relay catalysis pathway recommendation15Harnessing Higher Generative Artificial Intelligence for Educational Pedagogy0The hidden engine of AI in electrocatalysis: Databases and knowledge graphs at work8Advances in Gasoline Hydrodesulfurization Catalysts: The Role of Structure–Activity Relationships and Machine Learning Approaches13Transforming Catalysis with Machine Learning: Emerging Tools and Next-Gen Strategies5Autonomous Materials Synthesis Laboratories: Integrating Artificial Intelligence with Advanced Robotics for Accelerated Discovery4Atomic-scale characterization: a review of advances in microscopy, spectroscopy, and machine learning11Revealing the Impact of Aggregations in the Graph‐Based Molecular Machine Learning: Electrostatic Interaction Versus Pooling Methods1Large language model guided automated reaction pathway exploration6Large Language Models for Heterogeneous Catalysis10Recent Advances in CO (2) Electroreduction Driven by Artificial Intelligence and Machine Learning14Application of machine learning methods in the metallurgical industry: A bibliometric analysis and systematic literature review0AI Design for High Entropy Alloys: Progress, Challenges and Future Prospects16A research database for experimental electrocatalysis: Advancing data sharing and reusability10Artificial intelligence in materials science and chemistry: Past, present and future trajectories9Atomic Coordination Regulation in Electronic Structure of Electrocatalysts14Empowering scientific discovery with explainable small domain-specific and large language models3Artificial intelligence in chemical kinetics and reactor design0AI-Accelerated Discovery of Electrocatalyst Materials26Machine Learning for Accelerating Energy Materials Discovery: Bridging Quantum Accuracy with Computational Efficiency44MXenes for CO2 conversion to fuel: correlation between atomistic simulation, experimental and artificial intelligence0AI driven electrochemical interface design: Development and economic evaluation of low-cost electrode materials based on the 'structure-activity consumption' model6Autonomous catalysis research with human–AI–robot collaboration37Perspective on utilizing foundation models for laboratory automation in materials research2Advancing metal organic framework and covalent organic framework design via the digital-intelligent paradigm18Data-driven design of TiO 2 –zeolite photocatalysts for sustainable vanillin production0Opportunities of Large Language Models in the Development of Organic Electrosynthesis1Machine learning-driven catalyst and system optimization for sustainable CO2-to-aromatics development: participation and economic perspectives9Building 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 pathways6Large Language Models (LLMs) for Materials Design1430 years of AI for electrocatalysis: Where we are and what’s next?12Chemically-informed active learning enables data-efficient multi-objective optimization of self-healing polyurethanes38Recent Advances in Biomimetic Electrocatalysts for Water Splitting: Emerging Trends and Outlook5Accelerating catalytic advancements through the precision of high-throughput experiments & calculations4Can we automate scientific reasoning in closed-loop experiments using large language models?4Case studies on recent advances in applicability of computational tools for design, optimization, and automation of biochar-based catalysts for treatment of industrial effluents1Designing Functional Materials with Zeta Potential: From Controlling Surface Charges to Developing Sustainable Catalysts0Large language models for porous materials: from text mining to autonomous laboratory6PRISM: protocol refinement through intelligent simulation modeling0Spin polarization and chemical catalysis: what we know, what works, and what's next10Electrode–microbe–catalyst triple coupling for efficient nitrogen conversion and recovery in wastewater0Interpretable Machine-Learning-Assisted Design of Metal Oxide Catalysts by Decoding Key Descriptors for CO 2 -Assisted Propane Dehydrogenation5BiML-SyMO: Bridging multi-objective optimization of catalysts and chemical systems through a bilateral machine learning framework1Integrating large language models and machine learning for sustainable electrochemical upgrading of biomass-derived 5-hydroxymethylfurfural to 2,5-bis(hydroxymethyl)furan0Commercialization path of data-driven green catalytic technology: the application of machine learning in technology lifecycle management5Accelerating Catalyst Materials Discovery With Large Artificial Intelligence Models32Boosting Computational Catalysis and Chemical Reactivity with Artificial Intelligence12Accelerating Catalyst Materials Discovery With Large Artificial Intelligence Models2MDCrow: automating molecular dynamics workflows with large language models23ReactionSeek: LLM-powered literature data mining and knowledge discovery in organic synthesis7Agentic AI framework for accelerated catalyst design in biomass valorization via small language models and automated machine learning1Machine learning and catalyst engineering for sustainable hydrogen release from ammonia0Precision orientation of hydrogen evolution performance of iron-based electrocatalysts empowered by machine learning: From electronic structure regulation to rational construction0Automated multimodal knowledge extraction for economic insights in materials0Comparative analysis of OpenAI and DeepSeek in knowledge depth, analytical skills, and academic research impact0Machine Learning-Guided Prediction of Low-Barrier N 2 and CO 2 Activation for Catalyst Design0Explainable AI in Electrocatalysis and Photocatalysis: From Catalyst Design to Mechanistic Insights7From Chatbots to Chemists: Autonomous Agents for Heterogeneous Catalysis0Leveraging Large Language Models for Understanding Fundamental Principles of Catalysis0Catalyst Design for Sustainable Reactions: A Primer toward Knowledge-Driven Innovation0Data driven reveals the upgrading mechanism of waste PET electrolysis: Research progress of machine learning in collaborative production of high-value chemicals and green hydrogen energy0Information extraction from literature for ORR catalyst in fuel cell0Explainable artificial intelligence shines a light on catalysis: methods, applications, and future directions0مجلة القانون والأعمال الدولية الاصدار رقم 66 أكتوبر 2026 : اصدار عالمي بمشاركة باحثين من 16 جنسية مختلفة0Machine Learning for Synthetic Organic Chemistry: Methods, Applications, and Best Practices0Machine learning–assisted inverse design of PEMFC cathode ORR catalysts: A two-level framework from performance targets to device validation0Artificial intelligence for plastic pyrolysis to produce fuels and chemicals: From reaction kinetics and reactor design to intelligent agent development0Human-in-the-loop AI in analytical chemistry: a critical review from large language models to agentic systems0Photothermal CO2 conversion using two-dimensional and porous framework materials: an energy-cascade analysis of mechanistically complementary catalysts0Data-driven hydrodesulfurization of heavy feeds: from model compounds to refinery-relevant catalyst design, soft sensing, and process optimization0Optimization of a copper-based catalyst system for methanol reforming to hydrogen via interpretable machine learning0Artificial intelligence for sustainable chemical synthesis: Advances in catalysis, biocatalysis, solvents, materials, and life cycle assessment0Recent advances in electrochemical CO2 reduction to fuels enabled by emerging two-dimensional materials: From DFT to machine learning0Large Language Model-Assisted Development of Reliable Machine Learning Models for Hydrogen Evolution Reaction Catalysts0مجلة القانون والأعمال الدولية الاصدار رقم 66 أكتوبر 2026 : اصدار عالمي بمشاركة باحثين من 16 جنسية مختلفة0

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