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RESEARCH PAPER · Digital Discovery · 2023

Accelerated chemical science with AI

Seoin Back, Alán Aspuru‐Guzik, Michele Ceriotti, Ganna Gryn’ova, Bartosz A. Grzybowski, Geun Ho Gu, Jason E. Hein, Kedar Hippalgaonkar, Rodrigo Hormázabal, Yousung Jung, Seonah Kim, Woo Youn Kim, Seyed Mohamad Moosavi, Juhwan Noh, Chang-Young Park, Joshua Schrier, Philippe Schwaller, Koji Tsuda, Tejs Vegge, O. Anatole von Lilienfeld, Aron Walsh

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Accelerated chemical science with AIOriginalThe Coordination Problem in Multi-Model Materials AI Pipelines0Artificial intelligence-enabled optimization of battery-grade lithium carbonate production4Autonomous millimeter scale high throughput battery research system12Enhancing Low-Cost Molecular Property Prediction with Contrastive Learning on SMILES Representations4Extrapolation validation (EV): a universal validation method for mitigating machine learning extrapolation risk28Autonomous millimeter scale high throughput battery research system (Auto-MISCHBARES)0Autonomous millimeter scale high throughput battery research system (Auto-MISCHBARES)1Autonomous millimeter scale high throughput battery research system (Auto-MISCHBARES)0Comment on “Comparing the Performance of College Chemistry Students with ChatGPT for Calculations Involving Acids and Bases”24Elucidating Electronic Structure Variations in Nucleic Acid-Protein Complexes Involved in Transcription Regulation Using a Tight-Binding Approach0Active Learning of Ligands That Enhance Perovskite Nanocrystal Luminescence18Theoretical Design Strategies for Area-Selective Atomic Layer Deposition50General Aqueous System Simulation through an AI-Embedded Metaverse Chemistry Laboratory2Illustrating an Effective Workflow for Accelerated Materials Discovery14Large Language Models are Catalyzing Chemistry Education10Theoretical Investigation, Synthesis, Characterization, Molecular docking, predicted PkCSM and Profound Biological Implication of vanadium metal complexes0Large Language Models for Inorganic Synthesis Predictions73Discovery of Crystallizable Organic Semiconductors with Machine Learning28Top 20 influential AI-based technologies in chemistry50Toward accelerated discovery of solid catalysts using extrapolative machine learning approach10A FAIR comparison of activated carbon, biochar, cyclodextrins, polymers, resins, and metal organic frameworks for the adsorption of per- and polyfluorinated substances35Materials Acceleration Platforms (MAPs): Accelerating Materials Research and Development to Meet Urgent Societal Challenges80Im Weltall autonom synthetisieren0Computer-Aided Retrosynthesis for Greener and Optimal Total Synthesis of a Helicase-Primase Inhibitor Active Pharmaceutical Ingredient20Active Learning of Boltzmann Samplers and Potential Energies with Quantum Mechanical Accuracy5Artificial Intelligence (AI) Applications in Drug Discovery and Drug Delivery: Revolutionizing Personalized Medicine488The Future Integrated Computational and Experimental Research in Metaverse0Exploring the potential of large language model–based chatbots in challenges of ribosome profiling data analysis: a review1Classification-Based Detection and Quantification of Cross-Domain Data Bias in Materials Discovery9Adaptive representation of molecules and materials in Bayesian optimization16AMPERE-2: an open-hardware, robotic platform for automated electrodeposition and electrochemical validation6An Overview of Trustworthy and Sustainable AI Development for Catalyst Screening: The Role of Explainable AI (XAI)2Composition-property extrapolation for compositionally complex solid solutions based on word embeddings4Constrained composite Bayesian optimization for rational synthesis of polymeric particles6Democratizing self-driving labs: advances in low-cost 3D printing for laboratory automation25Harnessing the leading edge: machine learning ventures in chemistry and materials science3High-throughput robotic collection, imaging, and machine learning analysis of salt patterns: composition and concentration from dried droplet photos15Human-AI synergy in adaptive active learning for continuous lithium carbonate crystallization optimization1Identify structures underlying out-of-equilibrium reaction networks with random graph analysis3Robotic integration for end-stations at scientific user facilities5Empowering Lab Education: Integrating a Vision-Based Monitoring System with Small-Scale Self-Driving Experiment Platforms1Adapting hybrid density functionals with machine learning22An active representation learning method for reaction yield prediction with small-scale data8Explainable Synthesizability Prediction of Inorganic Crystal Polymorphs Using Large Language Models28Explainable Synthesizability Prediction of Inorganic Crystal Polymorphs Using Large Language Models1Kernel regression methods for prediction of materials properties: Recent developments22Design and optimization of a shared synthetic route for multiple active pharmaceutical ingredients through combined computer aided retrosynthesis and flow chemistry11Three decades of quantum science: how quantum chemistry transformed thermochemical database generation for benchmarking DFT and machine learning9Out-of-Distribution Material Property Prediction Using Adversarial Learning6Developing ChemDFM as a large language foundation model for chemistry47Miniaturized Supercritical Fluid Chromatography Coupled with Ion Mobility Spectrometry: A Chip-Based Platform for Rapid Chiral and Complex Mixture Analysis7Optimal transport for generating transition states in chemical reactions36Designing a large language model for chemists3Artificial Intelligence at the Crossroads of Engineering and Innovation6Implementation of reinforcement learning for enhanced pressure control in a 190,000-barrel crude distillation unit: The first full-scale commercial deployment4Connecting metal-organic framework synthesis to applications using multimodal machine learning40Generative Design of Functional Metal Complexes Utilizing the Internal Knowledge and Reasoning Capability of Large Language Models23Energy-GNoME: A living database of selected materials for energy applications5Robotic system takes chemistry into hyperspace0Seamless integration of legacy robotic systems into a self-driving laboratory via NIMO: a case study on liquid handler automation1Synthesis-Aware Materials Redesign via Large Language Models12Learning Multidimensional Electronegativity of Selected Atom Types in Organic Molecules Using Graph Neural Networks2A survey of AI-supported materials informatics7FastCat: Autonomous Discovery of Multielement Layered Double Hydroxide Alloy Catalysts for Alkaline Oxygen Evolution Reaction3Accelerating catalytic advancements through the precision of high-throughput experiments & calculations4Environment-Aware Multi-Agent Framework for Self-Driving Laboratories0Harnessing generative AI for efficient organic materials discovery in low-data regimes1Evaluating In‐Context Learning in Large Language Models for Molecular Property Regression1Analyzing the influence of technological proximity between research institutions and their common partners on performance of academic collaborative publications—evidence from Chinese cloud computing sector1Кристаллохимия в эпоху цифровой трансформации1Exploring the limitations of kNN noisy feature detection and recovery for self-driving labs0Pondering the Future of Chemical Research Amid the Wider Adoption of Artificial Intelligence Technologies0Generative Active Learning Discovers High-Performance O2 Reduction Catalysts for H2O2 Production2AI in Composite Overwrapped Pressure Vessels: A Review and Advanced Roadmap from Materials Design to Predictive Maintenance4BB-EIT: A Generalized Prediction Model for Protein Adsorption on Polymer Brushes Using Augmented Chemical Embeddings3Machine-Learning-Guided Discovery of CH 4 Combustion Catalysts Operating in the Presence of SO 22Experimental High‐Throughput Electrochemistry0MEP-CNN: A visual and explainable machine learning framework for explosive molecule classification based on molecular electrostatic potentials0Artificial Intelligence- and Machine Learning-Driven Strategies for Catalyst Design and Sustainable Chemical Processes5The impact of open data on research productivity and academic collaboration: A systematic literature review (2021–2025)0Artificial intelligence in the design and optimization approach of microextraction techniques: A critical review and future perspectives3Enhancing Generalization in Synthesizability Prediction of Structurally Dissimilar Materials0MACReD: A Multi-Agent Collaborative Reasoning Framework for Reaction Diagram Parsing0Structured HTE Data and Integrated Bayesian Optimization Accelerate Scalable Amidation Process Development0Integrating Mechanistic Knowledge into Machine Learning Enables Improved Reaction Prediction in Low‐Data Regimes0Artificial Intelligence in the Preparation of Scientific Articles0

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  2. Artificial intelligence-enabled optimization of battery-grade lithium carbonate production

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  4. Enhancing Low-Cost Molecular Property Prediction with Contrastive Learning on SMILES Representations

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  5. Extrapolation validation (EV): a universal validation method for mitigating machine learning extrapolation risk

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  6. Autonomous millimeter scale high throughput battery research system (Auto-MISCHBARES)

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  10. Elucidating Electronic Structure Variations in Nucleic Acid-Protein Complexes Involved in Transcription Regulation Using a Tight-Binding Approach

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  11. Active Learning of Ligands That Enhance Perovskite Nanocrystal Luminescence

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  12. Theoretical Design Strategies for Area-Selective Atomic Layer Deposition

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  13. General Aqueous System Simulation through an AI-Embedded Metaverse Chemistry Laboratory

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  14. Illustrating an Effective Workflow for Accelerated Materials Discovery

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  15. Large Language Models are Catalyzing Chemistry Education

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  16. Theoretical Investigation, Synthesis, Characterization, Molecular docking, predicted PkCSM and Profound Biological Implication of vanadium metal complexes

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  17. Large Language Models for Inorganic Synthesis Predictions

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  18. Discovery of Crystallizable Organic Semiconductors with Machine Learning

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  20. Toward accelerated discovery of solid catalysts using extrapolative machine learning approach

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  23. Im Weltall autonom synthetisieren

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  24. Computer-Aided Retrosynthesis for Greener and Optimal Total Synthesis of a Helicase-Primase Inhibitor Active Pharmaceutical Ingredient

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  25. Active Learning of Boltzmann Samplers and Potential Energies with Quantum Mechanical Accuracy

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