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Bayesian Optimization over Multiple Experimental Fidelities Accelerates Automated Discovery of Drug Molecules

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Machine learning optimized adsorption heat transformations from adsorbents screening to enhanced performances

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Bayesian Optimization Guiding the Experimental Mapping of the Pareto Front of Mechanical and Flame‐Retardant Properties in Polyamide Nanocomposites

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Artificial Intelligence Paradigms for Next-Generation Metal–Organic Framework Research

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A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation

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Intelligent screening of porous materials: A review of active-learning approaches in MOF research

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MOFs to Enhance Green NH3 Synthesis in Plasma Reactors: Hierarchical Computational Screening Enhanced by Iterative Machine Learning

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Toward Accelerating Discovery via Physics-Driven and Interactive Multifidelity Bayesian Optimization

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A case study in the development of improved promoted Pt catalysts for propane dehydrogenation through Bayesian optimization with uncertainty quantification

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Accelerating In Silico Discovery of Metal–Organic Frameworks for Ethane/Ethylene and Propane/Propylene Separation: A Synergistic Approach Integrating Molecular Simulation, Machine Learning, and Active Learning

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Active Learning for Transport Property Prediction in CO2–Hydrocarbon Systems: A Multifidelity Approach Integrating Molecular Dynamics and Experiments

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