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Bridging scales and paradigms: a perspective from atomistic simulation to AI-enhanced modeling of sodium-ion capacitors

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Accelerated Discovery of Refractory High-Entropy Alloys via Interpretable Machine Learning

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Transforming Catalysis with Machine Learning: Emerging Tools and Next-Gen Strategies

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Using Machine Learning for Green Substitution of Industrial Chemicals: Integrating Functionality, Hazard, and Life Cycle Impact

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Advances in Ta3N5‐Based Photoanodes for Photoelectrochemical Hydrogen Production and Beyond

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Accelerating Excited-State Calculations of Large Systems with Restricted Boltzmann Machines

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MELTS: Fully Automated Active Learning for Fewest-Switches Surface Hopping Dynamics

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Reactive Neural Network Potential Developed for Asphalt Aging Systems Through Active Learning and Enhanced Sampling

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Research progress on liquid-solid transition under synchrotron radiation X-ray and simulation

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The Reconstruction Mechanism and NH3‐SCR Kinetics of Mn Clusters on MoS2 by Ab Initio Data Driven Machine Learning Simulations

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Determination of Coverage-Dependent Surface Reaction Rates Using λ-Dynamics: Application to Molecular Desorption

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Recent Advances in CO(2) Electroreduction Driven by Artificial Intelligence and Machine Learning

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Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

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BUNNY: An N,N-Bidentate Nitrogen Ligand Descriptor LibraryDevelopment and Application to Modeling of Ni-Catalyzed Asymmetric Cross-Electrophile Coupling Reactions

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Six-Dimensional State-to-State Scattering of CO and NO from Au(111): A Comparison of Quantum and Quasi-Classical Dynamics

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Machine Learning Potential-Enabled Platform for the In Silico Design of Functional Organic Molecular Crystals

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Machine Learning in Theoretical Study of Single-Molecule Magnets: Current Status and Challenges

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Efficient Parallelization of Message Passing Neural Network Potentials for Large-Scale Molecular Dynamics

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Charting the Landscape of Oxygen Ion Conductors: A 60-Year Dataset with Interpretable Regression Models

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Smarter Data: Rethinking Data Generation for Machine Learning Potentials in Heterogeneous Catalysis

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