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cond-mat.mtrl-sci2026
Electrostatic Phenomenology Benchmarks for Machine-Learned Interatomic Potentials in Electrochemistry: Beyond the Energy-Force Metric
Barbara Sumić, Ria Vasdev, Sudheesh Kumar Ethirajan +8
Accurate treatment of long-range interactions in machine learning interatomic potentials (MLIPs) is essential for electrochemical simulations. However, aggregate energy and force e…
cond-mat.mtrl-sci2025
Nanoscale surface morphology controls charge storage at stepped Pt-water interfaces
Matthew T. Darby, Muhammad Saleh, Marialore Sulpizi +1
Platinum step edges dominate electrocatalytic activity in fuel cells and electrolysers, yet their atomistic electrochemical behaviour remains poorly understood. Here, we employ \te…
cond-mat.mtrl-sci2024
Enabling Ab-Initio Molecular Dynamics under Bias: The CP2K+SMEAGOL Interface for Integrating Density Functional Theory and Non-Equilibrium Green Functions
Christian S. Ahart, Sergey Chulkov, Clotilde S. Cucinotta
Density functional theory (DFT) combined with non-equilibrium Greens functions (NEGF) is a powerful approach to model quantum transport under external bias potentials, at reasonabl…