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Learning to Use the Force: Fitting Repulsive Potentials in Density

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Development of robust neural-network interatomic potential for molten salt - ScienceDirect

PDF) Accurate Many-Body Repulsive Potentials for Density-Functional Tight-Binding from Deep Tensor Neural Networks

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Previous Publications Fritz Haber Institute of the Max Planck Society

Force between Two Parallel Current Carrying Conductors

Density-Functional Tight-Binding Parameters for Bulk Zirconium: A Case Study for Repulsive Potentials

Ultra-fast interpretable machine-learning potentials

PDF] Enhancing the accuracy of density functional tight binding models through ChIMES many-body interaction potentials.

Force Fields and Interactions – Practical considerations for Molecular Dynamics

Biomolecular Force Field Parameterization via Atoms-in-Molecule Electron Density Partitioning

Materials, Free Full-Text