Author

Emil J. P. Frost

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Preprint Sep 2026

Energetically Driven Structure Matching for Autonomous Total X-ray Scattering Experiments

The emergence of autonomous laboratories motivates rapid conversion of experimental data into reliable atomistic models on time-scales compatible with closed-loop optimization. Here we develop an energetically driven structure matching framework for analysis during ongoing total X-ray scattering experiments. Using data...

Emil J. P. Frost, M. Karlsen, Jonas H. Jensen et al. · 0 citations

#machine learning Preprint Sep 2026

SoLiD26: A First Principles Solid-Liquid Interface Dataset for Machine-learned Interatomic Potentials

Machine-learned interatomic potentials (MLIPs) for solid-liquid interfaces in advanced materials applications, e.g., electrochemistry, catalysis and corrosion, require training data that samples both liquid environments, the solid and the interface itself. We present SoLiD26, a curated solid-liquid interface dataset, c...

Jonas Busk, Emil J. P. Frost, Yogeshwaran Krishnan et al. · 0 citations