Author

Ilkwon Cho

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Open access Sep 2026

Critical benchmarking of machine-learned interatomic potentials for intermolecular and noncovalent interactions

It is demonstrated that meaningful MLIP evaluation must carefully account for data provenance, reference theory consistency, and the distinction between interpolation and true out-of-distribution generalization, particularly as standard NCI benchmark sets become increasingly absorbed into large-scale training datasets.

Kamal Singh Nayal, Ilkwon Cho, O. Isayev · Machine Learning: Science an... · 0 citations

Open access Jul 2026

Machine learning-accelerated screening of hydroquinone analogs for proton-coupled electron transfer

Proton-coupled electron transfer (PCET) mediated by hydroquinone and related molecules is key to natural and artificial energy conversion. The reactivity of these molecules depends on their bond dissociation free energy (BDFE), but studying the relationship between structure and thermochemistry across this chemical spa...

Rajdeep Sarma, Yiwen Wang, David D Hebert et al. · Chemical Science · 0 citations