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physics.chem-ph2026
Molecular electrostatic potentials from machine learning models for dipole and quadrupole predictions
Kadri Muuga, Lisanne Knijff, Chao Zhang
The molecular electrostatic potential (MEP) is a key quantity for describing and predicting intermolecular and ion-molecule interactions. Here, we assess the ability of machine-lea…
physics.chem-ph2022★ 9 cited
Electric Double Layer at the Metal-Oxide/Electrolyte Interface
Lisanne Knijff, Mei Jia, Chao Zhang
Metal-oxide surfaces act as both Brønsted acids and bases, which allows the exchange of protons with the electrolyte solution and generates either positive or negative proton charg…
physics.chem-ph2021★ 10 cited
Machine Learning Inference of Molecular Dipole Moment in Liquid Water
Lisanne Knijff, Chao Zhang
Molecular dipole moment in liquid water is an intriguing property, partly due to the fact that there is no unique way to partition the total electron density into individual molecu…