activity
20182026
most citedGaussian Moments as Physically Inspired Molecular Descriptors for Accurate and Scalable Machine Learning Potentials

107 citations · 417 across the 22 of their papers we have counts for

collaborators
Showing astro-ph.GAShow all

4 papers · 1 filter

astro-ph.GA2023★ 29 cited

Reaction dynamics on amorphous solid water surfaces using interatomic machine learned potentials. Microscopic energy partition revealed from the P + H -> PH reaction

Germán Molpeceres, Viktor Zaverkin, Kenji Furuya +2

Energy redistribution after a chemical reaction is one of the few mechanisms to explain the diffusion and desorption of molecules which require more energy than the thermal energy…

astro-ph.GA2021

Neural-Network Assisted Study of Nitrogen Atom Dynamics on Amorphous Solid Water -- II. Diffusion

Viktor Zaverkin, Germán Molpeceres, Johannes Kästner

The diffusion of atoms and radicals on interstellar dust grains is a fundamental ingredient for predicting accurate molecular abundances in astronomical environments. Quantitative…

astro-ph.GA2020★ 31 cited

Neural-Network Assisted Study of Nitrogen Atom Dynamics on Amorphous Solid Water. I. Adsorption & Desorption

Germán Molpeceres, Viktor Zaverkin, Johannes Kästner

Dynamics of adsorption and desorption of (4S)-N on amorphous solid water are analyzed using molecular dynamics simulations. The underlying potential energy surface was provided by…

astro-ph.GA2018★ 11 cited

Tunnelling dominates the reactions of hydrogen atoms with unsaturated alcohols and aldehydes in the dense medium

V. Zaverkin, T. Lamberts, M. N. Markmeyer +1

Hydrogen addition and abstraction reactions play an important role as surface reactions in the buildup of complex organic molecules in the dense interstellar medium. Addition react…