3 papers
physics.chem-ph2025
Design, Assessment, and Application of Machine Learning Potential Energy Surfaces
Valerii Andreichev, Sena Aydin, Kai Töpfer +2
Potential Energy Surfaces (PESs) are an indispensable tool to investigate, characterise and understand chemical and biological systems in the gas and condensed phases. Advances in…
physics.chem-ph2025
Cluster Models for Next-Generation, Machine-Learning-Based Energy Functions for Molecular Simulations
JingChun Wang, Meenu Upadhyay, Eric D. Boittier +7
Energy functions for pure and heterogenous systems are one of the backbones for molecular simulation of condensed phase systems. With the advent of machine learned potential energy…
physics.chem-ph2024
Diffusion and Spectroscopy of H in Myoglobin
Jiri Käser, Kai Töpfer, Markus Meuwly
The diffusional dynamics and vibrational spectroscopy of molecular hydrogen (H) in myoglobin (Mb) is characterized. Hydrogen has been implicated in a number of physiologically…