5 citations · 9 across the 19 of their papers we have counts for
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Tripeptide-Dynamics from Empirical and Machine-Learned Energy Functions
Sena Aydin, Valerii Andreichev, Pantelis Maragkoudakis +1
Molecular dynamics simulations for tripeptides in the gas phase and in solution using empirical and machine-learned energy functions are presented. For cationic AAA a machine-learn…
Dynamics of Protonated Oxalate from Machine-Learned Simulations and Experiment: Infrared Signatures, Proton Transfer Dynamics and Tunneling Splittings
Valerii Andreichev, Silvan Käser, Erica L. Bocanegra +3
The infrared spectroscopy and proton transfer dynamics together with the associated tunneling splittings for H/D-transfer in oxalate are investigated using a machine learning-based…
End-to-End Photodissociation Dynamics of Energized HCOO
Cangtao Yin, Silvan Käser, Meenu Upadhyay +1
The end-to-end dynamics of the smallest energized Criegee intermediate, HCOO, was characterized for vibrational excitation close to and a few kcal/mol above the barrier for hyd…
Towards Large-Scale Condensed Phase Simulations using Machine Learned Energy Functions
Eric D. Boittier, Silvan Käser, Markus Meuwly
Accurate, yet computationally efficient energy functions are essential for state-of-the art molecular dynamics (MD) studies of condensed phase systems. Here, a generic workflow bas…
Augmenting chemical databases for atomistic machine learning by sampling conformational space
Luis Itza Vazquez-Salazar, Markus Meuwly
Machine learning (ML) has become a standard tool for the exploration of chemical space. Much of the performance of such models depends on the chosen database for a given task. Here…
Reaction Dynamics of the H + HeH He + H System
Meenu Upadhyay, Silvan Käser, Jayakrushna Sahoo +2
The reaction dynamics for the H + HeH He + H reaction in its electronic ground state is investigated using two different representations of the potential en…