134 citations · 279 across the 12 of their papers we have counts for
13 papers
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…
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…
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…
Energy Relaxation of NO in Gaseous, Supercritical and Liquid Xenon and SF
Kai Töpfer, Shyamsunder Erramilli, Lawrence D. Ziegler +1
Rotational and vibrational energy relaxation (RER and VER) of NO embedded in xenon and SF environments ranging from the gas phase to the liquid, including the supercritical…
Kernel-based Minimal Distributed Charges: A Conformationally Dependent ESP-Model for Molecular Simulations
Eric Boittier, Kai Töpfer, Mike Devereux +1
A kernel-based method (kernelized minimal distributed charge model - kMDCM) to represent the molecular electrostatic potential (ESP) in terms of off-center point charges whose posi…
SCN as a Local Probe of Protein Structural Dynamics
Sena Aydin, Seyedeh Maryam Salehi, Kai Töpfer +1
The dynamics of lysozyme is probed by attaching -SCN to all alanine-residues. The 1-dimensional infrared spectra exhibit frequency shifts in the position of the maximum absorption…
PhysNet Meets CHARMM: A Framework for Routine Machine Learning / Molecular Mechanics Simulations
Kaisheng Song, Silvan Käser, Kai Töpfer +2
Full dimensional potential energy surfaces (PESs) based on machine learning (ML) techniques provide means for accurate and efficient molecular simulations in the gas- and condensed…
Molecular-Level Understanding of the Ro-vibrational Spectra of NO in Gaseous, Supercritical and Liquid SF and Xe
Kai Töpfer, Debasish Koner, Shyamsunder Erramilli +2
The transition between the gas-, supercritical-, and liquid-phase behaviour is a fascinating topic which still lacks molecular-level understanding. Recent ultrafast two-dimensional…
Neural Network Potentials for Chemistry: Concepts, Applications and Prospects
Silvan Käser, Luis Itza Vazquez-Salazar, Markus Meuwly +1
Artificial Neural Networks (ANN) are already heavily involved in methods and applications for frequent tasks in the field of computational chemistry such as representation of poten…
Structure, Organization and Heterogeneity of Water-Containing Deep Eutectic Solvents
Kai Töpfer, Andrea Pasti, Anuradha Das +6
The spectroscopy and structural dynamics of a deep eutectic mixture (KSCN/acetamide) with varying water content is investigated from 2D IR (with the C-N stretch vibration of the SC…
Hydration Dynamics and IR Spectroscopy of 4-Fluorophenol
Seyedeh Maryam Salehi, Silvan Käser, Kai Töpfer +5
Halogenated groups are relevant in pharmaceutical applications and potentially useful spectroscopic probes for infrared spectroscopy. In this work, the structural dynamics and infr…
Quantitative Molecular Simulations
K. Töpfer, M. Upadhyay, M. Meuwly
All-atom simulations can provide molecular-level insights into the dynamics of gas-phase, condensed-phase and surface processes. One important requirement is a sufficiently realist…
Double Proton Transfer in Hydrated Formic Acid Dimer: Interplay of Spatial Symmetry and Solvent-Generated Force on Reactivity
Kai Töpfer, Silvan Käser, Markus Meuwly
The double proton transfer (DPT) reaction in hydrated formic acid dimer (FAD) is investigated at molecular-level detail. For this, a global and reactive machine learned (ML) potent…