activity
20122023
most citedPhysNet: A Neural Network for Predicting Energies, Forces, Dipole Moments and Partial Charges

1.1k citations · 2.2k across the 58 of their papers we have counts for

collaborators

63 papers

physics.chem-ph2023

Improving Potential Energy Surfaces Using Experimental Feshbach Resonance Tomography

Karl P. Horn, Luis Itza Vazquez-Salazar, Christiane P. Koch +1

The structure and dynamics of a molecular system is governed by its potential energy surface (PES), representing the total energy as a function of the nuclear coordinates. Obtainin…

physics.chem-ph2023

On the Effect of Aleatoric and Epistemic Errors on the Learnability and Quality of NN-based Potential Energy Surfaces

S. Goswami, S. Käser, R. J. Bemish +1

The effect of noise in the input data for learning potential energy surfaces (PESs) based on neural networks for chemical applications is assessed. Noise in energies and forces can…

physics.chem-ph2023

Molecular Simulation for Atmospheric Reaction Exploration and Discovery: Non-Equilibrium Dynamics, Roaming and Glycolaldehyde Formation Following Photo-Induced Decomposition of syn-Acetaldehyde Oxide

Meenu Upadhyay, Kai Töpfer, Markus Meuwly

The decomposition and chemical dynamics for vibrationally excited syn-CHCHOO is followed based on statistically significant numbers of molecular dynamics simulations. Using a n…

astro-ph.GA2023★ 9 cited

Low-Temperature Kinetics for the N + NO reaction: Experiment Guides the Way

Kevin M. Hickson, Juan Carlos San Vicente Veliz, Debasish Koner +1

The reaction N(4S) + NO -> O(3P) + N2 plays a pivotal role in the conversion of atomic to molecular nitrogen in dense interstellar clouds and in the atmosphere. Here we report a jo…

physics.chem-ph2023★ 30 cited

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…

physics.chem-ph2023★ 11 cited

Conformational and state-specific effects in reactions of 2,3-dibromobutadiene with Coulomb-crystallized calcium ions

Ardita Kilaj, Silvan Käser, Jia Wang +7

Recent advances in experimental methodology enabled studies of the quantum-state and conformational dependence of chemical reactions under precisely controlled conditions in the ga…

physics.chem-ph2023★ 23 cited

Transfer-Learned Potential Energy Surfaces: Towards Microsecond-Scale Molecular Dynamics Simulations in the Gas Phase at CCSD(T) Quality

Silvan Käser, Markus Meuwly

The rise of machine learning has greatly influenced the field of computational chemistry, and that of atomistic molecular dynamics simulations in particular. One of its most exciti…

physics.chem-ph2023★ 9 cited

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…

physics.chem-ph2022

Water Dynamics around T0 vs. R4 of Hemoglobin from Local Hydrophobicity Analysis

Seyedeh Maryam Salehi, Marco Pezzella, Adam Willard +2

The local hydration around tetrameric Hb in its T and R conformational substates is analyzed based on molecular dynamics simulations. Analysis of the local hydrophobicity (…

physics.atom-ph2022★ 40 cited

Tomography of Feshbach Resonance States

Baruch Margulis, Karl P. Horn, Daniel M. Reich +8

Feshbach resonances are fundamental to interparticle interactions and become particularly important in cold collisions with atoms, ions, and molecules. Here we present the detectio…

physics.chem-ph2022

Local Hydration Control and Functional Implications Through S-Nitrosylation of Proteins: Kirsten rat sarcoma virus (KRAS) and Hemoglobin (Hb)

Haydar Taylan Turan, Markus Meuwly

S-nitrosylation, the covalent addition of NO to the thiol side chain of cysteine, is an important post-transitional modification (PTM) that can affect the function of proteins. As…

physics.chem-ph2022★ 10 cited

Interaction at a Distance: Xenon Migration in Mb

Haydar Taylan Turan, Eric Boittier, Markus Meuwly

The transport of ligands, such as NO or O, through internal cavities is essential for the function of globular proteins, including hemoglobin, myoglobin (Mb), neuroglobin, trun…

physics.chem-ph2022★ 134 cited

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…

physics.chem-ph2022★ 9 cited

Combining Machine Learning and Spectroscopy to Model Reactive Atom + Diatom Collisions

Juan Carlos San Vicente Veliz, Julian Arnold, Raymond J. Bemish +1

The prediction of product translational, vibrational, and rotational energy distributions for arbitrary initial conditions for reactive atom+diatom collisions is of considerable pr…

physics.chem-ph2022

Transfer learning for affordable and high quality tunneling splittings from instanton calculations

Silvan Käser, Jeremy O. Richardson, Markus Meuwly

The combination of transfer learning (TL) a low level potential energy surface (PES) to a higher level of electronic structure theory together with ring-polymer instanton (RPI) the…

physics.chem-ph2022★ 1 cited

Uncertainty quantification for predictions of atomistic neural networks

Luis Itza Vazquez-Salazar, Eric D. Boittier, M. Meuwly

The value of uncertainty quantification on predictions for trained neural networks (NNs) on quantum chemical reference data is quantitatively explored. For this, the architecture o…

physics.chem-ph2022★ 76 cited

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…

physics.chem-ph2022★ 1 cited

Molecular Dynamics with Conformationally Dependent, Distributed Charges

Eric D. Boittier, Mike Devereux, Markus Meuwly

Accounting for geometry-induced changes in the electronic distribution in molecular simulation is important for capturing effects such as charge flow, charge anisotropy and polariz…

physics.chem-ph2022★ 8 cited

Quantum and Quasi-classical Dynamics of the C(P) + O() CO()+ O(D) Reaction on Its Electronic Ground State

Sugata Goswami, Juan Carlos San Vicente Veliz, Meenu Upadhyay +2

The dynamics of the C(P) + O() CO()+ O(D) reaction on its electronic ground state is investigated by using time-dependent wa…

physics.chem-ph2022

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…

physics.chem-ph2022

Computational Vibrational Spectroscopy

Markus Meuwly

Vibrational spectroscopy is a powerful technique to characterize the near-equilibrium dynamics of molecules in the gas- and the condensed-phase. This contribution summarizes effort…

physics.chem-ph2022

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…

physics.chem-ph2022★ 5 cited

Photodissociation dynamics of N

Sarbani Patra, Juan Carlos San Vicente Veliz, Debasish Koner +2

The photodissociation dynamics of N excited from its ground to the first excited singlet and triplet states is investigated. Three dimensional potential en…

physics.chem-ph2022

Atomistic Simulations for Reactions and Spectroscopy in the Era of Machine Learning -- Quo Vadis?

M. Meuwly

Atomistic simulations using accurate energy functions can provide molecular-level insight into functional motions of molecules in the gas- and in the condensed phase. Together with…