Machine learning force fields
In recent years, the use of machine learning (ML) in computational chemistry has enabled
numerous advances previously out of reach due to the computational complexity of …
numerous advances previously out of reach due to the computational complexity of …
Vibrational spectroscopy by means of first‐principles molecular dynamics simulations
Vibrational spectroscopy is one of the most important experimental techniques for the
characterization of molecules and materials. Spectroscopic signatures retrieved in …
characterization of molecules and materials. Spectroscopic signatures retrieved in …
[HTML][HTML] CP2K: An electronic structure and molecular dynamics software package-Quickstep: Efficient and accurate electronic structure calculations
CP2K is an open source electronic structure and molecular dynamics software package to
perform atomistic simulations of solid-state, liquid, molecular, and biological systems. It is …
perform atomistic simulations of solid-state, liquid, molecular, and biological systems. It is …
Automated fitting of neural network potentials at coupled cluster accuracy: Protonated water clusters as testing ground
Highly accurate potential energy surfaces are of key interest for the detailed understanding
and predictive modeling of chemical systems. In recent years, several new types of force …
and predictive modeling of chemical systems. In recent years, several new types of force …
Pure non-local machine-learned density functional theory for electron correlation
JT Margraf, K Reuter - Nature communications, 2021 - nature.com
Density-functional theory (DFT) is a rigorous and (in principle) exact framework for the
description of the ground state properties of atoms, molecules and solids based on their …
description of the ground state properties of atoms, molecules and solids based on their …
Reducing the cost of neural network potential generation for reactive molecular systems
K Brezina, H Beck, O Marsalek - Journal of Chemical Theory and …, 2023 - ACS Publications
Although machine learning potentials have recently had a substantial impact on molecular
simulations, the construction of a robust training set can still become a limiting factor …
simulations, the construction of a robust training set can still become a limiting factor …
Structure and dynamics of the instantaneous water/vapor interface revisited by path-integral and ab initio molecular dynamics simulations
J Kessler, H Elgabarty, T Spura, K Karhan… - The Journal of …, 2015 - ACS Publications
The structure and dynamics of the water/vapor interface is revisited by means of path-
integral and second-generation Car–Parrinello ab initio molecular dynamics simulations in …
integral and second-generation Car–Parrinello ab initio molecular dynamics simulations in …
Opposing Electronic and Nuclear Quantum Effects on Hydrogen Bonds in H2O and D2O
The effect of extending the O− H bond length (s) in water on the hydrogen‐bonding strength
has been investigated using static ab initio molecular orbital calculations. The “polar …
has been investigated using static ab initio molecular orbital calculations. The “polar …
Correlated dynamics in aqueous proton diffusion
SA Fischer, BI Dunlap, D Gunlycke - Chemical science, 2018 - pubs.rsc.org
The aqueous proton displays an anomalously large diffusion coefficient that is up to 7 times
that of similarly sized cations. There is general consensus that the proton achieves its high …
that of similarly sized cations. There is general consensus that the proton achieves its high …
Reduced rovibrational coupling Cartesian dynamics for semiclassical calculations: Application to the spectrum of the Zundel cation
We study the vibrational spectrum of the protonated water dimer, by means of a divide-and-
conquer semiclassical initial value representation of the quantum propagator, as a first step …
conquer semiclassical initial value representation of the quantum propagator, as a first step …