Efficient training of ANN potentials by including atomic forces via Taylor expansion and application to water and a transition-metal oxide | npj Computational Materials
First-principles simulations of atomic geometries, electronic properties and chemical reactions at interfaces
An experimentally validated neural-network potential energy surface for H- atom on free-standing graphene in full dimensionality - Physical Chemistry Chemical Physics (RSC Publishing)
The oxygen-oxygen-oxygen triplet angular distribution and tetrahedral... | Download Scientific Diagram
A simple molecular mechanics potential for μm scale graphene simulations from the adaptive force matching method: The Journal of Chemical Physics: Vol 134, No 18
PDF) Efficient training of ANN potentials by including atomic forces via Taylor expansion and application to water and a transition-metal oxide
Modeling materials using density functional theory
Nonadiabatic Ehrenfest molecular dynamics within the projector augmented-wave method: The Journal of Chemical Physics: Vol 136, No 14
Efficient training of ANN potentials by including atomic forces via Taylor expansion and application to water and a transition-metal oxide | npj Computational Materials
Quantifying exchange forces of a spin spiral on the atomic scale | Nature Communications
Atomic Interactions - Interaction Potential | Atomic Bonding | Van der Waals Force - PhET Interactive Simulations
56 questions with answers in PSEUDOPOTENTIAL | Science topic
Effect of an acetylene bond on hydrogen adsorption in diamond-like carbon allotropes: from first principles to atomic simulation - Physical Chemistry Chemical Physics (RSC Publishing)
56 questions with answers in PSEUDOPOTENTIAL | Science topic
Rational design of transition metal single-atom electrocatalysts: a simulation-based, machine learning-accelerated study - Journal of Materials Chemistry A (RSC Publishing)
Fast Neural Network Approach for Direct Covariant Forces Prediction in Complex Multi-Element Extended Systems
a) Solution enthalpy of Cr in Fe calculated with PAW as a function of... | Download Scientific Diagram
Water graphene contact surface investigated by pairwise potentials from force-matching PAW-PBE with dispersion correction: The Journal of Chemical Physics: Vol 146, No 5
Efficient training of ANN potentials by including atomic forces via Taylor expansion and application to water and a transition-metal oxide | npj Computational Materials
Molecular Dynamics Simulation: From “Ab Initio” to “Coarse Grained” | SpringerLink
Literature — GPAW
Efficient training of ANN potentials by including atomic forces via Taylor expansion and application to water and a transition-metal oxide | npj Computational Materials
Efficient training of ANN potentials by including atomic forces via Taylor expansion and application to water and a transition-metal oxide | npj Computational Materials
A fast neural network approach for direct covariant forces prediction in complex multi-element extended systems | Nature Machine Intelligence
arXiv:1905.02794v2 [cond-mat.mtrl-sci] 21 Aug 2019
Molecular Dynamics Simulation: From “Ab Initio” to “Coarse Grained” | SpringerLink
