Quantifying exchange forces of a spin spiral on the atomic scale | Nature Communications
PDF) Physically informed artificial neural networks for atomistic modeling of materials
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
Modeling materials using density functional theory
Atomistic Simulations of Pure Tin Based on a New Modified Embedded-Atom Method Interatomic Potential
Literature — GPAW
a) Solution enthalpy of Cr in Fe calculated with PAW as a function of... | Download Scientific Diagram
Efficient training of ANN potentials by including atomic forces via Taylor expansion and application to water and a transition-metal oxide | npj Computational Materials
Orbital-free density functional theory implementation with the projector augmented-wave method: The Journal of Chemical Physics: Vol 141, No 23
Efficient training of ANN potentials by including atomic forces via Taylor expansion and application to water and a transition-metal oxide | npj Computational Materials
Lattice dynamics simulation using machine learning interatomic potentials - ScienceDirect
Molecular Dynamics Simulation: From “Ab Initio” to “Coarse Grained” | SpringerLink
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
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
Fast Neural Network Approach for Direct Covariant Forces Prediction in Complex Multi-Element Extended Systems
Atomic force microscopy technique used for assessment of the anti-arthritic effect of licochalcone A via suppressing NF-κB activation - ScienceDirect
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
Efficient training of ANN potentials by including atomic forces via Taylor expansion and application to water and a transition-metal oxide | npj Computational Materials
The oxygen-oxygen-oxygen triplet angular distribution and tetrahedral... | Download Scientific Diagram
Modeling atomic force microscopy at LiNbO3 surfaces from first-principles - ScienceDirect
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)
arXiv:2004.13158v2 [physics.comp-ph] 21 Sep 2020
56 questions with answers in PSEUDOPOTENTIAL | Science topic
