A fast neural network approach for direct covariant forces prediction in complex multi-element extended systems | Nature Machine Intelligence
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
Molecular Dynamics Simulation: From “Ab Initio” to “Coarse Grained” | SpringerLink
Atomic force microscopy technique used for assessment of the anti-arthritic effect of licochalcone A via suppressing NF-κB activation - ScienceDirect
arXiv:1905.02794v2 [cond-mat.mtrl-sci] 21 Aug 2019
Nonadiabatic Ehrenfest molecular dynamics within the projector augmented-wave method: The Journal of Chemical Physics: Vol 136, No 14
Lattice dynamics simulation using machine learning interatomic potentials - ScienceDirect
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 simple molecular mechanics potential for μm scale graphene simulations from the adaptive force matching method: The Journal of Chemical Physics: Vol 134, No 18
color online) Top view of Cu(001) surface-layer-atoms, second-layer... | Download Scientific Diagram
Quantifying the evolution of atomic interaction of a complex surface with a functionalized atomic force microscopy tip | Scientific Reports
arXiv:2004.13158v2 [physics.comp-ph] 21 Sep 2020
56 questions with answers in PSEUDOPOTENTIAL | Science topic
Fast Neural Network Approach for Direct Covariant Forces Prediction in Complex Multi-Element Extended Systems
Atomic Interactions - Interaction Potential | Atomic Bonding | Van der Waals Force - PhET Interactive Simulations
Modeling materials using density functional theory
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
An experimentally validated neural-network potential energy surface for H- atom on free-standing graphene in full dimensionality - Physical Chemistry Chemical Physics (RSC Publishing)
Efficient training of ANN potentials by including atomic forces via Taylor expansion and application to water and a transition-metal oxide | npj Computational Materials
PDF) Physically informed artificial neural networks for atomistic modeling of materials
Quantifying the evolution of atomic interaction of a complex surface with a functionalized atomic force microscopy tip | Scientific Reports
Figure 1 from Globally-Optimized Local Pseudopotentials for (Orbital-Free) Density Functional Theory Simulations of Liquids and Solids. | Semantic Scholar
Orbital-free density functional theory implementation with the projector augmented-wave method: The Journal of Chemical Physics: Vol 141, No 23
56 questions with answers in PSEUDOPOTENTIAL | Science topic
