Litcius/Paper detail

Towards predictive design of electrolyte solutions by accelerating <i>ab initio</i> simulation with neural networks

Junji Zhang, Joshua Pagotto, Timothy T. Duignan

2022Journal of Materials Chemistry A16 citationsDOIOpen Access PDF

Abstract

Ab initio molecular dynamics can be massively accelerated using equivariant neural networks applicable to predict the properties of electrolyte solutions for predictive design in materials applications.

Topics & Concepts

Ab initioElectrolyteArtificial neural networkComputer scienceMassively parallelComputational chemistryMaterials scienceChemistryArtificial intelligencePhysical chemistryParallel computingOrganic chemistryElectrodeMachine Learning in Materials ScienceFuel Cells and Related MaterialsX-ray Diffraction in Crystallography