Machine-Learning Interatomic Potential for Radiation Damage and Defects in Tungsten

Physical Review B- United States

doi 10.1103/physrevb.100.144105

Full Text

Abstract

Available in

Date

Authors

Publisher

American Physical Society (APS)

Related search

Phonon Optimized Interatomic Potential for Aluminum

AIP Advances
NanotechnologyAstronomyPhysicsNanoscience
2017English

Optimizing Many-Body Atomic Descriptors for Enhanced Computational Performance of Machine Learning Based Interatomic Potentials

Physical Review B
OpticalElectronicCondensed Matter PhysicsMagnetic Materials
2019English

Trapping of Hydrogen Isotopes in Radiation Defects Formed in Tungsten by Neutron and Ion Irradiations

Journal of Nuclear Materials
High Energy PhysicsMaterials ScienceEngineeringNuclear EnergyNuclear
2013English

Magnesium Interatomic Potential for Simulating Plasticity and Fracture Phenomena

Modelling and Simulation in Materials Science and Engineering
Mechanics of MaterialsMaterials ScienceCondensed Matter PhysicsSimulationComputer Science ApplicationsModeling
2014English

Development of a Machine Learning Potential for Graphene

Physical Review B
OpticalElectronicCondensed Matter PhysicsMagnetic Materials
2018English

Potential Radiation Damage: Storage Tanks for Liquid Radioactive Waste

1992English

In-Situ Helium Implantation and TEM Investigation of Radiation Tolerance to Helium Bubble Damage in Equiaxed Nanocrystalline Tungsten and Ultrafine Tungsten-TiC Alloy

Materials
Materials ScienceCondensed Matter Physics
2020English

Natural Radiation-Induced Damage in Quartz. I. Correlations Between Cathodoluminence Colors and Paramagnetic Defects

Canadian Mineralogist
PetrologyGeochemistry
2005English

Machine Learning: Technologies and Potential Application at Mining Companies

E3S Web of Conferences
EarthEnergyPlanetary SciencesEnvironmental Science
2020English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2026 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy