Litcius/Paper detail

Prediction of vacancy formation energies at tungsten grain boundaries from local structure via machine learning method

Yuxuan Wang, Xiaolin Li, Xiaolin Li, Xiangyan Li, Xiangyan Li, Yuxiang Zhang, Yange Zhang, Yichun Xu, Yawei Lei, Changlan Liu, Xuebang Wu

2021Journal of Nuclear Materials21 citationsDOI

Topics & Concepts

Grain boundaryTungstenVacancy defectSupport vector machineDislocationKernel (algebra)Hybrid functionalBoundary (topology)Materials scienceAlgorithmArtificial intelligenceChemistryComputer scienceMathematicsCrystallographyDensity functional theoryMathematical analysisComputational chemistryMetallurgyMicrostructureCombinatoricsFusion materials and technologiesNuclear Materials and PropertiesAdvanced materials and composites