Predicting hydrogen segregation energy distributions in strained regions of tungsten using artificial neural network

Predicting hydrogen segregation energy distributions in strained regions of tungsten using artificial neural network

Employing the smooth overlap of atomic position (SOAP) descriptors, we established an artificial neural network (ANN) model with the ability to effectively and accurately predict the segregation energy Eseg distributions of hydrogen (H) atoms in various strained regions of tungsten (W). The model is...

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Bibliographic Details
Main Authors: Ke Xu, Shuo Jin, Guang-Hong Lu
Format: Article
Language:English
Published: Elsevier 2024-06-01
Series:Nuclear Materials and Energy
Subjects:
Tungsten
Hydrogen
Machine learning
Artificial neural network
Segregation energy
Online Access:http://www.sciencedirect.com/science/article/pii/S2352179124000607

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http://www.sciencedirect.com/science/article/pii/S2352179124000607

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