fig13

Advances in graph neural networks for alloy design and properties predictions: a review

Figure 13. Graph-neural model for atomic-stress prediction in defect-containing crystals. Atoms serve as nodes tagged by grain ID, nearest-neighbor bonds form edges, and message passing embeds grain-boundary and defect context before stress read-out. Adapted from Ref.[77]. © 2022 The Authors.

Journal of Materials Informatics
ISSN 2770-372X (Online)
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