Author

Guanghui Zhang

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Open access Sep 2026

Empowering material defect research with machine learning

: Material defects govern the performance limits, degradation pathways, and service lifetimes of functional and structural materials, yet their predictive modeling remains difficult because local electronic reconstruction, long-range interactions, rare kinetic events, and finite-temperature effects are coupled across s...

Fei-Fei Ren, Shi-Jie Hu, Guang-Hui Zhang et al. · AI & Materials · 0 citations

Preprint Jul 2026

SAGE-Net: Semantics-Augmented Geometric Encoder for Material Property Prediction

Reliable structure-property modeling is crucial for accelerating materials discovery, where crystal graphs and structure-derived crystallographic descriptions provide complementary geometric and semantic information. Existing multimodal materials models primarily incorporate textual information through post-encoding fu...

Guanghui Zhang, Yuxuan Yao, Kieran B. Spooner et al. · 0 citations