Graph neural networks are central to materials property prediction and machine-learning interatomic potentials, yet their reliance on specialized graph libraries hampers portability and reproducibility, and property and force-field models have historically required separate graph pipelines. We present ALIGNN 2.0, a dep...
Jaehyung Lee, C. R. Campbell, Akshaya Ajith et al.· 0 citations
X-ray diffraction (XRD) is fundamental to structural materials characterization, yet transforming a raw powder pattern into a refined crystal structure still demands considerable domain expertise. We present AGAPI-XRD, a hybrid framework integrating DiffractGPT generative structure prediction, database pattern matching...
C. R. Campbell, J. Ely, Jaehyung Lee et al.· 0 citations
This work presents and evaluates the AtomGPT reference checker, an open, web-accessible tool that verifies citations against the scholarly literature by combining large-language-model field extraction with structured retrieval from Semantic Scholar.
Harichandana Neralla, Jaehyung Lee, Aldo H. Romero et al.· 0 citations
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