End‐to‐End Crystal Structure Prediction from Powder X‐Ray Diffraction

End‐to‐End Crystal Structure Prediction from Powder X‐Ray Diffraction

Abstract Powder X‐ray diffraction (PXRD) is a prevalent technique in materials characterization. While the analysis of PXRD often requires extensive human manual intervention, and most automated method only achieved at coarse‐grained level. The more difficult and important task of fine‐grained cryst...

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Bibliographic Details
Main Authors: Qingsi Lai, Fanjie Xu, Lin Yao, Zhifeng Gao, Siyuan Liu, Hongshuai Wang, Shuqi Lu, Di He, Liwei Wang, Linfeng Zhang, Cheng Wang, Guolin Ke
Format: Article
Language:English
Published: Wiley 2025-02-01
Series:Advanced Science
Subjects:
crystal structure prediction
deep learning
equivariant deep generative model
metal–organic frameworks (MOFs)
powder X‐ray diffraction
Online Access:https://doi.org/10.1002/advs.202410722
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https://doi.org/10.1002/advs.202410722

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