Detecting deformation mechanisms of metals from acoustic emission signals through knowledge-driven unsupervised learning

Journal:

Nature Communications

Published:

2025-07-25

DOI:

10.1038/s41467-025-61707-z

Affiliations:

4

Authors:

7

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Institutions	Authors	Share
State Key Laboratory for Mechanical Behavior of Materials, XJTU, China	5.000000	0.71
Xi'an Jiaotong University (XJTU), China	1.000000	0.14
AiMaterials Research LLC, United States of America (USA)	0.500000	0.07
University of Cambridge, United Kingdom (UK)	0.500000	0.07

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