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Simultaneous analysis of the chemical composition and surface flatness of steel using laser-induced breakdown spectroscopy combined with a multi-task convolutional neural network

Ye, Jinrui, Li, Yaju, Zhang, Zhao, Zeng, Qiang, Wu, Yifan, Liu, Xueqi, Zhang, Yanshi, Qian, Dongbin, Liu, Zuoye, Yang, Lei, Zhang, Shaofeng, Ma, Xinwen·2025·Journal of Analytical Atomic Spectrometry
DOI 10.1039/d5ja00110b
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Abstract

An approach for simultaneous multi-element and flatness analyses of steel materials using LIBS combined with a multi-task CNN and its interpretability.

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Cited by 4

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Metadata

Authors
Ye, J., Li, Y., Zhang, Z., Zeng, Q., Wu, Y., Liu, X., Zhang, Y., Qian, D., Liu, Z., Yang, L., Zhang, S., & Ma, X.
Venue
Journal of Analytical Atomic Spectrometry
Publisher
Royal Society of Chemistry (RSC)
Published
2025
Volume
40
Issue
9
Pages
2538-2547
ISSN
  • 0267-9477
  • 1364-5544
DOI
10.1039/d5ja00110b
Cited by
4
Language
en
Licence
rsc.li/journals-terms-of-use (am, 570 d)
Funders
  • National Key Research and Development Program of China (2017YFA0402300)
  • Chinese Academy of Sciences (XDB1130401)
  • National Natural Science Foundation of China (U2241288)

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CoChat. (2026). Citation check: Simultaneous analysis of the chemical composition and surface flatness of steel using laser-induced breakdown spectroscopy combined with a multi-task convolutional neural network. https://app.cochat.ai/papers/10.1039/d5ja00110b
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Ye, J., Li, Y., Zhang, Z., Zeng, Q., Wu, Y., Liu, X., Zhang, Y., Qian, D., Liu, Z., Yang, L., Zhang, S., & Ma, X. (2025). Simultaneous analysis of the chemical composition and surface flatness of steel using laser-induced breakdown spectroscopy combined with a multi-task convolutional neural network. Journal of Analytical Atomic Spectrometry. https://doi.org/10.1039/d5ja00110b