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Big data mining of corrosion for weathering steel in marine atmospheric environments: Discovery and mechanism of critical temperature influencing corrosion resistance

  • Bingqin Wang
  • , Xuequn Cheng*
  • , Luntao Wang
  • , Zhong Li
  • , Chao Liu
  • , Dawei Zhang
  • , Xiaogang Li
  • *此作品的通讯作者
  • University of Science and Technology Beijing

科研成果: 期刊稿件文章同行评审

摘要

In this study, 2.40 million pieces of big data related to weathering steel corrosion in marine atmospheric environments were collected. An explainable machine learning model was developed to deeply mine this dataset, complemented by laboratory experiments to validate the data-driven insights. A critical atmospheric temperature point was identified, where the corrosion rate of weathering steel is universally low. The governing mechanism primarily operates by regulating the rust layer's protective performance. When temperature deviates from this critical value, the physical state of the rust layer, chemical reaction kinetics, and wet-dry cycle durations are disrupted, leading to compromised rust layer integrity, inhibited stable phase transformation, and disruption of the thickening-transformation equilibrium, ultimately degrading the corrosion resistance of weathering steel in marine environments.

源语言英语
页(从-至)221-235
页数15
期刊Journal of Materials Science and Technology
256
DOI
出版状态已出版 - 10 6月 2026
已对外发布

联合国可持续发展目标

此成果有助于实现下列可持续发展目标:

  1. 可持续发展目标 14 - 水下生物
    可持续发展目标 14 水下生物

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