Data-driven analysis of hydrogen embrittlement in martensitic steels with interpretable machine learning

A data-driven analytical framework integrating machine learning (ML), SHAP (SHapley Additive exPlanations) analysis, and symbolic regression (SR) was developed and applied to quantitatively analyze and interpret hydrogen embrittlement behavior in martensitic steels. Slow strain rate tests (SSRT) wer...

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Bibliographic Details

Published in:	Materials & Design
Main Authors:	Houichi Kitano, Yuuji Kimura, Akinobu Shibata
Format:	Article
Language:	English
Published:	Elsevier 2026-06-01
Subjects:	Hydrogen embrittlement Martensitic steel Machine learning Shap (shapley additive explanations) Symbolic regression
Online Access:	http://www.sciencedirect.com/science/article/pii/S0264127526006568