Understanding oxidation of Fe-Cr-Al alloys through explainable artificial intelligence

Roy, Indranil; Feng, Bojun; Roychowdhury, Subhrajit; Ravi, Sandipp Krishnan; Umretiya, Rajnikant V.; Reynolds, Christopher; Ghosh, Sayan; Rebak, Raul B.; Hoffman, Andrew

doi:10.1557/s43579-022-00315-0

Understanding oxidation of Fe-Cr-Al alloys through explainable artificial intelligence

Journal Article · 08 January 2023 · MRS communications

DOI:https://doi.org/10.1557/s43579-022-00315-0· OSTI ID:2418376

^[1]; Feng, Bojun; Roychowdhury, Subhrajit; Ravi, Sandipp Krishnan; Umretiya, Rajnikant V.; Reynolds, Christopher; Ghosh, Sayan; Rebak, Raul B.; Hoffman, Andrew

OSTI

Abstract

The oxidation resistance of FeCrAl based on alloying composition and oxidizing conditions is predicted using a combinatorial experimental and artificial intelligence approach. A neural network (NN) classification model was trained on the experimental FeCrAl dataset produced at GE Research. Furthermore, using the SHapley Additive exPlanations (SHAP) explainable artificial intelligence (XAI) tool, we explore how the NN can showcase further material insights that are unavailable directly from a black-box model. We report that high Al and Cr content forms protective oxide layer, while Mo in FeCrAl creates thick unprotective oxide scale that is vulnerable to spallation due to thermal expansion.

Graphical abstract

Research Organization:: GE Packaged Power, LLC, Houston, TX (United States)

Sponsoring Organization:: USDOE Office of Nuclear Energy (NE)

DOE Contract Number:: NE0009047

OSTI ID:: 2418376

Journal Information:: MRS communications, Journal Name: MRS communications Journal Issue: 1 Vol. 13; ISSN 2159-6867

Publisher:: Springer Nature

Country of Publication:: United States

Language:: English

References (17)

Effect of aluminum on the FeCr(Al) alloy oxidation resistance in steam environment at low temperature (400 °C) and high temperature (1200 °C) Chikhalikar, Atharva; Roy, Indranil; Abouelella, Hamdy Corrosion Science, Vol. 209 https://doi.org/10.1016/j.corsci.2022.110765	journal	December 2022
A machine learning-based alloy design system to facilitate the rational design of high entropy alloys with enhanced hardness Yang, Chen; Ren, Chang; Jia, Yuefei Acta Materialia, Vol. 222 https://doi.org/10.1016/j.actamat.2021.117431	journal	January 2022
Utilizing FeCrAl Oxidation Resistance Properties in Water, Air and Steam for Accident Tolerant Fuel Cladding Gupta, Vipul K.; Larsen, Michael; Rebak, Raul B. ECS Transactions, Vol. 85, Issue 2 https://doi.org/10.1149/08502.0003ecst	journal	April 2018
Predictions and mechanism analyses of the fatigue strength of steel based on machine learning Yan, Feng; Song, Kai; Liu, Ying Journal of Materials Science, Vol. 55, Issue 31 https://doi.org/10.1007/s10853-020-05091-7	journal	July 2020
GPUTreeShap: massively parallel exact calculation of SHAP scores for tree ensembles Mitchell, Rory; Frank, Eibe; Holmes, Geoffrey PeerJ Computer Science, Vol. 8 https://doi.org/10.7717/peerj-cs.880	journal	April 2022
In situ process quality monitoring and defect detection for direct metal laser melting Felix, Sarah; Ray Majumder, Saikat; Mathews, H. Kirk Scientific Reports, Vol. 12, Issue 1 https://doi.org/10.1038/s41598-022-12381-4	journal	May 2022
Data-Guided Feature Identification for Predicting Specific Heat of Multicomponent Alloys Roy, Ankit; Roy, Indranil; Santodonato, Louis J. JOM, Vol. 74, Issue 4 https://doi.org/10.1007/s11837-022-05183-6	journal	February 2022
Machine learning of mechanical properties of steels Xiong, Jie; Zhang, TongYi; Shi, SanQiang Science China Technological Sciences, Vol. 63, Issue 7 https://doi.org/10.1007/s11431-020-1599-5	journal	May 2020
Machine-learning-guided descriptor selection for predicting corrosion resistance in multi-principal element alloys Roy, Ankit; Taufique, M. F. N.; Khakurel, Hrishabh npj Materials Degradation, Vol. 6, Issue 1 https://doi.org/10.1038/s41529-021-00208-y	journal	January 2022
Data-driven predictive modeling of FeCrAl oxidation Roy, Indranil; Roychowdhury, Subhrajit; Feng, Bojun Materials Letters: X, Vol. 17 https://doi.org/10.1016/j.mlblux.2023.100183	journal	March 2023
Explainable AI: A Review of Machine Learning Interpretability Methods Linardatos, Pantelis; Papastefanopoulos, Vasilis; Kotsiantis, Sotiris Entropy, Vol. 23, Issue 1 https://doi.org/10.3390/e23010018	journal	December 2020
Machine-learning-assisted prediction of the mechanical properties of Cu-Al alloy Deng, Zheng-hua; Yin, Hai-qing; Jiang, Xue International Journal of Minerals, Metallurgy and Materials, Vol. 27, Issue 3 https://doi.org/10.1007/s12613-019-1894-6	journal	March 2020
Examining oxidation in β-NiAl and β-NiAl+Hf alloys by stochastic cellular automata simulations Roy, Indranil; Ray, Pratik K.; Balasubramanian, Ganesh npj Materials Degradation, Vol. 5, Issue 1 https://doi.org/10.1038/s41529-021-00202-4	journal	November 2021
Machine learning of phases and mechanical properties in complex concentrated alloys Xiong, Jie; Shi, San-Qiang; Zhang, Tong-Yi Journal of Materials Science & Technology, Vol. 87 https://doi.org/10.1016/j.jmst.2021.01.054	journal	October 2021
Steam Oxidation Behavior of FeCrAl Cladding Pint, B. A.; Terrani, K. A.; Rebak, R. B. The Minerals, Metals & Materials Series https://doi.org/10.1007/978-3-030-04639-2_96	book	October 2017
High-Dimensional Materials and Process Optimization Using Data-Driven Experimental Design with Well-Calibrated Uncertainty Estimates Ling, Julia; Hutchinson, Maxwell; Antono, Erin Integrating Materials and Manufacturing Innovation, Vol. 6, Issue 3 https://doi.org/10.1007/s40192-017-0098-z	journal	July 2017
Effect of Al and Cr Content on Air and Steam Oxidation of FeCrAl Alloys and Commercial APMT Alloy Unocic, Kinga A.; Yamamoto, Yukinori; Pint, Bruce A. Oxidation of Metals, Vol. 87, Issue 3-4 https://doi.org/10.1007/s11085-017-9745-1	journal	March 2017

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