2023
DOI: 10.1557/s43579-022-00315-0
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Understanding oxidation of Fe-Cr-Al alloys through explainable artificial intelligence

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. W… Show more

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Cited by 5 publications
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