[Article] - AI That Enables Real-Time Analysis of Steel Microstructure Using X-Ray Diffraction
Thursday, June 4, 2026 - 17:19
Sous titre
This work introduces an AI-based method to quantify phase fractions in steels directly from X-ray diffraction data in real time. It overcomes the limitations of traditional time-consuming analysis methods and enables fast, high-throughput experiments with real-time feedback.
Abstract
This work presents a convolutional neural network capable of directly predicting phase fractions (ferrite and austenite) in steels from experimental X-ray diffraction patterns. Trained on over 40,000 synchrotron datasets spanning diverse compositions and conditions, the model achieves high accuracy (~2% error), comparable to conventional Rietveld refinement.
Importantly, predictions are obtained in milliseconds, enabling real-time analysis during high-throughput experiments and paving the way for adaptive and autonomous materials research.
Autors
Imed-Eddine Benrabah, Guillaume Geandier, Olha Nakonechna, Benoît Denand, Hugo Van Landeghem, Alexis Deschamps, Sébastien Y. P. Allain
References
Advanced Engineering Materials, 2026
DOI
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