Integrating machine learning with advanced processing and characterization for polycrystalline materials: a methodology review and application to iron-based superconductors

In this review, we present a new set of machine learning-based materials research methodologies for polycrystalline materials developed through the Core Research for Evolutionary Science and Technology project of the Japan Science and Technology Agency. We focus on the constituents of polycrystallin...

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Bibliographic Details

Published in:	Science and Technology of Advanced Materials
Main Authors:	Akiyasu Yamamoto, Akinori Yamanaka, Kazumasa Iida, Yusuke Shimada, Satoshi Hata
Format:	Article
Language:	English
Published:	Taylor & Francis Group 2025-12-01
Subjects:	Bayesian optimization BOXVIA data assimilation data-driven process design deep learning DFT
Online Access:	https://www.tandfonline.com/doi/10.1080/14686996.2024.2436347