articleJournal of Material Science and TechnologyFeb 12, 2026Closed access

Deep learning-driven innovation in metallic materials: A comprehensive review on microstructure analysis, property prediction, and inverse design

YSYulin ShengcaoXQXu QinQWQinghang WangHYHuabao YangYCYanfu Chai

Yangzhou University · IMDEA Materials · +4 more institutions

Indexed incrossref

Abstract

No abstract available for this paper.

Citation impact

5
total citations
FWCI
42.26
Percentile
100%
References
146
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Authors

8

Topics & keywords

Topics
Keywords
  • Property (philosophy)
  • Microstructure
  • Inverse
  • Tracing
  • Generative grammar
  • Characterization (materials science)
  • Key (lock)
  • Inverse problem
UN Sustainable Development Goals
  • Industry, innovation and infrastructure
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