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AI+时代材料基因工程与智能科学的研究进展与挑战

武雅洁 李佩璇 卢佳琦 刘硕 樊晓倩 王毅 李金山

铸造技术2026,Vol.47Issue(1):1-15,15.
铸造技术2026,Vol.47Issue(1):1-15,15.DOI:10.16410/j.issn1000-8365.2026.5116

AI+时代材料基因工程与智能科学的研究进展与挑战

Research Progress and Challenges of Materials Genome Engineering and Intelligent Science in the AI+Era

武雅洁 1李佩璇 1卢佳琦 1刘硕 1樊晓倩 1王毅 1李金山1

作者信息

  • 1. 西北工业大学中国-哈萨克斯坦材料基因工程与智能科学"一带一路"联合实验室,陕西 西安 710072||西北工业大学凝固技术全国重点实验室,陕西 西安 710072
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摘要

Abstract

As a strategic and fundamental industry,new materials represent a crucial industrial direction for accelerating the development of new-quality products and steadily promoting high-quality development.Materials genome engineering(MGE)deeply integrates computational simulation,high-throughput experiments,and data science,significantly enhancing the R&D efficiency of new materials.Its material databases and cross-scale models are becoming the technological foundation for the in-depth application of artificial intelligence in material design,performance prediction,and other aspects.With the rapid development of artificial intelligence technology,the combination of MGE and intelligent science is facing unprecedented opportunities and challenges.This paper reviews the background and history of the emergence of artificial intelligence in materials in the AI+era,as well as its material data infrastructure and the AI technologies used.It summarizes the applications of technologies such as machine learning and natural language processing in material reverse design and screening,physical property prediction and characterization analysis,and performance optimization.It also introduces the paradigm innovation of autonomous laboratory systems.Finally,this paper looks ahead to the potential challenges that AI may face in the field of materials science and proposes directions and suggestions for future improvement.

关键词

材料基因工程/人工智能/数字化贯通/智能科学

Key words

materials genome initiative/artificial intelligence/digital integration/intelligent science

分类

通用工业技术

引用本文复制引用

武雅洁,李佩璇,卢佳琦,刘硕,樊晓倩,王毅,李金山..AI+时代材料基因工程与智能科学的研究进展与挑战[J].铸造技术,2026,47(1):1-15,15.

铸造技术

1000-8365

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