1. Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China
2. Yunnan Key Laboratory of Artificial Intelligence, Kunming University of Science and Technology, Kunming 650500, China
3. Faculty of Materials Science and Engineering, Kunming University of Science and Technology, Kunming 650093 China
4. Key Laboratory of Materials Genetic Engineering, Kunming University of Science and Technology, Kunming 650093, China
Steel is the core metal material in the world, and the rapid development of the times has new requirements for the properties of steel materials. However, the design of steel materials currently involves combinations of over millions of elements and process parameters, leading the design and development of steel materials by traditional trial-and-error method slower and more expensive.Machine learning technology has been widely used to guide the development and design of materials, which has emerged as a novel methodology and a trending domain in the field of materials research. In this paper, the application progress of machine learning in the research of steel materials were summarized, the working process and common algorithms of machine learning were introduced. Meanwhile, the research progress of machine learning in steel materials feature selection, composition-processperformance prediction, service behavior prediction and reverse design were reviewed. Finally, the problems of machine learning technology in the field of steel materials were analyzed and the development prospects were forecasted.