
AI-Powered Innovation in Materials Science
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Persons
Yanjing Su is a distinguished scholar and leading expert at the University of Science and Technology Beijing in materials big data, artificial intelligence, and corrosion science. With extensive expertise spanning fundamental research and industrial applications, he has made seminal contributions to the development of data-driven materials science and next-generation corrosion-resistant alloys. As a key advisor to China's national scientific initiatives, he serves on multiple high-level expert committees, including the Ministry of Industry and Information Technology's "Materials Genome Engineering Key Technologies" program, the National Key R&D Program on "Rare Earth New Materials," and the NSFC's major research plan on explainable AI technologies. His work has resulted in over 300 publications in top-tier journals including Acta Materialia, Corrosion Science, and npj Computational Materials, along with 4 influential academic monographs. His achievements have been recognized with numerous honors, including the National First Prize for Educational Achievement (China's highest teaching award) and six provincial/ministerial awards for scientific and technological progress. The integrated Materials Genome Engineering Platform he developed, combining databases, data acquisition, and machine learning tools, has become a valuable resource for both academic research and industrial R&D.
Content
Chapter 2: Fundamentals of Language Models and NLP
Chapter 3: Reinforcement Learning in Materials
Chapter 4: Large Language Models for Materials
Chapter 5: Materials Data Extraction from Literature by NLP and Large Language Models
Chapter 6: Predictive Modeling with Language-Augmented Approaches
Chapter 7: Chapter 7 Conversational Large Language Models for Materials Research
Chapter 8: Materials Agents for Autonomous Research
Chapter 9: Challenges and Future Developments
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