(Lecture, June 18) Intelligent chemical industry and AI enabling scientific discovery in the era of large models
Title：Smart chemicals and AI in the era of large models empower scientific discovery
Time: June 18, 2024 (Tuesday) 11:00 am - 12:00 am
Venue: Conference room 214, Building 16
[Biography]
Wang Xiaonan is an associate professor, researcher and doctoral supervisor of the Department of Chemical Engineering of Tsinghua University, honorary professor of the National University of Singapore, chief scientist and project leader of the National Science and Technology Major project of the new generation of Artificial Intelligence, and President of the Sustainable Development field of the American Institute of Chemical Engineers (AIChE). Selected by the National High-level Young Talent Program. Led the team to conduct research on AI+ energy chemical materials. He has published more than 150 academic papers in Nature Machine Intelligence, Nature Synthesis and Nature Reviews journals, including 13 ESI highly cited papers, cited more than 8000 times, and H-index 51. He received his bachelor's degree in Chemical Engineering from Tsinghua University in 2011 and his PhD in Chemical Engineering and Control science from the University of California, Davis in 2015. He went to Imperial College London as a postdoctoral researcher and master's supervisor. Since 2017, he has been Assistant Professor and doctoral supervisor of Chemical and biomolecular Engineering at the National University of Singapore. She has served as deputy editor and editorial board member of ten international journals including Applied Energy, won the American Chemical Society Sustainable Chemistry and Engineering Lecture Award, Cell Press China Women Scientist Award, Hou Debang Chemical Science and Technology Award "Youth Award", Forbes China Women in Science and Technology 50, Singapore Outstanding Young Principal Researcher Award, the Royal Society International Exchange Award and other awards. He was selected as one of the world's top 2% top scientists by Elsevier for three consecutive years.
[Abstract]
In recent years, the rapid development of Artificial Intelligence (AI) technology has brought new impetus to chemical, materials, energy and other fields. The intelligent chemical technology guided by AI integration is expected to break through the traditional model of long research and development cycle, high cost and reliance on experience, and enable new scientific discoveries. This report will introduce the progress of Artificial Intelligence, especially AI large models in molecular design, chemical synthesis, characterization analysis, mechanism discovery and other aspects, and analyze AI+ methods and application examples with typical systems such as single-molecule surface synthesis of carbon-based quantum materials, intelligent fabrication of separated membrane materials and intelligent design synthesis of industrial catalysts as examples. The report will introduce the research progress of general purpose large models in the field, and analyze the potential and advantages and disadvantages of related technologies.
Announced by School of Chemistry and Chemical Engineering
