MatPilot: an LLM-enabled AI Materials Scientist under the Framework of Human-Machine Collaboration

EXTENDED ABSTRACT: TThe rapid evolution of artificial intelligence, particularly large language models, presents unprecedented opportunities for materials science research. We proposed and developed an AI materials scientist named MatPilot, which has shown encouraging abilities in the discovery of new materials. The core strength of MatPilot is its natural language interactive human-machine collaboration, which augments the research capabilities of human scientist teams through a multi-agent system. MatPilot integrates unique cognitive abilities, extensive accumulated experience, and ongoing curiosity of human-beings with the AI agents' capabilities of advanced abstraction, complex knowledge storage and highdimensional information processing. It could generate scientiffc hypotheses and experimental schemes, and employ predictive models and optimization algorithms to drive an automated experimental platform for experiments. It turns out that our system demonstrates capabilities for efffcient validation, continuous learning, and iterative optimization.

Keywords: Framework of Human-Machine Collaboration; Multi-agent; AI Materials Scientist; Large Language Model; Autonomous Experimentation Platform

Brief Introduction of Speaker
Ye Yicong

Ye Yicong is a professor at the College of Aerospace Science and Engineering, National University of Defense Technology. He obtained his PhD from Tsinghua University in 2011. His research primarily focuses on artiffcial intelligence-assisted materials design. He has published over 90 journal articles. He has received two ffrst-class military progress prizes in science and technology and has been selected for the youth talent program.