Practice and Insights into AI-Driven Materials R&D: “Human Effort” Determines Artificial Intelligence

Jiayu Peng is an Assistant Professor of Materials Design and Innovation at the University at Buffalo, The State University of New York. He obtained his Ph.D. in Materials Science and Engineering from the Massachusetts Institute of Technology (MIT) in 2022, and subsequently served as a Postdoctoral Associate in the same department at MIT until 2024. His research group aims to combine data science and machine learning with materials physics and surface chemistry to understand and design materials for chemical transformation and energy technologies. He has been recognized with a Graduate Student Award from the Materials Research Society, the ENFL Future Investigator Spotlight from the Division of Energy and Fuels of the American Chemical Society, the IUPAC-Zhejiang NHU International Award for Advancements in Green Chemistry for Young Chemists from the International Union of Pure and Applied Chemistry, and the Healthcare & Science List of Forbes 30 Under 30 Asia.

Zhu Liang is an Associate Research Fellow at Tan Kah Kee Innovation Laboratory of Xiamen University. He earned his Ph.D. in Condensed Matter Physics from the University of Illinois at Chicago and conducted postdoctoral research at the Brookhaven National Laboratory in the United States. He has long been engaged in the interdisciplinary field of synchrotron radiation and complex matter. His research spans physics, materials science, and artificial intelligence, covering areas such as dynamics of complex systems, physically constrained machine learning for X-ray spectroscopy inversion, structure–dynamics correlation modeling, and high-throughput discovery of electrolytes. His relevant work has been published in internationally renowned journals such as PNAS and Physical Review. Since joining Xiamen University, his team has focused on artificial intelligence-assisted research on polymer dynamics and the discovery of novel materials. This includes leveraging machine learning to uncover mesoscopic mechanisms underlying polymer rheological behavior, developing machine learning potentials suitable for polymers, and constructing physically interpretable and extrapolatable intelligent modeling systems for materials.

Piao Ma graduated from the University of Science and Technology of China (USTC), and was the recipient of the Guo Moruo Scholarship. He received his Ph.D. from the University of Texas at Austin and is currently a researcher at the Gusu Laboratory of Materials, and the CTO of Suzhou Matsource AI Technology Co., Ltd., a company dedicated to building a globally leading AI agent platform for materials research and revolutionizing the paradigm of materials development. During his doctoral studies, he conducted research in theoretical computational chemistry and published several papers in international academic journals such as JACS, and JCTC. After completing his Ph.D., he worked at Huawei as an architect and served as the chief algorithm leader for multiple storage product projects, contributing to several trade secrets, including a Huawei major trade secret. He was awarded the BMT Annual Outstanding Individual Award for wireless terminal chips and the Huawei Quality Star Award. Since 2025, he has served as an editorial board member of the international journal AI Agent and as a youth editorial board member of AI for Materials.