AI-Empowered Materials Design: Transforming Collaboration Paradigms and Overcoming Incentive Barriers

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Linfeng Zhang

DP Technology and AI for Science Institute, Beijing, China

The rapid evolution of AI-assisted materials design demands collaborative efforts that transcend traditional academic and industrial paradigms. However, differing incentive structures—academia's focus on publishing and industry's focus on profits—pose significant challenges. In this talk, I will discuss strategies to foster such initiatives, drawing from my experiences in algorithm and model design, open-source software development, and creating computing platforms for teaching, research, and competitions. I will also highlight the importance of bridging computation and experimentation into intelligent closed-loop systems. These efforts underscore the need for interdisciplinary cooperation and innovative incentive models to advance AI-driven materials design.