200-strong researcher network fuels Yaghi’s AI materials lab at Tsinghua

The AI community should take note: a Nobel laureate’s move to Tsinghua isn’t just academic politics—it’s a strategic bet that machine learning will dominate the next era of materials discovery. Yaghi’s center will use AI to navigate the astronomical combinatorial space of metal-organic frameworks, promising the same revolution AlphaFold brought to biology. With a talent pool of 200 trained researchers and state backing, this could accelerate the emergence of AI-designed materials that capture carbon, generate water, and store energy, shifting the center of gravity for AI-for-science eastward.

In a move that underscores the intensifying global competition for scientific talent and the accelerating convergence of artificial intelligence with foundational research, Nobel Prize-winning chemist Omar Yaghi has left the University of California, Berkeley, to establish a new AI-driven research center at China’s Tsinghua University. The 61-year-old materials scientist, who shared the 2025 Nobel Prize for his pioneering work on metal-organic frameworks (MOFs), was appointed to lead a team that will apply AI to transform the design and synthesis of novel materials. Tsinghua announced that the center aims to shorten the development cycle of new materials “by orders of magnitude,” a claim that, if realized, could disrupt materials science as fundamentally as AI has transformed drug discovery and genomics.

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Yaghi’s center will use AI to navigate the astronomical combinatorial space of metal-organic frameworks, promising the same revolution AlphaFold brought to biology.

Yaghi’s departure from Berkeley—where he held the prestigious James and Neeltje Tretter chair—carries significant symbolic weight. MOFs, the ultra-porous crystals he helped invent, boast the highest surface areas of any known material, enabling applications from carbon capture and water harvesting in deserts to hydrogen storage for clean energy. His research directly addresses the climate emergency, making his relocation to the world’s largest carbon emitter both a strategic opportunity and a geopolitical statement. At Tsinghua, he plans to specifically target water shortages, carbon neutrality, and sustainable development, aligning with China’s dual-carbon goals and its growing ambitions in climate technology leadership.

The AI angle is equally critical. Yaghi is not simply moving a wet lab; he is building a program at the intersection of machine learning and chemistry. By using AI to predict and optimize the properties of MOFs and other framework materials, researchers could bypass years of trial-and-error experimentation. The promise is a leap in efficiency that mirrors AlphaFold’s impact on protein folding. This convergence comes as China invests heavily in AI for science, with Tsinghua already home to several world-class AI institutes. Yaghi’s center adds a prestigious Nobel laureate to that effort, potentially attracting top students and collaborators from around the globe.

The talent pipeline aspect cannot be overstated. Yaghi has trained approximately 200 researchers, nearly half of whom are Chinese, according to postdoctoral researcher Zhou Zihui. This deep connection with the Chinese scientific diaspora likely facilitated the move and ensures a ready network of skilled chemists familiar with his methods. Yaghi’s emphasis on mentoring and his philosophy of pursuing science that “changes people’s lives” rather than merely producing papers resonates with a Chinese system eager to translate research into industrial and societal impact. His presence could catalyze a new generation of AI-savvy materials scientists in China, further tilting the balance of high-tech human capital eastward.