Event

 

Abstract: This seminar presents data-driven strategies for designing metal-organic frameworks (MOFs). I will discuss the development of hygroscopic MOFs for atmospheric water harvesting, guided by gas sorption and structural characterization to define design rules for pore size, working capacity, energy efficiency, and scalability. These principles enabled portable water-harvesting devices validated through field testing in Death Valley National Park. I will also describe the integration of large language models into closed-loop materials discovery and chemical synthesis planning, combining AI-driven data mining, inverse design, and automated synthesis to accelerate synthesis–structure–property understanding and advance autonomous materials research.

 

Bio: Zhiling Zheng joined Washington University in St. Louis as an Assistant Professor of Chemistry in 2025. He completed postdoctoral research at MIT with Prof. Klavs F. Jensen and earned his PhD at UC Berkeley under Prof. Omar M. Yaghi. His current research focuses on using LLM-based AI agents to accelerate crystalline materials synthesis and characterization.