The Rise of Generative AI for Metal-Organic Framework Design and Synthesis
This perspective outlines how generative AI models, including variational autoencoders, diffusion models, and large language agents, are revolutionizing metal-organic framework (MOF) discovery by shifting from manual enumeration to autonomous design and synthesis, thereby accelerating the development of high-performance materials for clean air and energy applications while addressing challenges in synthetic feasibility and data diversity.
Chenru Duan, Aditya Nandy, Shyam Chand Pal, Xin Yang, Wenhao Gao, Yuanqi Du, Hendrik Kraß, Yeonghun Kang, Varinia Bernales, Zuyang Ye, Tristan Pyle, Ray Yang, Zeqi Gu, Philippe Schwaller, Shengqian Ma (…)2026-03-31🔬 cond-mat.mtrl-sci