Work

Generative intelligence explores the chemical space of ten million catalysts

Year: 2026

Type: article

Abstract: activation. This work establishes a generalizable paradigm that seamlessly bridges generative exploration with high-throughput performance mapping, dramatically accelerating catalyst discovery across unprecedented chemical spaces.

Source: Chemical Science

DOI: 10.1039/d6sc01469k

Authors: Ruili Li, Shuoqi Zhang, Qingli Tang, Qingqing Mao, Ritankar Das, Rui Qi, Beien Zhu, Yi Gao

Institutions: Chinese Academy of Sciences, Shanghai Institute of Applied Physics, University of Chinese Academy of Sciences, Shanghai Advanced Research Institute

Language: English

Topic: Machine Learning in Materials Science

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

Open Access status: diamond

Funders: National Natural Science Foundation of China, Chinese Academy of Sciences, Shanghai Advanced Research Institute, Chinese Academy of Sciences, National Supercomputing Center, Korea Institute of Science and Technology Information

Awards: G1542423122, G2000617234, G6506498885, G6804447127, G7618808230, G8023710041, G8381085490

OpenAlex ID: W7161155993

FWCI: 2.712

Cites:

Cited by: 2

Related to: 10