Researchers at the U.S. Department of Energy’s Argonne National Laboratory are employing generative artificial intelligence (AI) and machine learning to expedite the discovery of effective metal-organic framework (MOF) materials for carbon capture.

This collaborative effort has rapidly generated over 120,000 new MOF candidates in just 30 minutes, utilizing high-throughput screening and molecular dynamics simulations on supercomputers.

Meanwhile, a study led by the University of Illinois Urbana-Champaign (UIUC) underscores AI’s potential in molecular sciences, aiming to extend its applications to biomolecular simulations and drug design.

Spearheaded by graduate students and early-career scientists across institutions, the project highlights interdisciplinary collaboration.

Supported by DOE’s Office of Science and the National Science Foundation, these endeavors signify significant strides in leveraging AI to address pressing scientific challenges, offering promising avenues for advancing carbon capture tec
hnologies and enhancing drug discovery processes.

Source: Oman News Agency