The useful question is what changes for users, developers or buyers, and whether the announcement stays industry context or becomes something people can actually use.

The U.S. Department of Energy selected two Caltech-led projects for Genesis Mission funding, a national initiative using AI to double scientific productivity. The first project, led by Professor Theo Agapie, will develop an AI-driven electrochemical lab to automate chemical manufacturing, targeting cleaner and more diverse chemical production. The system will analyze over 10 billion possible reaction conditions to optimize synthesis of compounds like ethylene and ethanol from carbon dioxide.

Agapie’s team will build on Caltech’s automated gas diffusion electrode system, integrating machine learning to guide experiments. Collaborators include researchers from Lawrence Berkeley National Laboratory and LILA Sciences, which will provide AI algorithms trained on existing electrochemical data. The goal is to enable autonomous experimentation that identifies novel chemical pathways beyond traditional laboratory constraints.

The second project, led by Professor Victoria Orphan, will use AI to model complex microbial ecosystems, focusing on microorganisms that cannot be cultured in labs. The team aims to create dynamic models of microbe-microbe interactions in real-world environments, such as methane-consuming archaea and bacteria that exchange electrons through conductive matrices.

Orphan’s project involves experts from Argonne National Laboratory, the University of Georgia, and Dayhoff Labs, which will refine microbial gene annotations. The approach seeks to uncover microbial processes with applications in industrial biotechnology, environmental engineering, and synthetic biology. Both teams presented their work at a Genesis Mission Summit in Washington, D.C., on July 22.