The University of Wyoming School of Energy Resources (SER) has begun work on a major grant from the National Science Foundation (NSF) in collaboration with the University of Alaska Anchorage (UAA) to explore transformative bioprocessing and artificial intelligence (AI)-driven frameworks for sustainable critical mineral recovery.

Funded under the EPSCoR (Established Program to Stimulate Competitive Research) Infrastructure Improvement Program, the $6 million grant project establishes a smart bio-refinery framework with AI-enabled microbial recovery systems to address the nation’s reliance on foreign sources of rare earth elements.

The interdisciplinary research collaboration will integrate microbiology, mineralogy, AI and process engineering to advance critical mineral recovery. The project aims to strengthen U.S. economic and national security through reduced dependence on foreign sources of critical minerals.

Additional partners on the project include the University of Alaska Fairbanks and Montana Technical University.

The UW portion of the project will be led by Tyler Brown, program manager of the minerals team inside the school’s Center for Economic Geology Research. He will primarily be tasked with the characterization, economic analysis and workforce training components of the project.

“We have worked diligently to establish ourselves as the go-to authority in critical mineral characterization, and we are deeply grateful for our robust partnerships with premier institutions,” Brown says.

The project lead at UAA will use a proprietary bioleaching process to extract critical minerals from diverse feedstocks. By integrating pre- and post-optimization data directly into a machine learning feedback loop, the researchers aim to engineer tailored extraction solutions for varied regional materials. In collaboration with the partner institutions in Alaska and Montana, the team combines regional feedstock research with cutting-edge engineering and AI capabilities.

The four-year project is one of eight receiving a combined $39.9 million through NSF’s EPSCoR Infrastructure Improvement Program.