Energy Department Announces New Genesis Mission Awards to Advance Super Intelligence for Science

US Department of Energy Office of Science sent this bulletin at 10/09/2026 12:00 PM EDT

Energy Department Announces New Genesis Mission Awards to Advance Super Intelligence for Science

Twelve newly selected Phase II and six Phase I projects to advance the frontiers of Super Intelligence (SI) for science, capping a first-year cohort of 297 projects across the Genesis Mission portfolio.

The U.S. Department of Energy (DOE) today announced 12 Phase II Genesis Mission project awards totaling $159 million. Building on the Genesis Mission’s growing portfolio of projects, first announced in July, these Phase II project awards will unleash scientific discoveries with Super Intelligence (SI).

President Trump launched the Genesis Mission in November 2025 to accelerate discovery and strengthen U.S. leadership in science, medicine, and technology.

“These projects represent a critical step in turning the promise of Super Intelligence for science into transformative scientific capability,” said DOE Under Secretary for Science Dr. Darío Gil. “The Phase II teams have already demonstrated what is possible when SI is integrated with scientific expertise, data, and computing. These awards give them the opportunity to take that work to the next level. By bringing together our National Labs, universities, and industry partners, we are building on extraordinary work already underway and accelerating the pace of discovery.”

The Phase II awards are developing new, powerful capabilities to tackle the Nation’s most complex National Science and Technology Challenges. By connecting America’s leading scientists with advanced SI, supercomputing, scientific data, and DOE’s world-class research infrastructure, the Genesis Mission is strengthening U.S. leadership at the frontiers of science and technology.

Awarded Projects

Through DOE’s Office of Science, the 12 newly awarded projects are:

Accelerating the path to commercial fusion energy via an AI-enabled digital twin platform for SPARC: Led by Commonwealth Fusion Systems, this project will build a digital twin to simulate and optimize operations of a fusion demonstration device.
Decoding the RNA Structurome to Secure AI Advantage for the Bioeconomy: Led by the University of California San Diego, the project will expand the RNA structure database five-fold for training SI models to unlock the ability to engineer resilient crops and sustainable microbes.
Lattice Quantum Chromodynamics (LQCD) at the Intelligence Frontier: Led by MIT, this project will integrate Super Intelligence with supercomputing calculations of fundamental particle physics to dramatically accelerate discoveries about the basic building blocks of our universe.
Multi-agent AI Expert for Subsurface Reasoning and Optimization (MAESTRO): Led by the University of California Irvine, MAESTRO will establish an SI platform to accurately map, stimulate, and manage deep underground reservoirs to unleash vast resources of reliable geothermal energy.
AI-extended Interfacial Separations (AXIS): A Multiscale Framework for Redox-Active Ligand Design: Led by the University of Illinois Urbana-Champaign, AXIS will harness SI to design more efficient electrochemical processes for extracting critical rare-earth elements from domestic sources.
Overcoming barriers in computational enzyme design through improved sequence-structure ensemble modeling: Led by the University of Washington Seattle, this project will build foundational SI tools to predict and design functional enzymes.
Accelerating Extreme Environment Specs-to-Silicon (AXESS): Led by Fermilab, AXESS will use SI to rapidly design rugged, high-performance microchips capable of operating in extreme conditions such as space, high-radiation, and ultra-cold environments.
The Multi-office Accelerator Team Core (MOAT-Core): Led by Lawrence Berkeley National Laboratory, MOAT-Core will develop a shared SI platform across National Laboratories to autonomously run and design particle accelerators faster and more efficiently.
Application-Aware Error Correcting Codesign for Scientific Quantum Computing (ASQC): Led by Harvard University, ASQC combines SI with advanced quantum hardware to tackle quantum computing error correction.
An Iterative Framework of AI-Assisted Scientific Development and Optimization (AI4HPC): Led by Argonne National Laboratory, AI4HPC will create an SI framework to modernize, optimize, and verify supercomputing scientific software.
AI-empowered Design of Functional Quantum Magnets: Led by Oak Ridge National Laboratory, this project will develop a physics-informed SI framework to design new quantum magnets by working backward from desired properties, with applications in quantum sensing, low-power electronics, and quantum technologies.
Agentic Assistance for Advanced Rare Isotope Separator Operations at the Facility for Rare Isotope Beams (FRIB): Led by Northeastern University, this project will develop an intelligent, automated assistant to safely streamline the operation and tuning of the FRIB particle separator, unlocking hundreds of hours of research time annually.

These new selections bring the total number of Phase II projects to 14, alongside previously announced awards for GridFM 2.0 under the Office of Electricity and Prometheus under the Office of Nuclear Energy.

DOE is also issuing six new Phase I awards, expanding the Genesis Mission’s initial round of selections. More information about these and previously awarded projects is available here.