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The U.S. Department of Energy (DOE) announced $159 million for 12 new Phase II Genesis Mission projects on October 8, 2026. The projects propose applying AI and what DOE calls “Super Intelligence” to research ranging from fusion and chip design to quantum computing, particle physics, and geothermal energy. The amount covers these 12 awards—not the full Genesis Mission portfolio—and DOE did not publish a dollar breakdown by project.
What the $159 million award covers
The new awards bring the Genesis Mission’s Phase II project count to 14, DOE said, adding 12 newly selected projects to two announced earlier: GridFM 2.0 and Prometheus. The release also says DOE is issuing six new Phase I awards and describes the first-year Genesis Mission cohort as 297 projects. These are separate portfolio figures; the $159 million applies to the 12 new Phase II projects, not to all Genesis Mission work. DOE announcement, October 8, 2026.
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DOE Under Secretary for Science Darío Gil characterized the selections as “a critical step in turning the promise of Super Intelligence for science into transformative scientific capability.” That is the agency’s stated ambition, not evidence that the projects have already delivered the intended results.
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What the 12 projects aim to do
DOE’s announcement identifies each project’s lead and intended work. The descriptions below are project aims as announced; the release does not independently validate projected benefits or report results.
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| Field | Lead | Announced project aim |
|---|---|---|
| Fusion | Commonwealth Fusion Systems | Build an AI-enabled digital twin to simulate and optimize operations of its SPARC fusion demonstration device. |
| RNA and the bioeconomy | University of California San Diego | Expand an RNA structure database five-fold for training SI models aimed at engineering resilient crops and sustainable microbes. |
| Particle physics | MIT | Integrate SI with supercomputing calculations in lattice quantum chromodynamics. |
| Geothermal energy | University of California Irvine | Develop MAESTRO, an SI platform intended to map, stimulate, and manage deep underground reservoirs. |
| Critical materials | University of Illinois Urbana-Champaign | Develop AXIS to use SI in designing electrochemical processes for extracting rare-earth elements from domestic sources. |
| Enzyme design | University of Washington Seattle | Use sequence-structure ensemble modeling to predict and design functional enzymes. |
| Chip design | Fermilab | Develop AXESS to use SI to design rugged, high-performance microchips for extreme environments, including space, high radiation, and ultra-cold conditions. |
| Particle accelerators | Lawrence Berkeley National Laboratory | Develop MOAT-Core, a shared platform intended to help national laboratories run and design accelerators. |
| Quantum computing | Harvard University | Develop ASQC, combining SI with quantum hardware to address error correction. |
| Scientific software | Argonne National Laboratory | Develop AI4HPC, a framework to modernize, optimize, and verify scientific software for supercomputers. |
| Quantum materials | Oak Ridge National Laboratory | Develop a physics-informed framework to design functional quantum magnets from desired properties. |
| Rare isotope research | Northeastern University | Develop an automated assistant intended to streamline operation and tuning of the Facility for Rare Isotope Beams particle separator. |
What the announcement does—and does not—establish
The project list spans modeling, design, operations, and scientific software. Fusion, chip design, and quantum research are prominent examples, but they are only part of a broader set that also includes biology, geothermal energy, materials, and particle physics.
- It establishes: DOE’s announced funding total, the number of new Phase II selections, project leads, and the work each team says it intends to pursue.
- It does not establish: individual award amounts, detailed grant terms, independent assessments of impact or readiness, or evidence that the planned capabilities have been achieved.
Because DOE provides no per-project allocation, the $159 million cannot be divided reliably among the 12 projects from this release. Nor does the announcement support ranking the projects by likely impact or readiness.
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