At FRIB, the future of nuclear science is being shaped by intelligent systems. FRIB is integrating advanced artificial intelligence (AI) systems into the research infrastructure, strengthening U.S. leadership in nuclear science while transforming how science is done. FRIB applies machine learning (ML) approaches to shorten discovery timelines and drives new advances across experimental nuclear science, theoretical nuclear science, and accelerator science.
By uniting advanced computation with a world-leading rare isotope facility on the campus of a top research university, FRIB is:
- accelerating insight into the fundamental structure of matter,
- strengthening U.S. leadership in nuclear science,
- advancing capabilities critical to national security and innovation, and
- training the workforce of tomorrow.
FRIB and the DOE Genesis Mission
The DOE Genesis Mission is a “national initiative to build the world’s most powerful scientific platform to accelerate discovery science, strengthen national security, and drive energy innovation.” FRIB faculty have submitted 20 proposals in support of the Genesis Mission.
As a DOE Office of Science user facility based at a university, FRIB advances the goals of the DOE Genesis Mission by harnessing artificial intelligence to accelerate discovery in nuclear science and develop the workforce.
FRIB advances the goals of the Genesis Mission by integrating AI, machine learning (ML), and quantum innovation across its scientific and technical ecosystem, linking advanced computation with one of the world’s premier nuclear science user facilities. Together, these capabilities enable new approaches to experiment, simulation, and accelerator operations—accelerating discovery and expanding the frontiers of nuclear physics.
FRIB uses AI to improve particle identification, support real-time event selection, and help researchers process complex experimental data more rapidly. These capabilities support precision studies of rare isotopes, including measurements that probe nuclear structure, nuclear reactions, nuclear astrophysics, rare processes, fundamental symmetries, and quantum properties of nuclear systems.
FRIB uses AI and advanced computing to model nuclear structure, reactions, and dynamics, expanding what is computationally possible in nuclear many-body physics. Researchers are developing machine-learning emulators and intelligent systems that accelerate complex calculations and enable predictions for systems that are difficult to calculate directly. AI is also being used to accelerate computing with emerging technologies such as quantum computing as part of a broader toolkit for addressing nuclear many-body problems.
FRIB uses AI-guided beam tuning, diagnostics, and digital twins to improve accelerator performance and efficiency. These physics-informed virtual models integrate with real-time machine data to support rapid diagnostics, adaptive tuning, and automated optimization across the superconducting linear accelerator. FRIB is applying these data-driven techniques to systems such as the Advanced Rare Isotope Separator (ARIS) and the Separator for Capture Reactions (SECAR) to tune high-order optics, address complex beam aberrations, improve rare-isotope yield and purity, reduce setup times, and provide more reliable beam time for users.
As a university-based national user facility, FRIB plays a central role in training the next generation of scientists and engineers in areas critical to national needs. Students gain hands-on experience in accelerator science, cryogenic engineering, and radiochemistry while working at the intersection of AI, nuclear physics, and quantum science. This integrated environment prepares a highly skilled workforce to lead future advances in science, energy, and national security.
FRIB’s capabilities also enable a range of broader applications that align with national priorities. These include isotope harvesting for medicine and industry, testing and validation of radiation-tolerant microelectronics. These efforts extend the impact of nuclear science across energy, security, and emerging technologies.
At FRIB, students receive hands-on training with world-leading experts on world-unique systems, gaining critical skills and real-world experience. This training helps them win prestigious awards and contribute to a skilled workforce, lead in emerging industries, and drive national competitiveness.
Customized Bayesian optimization for efficient beam tuning at the facility for rare isotope beams
doi: 10.1103/5hyd-bhpx
Improved high-gradient performance for medium-velocity superconducting half-wave resonators: Surface preparation and trapped flux mitigation
doi: 10.1103/nh3z-zwz3
Mass of 101Sn and Bayesian extrapolations to the proton drip line
doi: 10.1103/vck7-1c4t
Apple highlighted the growing impact of the Apple Manufacturing Academy at MSU, where U.S. manufacturers are learning to apply AI and smart manufacturing techniques to improve efficiency, quality, and supply-chain operations. The academy’s inaugural Spring Forum in East Lansing featured tours of participating facilities, including FRIB, alongside discussions on how AI-driven tools are strengthening American manufacturing.
