Tritium-a rare hydrogen isotope essential for most nuclear fusion projects-is nearly nonexistent in nature, with global reserves measured only in kilograms, according to the International Atomic Energy Agency. This scarcity forces large experimental and future commercial fusion reactors to produce tritium onsite. A critical challenge has been identifying materials that can generate tritium efficiently without degrading under intense reactor conditions.
FLiBe, a molten salt composed of lithium fluoride and beryllium fluoride, has long been considered for fusion reactor blankets tasked with breeding tritium. However, predicting how its atomic structure interacts with tritium amid harsh environments-extreme heat, neutron irradiation, and strong magnetic fields near plasma chambers-remains difficult. Researchers tackled this by combining quantum computing with classical supercomputers to simulate FLiBe’s electronic structure. They modeled nine different atomic configurations, both with and without tritium, revealing which arrangements better trap the isotope.
IBM led the quantum computations as part of the Genesis Mission, a US initiative that integrates high-performance computing, artificial intelligence, and quantum technology to accelerate energy materials discovery. This marks IBM’s first use of hybrid quantum-classical methods applied specifically to thermonuclear fuel. Previously, similar approaches powered biochemical modeling at the Cleveland Clinic, including protein structure predictions involving up to 12,635 atoms.
The potential payoff is significant. FLiBe features prominently in fusion blanket designs and compact reactor concepts, and similar fluoride salts have long been studied for fission reactors. Scaling this modeling approach from nine atomic setups to larger, more complex simulations of actual reactor materials could provide developers of ITER, DEMO, and private fusion startups with a sharper tool for engineering tritium breeding systems.
Compared to traditional material simulations relying solely on classical computers, the hybrid quantum-classical approach offers a promising avenue to handle the immense complexity of these systems. As fusion research intensifies globally, advances in quantum-assisted materials science may become a competitive edge in solving tritium scarcity, making this collaboration between IBM, ORNL, and Cleveland Clinic a bellwether for next-generation fusion technology development.