Insider Brief<\/p>\n
Researchers from Oak<\/a> Ridge National Laboratory, Cleveland Clinic<\/a>, and IBM<\/a> have performed quantum computer-based calculations of nine molecular configurations of FLiBe, a key material for fusion energy fuel production. <\/p>\n The work demonstrates quantum-centric supercomputing applied to modeling complex fusion-relevant chemistry that is difficult to scale on classical computers alone. <\/p>\n The study aims to improve understanding of tritium production and extraction, a critical bottleneck in developing practical fusion energy systems<\/p>\n A team of scientists from Oak Ridge National Laboratory<\/a> (ORNL), Cleveland Clinic<\/a>, and IBM<\/a> (NYSE:\u00a0IBM<\/a>), have calculated nine molecular configurations of a promising material to produce fuel for fusion energy \u2013 the first-known instance of such computations on quantum computers.<\/p>\n Such calculations, demonstrated in a new paper published on\u00a0arXiv<\/a>, are computationally challenging for classical computers to scale when working alone. They are a fundamental step towards optimizing the production and extraction of tritium \u2013 an extremely rare material in nature that is necessary to produce fusion energy with most of the proposed machines. Ensuring adequate supplies of tritium has long been a barrier to realizing the promise of clean and abundant energy from fusion power plants, and solving this issue is a key objective of the United States Department of Energy\u2019s (DOE) Genesis Mission.<\/p>\n Quantum computers are well-suited to compute the atomic-level chemistry of a liquid salt that contains fluorine, lithium, and beryllium (FLiBe), one of the leading candidate materials for extracting tritium fuel in fusion reactors. To compute different configurations of clusters of FLiBe, the team used the same quantum-centric supercomputing techniques now being applied to 12,635-atom protein simulations with Cleveland Clinic<\/a>. These methods can calculate the quantum behavior of electrons in complex materials, complementing and enhancing the capabilities of classical supercomputers and algorithms.<\/p>\n \u201cIn order to demonstrate the capabilities catalyzed by the Genesis Mission, we have built a team of leading experts across seven DOE national labs, four universities, three industry partners, and Cleveland Clinic<\/a> to pursue a multi-pronged discovery cycle aimed at optimizing tritium production in molten salt fusion blanket materials,\u201d said\u00a0Tom Beck, Section Head for Science Engagement in the Computing and Computational Sciences Directorate at ORNL. \u201cQuantum computers, such as those built by IBM<\/a> and enhanced by AI and exascale computing, are key tools that accelerate the discovery and design cycles needed to produce sufficient tritium to fuel fusion reactors.\u201d<\/p>\n \u201cThis work builds on our advances in simulating complex biological systems at scale, including proteins spanning 12,635 atoms and extends those techniques into materials science to explore fusion-relevant systems with greater accuracy and efficiency,\u201d said corresponding author\u00a0Kenneth Merz, PhD, staff scientist at Cleveland Clinic<\/a>. \u201cAt Cleveland Clinic, we are focused on applying advanced technologies to deepen scientific understanding and accelerate discovery. This collaboration reflects the growing importance of quantum computing, AI, and high-performance computing as tools for scientific inquiry. By bringing these technologies together, researchers can provide solutions to challenging real-world problems with greater speed and precision.\u201d<\/p>\n \u201cBringing quantum, AI, and classical computing together is essential to tackling our society\u2019s most fundamental scientific challenges \u2013 unlocking capabilities which none of these paradigms can access alone,\u201d said\u00a0Jerry Chow, CTO of Quantum-Centric Supercomputing at IBM<\/a>. \u201cThese results add to mounting evidence that quantum-centric supercomputing is now a practical scientific tool for problems that have long challenged chemists, engineers, and materials scientists. As quantum computers scale, the path ahead is promising.\u201d<\/p>\n The Tritium Challenge at the Heart of Fusion Energy<\/p>\n The exploration aligns with the Genesis Mission\u2019s broader goal to unify high-performance computing (HPC), artificial intelligence, and quantum computing with the country\u2019s major scientific instruments across the DOE\u2019s 17 national laboratories to accelerate scientific discovery. As one of the mission\u2019s industry collaborators, IBM<\/a> is working with its partners to explore how quantum-centric supercomputing \u2013 which brings together CPUs, GPUs, and QPUs to solve problems they cannot tackle alone \u2013 could help to address critical national challenges, including precisely modeling complex material interactions to help unlock a fuel supply for widespread, fully working fusion power plants.<\/p>\n Optimizing the best recipe for FLiBe \u2013 whose composition is dynamically changing under intense neutron radiation, extreme heat, and magnetic fields \u2013 is one of the hardest science and engineering challenges today. It requires extensive study of its quantum mechanical properties including energetics, stability, and interaction with tritium to understand how it will perform multiple functions, including that of tritium breeding material at very hot temperatures. Today, such research is only possible through difficult and expensive experimentation, or through classical computing approximation methods that can lack accuracy.<\/p>\n To compute energies of different FLiBe conformations with and without tritium, the team used quantum-centric supercomputing to enable quantum and classical computers to work together \u2013 in which the parts of a problem that can be broken down into quantum circuits are solved on a quantum computer. This allowed the team to more precisely determine the electronic structure of the material and how its atoms behave, particularly how strongly they bind tritium at a fundamental molecular level. In turn, the scientists could identify the range of configurations the atoms moved through and extract properties\u00a0\u2013 such as how strongly and through which mechanism each configuration binds tritium \u2013 that would otherwise remain hidden.<\/p>\n The Road Ahead<\/p>\n The collaboration is ongoing, aiming to reduce the time it takes for data to transfer between quantum and classical resources and to scale the size of molecular interactions simulated. Eventually, the team hopes the fusion energy ecosystem will be able to use this workflow directly to design and verify their own materials.<\/p>\n This work adds to a growing body of 2026 milestones demonstrating IBM<\/a> quantum computers as useful scientific tools \u2013 including simulating real\u00a0magnetic materials<\/a>, creating a never-before-seen\u00a0half-M\u00f6bius molecule<\/a>, and modeling\u00a0proteins<\/a>\u00a0relevant to biological research that span up to 12,635 atoms.<\/p>\n