Fujitsu today announced the successful development of a technology for molecular dynamics (MD) simulation that enables atomic-level structural analysis of the solid electrolyte interphase (SEI) [1] formation process in all-solid-state batteries. This process, previously difficult to analyze, significantly impacts battery performance. Fujitsu achieved this breakthrough by developing a neural network potential (NNP) [2] training method using knowledge distillation [3], enabling stable, long-duration MD simulations. The newly developed technology can now rapidly and accurately reproduce the behavior of all-solid-state battery electrolyte membrane and electrode interface structures [4] with over 100,000 atoms for 10 nanoseconds, requiring only one week of computation.
The innovative nature of this technology has been recognized with the Electric Science and Technology Promotion Award for 2025 from The Promotion Foundation of Electrical Science and Engineering, which was awarded on November 25, 2025.
By linking these technologies, Fujitsu aims to establish a new materials development workflow that accelerates materials development through AI and create new materials together with its customers.
Fujitsu will add this technology into its materials chemistry calculation platform SCIGRESS and begin providing it to customers by March 2026.