Research

Our research focuses on designing new materials for next-generation batteries, such as all-solid-state, sodium-ion, and multivalent-ion batteries, through first principles calculations. We investigate physical and chemical properties of materials, such as electrical and mechanical properties, ionic conductivity, and phase stability, to develop high-performance materials. Furthermore, we use the Materials Project (MP) database to evaluate the chemical and electrochemical stability of the materials. Additionally, we also study surface and interface science for next-generation batteries, examining various interfacial properties such as chemical reactions, formation of defects, and binding energy of molecules at the interfaces.

Our research group utilizes machine learning techniques to enhance the discovery and optimization of battery materials. By identifying critical descriptors that govern material properties, we aim to improve the design of materials for all-solid-state batteries and sodium-ion batteries. Machine learning potentials (MLPs) enable both accurate and accelerated molecular dynamics (MD) simulations, facilitating efficient exploration of ionic conduction mechanisms in solid electrolytes and cathode materials. Additionally, MLPs facilitate the modeling of interface reactions, providing insights into complex interfacial phenomena. These approaches enable large-scale calculations, bridging atomistic simulations and practical applications, contributing to the development of next-generation battery technologies.

All-solid-state batteries (ASSBs) are promising candidates for next-generation batteries owing to their high energy density and enhanced safety. Solid electrolytes (SEs) in ASSBs enable the use of metallic anodes exhibiting higher energy density than graphite anodes. SEs also significantly enhance safety by replacing flammable organic liquid electrolytes in conventional Li-ion batteries. Among the various types of SEs, sulfide SEs have been broadly studied owing to their high ionic conductivities. For example, Li10GeP2S12 exhibits a high ionic conductivity above 10 mS/cm, which is comparable to that of conventional liquid electrolytes. Recently, lithium ternary halides have been reported as encouraging SEs owing to their high ionic conductivity, broad electrochemical stability window, and chemical stability against cathodes. We are focusing on the developments of all-solid-state batteries based on the sulfide and halide solid electrolytes, through systematically combined theoretical and experimental studies. 

Our research group focuses on advancing high-energy-density cathode materials for sodium-ion batteries, particularly P2- and O3-type layered oxides. Using first-principles calculations and machine learning, we aim to enhance energy density by increasing sodium content and improving structural stability under high-voltage charge conditions. This includes studying structural degradation mechanisms and oxygen redox activity during charge. Through first-principles calculations, we explore elemental substitution to address challenges such as Mn³⁺ Jahn-Teller distortion, irreversible structural transitions, and instability at high voltages. Additionally, we use machine learning and existing computational databases to identify key design descriptors and refine cathode compositions, supporting the advancement of high-energy-density sodium-ion batteries.