Advanced R&D

Spearheaded by a Tsinghua PhD team, we derive material intrinsics from the atomic level upward, with full vertical integration across the supply chain from raw materials to finished products. We have developed a proprietary "rapid materials validation closed loop" and a systematic knowledge graph, enabling multi-level modification and cross-generational evolution of customized raw material specifications.

The Mechanistic Investigation and Failure Analysis Platform is designed to cover the full life cycle of lithium-ion batteries, establishing a closed-loop capability integrating non-destructive diagnosis, degradation decoupling, and root-cause identification. The platform employs non-destructive techniques such as electrochemical impedance spectroscopy (EIS), galvanostatic intermittent titration technique (GITT), differential capacity analysis (dQ/dV), and CT imaging, in combination with spectral analysis methods such as DRT/DCT and equivalent-circuit/transport models, to quantitatively decouple key processes including ohmic resistance, pore/interfacial transport, and solid-state diffusion. In parallel, by integrating advanced characterization at both the materials and structural levels, the platform systematically identifies representative failure mechanisms, including electrode corrosion, transition-metal dissolution, particle cracking, separator clogging, lithium dendrite growth, silicon volume expansion, and graphite exfoliation. Based on a failure analysis tree, the platform attributes manufacturing defects, material degradation, structural failure, and operating/environmental impacts to verifiable chains of evidence, thereby delivering actionable design and process optimization strategies and providing robust support for the development of high-energy-density, fast-charging, highly safe, and long-life battery products.

The Platform Technology Team takes electrode sheets as the central technology carrier and focuses on the multiscale structure–property relationships across the “materials–electrode–cell” hierarchy in lithium-ion batteries, systematically linking material properties, electrode architecture, and interfacial transport to cell-level performance. Centered on materials optimization, formulation optimization, and advanced process development, the team co-optimizes the formulation system, areal loading, calendered density, pore structure, and key process parameters to enable efficient translation of material-level attributes into cell performance. By integrating physics-based simulation and modeling, advanced characterization, and data mining, the team accelerates multidimensional, synergistic innovation in electrochemical systems, electrode design, and manufacturing processes, continuously supporting the development of high–energy-density, fast-charging, high–rate-capable, long-life, and high-safety products, and laying a solid technological foundation for next-generation high-performance cylindrical lithium-ion batteries.

Leading the Industry into a Digital Twin Universe. We fuse first-principles science with advanced AI and big data to break through scale constraints—down to atomic orbital simulations, up to full-lifecycle 3D thermal-electrical modeling. By eradicating guesswork, we boost efficiency and accuracy, predict performance with precision, and fast-track innovation. Our mission: to unlock fully automated cell design.

Based on the QFD (Quality Function Deployment) model, customer needs are precisely captured and translated into standardized technical specifications. A comprehensive end-to-end process mapping—from factor screening to performance integration—enables visual design management and accurate filtering. Our research delineates operating condition boundaries: optimal performance is pursued within defined limits while safety redundancy is enhanced for operations beyond them. We forward-integrate material selection and formulation design through mechanism-based research, achieving functional optimization of every component. Finally, we incorporate 6-Sigma control principles to systematically balance theoretical performance potential with practical manufacturing feasibility, ensuring our customers receive products that are both highly desirable and fully achievable.