Research Report "Latest Industry Report on AI Data Center Batteries Worldwide"

■Title: "Explanation of Remaining Capacity and Degradation Estimation Techniques for Optimal Management of Lithium-Ion Batteries" ――Focusing on operating principles, modeling, and control methods, this seminar explains battery management technologies for EVs, HEVs, PHEVs, etc., from the perspectives of different battery types and applications. It covers everything from remaining capacity estimation and degradation diagnosis necessary for BMS to lifespan prediction. 【Knowledge Gained from the Seminar】 - Basic characteristics and operating principles of lithium-ion batteries - Electrical characteristics of batteries and equivalent circuit models - Extraction of equivalent circuit models from Nyquist plots - Battery simulation using MATLAB - High-precision remaining capacity estimation using Kalman filters - Degradation phenomena of batteries and modeling - Degradation diagnosis using Recursive Least Squares (RLS) - Latest technologies related to degradation diagnosis and lifespan prediction 【Target Audience for the Seminar】 - Beginners and young engineers who want to learn about battery technology - Engineers involved in BMS and battery simulation - Those interested in remaining capacity estimation, degradation diagnosis, and lifespan prediction technologies

■Title 2nd Session: Manufacturing Technology of Lithium-Ion Batteries - Application Edition (NCM Cathode and Graphite/Silicon Anode) This course is a 4-night, 5-day residential practical training program utilizing a large battery prototype factory in Tsuyama City, Okayama Prefecture. Aimed at individuals with laboratory-level research and development experience, participants will practically acquire manufacturing technology for lithium-ion batteries at the factory level. Participants will experience a series of manufacturing processes, including the preparation of cathode and anode slurries using a planetary mixer, optimization of coating and drying conditions, electrode pressing, slitting, stacking, terminal welding, cell assembly, electrolyte injection, and initial charging. Due to the small class size (limited to 6 participants), attendees will receive direct instruction from experienced instructors and systematically learn the entire battery manufacturing process. ■Event Details Date: August 31, 2026 (Monday) to September 4, 2026 (Friday) (4-night, 5-day course) Capacity: 6 participants (minimum number for the course to proceed is 4) *Includes transportation costs from Tsuyama Station, lunch costs for 5 days, and networking event fees *Accommodation costs are separate Instructors: Junichi Ogawa (Former Sony) Takashi Mukai (ATTACCATO LLC) Yoshiteru Kawabe (Former GS Yuasa) Tetsuo Sakai (CTO, STL JAPAN) Hiroichi Ninomiya (Senior Researcher, STL JAPAN)

■ Title: "Heat Dissipation/Cooling Technologies for AI Data Centers" ―― The rapid increase in data center power due to the expansion of generative AI. How to address PUE targets and high-heat GPUs. A practical overview from air cooling to liquid cooling, cold aisle, water cooling in-row, and immersion cooling. A strategic course to master thermal issues. ■ Date and Time: June 2, 2026 (Tuesday) 10:30 AM - 4:30 PM ■ Zoom Streaming (Archive available for missed sessions with materials) 【Knowledge Gained from the Seminar】 - Basic knowledge of heat transfer - Heat dissipation knowledge in component and circuit board design - Common thermal design methods for forced air cooling and natural air cooling equipment - Thermal design methods for heat sinks, etc. 【Target Audience for the Seminar】 Electronic device designers (assembly design, mechanical design, circuit design, circuit board design), heat dissipation device/material developers, quality assurance, and quality control departments.

■ Title: "Fundamentals and Applications of Neural Network Molecular Dynamics: AI-Driven Material Design" ―― Solving issues of "computational difficulties" and "uncertainty in applicability." This seminar will systematically explain the fundamentals, strengths, limitations, and countermeasures of NNMD, along with specific implementation strategies for material development. ■ Date and Time: May 20, 2026 (Wednesday) 10:30 AM – 4:30 PM ■ Zoom Streaming (with materials) 【Knowledge Gained from the Seminar】 - Successful case studies of NN molecular dynamics simulations - Differences and advantages over conventional MD - Basic theories and computational procedures - Countermeasures for computational issues - Applicable areas and limitations - Directions and strategies for corporate implementation 【Target Audience for the Seminar】 - Those who want to introduce NN molecular dynamics - Those who want to understand the differences and features compared to conventional MD - Those who want to strengthen their ability to handle computational troubles - Those who want to grasp the applicable range and limitations - Those who want to consider utilization strategies in their companies *Those interested in related fields are also welcome.