The Intelligent Secondary Battery Strategic Research Group
Research Overview
The Intelligent Secondary Battery Strategic Research Group has been designated as the lead organization for the Environment-Adaptive Smart Secondary Battery Strategic Research Group, one of the 10 Global TOP Strategic Research Group projects for 2025.
- It pursues the development of composite electrode and electrolyte materials for extreme environments and elucidates the energy storage mechanisms of topological quantum materials, securing full-cycle smart energy storage technologies from basic research to applications.
- Furthermore, it leads the development of foundational technologies for analyzing core materials and ensuring reliability of secondary batteries adapted to multiple environments (high temperature, low temperature, radiation), based on multidisciplinary convergence and materials-centered analytical science.
Research Groups
Research Content
- Development of Multi-Environment Adaptive Smart Materials Technology : Development of composite electrodes and electrolytes based on topological insulators, phase-change materials, and self-healing materials, including mass synthesis and electrochemical property analysis
- Performance Analysis of Electrodes and Electrolytes Based on Topological Quantum Materials : Identification and analysis of material properties that maintain performance under extreme conditions (100℃, -80℃, 100Gy)
- Multi-Environment Real-Time Diagnostics and Standardization : Real-time measurement using XRD, XPS, and Raman under operando environments, and development of standard reference materials
- International Collaborative Research : Conducting joint analytical studies in collaboration with Max-IV, KIT, and Forschungszentrum Jülich
- Integration of AI-Based Advanced Analytical Technology into Electron Microscopy Systems for High-Resolution Microstructural Analysis and Quantitative Data Interpretation : Development of automated analytical technology for advanced materials such as secondary batteries and semiconductors through AI analysis, in-situ TEM, and 3D reconstruction
Research Infrastructure
Personnel
Holds a large number of expert researchers in battery materials and property analysis, electrochemistry, and nanostructure interpretation (Strategic Materials Research Group, Intelligent EM Research Group).
Available Analytical Equipment
Category | Equipment Details |
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in-situ/operando | XRD, XPS, Raman analyzers operable under high and cryogenic temperatures |
Topological quantum materials | Single-crystal XRD, TEM, EELS, and electron microscope-based crystal and band structure analysis |
Thermal and magnetic properties | Electrical and magnetic property analysis support using MPMS and PPMS, and development of thermal property analysis methods |
Electron microscopy equipment | HVEM, Mono Cs TEM, Cs TEM, Double Cs TEM, FIB, Cryo FIB, environmental isolation chamber, in-situ TEM/SEM, and high-resolution EELS system |
Core Technologies in Electron Microscopy |
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Utilization Capabilities
- Nanostructure analysis of materials for extreme environment adaptation
- Identification of degradation causes of materials within battery cells
- Establishment of an integrated platform connecting material development, performance evaluation, and standardization
Collaboration Infrastructure
Operation of Inter-bridge Lab., Open Campus, and Fast Free Pass system
Representative Research Achievements
- 2021 National R&D Top 100: “All-Solid-State Battery That Works Even When Crumpled or Cut”
- 2020 Excellent Research Achievement of Government-Funded Institutes: “All-Solid-State Battery That Works Even When Crumpled or Cut”
- 2007 National R&D Top 100: “Hydrogen Energy Storage Material Using Inorganic Nanomaterials”
Category | Description |
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Publications |
“Battery Thermal Runaway Suppression” – Development of New Materials for Lithium Metal Secondary
Batteries
Compos. Pt. B-Eng. (2025), 292, 112109 (IF=12.7, Top 2% in JCR) |
Publications | Electrochemical Activation of VxS8/rGO Electrodes and Development of Aqueous
Zinc-Ion Batteries
Adv. Compos. Hybrid Mater. (2025), 8:186 (IF=23.2, Top 5% in JCR) |
Patent | Denoising System for STEM Atomic-Resolution Images Using an Artificial
Intelligence Model
Application No. 10-2024-0187396, Filing Date: 2024.12.17, Republic of Korea |
Patent | Method for Training a Neural Network to Predict Aberration Values of an
Electron Microscope and Device for Predicting Aberration Values of an Electron Microscope
Registration No. 10-2803933, Registration Date: 2025.04.29, Republic of Korea |