X-ray, GC/MSD, GC/SQ, Ion chromatography, Microscopy, Thermal Analysis, Particle characterization, Particle size analysis, MS Imaging, GPC/SEC, XRD, FTIR Spectroscopy, ICP/MS, HPLC, GC
IndustriesMaterials Testing, Environmental
ManufacturerShimadzu
Importance of the Topic
The widespread adoption of electric and hybrid vehicles demands improvements in lithium-ion battery performance, safety, and cost to reduce CO2 emissions and enhance driving range and charging speed.
Objectives and Study Overview
This study presents a range of analytical methods for evaluating battery materials—from electrodes and electrolytes to cells and separators—to support research, quality control, and degradation analysis in lithium-ion secondary batteries.
Methodology and Instrumentation
We review techniques applied to different battery components:
- Chemical bond analysis and X-ray absorption (XAFS) to monitor valence changes in Ni, Co, Mn-based cathodes.
- Micro-focus X-ray computed tomography for non-destructive imaging of cylindrical, prismatic, and polymer cells.
- Gas chromatography–mass spectrometry (GC-MS) and ion chromatography for electrolyte composition and degradation product analysis.
- Scanning probe microscopy and force curve measurements to characterize binder morphology and mechanical properties in electrolyte environments.
- Thermal analysis (DSC/TMA) and mechanical testing of separators for melting behavior, shrinkage, and puncture strength.
- X-ray photoelectron spectroscopy depth profiling with monoatomic and cluster Ar ions to assess solid electrolyte films.
- Dynamic particle image analysis and micro-compression testing for particle size, shape, and strength of solid electrolyte powders.
Main Results and Discussion
The chemical bond system quantified Ni valence shifts from +3 to +3.6 during charge/discharge cycles, with minor Co changes and stable Mn states. XAFS data corroborated these findings. CT imaging revealed internal electrode deformation and separator placement in 18650, prismatic, and polymer cells. GC-MS identified key solvents, additives, and high-temperature gas decomposition products including fluoride species. Ion chromatography detected increased F– and PO2F2– in aged electrolytes. SPM showed differential binder morphology, highlighting a gelled, rigid binder for silicon anodes. DSC/TMA characterized separator melting points (100–150°C) and anisotropic shrinkage under tensile loads. Mechanical tests demonstrated separator strength retention at 60°C but marked weakness at 90°C. XPS profiling favored cluster ion sputtering for accurate LiPON composition, avoiding Li migration artifacts. Particle analysis confirmed ~5 µm powders with uniform shapes, while micro-compression revealed varying particle fracture strengths (27–315 MPa).
Benefits and Practical Applications
These complementary techniques enable precise evaluation of material properties, inform the design of longer-lasting, safer batteries, and support quality control throughout manufacturing and after cycling.
Future Trends and Potential Applications
Advancements in in situ and operando analysis, integration of AI-driven data interpretation, growth of all-solid-state battery research, and development of novel electrolytes and binders will further accelerate battery innovation.
Conclusion
Implementing a holistic suite of analytical methods is essential for optimizing lithium-ion battery materials, improving performance and safety, and paving the way for next-generation energy storage solutions.
Used Instrumentation
- Xspecia Chemical Bond Analysis System (Valence state measurement)
- X-ray Absorption Fine Structure (XAFS)
- inspeXio SMX-225CT FPD HR Plus Micro-Focus X-ray CT
- GCMS-QP 2020 NX Gas Chromatograph Mass Spectrometer
- HIC-ESP Ion Chromatography for Anion Analysis
- SPM-9700HT Scanning Probe Microscope
- DSC-60 Plus Differential Scanning Calorimeter
- TMA-60 Thermomechanical Analyzer
- AGX-V Universal Testing Machine
- KRATOS Nova/ULTRA 2 XPS
- iSpect DIA-10 Dynamic Particle Image Analysis
- MCT-510 Micro Compression Tester
Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.