Multiplatform Approach for Lithium-Ion Battery Electrolyte Compositional Analysis

Significance of the Topic

Lithium-ion battery performance and longevity depend heavily on electrolyte composition. Precise profiling of solvents, salts and additives is vital for quality control, safety and reverse engineering of commercial formulations. A comprehensive multi-technique workflow addresses the complexity of organic and inorganic species in unknown samples.

Objectives and Study Overview

This study presents an integrated analytical strategy to decode the volatile, nonvolatile organic and elemental composition of three unknown lithium-ion battery electrolytes. Complementary platforms were applied to achieve a holistic characterization and to demonstrate consistency across techniques.

Methodology and Sample Preparation

Samples were obtained directly from a commercial source. Volatile organics were analyzed by gas chromatography with split (1,000× dilution) and splitless injections. Nonvolatile organic compounds were profiled via liquid chromatography with quadrupole time-of-flight mass spectrometry using a nontargeted statistical workflow. Elemental composition was determined by inductively coupled plasma mass spectrometry following dilution in battery-grade dimethyl carbonate.

Used Instrumentation

• Agilent 8890 GC combined with 7010 triple quadrupole MS (GC/TQ) for volatile profiling
• Agilent 1290 Infinity II LC with 6545XT AdvanceBio Q-TOF for accurate mass analysis of organics
• Agilent 7900 ICP-MS equipped with organic solvent introduction kit and QuickScan for elemental screening

Main Results and Discussion

GC/TQ analysis identified 28 volatile species, with eight common components—including dimethyl carbonate, diethyl carbonate, ethylene carbonate and additives such as trimethyl phosphate—displaying consistent retention times and high library match factors across samples. LC-Q-TOF and multivariate statistics revealed additional organic additives and enabled discrimination between formulations via principal component analysis, hierarchical clustering and unique feature Venn diagrams. ICP-MS profiling confirmed major lithium salts (LiPF6, LiBF4, LiClO4) and quantified trace impurities (e.g., Na, K, Mg, Fe, Zn), validating the QuickScan semiquantitative screening.

Benefits and Practical Applications

The multidisciplinary approach ensures robust identification of both major and trace electrolyte constituents. It supports reverse engineering of commercial formulations, routine quality control in battery manufacturing and monitoring of electrolyte degradation during cycling.

Future Trends and Applications

Advances in high-resolution mass spectrometry, expanded spectral libraries and data-driven workflows will enhance nontargeted screening capabilities. Integration of online sampling and in situ analysis is expected to enable real-time monitoring of electrolyte evolution under operating conditions.

Conclusion

The combined GC/TQ, LC-Q-TOF and ICP-MS workflow delivers a comprehensive platform for decoding complex electrolyte mixtures. The synergy of hardware and software tools provides a powerful solution for detailed compositional analysis and quality assurance in lithium-ion battery research and production.

References

• Lithium-Ion Batteries: Basics and Applications. Springer, 2018.
• J. Electrochem. Soc. 164(1), A5019–A5025, 2017.
• Zhang S. S. A Review on Electrolyte Additives for Lithium-Ion Batteries. J. Power Sources, 2006, 1379–1394.
• Zou A., Li S., Ang C.H., McCurdy E. Analysis of Elemental Impurities in Lithium-Ion Battery Electrolyte Solvents by ICP-MS. Agilent Technologies Application Note 5994-6883EN.
• Owens B.B., Reale P., Scrosati B. Primary Batteries | Overview. Encyclopedia of Electrochemical Power Sources, 2009, 22–27.