Determination of impurities in lithium salts used in battery manufacturing by ion chromatography and ICP-MS

Importance of the topic

Lithium-ion battery performance, safety and lifetime depend strongly on the purity of lithium salts used in electrolytes and electrode precursors. Trace ionic and elemental impurities can reduce capacity, catalyze unwanted side reactions, or compromise stability and safety. Robust, sensitive and routine analytical workflows are therefore essential for raw‑material quality control, supplier qualification and process troubleshooting in battery manufacturing.

Goals and study overview

This application study evaluated complementary analytical approaches to quantify anionic and elemental impurities and to assay lithium content in common lithium raw materials (lithium carbonate, lithium fluoride, lithium hydroxide monohydrate and phosphorus pentachloride). The objectives were to demonstrate sensitive, reproducible methods using ion chromatography (IC) with suppressed conductivity detection for anions/cations and inductively coupled plasma–mass spectrometry (ICP‑MS) for elemental impurities, to report method performance (linearity, precision, recovery) and to provide representative impurity profiles for typical material batches.

Used instrumentation

• Dionex ICS‑6000 high‑pressure ion chromatography (HPIC) system with electrolytic eluent generation (RFIC) and suppressed conductivity detection (ADRS 600 suppressor); Dionex IonPac AS11‑HC/AG11‑HC for anions; IonPac CS16/CG16 for cations.
• Thermo Scientific iCAP RQ ICP‑MS for elemental impurity determinations.
• Chromeleon CDS and Qtegra ISDS software for data acquisition and processing.

Methodology

• Anion analysis: KOH gradient eluent generated electrolytically, AS11‑HC column, suppressed conductivity detection; validated linearity over multiple concentrations with correlation coefficients >0.9996; runtime ~40 min.
• Cation (lithium assay): 30 mM methane sulfonic acid eluent on CS16 column, suppressed conductivity detection; lithium standards at 10 ppm used for precision assessment.
• Elemental impurities: samples dissolved or extracted and analyzed by iCAP RQ ICP‑MS using internal standards (Sc, Y, Tb, Ge), eight‑point calibration (1–500 ppb) and helium collision (KED) mode where required.
• Sample preparation: dissolution varied by matrix—1 M HCl or 2% v/v HNO3 for ICP‑MS; filtration through 0.2 µm membranes and, for anion analysis, additional OnGuard II H treatment to remove alkali/alkaline earth interferences where applicable.

Main results and discussion

• Linearity and precision: Excellent linearity for anions and elements (R2 >0.999); lithium assay precision showed RSD 0.31% (area) and 0.05% (retention time) for six injections, indicating high reproducibility.
• Anionic impurity profiles: Chloride, nitrate, sulfate, phosphate and fluoride were quantified in commercial batches. Phosphorus pentachloride showed extremely high phosphate due to its chemistry (reported in the study as a very large value after large dilution). Lithium carbonate, lithium fluoride and lithium hydroxide batches contained varying levels of chloride, nitrate and sulfate at mg/kg levels; fluoride was present in lithium carbonate samples at tens of mg/kg.
• Cation assay (lithium content): Recoveries for lithium across tested samples ranged 98–102%, demonstrating accurate assay capability for purity/assay determination of raw salts.
• Elemental impurities by ICP‑MS: Detected elements included Na, Si, Al, Ca, K, Fe and others with concentrations varying by material and batch. Silicon and sodium showed particularly high and variable concentrations in some batches (e.g., silicon in some LiOH batches was on the order of 100–190 mg/kg; sodium ranged from low mg/kg up to several hundred mg/kg in one Li2CO3 batch), illustrating heterogeneous contamination sources. Many trace metals (Fe, Al, Zn, Pb, etc.) were quantified at low mg/kg to sub‑mg/kg levels. Spike recovery tests mostly fell within acceptable ranges (~80–120%), confirming method accuracy; some matrix effects prevented spike testing for very high background analytes (e.g., Na, Si in selected samples).
• Method robustness: Internal standard signals (Y, Tb) remained stable throughout ICP‑MS runs, and the electrolytic eluent generation in IC reduced manual preparation variability and improved reproducibility.

Benefits and practical applications

• The combined IC + ICP‑MS workflow enables comprehensive ionic and elemental profiling of lithium raw materials, supporting quality control, supplier audits and acceptance testing in battery manufacturing supply chains.
• Electrolytic eluent generation simplifies routine IC, reduces reagent handling and improves inter‑day reproducibility—advantages for high‑throughput QC labs.
• ICP‑MS provides sub‑ppb capability and fast multi‑element quantitation, critical for detecting trace contaminants that can impact electrochemistry or safety.

Future trends and potential applications

• Tighter regulatory and product specifications will drive increased demand for lower detection limits, expanded element panels and routine spike/QA protocols; ICP‑MS platforms with improved interference management and higher throughput will be advantageous.
• Method integration and automation (robotic sample prep, online dilution, and direct hyphenation or data integration between IC and ICP‑MS) will speed QC and reduce human error.
• Advanced speciation and surface/impurity profiling (e.g., coupling chromatographic separation with high‑resolution MS, or using LA‑ICP‑MS for particulates) can provide deeper insight into contaminant forms that affect battery behavior.
• In‑line or at‑line sensor technologies informed by these laboratory methods may enable real‑time process control in salt production and electrolyte formulation.

Conclusion

The study demonstrates that modern IC with electrolytic eluent generation and suppressed conductivity, combined with ICP‑MS, provides a robust, sensitive and reproducible analytical solution for quantifying ionic and elemental impurities and for assaying lithium in common battery raw materials. The methods meet typical QC requirements for linearity, precision and recovery and reveal substantial batch‑dependent variability in certain contaminants (notably silicon and sodium). These workflows are well suited for routine quality control and supplier validation in battery material supply chains.

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