Determination of Metals in Recycled Li-ion Battery Samples by ICP-OES

Importance of the Topic

As demand for lithium-ion batteries (LIBs) soars in consumer electronics, electric vehicles, and renewable energy storage, the volume of spent batteries and associated electronic waste is rising. Recovering critical metals such as lithium, cobalt, nickel, and manganese from LIB “black mass” not only conserves scarce resources and reduces mining impact, but also mitigates environmental hazards from improper disposal. Reliable, high-throughput analytical methods are essential for quality control in recycling operations and for ensuring the purity of recovered materials.

Study Objectives and Overview

This application note presents a method for simultaneous quantification of 18 metals in LIB black mass using the Agilent 5800 Vertical Dual View (VDV) ICP-OES. Key goals include method development with semiquantitative screening, optimization of background correction and rinse protocols, and demonstration of accuracy, precision, and long-term stability for both major and trace elements in complex e-waste matrices.

Methodology and Instrumentation

Black mass samples from a recycling plant were digested in aqua regia at elevated temperature, filtered, and diluted. External calibration was performed in matching acid matrix over concentration ranges appropriate for each element. Two levels of dilution accommodated high-concentration analytes.

Instrumentation Used

• Agilent 5800 VDV ICP-OES with radial and axial plasma views
• SeaSpray nebulizer and double-pass cyclonic spray chamber
• Demountable 1.8 mm i.d. injector torch
• Agilent SPS 4 autosampler

Software features enabled during analysis:

• IntelliQuant Screening for rapid semiquantitative profiling and selection of interference-free wavelengths
• Fitted Background Correction (FBC) and Fast Automated Curve-fitting Technique (FACT) to address complex spectral interferences
• Intelligent Rinse to optimize washout and maximize sample throughput

Main Results and Discussion

The method delivered linear calibration (correlation coefficients > 0.999) across all elements. Detection limits ranged from sub-µg/L to tens of µg/L, corresponding to MDLs down to tens of µg/kg in solid samples. Semiquantitative heat maps identified cobalt as a dominant element in black mass.

Quantitative analysis of four samples showed Al, Co, Cu, and Li at levels above 1 %, with other elements present from high‐ppm to trace levels. Spike recoveries in all samples were within ±15 % of expected values, confirming accuracy in complex matrices.

Long-term stability was demonstrated by analyzing 198 solutions over seven hours without internal standard correction or recalibration. Recoveries of a control standard stayed within ±10 % and RSDs remained below 2.1 %, highlighting method robustness.

Benefits and Practical Applications

• Simultaneous quantification of major and trace elements in a single run streamlines quality control in recycling workflows
• Smart software tools reduce method development time and minimize sample remeasurements
• Optimized rinse protocols increase throughput, reduce argon consumption, and lower operating costs
• High sensitivity and precision support certification of recovered battery materials for reuse

Future Trends and Potential Applications

Advances in automation, machine learning–driven spectral deconvolution, and integration with online digestion systems are expected to further enhance throughput and data quality. Expansion of this ICP-OES approach to novel battery chemistries, direct analysis of slurries, and coupling with speciation techniques will support circular-economy initiatives and next-generation recycling processes.

Conclusion

The Agilent 5800 VDV ICP-OES method offers a reliable, accurate, and high-throughput solution for comprehensive elemental analysis of LIB black mass. With robust background correction, intelligent rinse control, and proven long-term stability, this approach addresses the analytical challenges of e-waste recycling and supports sustainable resource recovery.

References

1. Tarascon J-M, Armand M. Issues and challenges facing rechargeable lithium batteries. Nature. 2001;414:359.
2. Roy JJ, Rarotra S, Krikstolaityte V, et al. Green recycling methods to treat lithium-ion batteries e-waste: A circular approach to sustainability. Adv Mater. 2022;34:2103346.
3. Gong C, Lei L. Battery recycling technologies: Recycling waste lithium-ion batteries with the impact on the environment in-view. J Environ Ecol. 2013;4:14.
4. Makwarimba CP, Tang M, Peng Y, et al. Assessment of recycling methods and processes for lithium-ion batteries. iScience. 2022;25:104321.
5. Agilent. Determination of elements in ternary material nickel-cobalt-manganese hydride: Determination of 25 elements in materials for lithium battery cathodes using ICP-OES. Publication 5991-9506EN.
6. Agilent. Determination of 14 impurity elements in lithium carbonate using ICP-OES: Routine quality control of raw materials used to produce cathode material for lithium-ion batteries. Publication 5991-9507EN.
7. Agilent. Determination of elemental impurities in graphite-based anodes using ICP-OES: Accurate determination for lithium battery anodes. Publication 5991-9508EN.
8. Agilent. Rapid analysis of elemental impurities in battery electrolyte by ICP-OES: Quality control measurement of 12 elements in lithium hexafluorophosphate. Publication 5994-1937EN.
9. Agilent. Elemental analysis of brine samples used for lithium extraction. Publication 5994-5194EN.
10. Agilent. Agilent IntelliQuant Screening: Smarter and quicker semiquantitative ICP-OES analysis. Publication 5994-1518EN.
11. Agilent. Intelligent Rinse for ICP-OES. Publication 5991-8456EN.