Determination of Trace Metal Impurities in High Purity Aluminum Nitrate using ICP-OES

Significance of the Topic

The rapid growth of lithium-ion battery production places stringent demands on the purity of precursor materials. Trace metal impurities in high-purity aluminum nitrate can significantly impact cathode performance, cycle life, and safety. Accurate, reliable quantification of these impurities supports quality assurance throughout material supply chains and underpins consistent battery manufacturing outcomes.

Objectives and Study Overview

This study evaluates an ICP-OES method using the Agilent 5900 with Synchronous Vertical Dual View (SVDV) and AVS 7 switching valve to determine trace elements in high-purity Al(NO₃)₃. The goals were to develop a single-run procedure that measures percent-level aluminum alongside ppb-level impurities, to assess method accuracy via spike recoveries, and to confirm stability over extended operation.

Methodology

Solid Al(NO₃)₃ samples (>99.999%) and process liquids were dissolved or diluted in 5% ultrapure HCl. Calibration employed multi-element standards spanning low-ppb to percent levels, with an extra low standard for aluminum. Background effects and spectral overlaps were corrected using Fitted Background Correction (FBC) and FACT curve-fitting techniques. Customized internal standards matched atomic or ionic states and ionization energies to each analyte, compensating for the energy‐absorbing effects of high Al matrices.

Used Instrumentation

• Agilent 5900 SVDV ICP-OES with AVS 7 valve
• SeaSpray concentric nebulizer and double-pass cyclonic spray chamber
• Demountable VDV torch (1.8 mm injector)
• Vista Chip III detector (167–785 nm continuous coverage)
• SPS 4 autosampler and peristaltic pump system

Main Results and Discussion

Method detection limits ranged from sub-ppb for trace metals to 0.1 mg/L for aluminum. Analysis of three solid samples showed consistent impurity levels across B, Ba, Ca, Cr, Fe, K, Na, and other elements. Liquid process samples exhibited expected variability. Spike recovery tests at 100 ppb returned 93–109% for all analytes, confirming accuracy. A 7-hour run of 384 solutions with periodic QC checks demonstrated long-term stability, with recoveries within ±10% and RSDs below 2.2%.

Benefits and Practical Applications

• Simultaneous determination of major matrix element and trace impurities in one analysis
  
• Reduced sample introduction maintenance and argon consumption via AVS 7
  
• Robust interference correction supporting accurate QA/QC in battery material production
  
• Wide linear dynamic range eliminates multiple dilutions

Future Trends and Applications

Advancements in interference-correction algorithms and inline process monitoring will further enhance throughput and data quality. Extending the technique to other battery precursors, integrating with automated sample handling, and coupling with speciation methods can support comprehensive materials characterization in next-generation energy storage development.

Conclusion

The Agilent 5900 SVDV ICP-OES with AVS 7 provides a fast, accurate, and stable approach for quantifying trace metal impurities in high-purity aluminum nitrate. The method’s robust interference management and broad dynamic range make it well suited for QA/QC demands in lithium-ion battery manufacturing.

References

• 1. A Practical Guide To Elemental Analysis of Lithium Ion Battery Materials Using ICP-OES, Agilent publication 5994-5489EN
• 2. Wang, B., et al., Which of the nickel-rich NCM and NCA is structurally superior as a cathode material for lithium-ion batteries? J. Mater. Chem. A 2021, 9, 13540–13551.
• 3. Reduce Costs and Boost Productivity with the Advanced Valve System (AVS) 6 or 7 Port Switching Valve System, Agilent publication 5991-6863EN
• 4. Fitted Background Correction (FBC): Fast, accurate and fully automated background correction, Agilent publication 5991-4836EN
• 5. Real-time Spectral Correction of Complex Samples using FACT Spectral Deconvolution Software, Agilent publication 5991-4837EN