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Quantitative analysis of high purity metals using laser ablation coupled to an Agilent 7900 ICP-MS

Applications | 2015 | Agilent TechnologiesInstrumentation
ICP/MS, Laser ablation
Industries
Energy & Chemicals , Semiconductor Analysis
Manufacturer
Agilent Technologies

Summary

Importance of the Topic


Analysis of high purity metals is critical for quality control in advanced industries such as electronics, semiconductor manufacturing, metallurgy and material production.
Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) enables direct solid sampling with minimal preparation, reducing contamination and analyte loss.
Accurate trace element quantification supports regulatory compliance, product reliability and process optimization.

Objectives and Study Overview


This study evaluates two calibration strategies—matrix-matched and non-matrix matched—for quantitative LA-ICP-MS analysis of high purity metals.
The goal is to achieve high accuracy and precision using an Agilent NWR213 laser ablation system coupled to an Agilent 7900 ICP-MS.
Copper certified reference materials (CRMs) and additional metal CRMs are analyzed to assess performance of both approaches.

Methodology and Instrumentation


  • Laser Ablation: Agilent NWR213 deep UV (213 nm) Nd:YAG laser; 4 ns pulses; 200 µm spot; helium carrier gas; pre-ablation to remove surface contamination.

  • ICP-MS: Agilent 7900 with ORS4 collision/reaction cell using H₂ gas; RF power 1550 W; carrier gas 1.15 L/min; integration time 1 s/mass; 50 sweeps; three replicates per line.

  • Sample Prep and Calibration: Wire saw cutting and acid cleaning of CRMs; matrix-matched calibration with COPPERSPEC standards; non-matrix matched semi-quantitative calibration using NIST 612 glass.

  • Data Control: MassHunter 4.2 software with ESI plug-in for automated LA control and synchronized ICP-MS acquisition.

Results and Discussion


  • Matrix-Matched Calibration: Achieved excellent linearity (R²>0.999) for 11 trace elements with detection limits of 6–25 ppb. Measured values in copper CRMs agreed within ±10% of certified concentrations, with good repeatability over three days.

  • Non-Matrix Matched Calibration: Semi-quantitative analysis against NIST 612 produced recoveries within ±50% for most elements in copper, steel and aluminum CRMs. Lower accuracy is attributed to elemental fractionation and mass-dependent drift but remains useful for rapid screening when matched CRMs are unavailable.

Benefits and Practical Applications


  • Minimal sample preparation reduces contamination risk and analyte loss.

  • Matrix-matched calibration delivers high accuracy for trace metals in copper alloys.

  • Semi-quantitative non-matrix matched calibration enables versatile screening of diverse metal matrices.

  • Applicable to industrial QA/QC in metal production, semiconductor wafer inspection, forensic casework and geological materials.

Instrumentation Used


  • Agilent NWR213 UV Nd:YAG laser (213 nm, 4 ns).

  • Agilent 7900 ICP-MS with ORS4 collision cell and MassHunter 4.2 software.

  • Certified Reference Materials: COPPERSPEC copper standards, NIST 612 glass, BAM-M383b, BAM-M385, BAM-310, CRM-191-2.

Future Trends and Potential Applications


Advances in certified reference materials, laser technology (shorter wavelengths, finer spots) and enhanced collision/reaction cell designs will improve the accuracy of non-matrix matched analyses.
Automation, higher throughput platforms and refined data correction algorithms will expand LA-ICP-MS applications in environmental screening, biomedical imaging and rapid industrial QA/QC.

Conclusion


Matrix-matched LA-ICP-MS calibration achieves high accuracy and precision for trace element analysis in high purity metals, while semi-quantitative non-matrix matched methods offer a practical screening alternative.
Optimized laser parameters, internal standardization and advanced cell chemistry underpin reliable quantification and broaden the method’s industrial and research applications.

References


  1. J. Gonzales et al., Journal of Analytical Atomic Spectrometry, 2002, 17, 1108–1113.

  2. B. Wagner, A. Nowak, E. Bulska, K. Hametner, D. Günther, Analytical and Bioanalytical Chemistry, 2012, 402, 1667–1677.

  3. R. E. Russo, X. L. Mao, O. V. Borisov, H. Liu, Journal of Analytical Atomic Spectrometry, 2000, 15, 1115–1120.

  4. P. K. Diwakar et al., Journal of Analytical Atomic Spectrometry, 2014, 29, 339–346.

  5. V. Mozna, J. Pisonero, M. Hola, V. Kanicky, D. Günther, Journal of Analytical Atomic Spectrometry, 2006, 21, 1194–1201.

  6. J. Koch, A. von Bohlen, R. Hergenroder, K. Niemax, Journal of Analytical Atomic Spectrometry, 2004, 19, 267–272.

  7. N. J. G. Pearce et al., Journal of Geostandards and Geoanalysis, 1997, 21, 115–141.

  8. M. Guillong et al., Journal of Analytical Atomic Spectrometry, 2008, 23, 1581–1589.

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