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Experimental design optimization for the ICP-AES determination of Li, Na, K, Al, Fe, Mn and Zn in human serum

  • F. Bianchi
  • , M. Maffini
  • , A. Mangia
  • , E. Marengo
  • , C. Mucchino

Research output: Contribution to journalArticlepeer-review

Abstract

A chemometric approach based on experimental design and desirability functions was used to develop and validated a method for the determination of some metals of biological concern by a fast sequential ICP-AES. The elements considered are Al, Fe, Mn, Zn, Li, Na and K. The experimental design was used to investigate the effects of three instrumental most crucial parameters, such as sheath gas flow rate, pump speed and auxiliary gas flow rate. In order to improve the multielemental analysis speed, although a sequential instrument allows the use of a separate parameter set for each wavelength, regression models and desirability functions were applied to find the experimental conditions providing the highest global sensitivity. Validation was performed in terms of limits of detection (LOD), limits of quantitation (LOQ), linearity, precision and recovery. By using the 167.02 nm wavelength, aluminium LOD was 0.5 μg L-1 while the highest LOD was found for K (65 μg L-1). A linear range of at least three orders of magnitude was statistically demonstrated for each element. Precision was evaluated by testing two concentration levels, and good results in terms of intra-day repeatability were obtained, with R.S.D. values lower than 4.1% at the lowest concentration level. Lacking a suitable certified reference material, trueness was estimated using the recovery rate on fortified samples. The validated method was then used in the quantification of the elements considered in a serum sample.

Original languageEnglish
Pages (from-to)659-665
Number of pages7
JournalJournal of Pharmaceutical and Biomedical Analysis
Volume43
Issue number2
DOIs
Publication statusPublished - 17 Jan 2007

Keywords

  • Desirability function
  • Experimental design
  • ICP-AES
  • Multielemental determination
  • Optimization
  • Validation

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