Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Applied Spectroscopy
  • Vol. 54,
  • Issue 9,
  • pp. 1291-1302
  • (2000)

Multi-window Classical Least-Squares Multivariate Calibration Methods for Quantitative ICP-AES Analyses

Not Accessible

Your library or personal account may give you access

Abstract

The advent of inductively coupled plasma atomic emission spectrometers (ICP-AES) equipped with charge-coupled device (CCD) detector arrays allows the application of multivariate calibration methods to the quantitative analysis of spectral data. We have applied classical least-squares (CLS) methods to the analysis of a variety of samples containing up to 12 elements plus an internal standard. The elements included in the calibration models were Ag, Al, As, Au, Cd, Cr, Cu, Fe, Ni, Pb, Pd, and Se. By performing the CLS analysis separately in each of 46 spectral windows and by pooling the CLS concentration results for each element in all windows in a statistically efficient manner, we have been able to significantly improve the accuracy and precision of the ICP-AES analyses relative to the univariate and single-window multivariate methods supplied with the spectrometer. This new multi-window CLS (MWCLS) approach simplifies the analyses by providing a single concentration determination for each element from all spectral windows. Thus, the analyst does not have to perform the tedious task of reviewing the results from each window in an attempt to decide the correct value among discrepant analyses in one or more windows for each element. Furthermore, it is not necessary to construct a spectral correction model for each window prior to calibration and analysis. When one or more interfering elements were present, the new MWCLS method was able to reduce prediction errors compared to the single-window multivariate and univariate predictions. The MWCLS detection limits in the presence of multiple interferences are 15 ng/g (i.e., 15 ppb) or better for each element. In addition, errors with the new method are only slightly inflated when only a single target element is included in the calibration (i.e., knowledge of all other elements is excluded during calibration). The MWCLS method is found to be vastly superior to partial least-squares (PLS) in this case of limited numbers of calibration samples.

PDF Article
More Like This
Univariate and multivariate analyses of strontium and vanadium in soil by laser-induced breakdown spectroscopy

Cuiping Lu, Min Wang, Liusan Wang, Haiying Hu, and Rujing Wang
Appl. Opt. 58(27) 7510-7516 (2019)

Univariate and multivariate analyses of rare earth elements by laser-induced breakdown spectroscopy

Chet R. Bhatt, Fang Y. Yueh, and Jagdish P. Singh
Appl. Opt. 56(8) 2280-2287 (2017)

Evaluation of univariate and multivariate calibration strategies for the direct determination of total carbon in soils by laser-induced breakdown spectroscopy: tutorial

Wesley Nascimento Guedes, Diego Victor Babos, Vinícius Câmara Costa, Carla Pereira De Morais, Vitor da Silveira Freitas, Kleydson Stenio, Alfredo Augusto Pereira Xavier, Luís Carlos Leva Borduchi, Paulino Ribeiro Villas-Boas, and Débora Marcondes Bastos Pereira Milori
J. Opt. Soc. Am. B 40(5) 1319-1330 (2023)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All Rights Reserved