Use of multiple emission lines and principal component regression for quantitative analysis in inductively coupled plasma atomic emission spectrometry with charge coupled device detection

Sadler, D. A.; Littlejohn, David

doi:10.1039/ja9961101105

Cited by 21 publications

(9 citation statements)

References 26 publications

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“…They concluded that the PLS algorithm yielded better accuracy in the presence of uncorrected additive spectral interferences and that there was no theoretical improvement in the detection limit due to the concentration dependence of the noise on the analytical emission line. The procedure was extended by Sadler and Littlejohn 72 to detect the presence of uncorrected additive interferences. The procedure requires no prior knowledge of the matrix components, making the procedure ideal for analysing samples with unknown or complex matrices.…”

Section: Multivariate Calibration Methodsmentioning

confidence: 99%

Improving the Analytical Performances of Inductively Coupled Plasma Optical Emission Spectrometry by Multivariate Analysis Techniques

Grotti

2004

Annali di Chimica

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Section: Multivariate Calibration Methodsmentioning

confidence: 99%

Improving the Analytical Performances of Inductively Coupled Plasma Optical Emission Spectrometry by Multivariate Analysis Techniques

Grotti

2004

Annali di Chimica

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“…Although multi-window approaches have been presented in the literature, [16][17][18][19][20][21] another alternative to selecting a single window is to let the data automatically de ne a statistically determined weighted average of the results…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2000

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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 amdyses 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 aI1spectral 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 ..

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“…special benefit of performing simultaneous multi-element detection and obtains spectral-free lines for each element as required for qualitative analysis (11). The CCD detector provides better resolution so that the spectral-free lines of the trace elements and the REEs can be determined.…”

mentioning

confidence: 99%

Appraising the Spectral Interference of Dysprosium on 27 Analytes Using Capacitively Coupled Device Detector-based Inductively Coupled Plasma Atomic Emission Spectrometry Without Physical/Chemical Separation

Sengupta¹

2016

At.Spectrosc.

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Use of multiple emission lines and principal component regression for quantitative analysis in inductively coupled plasma atomic emission spectrometry with charge coupled device detection

Cited by 21 publications

References 26 publications

Improving the Analytical Performances of Inductively Coupled Plasma Optical Emission Spectrometry by Multivariate Analysis Techniques

Improving the Analytical Performances of Inductively Coupled Plasma Optical Emission Spectrometry by Multivariate Analysis Techniques

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

Appraising the Spectral Interference of Dysprosium on 27 Analytes Using Capacitively Coupled Device Detector-based Inductively Coupled Plasma Atomic Emission Spectrometry Without Physical/Chemical Separation

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