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Proceedings Paper

Multivariate calibration applied to the quantitative analysis of infrared spectra
Author(s): David M. Haaland
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Paper Abstract

Multivariate calibration methods are very useful for improving the precision, accuracy, and reliability of quantitative spectral analyses. Spectroscopists can more effectively use these sophisticated statistical tools if they have a qualitative understanding of the techniques involved. A qualitative picture of the factor analysis multivariate calibration methods of partial least squares (PLS) and principal component regression (PCR) is presented using infrared calibrations based upon spectra of phosphosilicate glass thin films on silicon wafers. Comparisons of the relative prediction abilities of four different multivariate calibration methods are given based on Monte Carlo simulations of spectral calibration and prediction data. The success of multivariate spectral calibrations is demonstrated for several quantitative infrared studies. The infrared absorption and emission spectra of thin-film dielectrics used in the manufacture of microelectronic devices demonstrate rapid, nondestructive at-line and in- situ analyses using PLS calibrations. Finally, the application of multivariate spectral calibrations to reagentless analysis of blood is presented. We have found that the determination of glucose in whole blood taken from diabetics can be precisely monitored from the PLS calibration of either mid- or near-infrared spectra of the blood. Progress toward the noninvasive determination of glucose levels in diabetics is an ultimate goal of this research.

Paper Details

Date Published: 1 March 1992
PDF: 9 pages
Proc. SPIE 1575, 8th Intl Conf on Fourier Transform Spectroscopy, (1 March 1992); doi: 10.1117/12.56281
Show Author Affiliations
David M. Haaland, Sandia National Labs. (United States)


Published in SPIE Proceedings Vol. 1575:
8th Intl Conf on Fourier Transform Spectroscopy

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