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Applied Spectroscopy

Applied Spectroscopy

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  • Vol. 58, Iss. 3 — Mar. 1, 2004
  • pp: 272–278

Second-Derivative Variance Minimization Method for Automated Spectral Subtraction

Yvette L. Loethen, Dongmao Zhang, Ryan N. Favors, Sara B. G. Basiaga, and Dor Ben-Amotz

Applied Spectroscopy, Vol. 58, Issue 3, pp. 272-278 (2004)


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Abstract

A new second-derivative variance minimization (SDVM) procedure is used to automatically extract spectra of a dilute component (solute) from a mixture whose spectrum is dominated by a major component (solvent). This procedure involves the subtraction of Savitzky-Golay second-derivative preprocessed pure solvent and mixture spectra by minimizing the variance of the difference spectrum. The resulting undifferentiated output spectra contain primarily features associated with the solute and/or solute-induced perturbations of the solvent. The SDVM method is found to outperform several related methods, including a previously proposed derivative minimization method, as demonstrated using 1000 randomly generated solute/solvent synthetic spectral pairs and experimental Raman spectra of dilute solutions of benzene in n-hexane and water in acetone. The former experimental solution produced SDVM difference spectra containing benzene bands with virtually no n-hexane interference, while the latter revealed water-induced shifts in acetone spectral features. Several other types of SDVM applications, such as the spectroscopic analysis of layered composites, are discussed.

Citation
Yvette L. Loethen, Dongmao Zhang, Ryan N. Favors, Sara B. G. Basiaga, and Dor Ben-Amotz, "Second-Derivative Variance Minimization Method for Automated Spectral Subtraction," Appl. Spectrosc. 58, 272-278 (2004)
http://www.opticsinfobase.org/as/abstract.cfm?URI=as-58-3-272

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