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Second-Derivative Variance Minimization Method for Automated Spectral Subtraction
Volume 58, Number 3 (March 2004) Page 272-278
Loethen, Yvette L.; Zhang, Dongmao; Favors, Ryan N.; Basiaga, Sara B.G.; Ben-Amotz, Dor
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.