title: Second-derivative variance minimization method for automated spectral subtraction.
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.
authors.affiliation: Purdue University, Department of Chemistry, West Lafayette, Indiana 47907, USA.
authors.forename: Yvette L
authors.initials: YL
authors.lastname: Loethen
authors.forename: Dongmao
authors.initials: D
authors.lastname: Zhang
authors.forename: Ryan N
authors.initials: RN
authors.lastname: Favors
authors.forename: Sara B G
authors.initials: SB
authors.lastname: Basiaga
authors.forename: Dor
authors.initials: D
authors.lastname: Ben-Amotz