title: Characterization of surfactant complex mixtures using Raman spectroscopy and signal extraction methods: Application to laundry detergent deformulation.
abstract: This paper presents the analysis of surfactants in complex mixtures using Raman spectroscopy combined with signal extraction (SE) methods. Surfactants are the most important component in laundry detergents. Both their identification and quantification are required for quality control and regulation purposes. Several synthetic mixtures of four surfactants contained in an Ecolabel laundry detergent were prepared and analyzed by Raman spectroscopy. SE methods, Independent Component Analysis and Multivariate Curve Resolution, were then applied to spectral data for surfactant identification and quantification. The influence of several pre-processing treatments (normalization, baseline correction, scatter correction and smoothing) on SE performances were evaluated by experimental design. By using optimal pre-processing strategy, SE methods allowed satisfactorily both identifying and quantifying the four surfactants. When applied to the pre-processed Raman spectrum of the Ecolabel laundry detergent sample, SE models remained robust enough to predict the surfactant concentrations with sufficient precision for deformulation purpose. Comparatively, a supervised modeling technique (PLS regression) was very efficient to quantify the four surfactants in synthetic mixtures but appeared less effective than SE methods when applied to the Raman spectrum of the detergent sample. PLS seemed too sensitive to the other components contained in the laundry detergent while SE methods were more robust. The results obtained demonstrated the interest of SE methods in the context of deformulation.
authors.affiliation: UMR 5280 CNRS, Institut des Sciences Analytiques, Université de Lyon, Lyon 1, 5 rue de la DOUA, 69100 Villeurbanne, France.
authors.forename: Alexandra
authors.initials: A
authors.lastname: Gaubert
authors.affiliation: UMR 5280 CNRS, Institut des Sciences Analytiques, Université de Lyon, Lyon 1, 5 rue de la DOUA, 69100 Villeurbanne, France.
authors.forename: Yohann
authors.initials: Y
authors.lastname: Clement
authors.affiliation: UMR 5280 CNRS, Institut des Sciences Analytiques, Université de Lyon, Lyon 1, 5 rue de la DOUA, 69100 Villeurbanne, France.
authors.forename: Anne
authors.initials: A
authors.lastname: Bonhomme
authors.affiliation: Parrot Drones SAS, Varioptic Business Unit, 24B rue Jean Baldassini, 69007 Lyon, France.
authors.forename: Benjamin
authors.initials: B
authors.lastname: Burger
authors.affiliation: AgroParisTech, UMR 1145 Ingénierie Procédés Aliments, F-75005 Paris, France; INRA, UMR 1145 Ingénierie Procédés Aliments, F-75005 Paris, France.
authors.forename: Delphine
authors.initials: D
authors.lastname: Jouan-Rimbaud Bouveresse
authors.affiliation: AgroParisTech, UMR 1145 Ingénierie Procédés Aliments, F-75005 Paris, France; INRA, UMR 1145 Ingénierie Procédés Aliments, F-75005 Paris, France.
authors.forename: Douglas
authors.initials: D
authors.lastname: Rutledge
authors.affiliation: UMR 5280 CNRS, Institut des Sciences Analytiques, Université de Lyon, Lyon 1, 5 rue de la DOUA, 69100 Villeurbanne, France.
authors.forename: Hervé
authors.initials: H
authors.lastname: Casabianca
authors.affiliation: UMR 5280 CNRS, Institut des Sciences Analytiques, Université de Lyon, Lyon 1, 5 rue de la DOUA, 69100 Villeurbanne, France.
authors.forename: Pierre
authors.initials: P
authors.lastname: Lanteri
authors.affiliation: UMR 5280 CNRS, Institut des Sciences Analytiques, Université de Lyon, Lyon 1, 5 rue de la DOUA, 69100 Villeurbanne, France. Electronic address: claire.bordes@univ-lyon1.fr.
authors.forename: Claire
authors.initials: C
authors.lastname: Bordes
keywords: Deformulation; Design of experiments; ICA; MCR-ALS; Raman spectrometry; Surfactant