Université de Lyon, Institut des Sciences Analytiques, UMR 5280 CNRS, Université Claude Bernard Lyon 1, 5 rue de la Doua, 69100 Villeurbanne, France.
ARNA laboratory, Inserm U1212, CNRS UMR 5320, Université de Bordeaux, 146 rue Léo Saignat, 33076 Bordeaux Cedex, France.
Talanta. 2019 Apr 1;195:441-446. doi: 10.1016/j.talanta.2018.11.064. Epub 2018 Nov 27.
Deformulation of a commercial surfactant mixture using Raman spectroscopy and advanced chemometric tools have been investigated. Since the use of surfactants is drastically expanding, their fine identification and quantification are required for quality control and regulation. Dilution of the detergent mixtures combined with Raman spectroscopy for signal extraction tools allowed the extraction of the first information concerning the composition of the mixture. The raw materials identified were thus used in an experimental design to obtain a robust model for the determination of detergent composition. The combination of chemometric tools (independent component analysis and Partial Least Square) and spectroscopic methods provided pertinent information for detergent composition. This methodology can easily be transposed to the industrial world.
使用拉曼光谱和先进的化学计量学工具对商业表面活性剂混合物进行了剖析。由于表面活性剂的使用正在急剧扩大，因此需要对其进行精细的识别和定量，以进行质量控制和监管。将清洁剂混合物稀释后，结合拉曼光谱信号提取工具，可提取有关混合物组成的初步信息。然后，将识别出的原材料用于实验设计，以获得用于确定清洁剂组成的稳健模型。化学计量学工具（独立成分分析和偏最小二乘法）和光谱方法的组合为清洁剂的组成提供了相关信息。这种方法可以很容易地应用于工业领域。
