Differentiation of aged fibers by Raman spectroscopy and multivariate data analysis

Area of Science:

• Analytical Chemistry
• Materials Science
• Spectroscopy

Background:

• Textile aging affects fiber properties and appearance.
• Accurate methods are needed to assess textile aging.
• Dye formulation and aging conditions can alter fiber spectra.

Purpose of the Study:

• To develop and validate a Raman spectroscopy method for discriminating aged cotton fibers.
• To assess the method's reliability across different textile types and aging conditions.

Main Methods:

• Raman spectroscopy with a 780nm near-infrared laser was employed.
• Multivariate data analysis, including discriminant analysis, was used for spectral interpretation.
• Leave-one-out cross-validation was performed to assess model prediction ability.

Main Results:

• Discriminant analysis achieved 100% correct classification of aged cotton fibers.
• The predictive model demonstrated 100% accuracy for 3 out of 4 investigated series.
• The approach successfully discriminated aged vs. new polyamide and polyester textiles.

Conclusions:

• Raman spectroscopy combined with multivariate analysis is a highly effective tool for identifying aged textile fibers.
• The developed method is reliable and applicable to various synthetic and natural fibers.
• This technique offers a robust solution for textile quality control and authentication.