研究目的
Investigating the effects of weathering and photodegradation on pre-dyed textile fibers using non-destructive excitation-emission fluorescence spectroscopy paired with discriminant unfolded-partial least squares for classification and differentiation.
研究成果
Fluorescence spectroscopy combined with DU-PLS effectively classified and differentiated dyed cotton and nylon fibers exposed to different weathering conditions and time intervals. The method provides a non-destructive approach for forensic analysis, with potential applications in determining the weathering history of fibers. Future studies should explore broader fiber types and environmental factors.
研究不足
The study had limitations in differentiating acrylic fibers exposed to certain weathering conditions, as they showed less sensitivity to photodegradation. The method may not be fully effective for all fiber types or under all environmental conditions, and computational time was optimized by excluding certain wavelength regions, which could potentially omit relevant data.
1：Experimental Design and Method Selection:
The study involved exposing pre-dyed textile fibers to outdoor weathering conditions in Arizona (dry) and Florida (humid) for 0, 3, 6, 9, and 12 months. Fluorescence microscopy was used to collect excitation-emission matrices (EEMs), and discriminant unfolded partial least-squares (DU-PLS) was applied for statistical analysis and discrimination between fiber samples.
2：Sample Selection and Data Sources:
Undyed fabrics (Acrylic 864, Nylon 361, Cotton 400) were pre-dyed with specific dyes (Basic Green 4, Acid Yellow 17, Direct Blue 1) and exposed to weathering. Ten fibers were sampled from each cloth piece after each exposure interval.
3：List of Experimental Equipment and Materials:
Equipment included a BX-51 epifluorescence microscope (Olympus), FluoroMax-P spectrofluorimeter (Horiba Jobin Yvon), fiber-optic bundles, objective lens, pinhole wheel, CCD camera, xenon arc lamp, monochromators, photomultiplier tube, and DataMax software. Materials included textile fabrics, dyes from Sigma-Aldrich, and cleaning agents like methanol.
4：Experimental Procedures and Operational Workflow:
Fibers were mounted on quartz slides, EEMs were recorded using specific excitation and emission ranges, with scatter regions excluded. Data were processed using MATLAB for DU-PLS analysis, involving calibration and validation sets.
5：Data Analysis Methods:
DU-PLS algorithm was used for discriminant analysis, with cross-validation to determine optimal latent variables. Data matrices were unfolded and analyzed to classify fibers based on weathering conditions and exposure times.
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