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Identification of Hydroxyl and Polysiloxane Compounds via Infrared Absorption Spectroscopy with Targeted Noise Analysis
Summary
This study developed an improved method for identifying specific chemical compounds in polymer materials using infrared spectroscopy with a noise-reduction technique. While focused on polymer analysis rather than microplastics directly, the enhanced detection method could be applied to better identify and characterize microplastic particles in environmental samples. More accurate identification tools are essential for understanding what types of plastics people are exposed to.
This investigation of hydroxyl and polysiloxane absorption peaks in elastic polymer composites reveals significant spectral shifts within the fingerprint region of FTIR spectra. Using poly(vinyl butyral) (PVB) as the base polymer and poly(vinyl acetate) (PVAc) and poly(vinyl alcohol) (PVA) as reference materials, solvent effects on polymer-solvent interactions were systematically analyzed. Among the tested alcohol solvents, PEG 400 induced the most pronounced spectral changes, with the C=O stretching band shifting from 1740 to 1732 cm-1 and the O-H band significantly broadening and downshifting to around 3300 cm-1, reflecting strong hydrogen-bonding interactions. Wavelet-based noise reduction effectively enhanced the signal-to-noise ratio, reducing the baseline standard deviation by over 90%. This study introduces a novel noise-enhanced FTIR recognition model that integrates baseline noise metrics to improve detection sensitivity. The model successfully uncovers subtle structural variations in polymer-solvent systems that are typically masked by conventional FTIR techniques, advancing materials analysis and providing a robust framework for future FTIR-based diagnostics and material characterization.
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