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Thermogravimetry as a tool to evaluate the contribution of different fabric constituents to fibre release
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This study introduces a thermogravimetric analysis method using DTG signal deconvolution to rapidly estimate the composition of textile fiber blends, demonstrating its accuracy across polyester, cotton, wool, and acrylic mixtures and its applicability to identifying fibers shed during pilling — a major source of microplastic release.
Abstract This study introduces a methodology to easily estimate the composition of textile fibre mixtures, whether they are arranged in fabrics or fibre bundles, in order to assist the examination of fibre release from textiles, simplifying the process of analysis. The proposed method consists of the deconvolution of DTG signals, and the identification of the constituent associated with each peak. To assess the effectiveness of this method, the study analyses raw textile fibres, both individually and blended in different systems to characterize the thermal degradation of each one and their interaction when mixed. Such analysis of raw fibres is applied to commercial fabrics with known compositions and their released fibres in pilling experiments. The studied fibres are polyester (PET), cotton, wool and acrylic, while the blends encompass the systems PET + cotton, PET + wool, PET + cotton + acrylic. Hence, the method is evaluated. It can be applied to fast identification of textile compositions and can further aid in the identification of fibres in pilling tests.
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