The viscoelastic properties of cellulose fibers play an important role in chemical recycling of textiles. Here we discriminated the intrinsic viscosity of cotton roll towels and bed linens using near-infrared imaging spectroscopy and supervised pattern recognition. The classification results showed training and test set accuracies of 84–97% and indicated that the relevant spectral features were related to water, cellulose, and cellulose crystallinity. We hypothesized that the decreasing intrinsic viscosity of cotton was associated with changes in cellulose crystallinity and water adsorption, which was supported by additional X-ray and sorption measurements. These results are important as they indicate the potential to non-invasively estimate the degree of polymerization and the suitability of different cotton materials for chemical recycling. We propose that changes in the degree of polymerization and cellulose crystallinity could be used as an indicator of the chemical quality of cellulose fibers, which would have wider impacts for textile recycling.

纤维素纤维的粘弹性在纺织品的化学回收中起着重要作用。在这里，我们使用近红外成像光谱和监督模式识别来区分棉卷毛巾和床单的特性粘度。分类结果显示训练集和测试集的准确率为 84-97%，并表明相关光谱特征与水、纤维素和纤维素结晶度有关。我们假设棉花特性粘度的降低与纤维素结晶度和吸水性的变化有关，这得到了额外的 X 射线和吸附测量的支持。这些结果很重要，因为它们表明有可能以非侵入方式估计聚合度和不同棉花材料对化学回收的适用性。