Search Results (9)

Surface stain contamination poses a critical barrier to the automated, high-precision fiber identification required for industrial-scale waste textile recycling. In this study, a dataset comprising 120 physical specimens (yielding 1200 regions of interest, ROIs) across 12 contamination categories was constructed by contaminating cotton, polyester, and poly-cotton blend textiles with carbon black, protein, and oil stains. The spectral interference effects of stains—including baseline drift and spectral overlapping induced by physical shielding and chemical absorption—were systematically analyzed. To identify the optimal classification pipeline, three mathematical preprocessing methods (First Derivative, FD; Standard Normal Variate, SNV; and Multiplicative Scatter Correction, MSC) were evaluated alongside Support Vector Machine (SVM) and One-Dimensional Convolutional Neural Network (1D-CNN) models. Results show that among the SVM-based pipelines, the FD-SVM model effectively resolves overlapping absorption peaks, achieved an average accuracy of 98.17% ± 1.33%, but remains highly dependent on mathematical preprocessing. In contrast, the 1D-CNN model employing a progressive stacking architecture of multi-scale convolutional kernels attains a highly robust mean accuracy of 99.58% ± 0.56% under a strict specimen-level 10-fold cross-validation. It achieves this by directly utilizing radiometrically calibrated raw spectra, thereby effectively bypassing manual spectral feature engineering. These findings demonstrate that Hyperspectral Imaging coupled with end-to-end deep learning provides a feasible and industrially deployable solution for simultaneous stain detection and fiber identification in waste textile sorting. Full article

Blended polyester (PET)-based textiles comprise a significant portion of post-consumer waste, posing substantial challenges to circular economy initiatives while contributing to microfiber (MF) pollution. Despite the considerable recycling potential of PET textiles, no commercially viable technologies currently exist that can efficiently separate and recycle blended PET-based textile waste on an industrial scale. This review provides a comprehensive analysis of recycling strategies for post-consumer blended PET-based textiles and their subsequent valorization pathways. Mechanical, chemical, and biological recycling processes are mostly not yet market-ready, although chemical approaches are considered particularly promising. The findings highlight a critical need for advanced sorting technologies, enhanced material traceability, and robust MF mitigation strategies to foster circularity and contribute to the United Nations Sustainable Development Goals (SDGs). The results further indicate that mechanical recycling of blended PET textiles leads to significant MF release due to fiber fragmentation, whereas chemical recycling offers the potential for improved material recovery, but remains limited by high energy demand and solvent-related challenges. While closed-loop approaches support true circularity by maintaining textile-to-textile material flows, open-loop pathways repurpose textile waste for high-value non-textile applications. Full article

Canvases and preparation layers consist of diverse materials that respond differently to mechanical stress. In a canvas painting, elongations and shrinkages can cause deformations—either recoverable or permanent—as well as shear stresses and potential cracks, which may weaken the overall structure. This study aims to better understand the interaction between the canvas and preparatory strata in terms of mechanical behavior. To achieve this, a set of canvases and the same types of canvases with preparation layers were selected. Two types of linen and two types of polycotton were chosen to represent contemporary materials currently available in fine-art stores. Additionally, an accelerated aging process was applied to the samples to compare their mechanical response before and after aging. By examining the mechanical behavior of both primed and unprimed canvases through dynamometric tests, a method to evaluate the mechanical degradation attributable to the ground layer has been developed and explained in detail. This method is applicable to cases with similar characteristics. Analysis of the force/elongation graphs for the ground layer allows for the calculation of how this layer evolves with increasing elongation and how the mechanical degradation worsens. The results highlight the differing mechanical behaviors among the analyzed canvas types in both the warp and weft directions, as well as the degradation values resulting from both the aging process and the dynamometric testing of the canvases and ground layers. Full article

Rising volumes of textile waste necessitate the development of more efficient recycling systems, with a primary focus on the optimization of sorting technologies. Near-infrared (NIR) spectroscopy is a state-of-the-art method for fiber identification; however, its accuracy in quantifying textile blends, particularly common polyester/cotton blend textiles, still requires refinement. This study explores the potential and limitations of NIR spectroscopy for quantifying cotton content in post-consumer textiles. A lab-scale NIR sorter and a handheld NIR spectrometer in complementary wavelength ranges were applied to a diverse range of post-consumer textile samples to test model accuracies. Results show that the commonly assumed 10% accuracy threshold in industrial sorting can be exceeded, especially when excluding textiles with <35% cotton content. Identifying and excluding the range of non-linearity significantly improved the model’s performance. The final models achieved an RMSEP of 6.6% and bias of −0.9% for the NIR sorter and an RMSEP of 3.1% and bias of −0.6% for the handheld NIR spectrometer. This study also assessed how textile characteristics—such as color, structure, product type, and alkaline treatment—affect spectral behavior and model accuracy, highlighting their importance for refining quantification when high-purity inputs are needed. By identifying current limitations and potential sources of errors, this study provides a foundation for improving NIR-based models. Full article

Textile production has doubled in the last 20 years, but only 1% is recycled into new fibers. It is the third largest contributor to water pollution and land use, accounting for 10% of global carbon emissions and 20% of clean water pollution. A key challenge in textile recycling is blended yarns, such as polycotton blends, which consist of polyester and cotton. Chemical recycling offers a solution, in particular, alkali treatment, which hydrolyzes polyester (PET) into its components while preserving cotton fibers. However, conventional methods require high temperatures, long durations, or catalysts. Our study presents, for the first time, the heated high-ethanol alkaline aqueous (HHeAA) process that efficiently hydrolyzes PET from polycotton at lower temperatures and without a catalyst. A near-complete PET hydrolysis was achieved in 20 min at 90 °C, while similar results were obtained at 70 °C and 80 °C with longer reaction times. The process was successfully scaled at 90 °C for 20 min, and complete PET hydrolysis was achieved, with a significantly reduced liquid-to-solid ratio, from 40 to 7 (L per kg), signifying its potential to be implemented in an industrial context. Additionally, the cotton maintained most of its properties after the treatment. This method provides a more sustainable and efficient approach to polycotton recycling. Full article

This study evaluates the efficacy of using textile waste blended with paper waste to form biodegradable seedling pots. A bio-composite blend of cotton (20% cotton, 40% newspaper, and 40% corrugated cardboard) and polycotton (20% polycotton, 40% newspaper, and 40% corrugated cardboard) with an optimum strength was formed into seedling pots. The appreciated seedling pots (untreated blends of cotton and polycotton) were compared with the commercial pots (cardboard seed starter pot and Jiffy pot) in terms of mechanical properties (tensile strength and compressive strength), biodegradability (soil burial test and anaerobic digestion), and seed germination. The untreated blends of cotton and polycotton pots demonstrated a comparable optimum strength, while the Jiffy pot and cardboard seed starter pot obtained the least tensile and compressive strengths, respectively. The anaerobic biodegradability assay suggests that the cotton blend pot, polycotton blend pot, and cardboard seed starter pot can degrade anaerobically because of high biogas and methane generation potential. A 100% seed germination was observed from the four seedling pots tested. Thus, the results demonstrate the efficacy of utilizing textile waste and paper waste to develop seedling pots with desirable strength and biodegradability compared to the commercial pots. Full article

This study investigates the efficacy of using discarded textile (cotton and polycotton) and paper waste (newspaper and corrugated cardboard) as substrates to form sheets with optimum tensile strength. The effect of alkali treatment (sodium hydroxide (NaOH) and sodium bicarbonate (NaHCO₃)), compressive loads (200 N and 500 N), and the use of binding agents (blackstrap molasses, sodium alginate, and cornstarch) were studied to optimize the tensile strength of homogeneous sheets. The alkali treatment using 5% NaOH for 5 h of soaking demonstrated the highest increase in tensile strength of 21% and 19% for cotton and newspaper, respectively. Increasing compressive load from 200 N to 500 N showed the highest increase in tensile strength of 37% and 42% for cotton and newspaper, respectively. Remarkably, among the binders, cornstarch at 20% concentration obtained an increase in tensile strength of 395%, 320%, 310%, and 185% for cotton, polycotton, corrugated cardboard, and newspaper sheets, respectively. The optimum results obtained from this study will be utilized to develop biodegradable seedling pots using discarded textile and paper waste. Full article

Designing high-efficiency antennas on textiles is fundamental for the development of wirelessly-connected smart garments. Furthermore, large antenna arrays could be used to receive or harvest directional and ambient radio-frequency (RF) power from the environment, thus enabling battery-free e-textiles. The key challenges that are hindering the realisation of high efficiency antennas lie in the dielectric properties of fabrics, the conductivity of their traces, and their low textile thickness. This work numerically and experimentally analyses different RF transmission line structures to establish the limitations of widely utilised antenna designs, such as the microstrip patch, and proposes alternative wearable antenna design based on coplanar waveguide (CPW) structures. It is demonstrated that by using a CPW, insertion losses in a 20 mm line can be minimized by up to 40% for the same substrate, as compared to a microstrip, at 30 GHz. A CPW monopole antenna is demonstrated with more than 80% efficiency on a lossy, thin, poly-cotton substrate. Moreover, it is shown that the efficiency of the CPW monopole is independent of the substrate’s thickness and type of fabric. Full article

This research aims to develop a non-fluorine based and durable coating technology that brings excellent hydrophobic, oleophobic and aqueous liquid repellent properties to polycotton fabrics (blend ratio 80/20 for cotton/polyester) while maintaining comfort to an acceptable level. A crosslinked network from thermoplastic polyurethane (TPU), polydimethylsiloxane (PDMS) and trimethylated silica (TMS) has been formed on the surface of polycotton fabrics by the conventional padding-knife coating-padding-curing technique. A series of characterizations have been conducted to understand the chemical components, morphology, versatile protection and comfort of the coated fabrics. The TPU-PDMS-TMS (TPT) coated fabrics showed a high hydrophobic surface with a high water contact angle of 142°, and the coating was durable against different cycles of laundering and crocking. The coated fabrics also showed excellent repellency against oils, liquids and chemicals for a long period of time. The coating has affected the air permeability and water vapor permeability together with the moisture management property of the polycotton fabrics, and the thermal resistance of the polycotton fabric has been enhanced at the same time. The coating technology developed can be further applied in protective clothing and functional textiles in different areas including military, mining and outdoor protection gear. Full article