Textiles, Volume 5, Issue 4 (December 2025) – 14 articles

Classification is a crucial task for reintroducing end-of-life fabrics as raw materials in a circular process, thus reducing reliance on dyeing processes. In this context, this review explores the evolution of automated and semi-automated colour classification methods, emphasizing the transition from deterministic techniques to advanced methods, with a focus on machine learning, deep learning, and particularly Convolutional Neural Networks (CNNs), and Recurrent Neural Networks (RNNs). These technologies show potential for improving accuracy and efficiency. The results highlight the need for enriched datasets, deeper AI integration into industrial processes, and alignment with circular economy objectives to enhance sustainability without compromising industrial performance. Tested against a case study, the different architectures confirmed the state-of-the-art statements demonstrating that they are effective in classification, with better performance reached by CNN-based methods, which outperforms other methods in most colour families, with an average accuracy of 86.1%, indicating its adaptability for this task. The adoption of the proposed AI-based colour-classification roadmap could be effective in reducing dyeing operations, lower costs, and improve sorting efficiency for textile SMEs. Full article

Flexible and wearable thermoelectric devices can convert body waste heat into electricity, showing a new direction to solve the long-lasting issue of energy supply on portable devices. However, thermoelectric fibers are prone to short circuits and failure due to sweat stains and washing practices. Therefore, it is quite necessary to solve this problem to realize the practical thermoelectric device. PDMS, with its excellent insulation and flexibility, can effectively address short-circuit issues by encapsulating the surface of thermoelectric fibers. In this work, hydrophilic nano-silica (H-SiO₂)-modified PDMS that insulates materials was prepared and coated on the surfaces of polyethyleneimine (PEI)- and hydrochloric acid (HCl)-treated dual-surface-modified thermoelectric fibers. The encapsulated fibers were then woven into spacer fabric to prepare thermoelectric textiles (TETs). After 50 water washing cycles, the fibers retained 97% of their conductivity, and the textiles continued to function normally underwater, indicating that the thermoelectric fibers are effectively protected under PDMS encapsulation. Full article

This study explores the development of luminescent wearables using machine embroidery with phosphorescent threads to enhance the visibility and safety of children in low-light environments, addressing the need for improved child protection in urban settings. Five embroidery designs incorporating sports, animal, celestial, and typographic motifs were created using Digitizer MBV 2.0 software and produced on a Janome MB4 embroidery machine with phosphorescent threads on black woven fabric for optimal contrast. The luminous performance was evaluated through photographic documentation and lux meter measurements in a controlled light-tight chamber, assessing light emission intensity and decay over time after UV activation. Results demonstrate that designs with higher stitch counts and densities exhibit stronger initial illuminance and longer persistence, with exponential decay curves highlighting rapid initial intensity loss. Variations in design size and stitch density showed linear correlations with illuminance. The study demonstrates the feasibility of luminescent embroidery as a scalable and child-friendly approach to enhancing low-light visibility and safety, combining functionality with aesthetic appeal. Full article

Washing performance depends on the specific interactions between textiles, stains, detergents, mechanical action, temperature, and time. Its evaluation therefore requires a fundamental and practical understanding of the effects of the washing parameters, the type of soiling, and the tendency of the textiles to stain. Due to the complexity of these interactions, the evaluation of stain removal requires specific types of textiles, stains, and detergents. In this study, the temperature-specific behavior of detergents was studied in the washing process of cotton knitwear with a blank spot and 15 stains of different origin and composition at 60 °C and 90 °C. Despite the labeled composition of detergents, the detergent ingredients, surfactants, and bleaching agents were analyzed by titration methods. The evaluation of the total washing performance (TWP) and specific washing performance (SWP) was carried out by measuring reflectance as a spectral parameter. A hierarchical cluster analysis was carried out to compare the specific effects of detergents at both temperatures. The analysis of the detergents revealed fluctuations in the content of the surfactants and bleach. Some detergents with a higher surfactant content (SAS) showed poorer performance in washing at 60 °C compared to detergents with a lower SAS content. The dendrogram showed subtle similarities and dissimilarities between the detergents, which contributed to clarification of the total wash performance at both temperatures. The results proved that the quantitative indicators of the proportions of certain ingredients in a detergent are not the only criteria for evaluating the quality of a particular detergent. All detergents investigated showed a temperature-specific behavior, which was reflected in an increased TWP at 90 °C, while some detergents selectively improved the SWP at 90 °C. Full article

Digital Twin (DT) models are gaining attention as promising tools for improving efficiency, sustainability, and responsiveness in textile manufacturing. This paper provides a critical review of existing DT applications and outlines seven underexplored areas where such systems could offer tangible benefits. By linking DT models with real-time data, textile producers can optimise energy usage, reduce production errors, enhance machine reliability, and accelerate decision-making processes. Moreover, DTs offer long-term opportunities for smarter waste management, personalised production with lower return rates, and better workforce training. The paper concludes with stakeholder-specific recommendations, such as integrating digital product passports for recyclability, and calls for a cross-disciplinary approach to digital transformation in the sector. These findings offer practitioners a roadmap for adopting DT technologies not only as monitoring tools but as strategic enablers for circularity, agility, and competitiveness. Full article

The apparel industry is changing dynamically and quickly to manufacturing sustainable fashion products and the development of sustainable design strategies that minimize material consumption at the source. This study addresses a critical research gap by quantitatively evaluating the impact of fusing traditional South Asian garment construction (the kameez) with varied, Western-inspired sleeve geometries on key manufacturing metrics. Thirty-three distinct women’s garment styles, comprising three kameez types (simple, princess-cut, open-front) each paired with eleven different sleeve designs, were developed in the apparel industry to study the effect of fabric efficiency, wastage, and cost-effectiveness. The virtual patterns and markers were drafted and accomplished through Garment Gerber Technology (GGT) software to analyze fabric consumption, fabric efficiency, and cost-effectiveness. The results revealed that paneled kameez styles, such as the princess-cut and open-front, are significantly more material-efficient, achieving average fabric efficiencies of up to 83.95%, compared to the monolithic simple kameez, which averaged only 75.68%. Among sleeve types, multi-constructions like the slit sleeve and cuff sleeve proved most efficient (achieving up to 86.91% efficiency), while voluminous, single-piece designs like the umbrella sleeve consumed the most fabric and were the least efficient. Open-front kameez slit sleeves (OFSL3), simple kameez slit sleeves (SSL3), and princess-cut kameez slit sleeves (PCSL3), were better and more sustainable selections since they were most efficient in fabric efficiency (i.e., 86.91%, 86.17%, and 86.09%). Furthermore, the simple kameez style has the highest fabric wastage (above 22%), while the princess kameez style has the least (below 19%). The simple kameez slit sleeves design (SSL3) has the minimum wastage, while the simple kameez umbrella sleeves design (SSL4) has the maximum wastage. From a cost perspective, the open-front kameez slit sleeve (OFSL1) was identified as the most economical design, whereas the simple kameez with an umbrella sleeve (SSL4) was the most expensive. Statistical analysis confirmed that the differences between kameez styles were significant (p < 0.05). Thus, adoption of specific, sustainable, deliberate design choices and incorporating paneling into the garment body and utilizing multi-piece sleeve constructions offer a quantifiable and strategic approach for manufacturers to reduce material waste, optimize fabric utilization, and improve production cost-effectiveness. Full article

Distressed fabric is a popular fashion trend that adds a distinct visual appeal to garments. Distressing involves acid washing with pumice stones containing potassium permanganate. This approach is inappropriate for knitted textiles, which can generate holes and reduce quality. This project seeks to create an Elasto Ball (EB) as an alternative to pumice stones in the acid-washing procedure of knitted materials. The Elasto Ball consists of natural rubber foam filled with silica and a silica–lignin hybrid derived from rice husks. The efficacy of the filler is enhanced during the manufacturing of Elasto Ball by employing the NXT silane coupling agent throughout the silanization process. The silanized elasto ball exhibits thermal stability up to 400 °C and a porosity of up to 5%. In garment washing assessments, the Elasto Ball can diminish the fabric’s color by 40–50% without causing damage. The findings of this study indicate that Elasto Ball can function as an efficient, eco-friendly substitute for washing balls in garment washing procedures. Full article

This paper presents an innovative protocol for fabric functionalization using Tormentillae rhizoma extract, the chemical composition of which was proved via LC/MS analysis. The extract demonstrated antioxidant activity > 99%, and antibacterial efficacy against E. coli and S. aureus > 99%. Cotton, wool, polyamide, and cellulose acetate were functionalized with the prepared extract, all showing > 90% antioxidant activity. Functionalized cotton, wool, and polyamide exhibited > 99% antibacterial activity against both bacteria. Based on these findings and the fabrics’ ability to release bioactive compounds, functionalized cotton and polyamide fabrics having excellent bioactivity but a lower ability to release bioactive compounds can serve as protective fabrics for people with sensitive skin prone to wounds, and various products for hospitals. Functionalized wool was identified as the most suitable wound dressing for in vivo preclinical investigation on Wistar albino rats. The obtained results showcased a wound-healing rate of 95.54%, and hydroxyproline content of 8.08 µg/mg dry tissue for rats treated with functionalized wool. Compared to negative, positive, and a group of rats treated with non-functionalized wool, those treated with functionalized wool demonstrated elevated values of tissue redox state parameters, superoxide dismutase (SOD) and catalase (CAT), and a notable reduction in thiobarbituric acid reactive substances (TBARS) value. Analysis of the blood samples of rats treated with functionalized wool indicated increased levels of antioxidant defense system parameters (SOD and CAT) and decreased pro-oxidative markers superoxide (O₂⁻) and TBARS. Further clinical trials are needed to validate these findings. Full article

The garment manufacturing industry, being labor-intensive, has long faced challenges in automating the sewing process due to the flexibility and deformability of fabrics. This study proposes a novel strategy for automated sewing by integrating soft fingers and machine vision technology. Firstly, leveraging the flexibility and adjustability of soft fingers, combined with the motion characteristics of the sewing machine, a sewing model was established to achieve coordinated operation between the soft fingers and the sewing machine. Experimental results indicate that the fabric feeding speed and waiting time of the soft fingers are significantly correlated with the sewing speed and stitch density of the sewing machine, but not with the fabric properties. Secondly, machine vision technology was employed to inspect the quality of the sewn fabrics, achieving a classification accuracy of 97.84%. This study not only provides theoretical and technical support for the intelligent upgrading of the garment manufacturing industry but also lays the foundation for the automation of complex sewing processes such as quilting. Future research will further optimize the system’s performance and expand its applications in more complex sewing tasks. Full article

As the importance of sustainability and performance increases, new developments in the manufacturing of fiber-reinforced polymer composites (FRPC) are requested. Ultraviolet (UV) curing offers a faster, more economical, and eco-friendlier alternative to conventionally used thermal curing methods, e.g., autoclave curing, but according to extant research, also presents some shortcomings, such as limitations to thin FRPCs and transparent glass fibers (GFs). This study analyses the UV light transmission in different thermoset FRPCs by irradiating various fiber samples on one side, while a sensor on the opposite side measures the transmitted irradiance. The materials investigated include unidirectional (UD) carbon fibers (CF), UD flax fibers (FF), and six GF fabrics with different ply structures. The fiber samples are tested in a dry, non-impregnated state and a resin-impregnated state using a UV-curable vinyl-ester-based resin. The results show that up to 16 plies of five GF fabrics are fully cured within the 20 s irradiation time and still exhibit a relatively high light transmission, revealing the potential of curing thick FRPCs with UV light. Furthermore, up to three plies of non-transparent FFs are cured, which is promising for the UV curing of natural fibers. Full article

Water scarcity is an escalating global challenge, driven by climate change and population growth. With only 2.5% of Earth’s freshwater readily accessible, there is an urgent need to explore sustainable alternatives. Textile-based fog collectors are advanced tools which have shown great potential and have gained remarkable attention across the world. This review critically evaluates emerging technologies for freshwater generation, including desalination (thermal and reverse osmosis (RO)), fog and dew harvesting, atmospheric water extraction, greywater reuse, and solar desalination systems, e.g., WaterSeer and Desolenator. Key performance metrics, e.g., water yield, energy input, and water collection efficiency, are summarized. For instance, textile-based fog harvesting devices can yield up to 103 mL/min/m², and modern desalination systems offer 40–60% water recovery. This work provides a comparative framework to guide future implementation of water-scarcity solutions, particularly in arid and semi-arid regions. Full article

Detecting chemical residues on surfaces is critical in environmental monitoring, industrial hygiene, public health, and incident management after chemical releases. Compounds such as acrylonitrile (ACN) and tetraethylguanidine (TEG), widely used in chemical processes, can pose risks upon residual exposure. Hyperspectral imaging (HSI), a high-resolution, non-destructive method, offers a secure and effective solution to identify and spatially map chemical contaminants based on spectral signatures. In this study, we present an HSI-based framework to detect and differentiate ACN and TEG residues on textile surfaces. High-resolution spectral data were collected from three representative textiles using a hyperspectral camera operating in the short-wave infrared range. The spectral datasets were processed using standard normal variate transformation, Savitzky–Golay filtering, and principal component analysis to enhance contrast and identify material-specific features. The results demonstrate the effectiveness of this approach in resolving spectral differences corresponding to distinct chemical residues and concentrations but also provide a practical and scalable method for detecting chemical contaminants in consumer and industrial textile materials, supporting reliable residue assessment and holding promise for broader applications in safety-critical fields. Full article

The fast fashion industry has significantly increased global textile demand, driving a surge in fiber production. However, only a minimal portion of this fiber comes from recycled sources. In the United States alone, a vast amount of textile waste is generated annually, with over half ending up in landfills, contributing to environmental degradation and global warming. These developments underscore the urgent need for scalable and efficient textile recycling solutions to address both economic and ecological challenges in the fashion industry. Among recycling methods, mechanical recycling stands out for its low cost and simplicity, making it suitable for processing various types of textile waste. This article reviews current knowledge, identifies key research gaps, and provides direction for future studies in mechanical textile recycling. Despite progress, significant challenges remain in improving the quality and efficiency of recycled fiber. This study shows the importance of advancing pretreatment methods and sorting technologies, and highlights understanding regarding shredding, opening processes, and fabric structural properties. Full article

This study presents the influence of the type of weave and relative fabric density on surface roughness and the coefficient of friction in raw cotton woven fabrics. Relative fabric density, which represents how full a fabric is compared to the maximum packing density allowed by its weave, provides a more accurate basis for comparison than absolute fabric density. Analysis revealed that both the type of weave and relative fabric density have a statistically significant effect on surface roughness, while neither factor significantly impacts the coefficient of friction. Notably, increasing relative fabric density consistently reduces surface roughness in plain, 2/2 twill, and, to some extent, 5-end satin fabrics, with plain fabrics showing the highest roughness overall. At high densities, 2/2 twill fabrics exhibit greater structural stability, yielding smoother surfaces than 5-end satin fabrics, reversing trends detected at lower densities. Furthermore, the relationship between surface roughness and friction was decoupled in plain and 2/2 twill fabrics—specifically, increased density leads to smoother surfaces and higher friction. 5-end satin fabrics were unique in showing a simultaneous reduction in both surface-mechanical properties as fabric density increased. These findings highlight that relative fabric density is a critical parameter for engineering fabrics with tailored performance properties. Full article