Search Results (1,575)

Smart textiles are an evolving field, but challenges in durability, washing, interfacing, and sustainability persist. Widespread adoption requires robust, lightweight, fully integrated fiber-based conductors. This paper proposes using ultralong carbon nanotube (UCNT) yarns with a width-to-length ratio of several orders of magnitude larger than typical carbon nanotube fibers. These yarns enable the manufacturing of stable, workable structures, composed of a network of twisted fibers (tows), which are suitable for fabric integration. Our research includes the creation of textile prototype demonstrators integrated with coated and non-coated UCNT yarns, tested under military-grade standards for both mechanical durability and electric functionality. The demonstrators were evaluated for their electrical and mechanical properties under washability, abrasion, and weathering. Notably, polymer-coated UCNT yarns demonstrated improved mechanical durability and electrical performance, showing promising results. However, washing tests revealed the presence of UCNT nanofibers in the residue, raising concerns due to their classification as hazards by the World Health Organization. This paper examines the sources of fiber release and discusses necessary improvements to coating formulations and testing protocols to mitigate fiber loss and enhance their practical viability. These findings underscore both the potential and limitations of UCNT yarns in military textile applications. Full article

Automated fabric defect detection is crucial for improving quality control, reducing manual labor, and optimizing efficiency in the textile industry. Traditional inspection methods rely heavily on human oversight, which makes them prone to subjectivity, inefficiency, and inconsistency in high-speed manufacturing environments. This review systematically examines the evolution of the You Only Look Once (YOLO) object detection framework from YOLO-v1 to YOLO-v11, emphasizing architectural advancements such as attention-based feature refinement and Transformer integration and their impact on fabric defect detection. Unlike prior studies focusing on specific YOLO variants, this work comprehensively compares the entire YOLO family, highlighting key innovations and their practical implications. We also discuss the challenges, including dataset limitations, domain generalization, and computational constraints, proposing future solutions such as synthetic data generation, federated learning, and edge AI deployment. By bridging the gap between academic advancements and industrial applications, this review is a practical guide for selecting and optimizing YOLO models for fabric inspection, paving the way for intelligent quality control systems. Full article

The draping of textile semi-finished products for complex geometries is still prone to errors, e.g., wrinkles, gaps, and fiber undulations, leading to reduced mechanical properties of the composite. Reinforcing textiles made from carbon fiber (CF) rovings (i.e., endless continuous fibers) can be draped mainly based on their ability to deform under in-plane shearing. However, CF rovings are hardly stretchable in the fiber direction. These limited degrees of freedom make the production of complex shell-shaped geometries from standard CF-roving fabrics challenging. Contrary to continuous rovings, this paper investigates the processing of spun yarns made of recycled carbon fibers (rCFs), which are discontinuous staple fibers with defined lengths. rCFs are obtained from end-of-life composites or production waste, making them a sustainable alternative to virgin carbon fibers in the high-performance components of, e.g., automobiles, boats, or sporting goods. These staple fiber-spun yarns are considerably more stretchable, which is due to the ability of the individual fibers to slide against each other when deformed, resulting in improved formability of fabrics made from rCF yarns, enabling the draping of much more complex structures. This study aims to develop and characterize woven fabrics based on previous studies of rCF yarns for thermoset composites. In order to investigate staple fiber-spun yarns, a previous micro-scale modeling approach is extended. The formability of fabrics made from those rCF yarns is investigated through experimental forming tests and meso-scale simulations. Full article

This paper presents the research and numerical modeling of heat flow through a textile heat sink (THS). The aim of this research is to create a numerical model of a THS that not only simulates the thermal behavior of knitted fabrics, which are used to construct a THS, but also serves as a predictive tool for the heat flow coming from different devices, thus increasing thermal management safety. By integrating modeling tools with textile engineering, this study contributes valuable insights to the development of effective passive cooling solutions for textronics applications, e.g., in thermal management in the military or air space sectors. THS is a support tool for multilayer insulation (MLI) blankets in space satellites, used to maintain the insulation performance of MLI to retain the extremely low temperature of satellite sensors or fuel tanks. The textile radiator made of spacer knitted 3D fabric consists of monofilament yarns covered with aluminum. THS samples were made on the HD 6/20-65 EL machine of Karl Mayer, with the calibration number E12. Numerical modeling was performed using ANSYS software. The numerical simulations of the temperature gradient presented the heat flow for source temperatures of 50 °C and 70 °C for different values of air velocity. Full article

A significant number of UK fire fatalities have been reported to involve textiles contaminated with emollients. In the following study, the flammability of a variety of fabrics containing 14 different emollients, including paraffin-free creams, was evaluated. This is the first time the impact of the presence of such a large range of emollients has been examined. Horizontal burn tests were conducted on emollient-contaminated fabrics. Significantly earlier ignition time were noted upon heating for all emollient-contaminated fabrics (p < 0.001) when compared to the behaviour of blank fabrics were noted using a vertical burn test. The mean time to ignition for 100% cotton fabric (151 ± 2 g/m²) was reduced from 71.5 to 14.4 s and for 52%/48% polyester/cotton fabric (103 ± 2 g/m²) from 328 to 12.9 s by the presence of emollients. Horizontal burn tests with a direct flame on 100% cotton fabric (114 ± 1 g/m²) displayed an accelerated mean flame speed from 0.0032 to 0.0048 ms⁻¹ and an increased maximum flame height of 56.6 to 175.4 mm for emollient-contaminated fabrics. These findings demonstrate the fire risk of fabrics contaminated with a dried emollient. Their potential to ignite quickly and to propagate a fire may strongly decrease the reaction time of an impacted individual. Therefore, it is important that this risk and appropriate safety advice be continually highlighted and communicated not only in the UK but worldwide. Full article

This study explores how functionalized aromatic P-FRs, specifically phenyl- and phenoxy-based phosphoric acid derivatives, influence the flame retardancy of cotton textiles. By systematically investigating derivatives with varying degrees of phenyl, phenoxy, and acidic hydroxyl terminations, alongside ortho-phosphoric acid as a reference, this work aimed to elucidate the role of aromaticity and functional group composition on both gas- and condensed-phase flame retardant efficacy. Cotton fabrics were treated with comparable phosphorus loadings (~3 g/m²), quantified using inductively coupled plasma optical emission spectroscopy (ICP-OES), to evaluate the gas- and condensed-phase efficacy of the flame retardants. Notably, derivatives with a higher number of acidic hydroxyl terminations exhibited the best flame retardant performance, enhancing char formation through dehydration and condensation reactions during combustion. Thermal analysis (TGA) and microscale combustion calorimetry (MCC) confirmed that phenoxy systems catalyze cotton decomposition more effectively, promoting dehydration through the hydrolysis of phenoxy groups. Furthermore, IR analysis of evolved gases revealed a significant reduction in volatile emissions for phenoxy systems, while this was not observed for phenyl derivatives. These findings underscore the importance of robust condensed-phase mechanisms for achieving effective flame retardancy in cotton textiles. Full article

According to the global strategy of Green course, the production of sustainable textiles using different biodegradable fibres has immense potential for the development of sustainable products. Using one of the most sustainable biobased pure hemp and polylactide fibers yarns, four new biodegradable three-layer weft knitted fabrics with good thermal comfort properties were developed. The inner layer (worn next to the skin) and the middle layer of the knits were formed of hydrophobic polylactide fibers, the outer layer of different amounts (36–55%) of hydrophilic natural hemp fibers. Biodegradable polylactide fiber yarns were used as a replacement for conventional petroleum-based synthetic fibers. Natural hemp fibers are one of the most sustainable fibers derived directly from Cannabis sativa L. plants. The properties of the knitted fabrics were analysed and compared under thermoregulatory-moisture management, thermal resistance, air and water vapour permeability-properties. The results showed that all newly developed knits are ascribed to ‘moisture management’ fabrics according to the summary grading of all indices of moisture management parameters. In addition, it was found that the highest overall moisture management capability is related to the quantity of natural hemp fiber composition in different knitting structures. Based on the overall moisture management capacity (OMMC) index and thermal resistance values of developed knitted fabrics, the performance levels for these materials contacting the skin and intended for the intermediate layer were determined. Full article

Cotton fiber, renewable natural cellulose, make up the largest portion of textile waste. The ionic liquid method has been successfully employed to regenerate waste colored cotton fabric in this study, offering a comprehensive approach to the recycling of waste cotton. The chemical recovery process for reclaimed cellulose materials is crucial for high-value recycling of waste cotton fabrics. In this study, waste and new, colored and white cotton fabrics were used as experimental subjects. The breaking strength, degree of polymerization, iodine adsorption equilibrium value, and crystallinity between old and new fabrics were investigated. Ionic liquid 1-allyl-3-methylimidazole chloride ([AMIM]Cl) and zinc chloride (ZnCl₂) were selected to dissolve decolorized waste cotton fabric. Optimal conditions for dissolving the fabric using [AMIM]Cl were investigated. The best dissolution conditions identified were DMSO at a ratio of 1:1 with a dissolution temperature of 110 °C over a duration of 120 min. Additionally, the optimal film formation parameters included a solution concentration of 6%, solidification time of 3 min, and solidification bath temperature of 0 °C. Regenerated cellulose films from both the ionic liquid system (A-film) and zinc chloride system (Z-film) were prepared. The characteristics of the film produced using the most advanced technology were systematically investigated and evaluated. The results of this study provide a crucial theoretical foundation for the recovery and regeneration of waste cotton fabrics. Full article

Diabetic Foot Ulcers (DFUs) are a significant health and economic burden, potentially leading to limb amputation, with a severe impact on a person’s quality of life. During active movements like gait, the monitoring of shear has been suggested as an important factor for effective prevention of DFUs. It is proposed that, in textiles, strain can be measured as a proxy for shear stress at the skin. This paper presents the conceptualisation and development of a novel strain-sensing approach that can be unobtrusively integrated within sock textiles and worn within the shoe. Working with close clinical and patient engagement, a sensor specification was identified, and 12 load-sensing approaches for the prevention of DFU were evaluated. A lead concept using a conductive adhesive was selected for further development. The method was developed using a Lycra sample, before being translated onto a knitted ‘sock’ substrate. The resultant strain sensor can be integrated within mass-produced textiles fabricated using industrial knitting machines. A case-study was used to demonstrate a proof-of-concept version of the strain sensor, which changes resistance with applied mechanical strain. A range of static and dynamic laboratory testing was used to assess the sensor’s performance, which demonstrated a resolution of 0.013 $\mathrm{\Omega }$ across a range of 0–430 $\mathrm{\Omega }$ and a range of interest of 0–20 $\mathrm{\Omega }$. In cyclic testing, the sensor exhibited a cyclic strain threshold of 6% and a sensitivity gradient of 0.3 ± 0.02, with a low dynamic drift of 0.039 to 0.045% of the total range. Overall, this work demonstrates a viable textile-based strain sensor capable of integration within worn knitted structures. It provides a promising first step towards developing a sock-based strain sensor for the prevention of DFU formation. Full article

This study proposes a Residual Neural Network (ResNet) Convolutional Neural Network (CNN) model for predicting the resistance of colorized conductive fabrics (white, red, green, and blue) fabricated through the Single-Walled Carbon Nanotube dip-coating process using a non-contact image analysis approach. The Analysis of Variance (ANOVA) resulted in a p-value of 2.48426 × 10⁻⁸, confirming a statistically significant relationship between the brightness and resistance of conductive fabrics. Histogram equalization preprocessing was applied to enhance the efficiency of model training. The ResNet model achieved an RMSE of 0.0622 and a coefficient of determination of 0.941585, demonstrating approximately a 58% improvement in performance compared to the baseline CNN. The non-contact resistance evaluation method proposed in this study opens new possibilities for the development of wearable electronic devices and smart textiles, offering a foundational approach for real-time process monitoring and automated quality control in manufacturing. Full article

Due to the lack of UV-protective properties for cotton textiles and the potential of cotton textiles to cause microbes to their users, we synthesized benzimidazole Schiff base derivative (BZI) namely N-((1H-benzo[d]imidazol-2-yl)methyl)-1-(4-fluorophenyl)methanimine and their V(III), Fe(III), Co(II), Ni(II), and Cu(II) complexes as UV protection and antimicrobial agents for cotton textile. Several techniques investigated these compounds: ¹H, ¹³C NMR, IR, UV–Vis, elemental analysis, DTA, and TGA. The Schiff base ligand behaved as a bidentate ligand. The prepared ligand and its complexes are used to treat the cotton fabrics (CFs) by immersing the fabric in the solution of the samples under ultrasonic. The treated cotton fabrics were investigated using IR and SEM-EDX analysis. The UPF values of the treated cotton fabric were obtained. The results showed that the cotton fabric treated with Fe(III) and Cu(II) complexes had excellent UV protection with UPF values of 50+. The disc diffusion method evaluated the treated cotton fabric’s antimicrobial activity. The antifungal activities of the treated CFs demonstrated that the Co(II)-BZI-CF was active on C. albicans with an inhibition zone of 12 mm, while the other samples were inactive on C. albicans and A. flavus. The V(III)-BZI-CF and Fe(III)-BZI-CF had no activity against S. aureus and E. coli bacteria while the other samples gave an inhibition zone of between 10 to 17 mm. Unlike previous studies that primarily focused on either UV protection or antimicrobial properties of metal complexes separately, this research integrates both functionalities by synthesizing benzimidazole Schiff base metal complexes and applying them to cotton textiles, demonstrating enhanced UV protection and selective antimicrobial activity. Full article

Graphene-based textile pressure sensors are emerging as promising candidates for wearable sensing applications due to their high sensitivity, mechanical flexibility, and low energy consumption. This study investigates the design, fabrication, and electromechanical behaviour of graphene-coated nonwoven textile-based piezoresistive pressure sensors, focusing on the impact of different electrode materials and fabrication techniques. Three distinct sensor fabrication methods—drop casting, electrospinning, and electro-spraying—were employed to impregnate graphene onto nonwoven textile substrates, with silver-coated textile electrodes integrated to enhance conductivity. The fabricated sensors were characterised for their morphology (SEM), chemical composition (FTIR), and electromechanical response under cyclic compressive loading. The results indicate that the drop-cast sensors exhibited the lowest initial resistance (~0.15 kΩ) and highest sensitivity (10.5 kPa⁻¹) due to their higher graphene content and superior electrical connectivity. Electro-spun and electro-sprayed sensors demonstrated increased porosity and greater resistance fluctuations, highlighting the role of fabrication methods in sensor performance. Additionally, the silver-coated knitted electrodes provided the most stable electrical response, while spun-bonded and powder-bonded nonwoven electrodes exhibited higher hysteresis and resistance drift. These findings offer valuable insights into the optimisation of graphene-based textile pressure sensors for wearable health monitoring and smart textile applications, paving the way for scalable, low-power sensing solutions. Full article

Compression stockings have long been manufactured in a single color without patterns, but enhancing their aesthetic appeal through knitted designs can improve user compliance. This study explores the potential of punch lace knitted structures to create patterns in compression textiles by seamless knitting technology while maintaining sufficient pressure. The effects of yarn material, number of yarns used, and knitted patterns on pressure and thermal comfort will be studied. The fabric pressure was evaluated using pressure sensors with a leg mannequin, while the thermal properties were measured according to the textile standard. This study found that the pressure and thermal conductivity of fabric are significantly influenced by the number of yarn and yarn materials, but not the knitted pattern. Cupro/cotton/polyurethane yarn (A) exhibits the strongest positive impact on pressure, increasing by 2.03 mmHg with the addition of one end of yarn A while polyamide/lycra yarn (C) exhibits a higher thermal conductivity than yarn A. For air permeability, the number of yarn and knitted patterns significantly affects the ventilation resistance. Pattern B with an additional needle in a float stitch shows 0.023 kPa·s/m lower resistance than pattern A. The findings from this study can be widely used in health, medical, and sports applications. Full article

This study investigated the effectiveness of two lamination methods for integrating electrospun nanofiber membranes with woven nylon fabric for personal protective applications. The first method used a thermoplastic urethane (TPU) nonwoven adhesive, while the second method incorporated both the adhesive and a yarn, with the yarn embedding by sewing. Lamination with the TPU nonwoven adhesive slightly improved the adhesion between the nanofiber membrane and the nylon fabric. However, it decreased the air permeability, with the degree of the decrease depending on the areal density of the TPU adhesive. As the areal density of the TPU increased from 10 g/m² to 30 g/m², the air permeability decreased from 107.6 mm/s to 43.4 mm/s. The lamination resulted in a slight increase in the filtration efficiency for oil aerosol particles (0.3 µm, PM0.3, at a flow rate of 32 L/min) to 96.4%, with a pressure drop of 83 Pa. Embedding non-fusible yarns in the laminate increased the nanofiber/fabric adhesion and permeability. Still, the filtration efficiency and pressure drop were reduced to 74.4% and 38 Pa, respectively, due to numerous pinholes formed in the nanofiber layer during the sewing process. Conversely, incorporating fusible TPU yarns not only improved the interlayer adhesion by 175% compared to using TPU fabric adhesive alone but also increased the air permeability to 136.1 mm/s. However, the filtration performance (87.7%, 72 Pa) was slightly lower than that of the unlaminated nanofiber/fabric pack because the TPU yarns sealed the pinholes during lamination. Lamination embedded with hot-melt yarns provides a versatile approach for combining nanofiber membranes with conventional fabrics. It can be used to develop nanofiber-functionalized textiles for a wide range of applications, including fire protection, electrical insulation, sound absorption, filtration, marine applications, and more. Full article

The exponential increase in medical waste production has increased the difficulty of waste management, resulting in higher medical waste dispersion into the environment. By employing a circular economy approach, it is possible to develop new materials by waste valorization. The employment of biodegradable and renewable agro-food, waste-derived materials may reduce the environmental impact caused by the dispersion of medical waste. In this work, tomato peel recovered cutin was blended with poly(L-lactide-co-ε-caprolactone) (PLAPCL) to develop new textiles for medical application through electrospinning. The textile fabrication process was studied by varying Cut content in the starting suspensions and by optimizing fabrication parameters. Devices with dense and porous structures were developed, and their morphological, thermal, and physical–chemical properties were evaluated through scanning electron microscopy, differential scanning calorimetry, thermogravimetric analysis, and Fourier transformed infrared spectroscopy. Textile material stability to γ-irradiation was evaluated through gel permeation chromatography, while its wettability, mechanical properties, and biocompatibility were analyzed through contact angle measurement, tensile test, and MTT assay, respectively. The LCA methodology was used to evaluate the environmental impact of textile production, with a specific focus on greenhouse gas (GHG) emissions. The main results demonstrated the suitability of PLAPCL–cutin blends to be processed through electrospinning and the obtained textile’s suitability to be used to develop surgical face masks or patches for wound healing. Full article