Search Results (185)

This study presents an advanced framework for fabric texture classification by leveraging macro- and micro-texture extraction techniques integrated with deep learning architectures. Co-occurrence histograms, local binary patterns (LBPs), and albedo-dependent feature maps were employed to comprehensively capture the surface properties of fabrics. A late fusion approach was applied using four state-of-the-art convolutional neural networks (CNNs): InceptionV3, ResNet50_V2, DenseNet, and VGG-19. Excellent results were obtained, with the ResNet50_V2 achieving a precision of 0.929, recall of 0.914, and F1 score of 0.913. Notably, the integration of multimodal inputs allowed the models to effectively distinguish challenging fabric types, such as cotton–polyester and satin–silk pairs, which exhibit overlapping texture characteristics. This research not only enhances the accuracy of textile classification but also provides a robust methodology for material analysis, with significant implications for industrial applications in fashion, quality control, and robotics. Full article

The textile industry’s reliance on synthetic dyes contributes significantly to pollution, highlighting the need for sustainable alternatives like biopigments. This study investigates the production and application of the biopigment prodigiosin, which was produced by Pseudomonas putida with a yield of 1.85 g/L. Prodigiosin was prepared under acidic, neutral, and alkaline conditions, resulting in varying protonation states that influenced its affinity for cotton and polyester fibers. Three surfactants (anionic, cationic, non-ionic) were tested, with non-ionic Tween 80 yielding a promising color strength (above 4) and fastness results with neutral prodigiosin at 1.3 g/L. Cotton and polyester demonstrated good washing (color difference up to 14 for cotton, 5 for polyester) and light fastness (up to 15 for cotton, 16 for polyester). Cellulose acetate, used in the conventional printing process as a thickener, produced superior color properties compared to commercial thickeners. Neutral prodigiosin achieved higher color strength, and cotton fabrics displayed halochromic properties, distinguishing them from polyester, which showed excellent fastness. Prodigiosin-printed samples also exhibited strong antimicrobial activity against Pseudomonas aeruginosa and retained halochromic properties over 10 pH cycles. These findings suggest prodigiosin as a sustainable dye alternative and pH sensor, with potential applications in biomedical materials, such as antimicrobial and pH-responsive wound dressings. 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

The textile industry is progressively shifting towards more sustainable solutions, particularly in the field of printing technologies. This study reports the development and evaluation of water-based pigment inks formulated with bio-based pigments derived from intermediates produced via bacterial fermentation. Two pigments—indigo (blue) and quinacridone (red)—were incorporated into ink formulations and applied on cotton and polyester fabrics through valve-jet inkjet printing (ChromoJet). The physical properties of the inks were analyzed to ensure compatibility with the equipment, and printed fabrics were assessed as to their color fastness to washing, rubbing, artificial weathering, and artificial light. The results highlight the good performance of the bio-based inks, with excellent light and weathering fastness and satisfactory wash and rub resistance. The effect of different pre-treatments, including a biopolymer and a synthetic binder, was also investigated. Notably, the biopolymer pre-treatment enhanced pigment fixation on cotton, while the synthetic binder improved wash fastness on polyester. These findings support the integration of biotechnologically sourced pigments into eco-friendly textile digital printing workflows. Full article

The widespread phase-out of long-chain per- and poly-fluoroalkyl substances (PFASs) has created an urgent need for durable, fluorine-free water-repellent finishes that match the performance of legacy chemistries while minimising environmental impact. Here, the performance of an eco-friendly hybrid organic–inorganic treatment obtained by the in situ hydrolysis–condensation of triethoxy(octyl)silane (OS) in an amino-terminated polydimethylsiloxane (APT-PDMS) aqueous dispersion was investigated. The sol was applied to plain-weave cotton and polyester by a pad-dry-cure process and benchmarked against a commercial fluorinated finish. Morphology and chemistry were characterised by SEM–EDS, ATR-FTIR, and Raman spectroscopy; wettability was assessed by static contact angle, ISO 4920 spray ratings, and AATCC 193 water/alcohol repellence; and durability, handle, and breathability were evaluated through repeated laundering, bending stiffness, and water-vapour transmission rate measurements. The silica/PDMS coating formed a uniform, strongly adherent nanostructured layer conferring static contact angles of 130° on cotton and 145° on polyester. After five ISO 105-C10 wash cycles, the treated fabrics still displayed a spray rating of 5/5 and AATCC 193 grade 7, outperforming or equalling the fluorinated control, while causing ≤5% loss of water-vapour permeability and only a marginal increase in bending stiffness. These results demonstrate that the proposed one-step, water-borne sol–gel process affords a sustainable, industrially scalable route to high-performance, durable, water-repellent finishes for both natural and synthetic textiles, offering a viable alternative to PFAS-based chemistry for outdoor apparel and technical applications. Full article

Classical and modern methods are used to release curcumin by degrading the polysaccharides found in the turmeric powder matrix. Classical methods use chemicals as acids (HCl, H₂SO₄, CH₃COOH), oxidants (H₂O₂, kojic acid), and enzymes (amylase type) that can degrade amylose and amylopectin from starch. The modern applied methods consist of the degradation of the polysaccharides in the turmeric powder during eco-friendly processes assisted by ultrasound or microwaves. The extraction medium can consist of only water, water with a solvent, and/or an oxidizing agent. The presence of curcumin in turmeric powder is confirmed by FTIR analysis. The UV–VIS analysis of the extracts allows the determination of the efficiency of modern extraction processes. The release of curcumin from turmeric is highlighted quantitatively by colorimetric measurements for the obtained extracts, using a portable DataColor spectrophotometer. The comparison of the results leads to the conclusion that microwave-assisted extractions are the most effective. These extracts are able to dye many types of textile fibers: wool, cotton, hemp, silk, polyacrylonitrile, polyamide, polyester, and cellulose acetate. CIELab and color strength (K/S) measurements indicate that the most intense yellow colors are obtained on polyacrylonitrile (b* = 86.32, K/S = 15.14) and on cellulose acetate (b* = 90.40, K/S = 14.17). Full article

Alzheimer’s disease (AD) affects a significant portion of humanity’s elderly population across the globe. Recent studies have identified Amyloid-Beta 42 (Aβ₄₂) as a key biomarker for AD. In this research, we examined the feasibility of using string-shaped electrodes to develop a potentially wearable biosensor for the early detection of AD. Two types of flexible electrochemical electrodes were fabricated using a commercial thread (25% cotton-75% polyester) and an electrospun nanofiber-based string. Decorating the strings with either gold or SiC nanoparticles, several different electrodes were tested to explore their responses to Aβ₄₂. Our results show that the nanofiber-based electrode decorated with gold nanoparticles had the highest sensitivity of 1.71 µA/pg.cm and the best limit of detection (LoD) of 8.36 pg/mL. These findings highlight the importance of the string structure in designing highly sensitive sensors. Full article

Overconsumption and unplanned disposal of garments result in millions of tons of textile products going to landfills. Understanding the environmental benefits and impact of various recycling options is crucial for integrating recycling into the apparel waste stream. This study aims to assess the environmental impacts of products made from post-consumer textile waste fibers, highlighting the importance of closed-loop textile supply chains in developing countries. Using Open LCA software, the cradle-to-gate approach for life cycle assessment is used to calculate the environmental impacts of post-consumer textile waste, virgin cotton, virgin polyester fibers, and their blends in two different scenarios. The life cycle inventory data for functional units (1000 kg apparel) has been collected from the industrial units and the Ecoinvent v3.0 database. The results of 16 environmental impact categories are computed, showing that textile products made from virgin cotton fiber have 60% more global warming potential than those made from post-consumer textile waste fibers. Hence, the environmental impact of textile products can be controlled by recycling them. Consumption of post-consumer textile waste fiber is the key to reducing the new material needs in the textile supply chain. The closed-loop apparel supply chain can help developing countries generate maximum financial value with minimal environmental damage. In developing countries, value extraction from post-consumer textile waste recycling is essential to meet international consumer demands for cleaner production. Full article

Textile structures with ohmic (Joule) heating capability are frequently used for personal thermal management by tuning fluctuations in human body temperature that arise due to climatic changes or for medical applications as electrotherapy. They are constructed from electrically conductive textile structures prepared in different ways, e.g., from metallic yarns, conductive polymers, conductive coatings, etc. In comparison with other types of flexible ohmic heaters, these structures should be corrosion resistant, air permeable, and comfortable. They should not loose ohmic heating efficiency due to frequent intensive washing and maintenance. In this study, the basic electrical properties of a conductive fabric composed of a polyester/cotton fiber mixture and a small amount of fine stainless-steel staple fibers (SS) were evaluated and predicted. Even though the basic conductive component of SS fibers is iron and its electrical characteristics obey Ohm’s law, the electrical behavior of the prepared fabric was highly nonlinear, resembling a more complex response than that of a classical conductor. The non-linear behavior was probably due to non-ideal, poorly defined random interfaces between individual short SS fibers. A significant time–dynamics relationship was also shown. Using the Stefan–Boltzmann law describing radiation power, we demonstrated that it is possible to predict surface temperature due to the ohmic heating of a fabric related to the input electrical power. Significant local temperature variations in the heated hybrid fabric in both main directions (warp and weft) were identified. Full article

This paper presents an algorithm for evaluating the environmental impact of clothing swaps, promoting extended use and responsible consumption. Implemented in an online swapping platform, the algorithm quantifies reductions in environmental impact due to extended clothing lifespan and avoided purchase of new garments, promoting swapping activities. Developed through scientific literature analysis, life cycle assessment (LCA), and swapping practice studies, the algorithm uses the following key environmental indicators: carbon footprint, water use, energy consumption, and land use. It integrates consumer behavior insights and uses both default and user-entered clothing data to calculate environmental savings. Results show that clothing impact varies by fabric. Viscose and polyester clothing have the lowest environmental impact, while swapping cotton and wool items yields the highest savings, as these materials are more resource intensive. The platform-integrated algorithm recorded 251 swaps over two months, preventing 4203 kg CO₂ emissions, 6813 m³ of water use, 3118 m²a crop eq of land use, and 88.79 GJ of energy consumption. These findings highlight the significant environmental benefits of prolonging clothing use through swapping. Full article

Advanced deep learning has assisted in various operations in different industries. In the textile industry, the professional must be trained and experienced in fabric classification. Fabrics such as Abaca are difficult to classify as the same base material is intertwined with a different material. The versatile nature of Abaca is used in various products including paper bills, ropes, handwoven handicrafts, and fabric. Abaca fabric is an unsought product of fabric due to its rough texture. Blended Abaca fabrics are traditionally mixed with cotton, silk, and polyester. Due to the combination of the characteristics of the materials, the fabric classification is prone to human error. Therefore, we created a device capable of classifying blends of Abaca fabric using YOLOv8 architecture. We used a Raspberry Pi 4B with camera module v3 to capture images for classification. The dataset consisted of four blends, specifically Abaca, Cotton Abaca, Polyester Abaca, and Silk Abaca. A total 500 images were used to test the model’s performance, and the performance accuracy was 94.6%. Full article

This study focused on developing a color-changing fabric face mask for fever detection. Reversible Thermochromic Leuco dye (RTL) was applied as an indicator to alert wearers of elevated body temperatures, with the color change occurring at 37.5 °C. Five fabric types Polyethylene (PE), cotton (CO), a cotton–polyester blend (TC), polyester (PL), and Polyamide (PA) were coated with blue RTL to evaluate their color change responsiveness. The results showed that fabrics with higher thermal conductivity (λ), thermal absorptivity (b), and heat flow (q) exhibited faster color transitions. RTL-coated PE fabric demonstrated the best performance, with a thermal absorptivity of 312.8 Ws^0.5m⁻²K⁻¹ and a heat flow of 2.11 Wm⁻², leading to a rapid color-change time of approximately 4.20 s. Although PE fabric had a lower thermal conductivity (57.6 × 10⁻³ Wm⁻¹K⁻¹) compared to PA fabric 84.56 (10⁻³ Wm⁻¹K⁻¹), the highest thickness 0.65 mm of PA fabric slowed its color-change reaction to 11.8 s. When selecting fabrics for optimal heat transfer, relying solely on fiber type or thermal conductivity (λ) is insufficient. The fabric’s structural properties, particularly thickness, significantly impact thermal resistance (γ). Experimental results suggest that thermal absorptivity and heat flow are more effective criteria for fabric selection, as they directly correlate with color-change performance. Full article

Vineyard smoke exposure can lead to the accumulation of free and glycosylated volatile phenols (VPs) in grapes, negatively affecting wine quality. Activated carbon fibre (ACF) cloth has proven effective in mitigating smoke contamination of grapes, but its commercial use is hindered by low tensile strength and light transmission. This study therefore compared the efficacy of different fabrics (polyester, polypropylene, cotton and viscose) to mitigate the smoke contamination of grapes (benchmarking against ACF cloth), alongside their physical properties (i.e., tensile strength and air permeability). Polyester and polypropylene provided limited protection, whereas grapes enclosed in cotton or viscose had VP profiles that were comparable to grapes enclosed in ACF cloth (i.e., VP concentrations ≤ 5.3 µg/kg). In a subsequent trial, ACF cloth prevented the uptake of >90% of smoke-derived VPs during ten successive smoke treatments, but after repeated smoke exposure, VP concentrations had increased in grapes enclosed in cotton and viscose, presumably due to saturation. Washing and drying restored the protection afforded by cotton and viscose but resulted in the disintegration of the ACF cloth. However, the application of a non-woven fabric to one or both sides of the ACF cloth improved tensile strength, without significantly compromising air permeability. These findings demonstrate the potential for fabric coverings to be used to mitigate the occurrence of smoke taint in the vineyard, with ACF affording superior protection. 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

Zinc oxide-modified tourmaline-based negative ion polyester fiber (ZnO/TM/PET), as a new functional fiber with excellent negative ion emission characteristics, is of great significance to human health, and its industrial application needs to be expanded and promoted. In this paper, using zinc oxide, tourmaline, and polyethylene terephthalate as the main raw materials, ZnO/TM/PET negative ion functional fiber with 5% ZnO/TM composites was prepared. Then, it was blended with cotton fiber and interknitted with wool yarn and spandex yarn, from which we developed five kinds of negative ion polyester/cotton-blended yarn and four different kinds of knitted double-sided fabric using different equipment and process parameters. The micromorphology of the fiber samples, the basic properties of the blended yarns, and the wearability and functional properties of the knitted fabrics were tested. The results show that the ZnO/TM negative ion additive is randomly dispersed in the polymer matrix without visible conglobation and the fiber has a good appearance. The blending ratio has an important effect on the properties of functional polyester/cotton blended yarn. The higher the ratio of negative ion polyester fiber in the blended yarn, the better the mechanical index of the blended yarn, the higher the negative ion emission, and the lower the hairiness index. The performances of fabric are influenced by the comprehensive action of fiber raw material type, yarn ratio, fabric tightness, and structure. The mechanical properties of the fabric knitted from negative ion polyester/cotton-blended yarn are lower than those made from negative ion polyester filament yarn. In the case of the same fabric structure, the negative ion emission performance, far-infrared emission performance, and antibacterial property of the fabric with a higher ratio of negative ion functional fiber is better than the lower ratio. With the same yarn composition, the negative ion emission performance and air permeability of the fabric with a loose structure are better than that of the fabric with a tight structure, but the moisture permeability, far-infrared emission properties, and antibacterial properties show little difference. Full article