Search Results (1,767)

The combination of nanogenerator technology and traditional textile materials has given rise to textile-based triboelectric nanogenerators (T-TENGs) structured from fibers, yarns, and fabrics. Due to their lightweight, flexibility, washability, and cost-effectiveness, T-TENGs offer a promising platform for powering and sensing in next-generation wearable electronics, with particularly significant potential in smart healthcare and sports monitoring. However, the inherent electrical and structural limitations of textile materials often restrict their power output, signal stability, and sensing range, making it challenging to achieve both high electrical performance and high sensing sensitivity. This review focuses on the application of T-TENGs in smart healthcare and sports. It systematically presents recent developments in textile material selection, sensing structure, fabric design, working mechanisms, accuracy optimization, and practical application scenarios. Furthermore, it provides a critical analysis of the recurring structural and material limitations that constrain performance and offers constructive pathways to address them. Key challenges such as the low charge density of textile interfaces may be mitigated by selecting low-hygroscopicity materials, applying hydrophobic treatments, and optimizing textile structures to enhance contact efficiency and environmental stability. Issues of signal instability under dynamic deformation call for advanced structural designs that accommodate strain without compromising electrical pathways, coupled with robust signal processing algorithms. By providing a comparative analysis across materials and structures, this review aims to inform future designs and accelerate the translation of high-performance T-TENGs from laboratory research to real-world implementation. Full article

Texture mapping of weft-knitted fabrics plays a crucial role in virtual try-on and digital textile design due to its computational efficiency and real-time performance. However, traditional texture mapping techniques typically adapt pre-generated textures to deformed surfaces through geometric transformations. These methods overlook the complex variations in yarn length, thickness, and loop morphology during stretching, often resulting in visual distortions. To overcome these limitations, we propose Knit-Pix2Pix, a dedicated framework for generating realistic weft-knitted fabric textures directly from knitted unit mesh maps. These maps provide grid-based representations where each cell corresponds to a physical loop region, capturing its deformation state. Knit-Pix2Pix is an integrated architecture that combines a multi-scale feature extraction module, a grid-guided attention mechanism, and a multi-scale discriminator. Together, these components address the multi-scale and deformation-aware requirements of this task. To validate our approach, we constructed a dataset of over 2000 pairs of fabric stretching images and corresponding knitted unit mesh maps, with further testing using spring-mass fabric simulation. Experiments show that, compared with traditional texture mapping methods, SSIM increased by 21.8%, PSNR by 20.9%, and LPIPS decreased by 24.3%. This integrated approach provides a practical solution for meeting the requirements of digital textile design. Full article

The interaction between moisture and textile materials plays a critical role in transient thermal comfort, particularly through the exothermic heat released during wetting. While the heat of wetting has been extensively characterized at the fiber level, its behavior in finished fabrics, where structure, porosity, and air gaps influence moisture uptake, remains poorly understood. This study quantifies the heat of wetting of clothing fabrics using a TAM Air isothermal microcalorimeter under controlled isothermal conditions (23 °C). Five fabric types representing different fiber chemistries (Merino wool, cotton, viscose, and polyester) were evaluated in both folded and dissected forms to assess the influence of sampling methods. Wool fabrics exhibited the highest heat release, followed by viscose and cotton, whereas polyester showed negligible exothermic response due to its non-hygroscopic nature. Overall, fabric-level heat of wetting values were lower and more variable than the corresponding fiber-level values reported in the literature, reflecting the combined effects of fabric structure, air permeability, surface hydrophilicity, and sampling uniformity. These findings demonstrate the feasibility and limitations of isothermal microcalorimetry for characterizing moisture–fabric interactions and highlight the need for improved sampling and measurement protocols to more accurately capture fabric-level sorption heat relevant to clothing comfort. Full article

The increasing environmental impact of the textile industry has led to the development of sustainable production methods. One of the effective approaches is the use of recycled fibers, which helps to save resources, reduce carbon emissions, and support the circular economy. This study investigates the feasibility of producing durable upholstery fabrics incorporating recycled polypropylene (r-PP) and virgin polypropylene (v-PP). Filament yarns with varying r-PP/v-PP blend ratios, produced by the melt spinning process, were used as weft yarns, while commercially available virgin polyester filament yarns were employed in the warp direction for all fabric samples. Performance tests in accordance with the standards were applied to the fabrics and the results were also evaluated statistically. The results show that acceptable performance is achieved in some mechanical properties if similar blend ratios and production parameters are used. In the study, an optimization model was developed to maximize the weft breaking strength using the equations obtained from the regression analyses. With the help of the mathematical model created, the values of other physical and performance properties of the fabric depending on the maximum breaking strength value could be estimated without the need for trial production. The model was solved using Lingo 18.0 optimization software. The solution of the model revealed that the optimum weft yarn blend ratio is 10/90 r-PP/v-PP, and the maximum weft breaking strength value is 562.45 N. Full article

To mitigate the attenuation of color-change sensitivity in cholesteric liquid crystals (CLCs) post-microencapsulation, this study developed MXene-reinforced thermochromic textiles. Monolayer/few-layer MXene nanosheets were fabricated via an etching-intercalation-dispersion approach, while cholesteric liquid crystal microcapsules (CLCMs) were synthesized through a solvent evaporation method. Cotton fabrics were pretreated with polydopamine (PDA), followed by the fabrication of poly(diallyldimethylammonium chloride) (PDAC)/MXene composite coatings via layer-by-layer (LbL) self-assembly and subsequent hydrophobic modification. Systematic characterizations (scanning electron microscopy, SEM; atomic force microscopy, AFM) and performance evaluations revealed that MXene nanosheets have an average thickness of 1.54 nm, while CLCMs display a uniform spherical morphology. The resultant textiles exhibit a reversible red-green-blue color transition over the temperature range of 26.5–29.5 °C, with sensitivity comparable to pristine CLCs and excellent hydrophobicity. This work overcomes the long-standing bottleneck of inadequate color-change sensitivity in conventional liquid crystal microcapsule textiles, offering a novel strategy for the advancement of smart wearable color-changing materials. Full article

This study introduces a synergistic drop-casting, sonication, and thermal treatment (DSTT) method for fabricating multi-walled carbon nanotube (MWCNT)-coated conductive cotton fabrics. The process produced uniform MWCNT networks with a minimum sheet resistance of 0.072 ± 0.004 kΩ/sq. at ~30 wt.% loading. Scanning electron microscopy confirmed an improved MWCNT network. Reproducibility was demonstrated for different fabric sizes, with resistance values remaining consistent within experimental errors. Stability tests showed only minor changes in sheet resistance after 16 weeks of ambient storage and periodic manual bending. Compared to conventional methods such as room-temperature drying, vacuum drying, and sonication alone, DSTT consistently performed better, yielding fabrics with lower resistance and more reliable conductivity. These results highlight DSTT as a reproducible and scalable method for producing conductive cotton fabrics suitable for smart textiles and wearable electronics. Full article

Integrating antibacterial fabrics into wearable technology represents a transformative advancement in healthcare, fashion, and personal hygiene. Antibacterial fabrics, designed to inhibit microbial growth, are gaining prominence due to their potential to reduce infections, enhance durability, and maintain cleanliness in wearable devices. These fabrics offer effective antimicrobial properties while retaining comfort and functionality by incorporating nanotechnology and advanced materials, such as silver nanoparticles, zinc oxide, titanium dioxide, and graphene. The production techniques for antibacterial textiles range from chemical and physical surface modifications to biological treatments, each tailored to achieve long-lasting antibacterial performance while preserving fabric comfort and breathability. Advanced methods such as nanoparticle embedding, sol–gel coating, electrospinning, and green synthesis approaches have shown significant promise in enhancing antibacterial efficacy and material compatibility. Wearable technology, including fitness trackers, smart clothing, and medical monitoring devices, relies on prolonged skin contact, making the prevention of bacterial colonization essential for user safety and product longevity. Antibacterial fabrics address these concerns by reducing odor, preventing skin irritation, and minimizing the risk of infection, especially in medical applications such as wound dressings and patient monitoring systems. Despite their potential, integrating antibacterial fabrics into wearable technology presents several challenges. This review provides a comprehensive overview of the key antibacterial agents, the production strategies used to fabricate antibacterial textiles, and their emerging applications in wearable technologies. It also highlights the need for interdisciplinary research to overcome current limitations and promote the development of sustainable, safe, and functional antibacterial fabrics for next-generation wearable. Full article

CO₂ laser processing has emerged as an efficient dry-finishing technique capable of inducing controlled chemical and morphological transformations in cotton and denim textiles. The strong mid-infrared absorption of cellulose enables localised photothermal heating, leading to selective dye decomposition, surface oxidation, and micro-scale ablation while largely preserving the bulk fabric structure. These laser-driven mechanisms modify colour, surface chemistry, and topography in a predictable, parameter-dependent manner. Low-fluence conditions predominantly produce uniform fading through fragmentation and oxidation of indigo dye; in comparison, moderate thermal loads promote the formation of carbonyl and carboxyl groups that increase surface energy and enhance wettability. Higher fluence regimes generate micro-textured regions with increased roughness and anchoring capacity, enabling improved adhesion of dyes, coatings, and nanoparticles. Compared with conventional wet processes, CO₂ laser treatment eliminates chemical effluents, strongly reduces water consumption and supports digitally controlled, Industry 4.0-compatible manufacturing workflows. Despite its advantages, challenges remain in standardising processing parameters, quantifying oxidation depth, modelling thermal behaviour, and assessing the long-term stability of functionalised surfaces under real usage conditions. In this review, we consolidate current knowledge on the mechanistic pathways, processing windows, and functional potential of CO₂ laser-modified cotton substrates. By integrating findings from recent studies and identifying critical research gaps, the review supports the development of predictable, scalable, and sustainable laser-based cotton textile processing technologies. Full article

Biomedical antennas are essential components in modern healthcare systems, supporting wireless communication, physiological monitoring, diagnostic imaging, and therapeutic energy delivery. Their performance is strongly influenced by proximity to the human body, creating challenges such as impedance detuning, signal absorption, and size constraints that motivate new materials and fabrication approaches. This work reviews recent advances enabling next-generation wearable and implantable antennas, with emphasis on printed electronics, additive manufacturing, flexible hybrid integration, and metamaterial design. Methods discussed include 3D printing and inkjet, aerosol jet, and screen printing for fabricating conductive traces on textiles, elastomers, and biodegradable substrates, as well as multilayer Flexible Hybrid Electronics that co-integrate sensing, power management, and RF components into thin, body-conforming assemblies. Key results highlight how metamaterial and metasurface concepts provide artificial control over dispersion, radiation, and near-field interactions, enabling antenna miniaturization, enhanced gain and focusing, and improved isolation from lossy biological tissue. These approaches reduce SAR, stabilize impedance under deformation, and support more efficient communication and energy transfer. The review concludes that the convergence of novel materials, engineered electromagnetic structures, and AI-assisted optimization is enabling biomedical antennas that are compact, stretchable, personalized, and highly adaptive, supporting future developments in unobtrusive monitoring, wireless implants, point-of-care diagnostics, and continuous clinical interfacing. Full article

The problem of textile industry waste has become increasingly relevant. Recycling clothing industry waste to build acoustic panels is one of the most popular and relatively inexpensive ways to use clothing industry waste. We see a lack of information on the acoustic properties of panels made from waste from the clothing industry. The aim of this research is to determine the acoustic properties of a wide range of clothing industry waste recycled into acoustic panels. The acoustic panels were made from clothing industry waste, a different composition of textile and paper residues generated during digital printing processes. We see that panels made from square-cut scraps knitted and woven fabrics, and from yarns and fibers have relatively good acoustic properties. The panel made only of paper had good acoustic properties, the production of panels from paper and textile resulted in similar acoustic properties. Analyzing the acoustic properties of the double specimen, it was found that testing the double-layered panels, the insertion loss is better; by tripling the samples, it was found that although the acoustic properties improved, they were only marginal. Cellulose fiber boards were characterized by significantly higher air resistance. The air resistance of the boards made from fabric scraps was lower. Full article

The rapid evolution of innovative materials and their 4D printing on fabrics allows textiles to change shape or properties when exposed to external stimuli. This work reviews the fundamentals of 4D printing, briefly revisiting additive manufacturing technology and materials, as both are extensively described in various articles and reviews. It also outlines the advancements in smart textiles and their functionality as multifunctional fabrics. The review focuses primarily on reviewing the technical foundations and emerging applications of 4D-printed smart polymers and their integration onto passive textiles for smart applications. Finally, a critical review is presented, emphasizing the numerous individual developments undertaken not only in academia but also by young students, independent engineers, and entrepreneurs who showcase their progress and various challenges through social media. Easy access to knowledge, digital communication, and an interest in creating new materials and structures with a relatively low budget will allow the advancement and development of 4D printing processing strategies for functional materials, promoting the creation of intelligent and adaptive textile systems. Full article

The increasing discharge of recalcitrant organic dyes from the textile industry necessitates the development of efficient and sustainable wastewater treatment technologies. This study reports the successful eco-friendly fabrication of magnetically separable cerium–manganese ferrite (Ce-MnFe₂O₄) nanocatalysts via a one-pot green synthesis route, utilizing an aqueous extract of Brachychiton populneus leaves. The structural, morphological, magnetic, and optical properties of the synthesized nanocatalysts were systematically investigated. X-ray diffraction (XRD) analysis confirmed the formation of a phase-pure cubic spinel structure, with evidence of Ce³⁺ ion incorporation leading to lattice expansion and the formation of beneficial oxygen vacancies. The composite material exhibited superparamagnetic behavior with a high saturation magnetization of 38.7 emu/g, which facilitates efficient magnetic separation and recovery. Optical studies revealed a direct bandgap of 2.33 eV, enabling significant photocatalytic activity under visible light irradiation. The Ce-MnFe₂O₄ nanocatalyst demonstrated superior performance, achieving degradation efficiencies of 96% for methylene blue and 98% for Congo Red within 90 min. Furthermore, the catalyst demonstrated good operational stability, maintaining 62% of its initial degradation efficiency for CR and 51% for MB after five consecutive reuse cycles. These results underscore the potential of this green-synthesized, magnetically recoverable nanocatalyst as a highly effective and sustainable solution for the remediation of dye-contaminated industrial effluents. Full article

Predicting the thermo-physiological comfort of technical clothing requires an understanding of how microscopic textile structures influence macroscopic properties such as air, heat, and moisture permeability. This work represents the first step towards a multi-scale predictive tool capable of estimating key comfort-related properties from the geometrical features of woven fabrics. Focusing on air permeability, the effect of structural and design parameters was investigated while keeping the fibre material (cotton) constant. A computational framework that combines validated Computational Fluid Dynamics (CFD) simulations with a Fully Connected Neural Network (FCNN) was developed, enabling fast and accurate predictions before production. The CFD model accounts for both intra- and inter-yarn porosity, ensuring reliability across a wide range of fabric configurations. The FCNN, trained on simulation and literature data, achieved a mean absolute relative error of 2.01% and a maximum error of 7.72%, demonstrating excellent agreement with experimental results. The analysis highlights how weave type and yarn density govern airflow resistance, offering an efficient tool for the design and optimisation of breathable technical textiles. Full article

In this work, a multifunctional surface engineering strategy was developed to impart both flame-retardant and hydrophobic properties to cotton fabrics. In the first stage, cellulose fibers were modified with poly(methylvinyl)siloxane containing trimethoxysilyl groups, 2,4,6,8-tetramethyl-divinyl-bis(trimethoxysilylpropyltioethyl)cyclotetrasiloxane, or tetrakis(vinyldimethylsiloxy)tetrakis(trimethoxysilylpropyltioethyl)octasilsesquioxane (POSS). All modifiers contained alkoxysilyl groups capable of forming covalent bonds with cellulose hydroxyl groups. The modification was performed using a dip-coating process followed by thermal curing. This procedure enabled the formation of Si-O-C linkages and the generation of a reactive organosilicon layer on the cotton surface. In the second step, O,O′-diethyl dithiophosphate was grafted directly onto the vinyl-functionalized fabrics via a thiol-ene click reaction. This process resulted in the formation of a phosphorus- and sulfur-containing protective layer anchored within the siloxane-based network. The obtained hybrid coatings were characterized using Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), and SEM-EDS. These analyses confirmed the presence and uniform distribution of the modifiers on the fiber surface. Microscale combustion calorimetry demonstrated a substantial reduction in the heat release rate. Thermogravimetric analysis (TG/DTG) revealed increased char formation and altered thermal degradation pathways. The limiting oxygen index (LOI) increased for all modified fabrics, confirming enhanced flame resistance. Water contact angle measurements showed values above 130°, indicating effective hydrophobicity. As a result, multifunctional textile surfaces were obtained. In addition, the modified fabrics exhibited partial durability toward laundering and retained measurable flame-retardant and hydrophobic performance after repeated washing cycles. Full article

Compression garments are widely employed in medical and sports contexts for their ability to promote venous return, manage oedema, support musculoskeletal function, and enhance athletic recovery. Advances in textile-based compression systems have been driven by innovations in fibres, yarn structures, fabric structure engineering, and design methods. This review critically examines the current literature on compression garments, highlighting the influence of raw materials and yarn architectures on performance, durability, and wearer comfort. Attention is given specially to fabric structures and manufacturing methods, where the evolution from traditional cut-and-sew methods to advanced seamless, flatbed, and circular knitting technologies is highlighted, along with their impact on pressure distribution and overall garment efficacy. The integration of 3D body scanning, finite element analysis, and predictive modelling, which enables more personalised and precise garment design, is also speculated upon. Moreover, the review highlights testing and evaluation methodologies, spanning both in vivo and in vitro based assessments, pressure sensor studies for real-time monitoring, and theoretical models mostly based on Laplace’s law. This literature survey provides a foundation for future innovations aimed at optimising compression garment design for both therapeutic and athletic use. Full article