Synthetic-materials-induced environmental burdens have shifted the focus of scientists towards sustainable packaging solutions. Three-dimensional (3D) woven fabrics offering superior mechanical durability are a promising solution to the problem. However, this area has remained unattended by researchers in the field of packaging technology. Hence this study focuses on development of warp, weft, and bidirectional interlock 3D woven fabrics for packaging applications. Aiming at mechanical durability, tensile and creep characterization have been carried out, depicting the strong influence of interlacement patterns on mechanical properties. Increasing the number of interlacements decreased tensile and creep strength, such as the lower weftwise tensile strength offered by weft interlock 3D, and vice versa for warp interlock. While elongations were found higher in interlocking directions, creep loadings carried out at 30% and 60% of breaking loads revealed unique after tensile creep behaviors. Weftwise tensile strength decreased after creep; warp interlock 3D entailed 42% decrease in tensile strength after creep. However, warpwise tensile strength was noticed to be higher for weft interlock 3D, owing to alignment of yarns during applied creep, while a decrease was noticed in elongation percentages. In a nutshell, the engineered 3D interlacements entailed successful tailoring of mechanical properties, paving a pathway towards high-strength sustainable packaging.

The study presents an exploratory design-space mapping approach for analysing knitted fabrics through the combined consideration of structural, comfort-related, and optical parameters. The methodology addresses the multi-parameter nature of knitted macrostructures, where functional behaviour emerges from the interaction of yarn composition, stitch architecture, and structural configuration rather than from isolated descriptors. Twelve knitted samples differing in stitch type and yarn linear density, and incorporating photoluminescent and reflective yarns, were analysed. Fabric thickness and air permeability were selected as representative structural and comfort-related parameters, while optical response was characterised using a dimensionless reflectance ratio under multiple illumination conditions. All parameters were normalised to enable comparative representation within a unified design space. The resulting maps reveal visual clusters, structurally isolated cases, and illumination-dependent optical equivalence between structurally different configurations. The findings demonstrate that similar optical performance can be achieved through alternative structural solutions, depending on the illumination context. The proposed approach provides a qualitative, design-oriented framework that supports engineering decision-making without implying optimisation or ranking, while revealing alternative design pathways and context-dependent equivalence.

The effects of fabric type and of the duration of application on fabric water retention, water transfer to skin, and skin hydration do not appear to have been systematically examined despite frequent use of skin hydration as an indicator of skin health and wet fabrics being applied to the skin to increase skin hydration, enhance penetration of treatment, and/or facilitate cooling. In this work, three fiber types (nylon, wool/polyester, and wool), three fabric structures (single jersey, rib 1 × 1, and interlock 1 × 1), and five water levels (30%, 60%, 120%, 180%, and 240%—percent of dry fabric weight) were examined to determine which variables affect water transfer from wet fabrics to Vitro-Skin® (‘skin’). Water transfer was determined by measuring ‘skin’ hydration after exposing ‘skin’ to wet fabric (for 5, 10, and 20 min) when ‘covered’ (i.e., under an occlusive layer) and when ‘not covered’. ‘Skin’ hydration was greater with an occlusive layer and increased as the fabric water content increased. While ‘skin’ hydration increased with longer exposure, hydration decreased when ‘skin’ was under the wet nylon fabric for 20 min without a cover. The highest ‘skin’ hydration was recorded for wool rib and interlock fabrics with a water content of 240% used in combination with an occlusive layer. Where a cover was not used, the effects of fabric variables on ‘skin’ hydration were more pronounced.

Yarn tenacity is one of the vital quality parameters that determine the performance, fabric durability and end use suitability. The tenacity of yarn is largely influenced by the fibre characteristics used. The physical properties of jute fibres, including root content, defect, bundle strength, and fineness, exert a significant influence on yarn tenacity. This study utilized metaheuristic optimized random forest regression (RFR) to predict jute yarn tenacity from fibre parameters. The hyperparameters of the RFR models were optimized using four metaheuristic algorithms: whale optimization algorithm (WOA), grey wolf optimization (GWO), beetle antennae search (BAS) and ant colony optimization (ACO). The model utilized a dataset comprising 414 experimental data with 70% data for training and 30% for testing the model, using input variables such as bundle strength (g/tex), defects (%), root content (%) and fineness (tex) to predict yarn tenacity (cN/tex). The developed models effectively predicted yarn tenacity. However, RFR–GWO achieved slightly better performance with R2 of 1.0 for training set and 0.96 for test set. Regarding execution time, RFR–GWO is the fastest requiring only 14.25 s. SHAP analysis revealed that bundle strength and root content of jute fibre are the most influential factors, whereas defect and fineness exert the least influence on model’s prediction. The best model RFR–GWO was deployed into an interactive Streamlit web application, offering an intuitive and user-friendly platform for the real-time estimation of yarn tenacity.

This paper presents a yarn tension sensor based on Surface Acoustic Waves (SAW). To enhance the detection accuracy of the sensor, an improved beam structure is designed for tension measurement, along with intelligent algorithms for temperature compensation. Firstly, regarding the sensor structure, a simply supported beam with a hyperbolic surface is designed to achieve stress concentration by reducing the section modulus at the beam’s midpoint. Secondly, by incorporating an unbalanced split-electrode Interdigital Transducer (IDT) design, the sensor effectively suppresses signal sidelobe interference and significantly improves the structure’s tension sensitivity. Finally, in terms of signal processing, to eliminate the influence of environmental temperature fluctuations on measurements, a temperature-compensation algorithm based on Bayesian Optimization Least Squares Support Vector Machine (BO-LSSVM) with Gaussian Process regression is proposed. Experimental results show that the tension sensitivity of the improved structure was 8.2% higher than that of the doubly clamped beam and 12.7% higher than that of the cantilever beam. For temperature compensation, the BO-LSSVM model reduced the Mean Relative Error (MRE) by 5.67 percentage points relative to raw data and by 2.04 percentage points relative to the fixed-parameter LSSVM model, lowering the temperature sensitivity coefficient from 4.09 (×10−3/°C) to 0.41 (10−3/°C).

Algae extracts have emerged as a sustainable and eco-friendly alternative to synthetic dyes and functional additives in the textile industry, particularly for dyeing and functionalizing of cotton fabrics. Herein, two types of water-soluble algae extracts from Arthrospira platensis and Porphyridium cruentum were characterized in terms of thermal, structural, and functional properties and used as dye and/or functional agents. Cotton samples were pre-treated with chitosan and alum mordants and compared with commercially treated cationic cotton. The algae extracts were applied through the exhaust method, with variations in temperature, pH, liquor ratio, temperature rise gradient, and extract percentages. The resulting colours, assessed through CIE L*a*b* coordinates and K/S values using UV–Vis spectroscopy, displayed green and pink coloration, with commercial cationic cotton exhibiting more intense colours. Colour fastness measurements were also performed on functionalized cotton fabrics. The water-based algae extracts and functionalized samples were additionally characterized for functional features, displaying an antioxidant activity exceeding 60% (68.13 ± 3.60 and 60.76 ± 1.18, for A. platensis and P. cruentum, respectively). This work highlights their dual role in providing both aesthetic dyeing and functional enhancement of cotton. By using renewable marine resources and eco-friendly water-based processes, this approach supports the development of greener, more sustainable textile technologies.

This study investigates the development of workwear designed to withstand harsh conditions and support physically demanding tasks. Its central aim is to create garments that enhance workers’ comfort and mobility by optimizing ergonomic and anthropometric factors. First of all, expert surveys were collected, and the importance of posture adaptability and material comfort was highlighted. To investigate realistic body–garment interactions, the 3D body scans of the upper body from 34 participants in common working poses were captured. These scans revealed the zones of high deformation, guiding the placement of elastic inserts to improve flexibility in targeted areas. The redesigned garments underwent a two-stage evaluation process. First, Clo3D virtual fittings provided qualitative insights into overall jacket fit and movement behavior. Next, stress and strain mapping offered quantitative validation, showing that fabric stress levels remained below 120 kPa, providing evidence that the added elasticity effectively reduced mechanical load and improved wearability. Expert reviewers confirmed the enhanced fit and functional performance. Overall, the study demonstrates an integrated design strategy that unites textile behavior, body dimensions and biomechanics. This approach not only improves workwear but also offers a transferable framework for developing specialized clothing across other physically intensive professions.

The construction sector faces increasing pressure to reduce the embodied energy of building materials while valorizing industrial waste streams. This study evaluates the direct incorporation of post-industrial textile waste (100% cotton and cotton–polyester blends) in its native form to develop high-performance cementitious ceiling sheets. Composites were fabricated under a controlled hydraulic compaction pressure of 2.0 MPa, optimized to achieve matrix densification while preserving the integrity of the fibrous network. Viscoelastic recovery of the compressed fibers induced a hierarchical double-porosity architecture characterized by macro-voids and hollow fiber lumens. This microstructural evolution reduced thermal conductivity to 0.091 W/m·K, approximately 50% lower than commercial cement–fiber benchmarks—without compromising mechanical compliance. Scanning Electron Microscopy (SEM) revealed a mechanistic decoupling between water absorption and dimensional stability. Although the CP15 formulation (15 wt.% cotton–polyester) exhibited high moisture uptake (~21%), thickness swelling remained limited to 1.35%. This dimensional stability is attributed to the hydrophobic polyester framework, which bridges microcracks and constrains hygroscopic expansion within the cellulosic phase. The optimized CP15 composite achieved a Modulus of Rupture (MOR) of 8.75 MPa, exceeding ISO 8336 Category C, Class 2 requirements. Despite increased thickness, the areal density (10.84 kg/m2) remains compatible with standard gypsum-grade suspension systems, eliminating the need for structural modification. These findings establish a scalable, direct-valorization strategy for circular construction materials delivering enhanced thermal insulation and robust performance under tropical climatic conditions.

Functional polymers are designed to enhance the evaporative cooling capacity of sports clothing ensembles, though little is known about how they alter the material properties of commonly used fabrics. The aim of this study was to quantify the impact of a commercially available textile finish treatment (HeiQ Smart Temp TM) on the structural, thermal, and moisture management properties of synthetic (SYN; 100% polyester) and blended (BLEND; 47% lyocell, 46% cotton, 7% elastane) fabrics. Structural (fabric mass, thickness, bulk density, relative porosity), thermal (air permeability, water vapour permeability, water vapour resistance) and moisture management properties (wetting time, spreading speed, wetting radius, absorption, vertical wicking rate) were assessed and compared between treated and untreated samples. Significant improvements (p < 0.05) in air permeability (SYN: Δ 26.0 mm.s−1; BLEND: Δ 61.6 mm·s−1), wetting time (SYN: Δ 0.3 s; BLEND: Δ 0.3 s), and spreading speed (BLEND: Δ 1.1 mm·s−1; SYN: no change) were recorded following treatment. Non-significant changes in water vapour permeability (SYN: Δ 0.1; BLEND: Δ 0.1), water vapour resistance (SYN: Δ 0.7 Pa·m2W−1; BLEND: Δ 0.4 Pa·m2W−1) and vertical wicking (BLEND: Δ 6.1 mm·s−1; SYN: no change) were also observed following treatment. Though not all material properties improved, this study provides evidence that the functional polymer treatment can enhance the evaporative cooling capacity of sports clothing fabrics. Future research is needed to understand how these results translate to physiological, perceptual, and performance-based effects in wearer trials during exercise.

Deployed armed forces and the public engaged in outdoor activities are at high risk for mosquito bites and the diseases they transmit. Current mosquito bite-resistant garments prevent blood-feeding with slow-release insecticide formulations. Many people today want to avoid contact with pesticides, especially in their clothing. Insecticide treated clothing also is costly and requires regulatory agency approvals. Using mosquito bite-resistant mathematical textile models and a WholeGarment® knitting technique, a seamless garment was constructed with military-compliant, no-melt, no-drip flame retardant yarns using an AiryPique knit architecture. The garment was 99.5% bite proof in walk-in cage bioassays with 200 Aedes aegypti host-seeking mosquitoes where the human subjects did not move for 20 min. A standard flame test and a PyroManTM flammability study validated the garment’s fire protection, a requirement for military uniforms. The thermal physiological comfort tests (air permeability, wetting time/radius, thermal resistance, evaporative resistance, and sweating thermal manikin test) were similar to current army combat uniforms and appropriate for use in everyday clothing. Bite prevention occurred by physically blocking the insect mouth parts from obtaining a blood meal. The knitting technique is well-suited for mass production of bite-resistant clothing through automation, significantly reducing labor, time, and cost by optimizing “fit on demand” for different body types compared to traditional manufacturing methods. This innovation provides a non-insecticidal, safe, scalable, and efficient solution for protecting individuals against mosquito bites.