Nowadays, Water pollution is a major global issue brought on by the mixing of effluents from various industries, such as leather, paper, printing, cosmetics, Textile etc., containing metal ions and dyes. This impact causes severe damage to the health of humans, aquatic plants and animals. In view of removing the dyes from the wastewater, several techniques available pose certain drawbacks. To combat such issues, a rapid, cost-effective, eco-friendly, and sludge-less method for removing dye from the effluent using activated Ricinus communis stem as a catalyst in the solar irradiation method is discussed and reported with results. The adsorption studies carried out, followed by degradation of methyl red onto Si-RCS, shows 86% in the presence of natural sunlight, and the optimum dye concentration was 20 ppm at 0.25 g photocatalyst dosage. It depicts that the prepared adsorbent material, Si-RCS, can be used as an effective adsorbent as well as a photo-catalyst to treat textile effluents. The best fit model was found to be pseudo-second order based on the R2 value. Among the isotherm models studied, it was found that Langmuir is the best fit model.
We introduce Textile IR, a bidirectional intermediate representation that connects manufacturing-valid CAD, physics-based simulation, and lifecycle assessment for fashion design. Unlike existing siloed tools where pattern software guarantees sewable outputs but understands nothing about drape, and physics simulation predicts behaviour but cannot automatically fix patterns, Textile IR provides the semantic glue for integration through a seven-layer Verification Ladder -- from cheap syntactic checks (pattern closure, seam compatibility) to expensive physics validation (drape simulation, stress analysis). The architecture enables bidirectional feedback: simulation failures suggest pattern modifications; material substitutions update sustainability estimates in real time; uncertainty propagates across the pipeline with explicit confidence bounds. We formalise fashion engineering as constraint satisfaction over three domains and demonstrate how Textile IR's scene-graph representation enables AI systems to manipulate garments as structured programs rather than pixel arrays. The framework addresses the compound uncertainty problem: when measurement errors in material testing, simulation approximations, and LCA database gaps combine, sustainability claims become unreliable without explicit uncertainty tracking. We propose six research priorities and discuss deployment considerations for fashion SMEs where integrated workflows reduce specialised engineering requirements. Key contribution: a formal representation that makes engineering constraints perceptible, manipulable, and immediately consequential -- enabling designers to navigate sustainability, manufacturability, and aesthetic tradeoffs simultaneously rather than discovering conflicts after costly physical prototyping.
Traditional textile factories consume substantial energy, making energy-efficient production optimization crucial for sustainability and cost reduction. Meanwhile, deep neural networks (DNNs), which are effective for factory output prediction and operational optimization, require extensive historical data, posing challenges due to high sensor deployment and data collection costs. To address this, we propose Ensemble Deep Transfer Learning (EDTL), a novel framework that enhances prediction accuracy and data efficiency by integrating transfer learning with an ensemble strategy and a feature alignment layer. EDTL pretrains DNN models on data-rich production lines (source domain) and adapts them to data-limited lines (target domain), reducing dependency on large datasets. Experiments on real-world textile factory datasets show that EDTL improves prediction accuracy by 5.66% and enhances model robustness by 3.96% compared to conventional DNNs, particularly in data-limited scenarios (20%-40% data availability). This research contributes to energy-efficient textile manufacturing by enabling accurate predictions with fewer data requirements, providing a scalable and cost-effective solution for smart production systems.
The increasing demand for sustainable textile recycling requires robust automation solutions capable of handling deformable garments and detecting foreign objects in cluttered environments. This work presents a digital twin driven robotic sorting system that integrates grasp prediction, multi modal perception, and semantic reasoning for real world textile classification. A dual arm robotic cell equipped with RGBD sensing, capacitive tactile feedback, and collision-aware motion planning autonomously separates garments from an unsorted basket, transfers them to an inspection zone, and classifies them using state of the art Visual Language Models (VLMs). We benchmark nine VLM s from five model families on a dataset of 223 inspection scenarios comprising shirts, socks, trousers, underwear, foreign objects (including garments outside of the aforementioned classes), and empty scenes. The evaluation assesses per class accuracy, hallucination behavior, and computational performance under practical hardware constraints. Results show that the Qwen model family achieves the highest overall accuracy (up to 87.9 %), with strong foreign object detection performance, while lighter models such as Gemma3 offer competitive speed accuracy trade offs for edge deployment. A digital twin combined with MoveIt enables collision aware path planning and integrates segmented 3D point clouds of inspected garments into the virtual environment for improved manipulation reliability. The presented system demonstrates the feasibility of combining semantic VLM reasoning with conventional grasp detection and digital twin technology for scalable, autonomous textile sorting in realistic industrial settings.
Md. Himel Mahmud, M. Repon, Md. Tanvir Raihan
et al.
Mosquito-borne diseases such as malaria, dengue, chikungunya, and yellow fever pose a significant global health threat, with malaria alone causing hundreds of thousands of deaths annually. Climate change has exacerbated mosquito proliferation, necessitating innovative solutions to combat these diseases. Textiles engineered with mosquito-repellent characteristics have become a practical alternative to fight against vector-borne diseases. Not only synthetic chemicals, i.e., DEET, permethrin, etc, but also natural agents like essential oils or plant extract have been successfully applied onto fabrics through dyeing, printing, coating, grafting, and encapsulation. These techniques not only introduce the insect repellency but also embed multifunctional activity, e.g., UV protection, antimicrobial activity, etc Although this domain of functional textiles has made notable progress, the research communities are still trying to find a more feasible and suitable approach, and at the same time, overcome the existing limitations in achieving long-term effectiveness, user comfort, and environmentally sustainable options. This review discusses the advancements mosquito repellent textiles by applying both natural and synthetic repellents, covering application methods, assessment criteria, and material selection. It offers insights for developing effective and diverse mosquito-repellent textiles. This study contributes a unique, in-depth analysis of this field, highlighting the opportunities and limitations of current strategies while enhancing understanding and guiding future research endeavours.
Ginan Al-Massri, Hassan Ghanem, Jamal Khatib
et al.
Paving blocks are prone to cracking during their service life. Therefore, the use of fibers such as banana fibers (BF) in paving blocks can improve their mechanical properties and long-term performance. Banana fibers can be considered as an environmentally friendly building material, thus contributing toward sustainability. The impact of BF incorporation on mortar’s mechanical properties and volume stability is examined in this research. To this end, five mixes were developed with various BF additions relative to the total volume of mortar: 0%, 0.5%, 1%, 1.5%, and 2%. Compressive strength, flexural strength, chemical shrinkage, autogenous shrinkage, drying shrinkage, and expansion experiments were conducted for up to 90 days. The incorporation of 0.5% BF resulted in an increase in compressive and flexural strength by 7% and 5% compared to the control mix. Regarding volume stability, the results show that 2% BF decreases chemical shrinkage by 15%, autogenous shrinkage by 59%, drying shrinkage by 48%, and expansion by 61% when compared to the control mix. A hyperbolic model was used to accurately predict the variation in length change as a function of the curing age, which served to further explain experimental data. A significant correlation is noted between chemical shrinkage and other length change parameters.
Science, Textile bleaching, dyeing, printing, etc.
K. Murugananthan, S. Senthil, P. Senthamaraikannan
et al.
The chemical, physical, thermal, and morphology analysis of Caesalpinia bonducella seed shell powder (CBSSP) has been conducted for behavior investigation. CBSSP has a high availability of cellulose (61.26 wt.%) from the chemical analysis and also contains minimum contents of hemi cellulose (13.74 wt.%), lignin (12.59 wt.%), wax (0.52 wt.%), ash (8.61 wt.%) and moisture (3.28 wt.%). The X-ray diffraction analysis calculated the crystallinity index as 23.04% and crystalline size as 4.745 nm of CBSSP. CBSSP was probative to surface morphology investigation by Scanning Electron Microscope (SEM) and Atomic Force Microscope (AFM). The thermogravimetric study (TGA) of the CBSSP shows a kinetic energy activation of 66.32 kJ/mol with temperature consistency as high as 225°C, implying the substance could be used as a material filler for thermoplastic resins that perform well at temperatures for processing. Mechanical testing results of CBSSP/Epoxy composite plates revealed that 9 wt.% CBSSP reinforced CBSSP/Epoxy composite plates have improved tensile strength (38.73 MPa), flexural strength (64.41 MPa), and impact strength (4.57 GPa). The results of the specified behavior features of filler could be employed in developing reinforced epoxy composites.
Science, Textile bleaching, dyeing, printing, etc.
Environmental concerns have increased with industrialization, and the growing demand for dyes has seen an exponential rise across industries like textile, leather, printing, etc. Most of the dyes are extremely toxic to the environment and thus affect both marine and terrestrial life. Sustainable dye removal technologies are, therefore, an urgent need. Most of the adsorbents selectively adsorb either cationic or anionic dyes, limiting their applicability. A simple yet effective approach is being reported to develop chemically cross-linked films from waste protein (human hair keratin) for both cationic and anionic dye adsorption. Keratin-based bioplastic films have been fabricated using waste human hair, and a comparative study with pristine keratin films was conducted. The cross-linked films exhibit improved surface morphology and mechanical properties compared to the pristine films by reducing the microcracks within the films. Secondary structural information using FT-IR and XRD suggests conformational changes in the protein from a predominant α-helix to β-sheet structure during film formation. The cross-linked films maintain thermal stability up to 200 °C and are biodegradable in the presence of soil bacteria. Batch adsorption studies of the films were performed to study the dye adsorption with three model dyes, i.e., methylene blue (MB), rhodamine 6G (R6G), and bromophenol blue (BB). Cross-linked films are able to adsorb both cationic and anionic dyes with higher efficiency and capacities compared with pristine films. The adsorption capacities increased upon cross-linking by ∼10% for methylene blue, ∼50% for rhodamine 6G, and ∼70% for bromophenol blue. Kinetic modeling and the modified Weber–Morris diffusion model demonstrate that intraparticle diffusion is the rate-limiting step of the dye adsorption process. While a full life cycle assessment would be required to precisely estimate the environmental impact, keratin-based films could be a promising pathway toward sustainability. This study demonstrates a strategy for developing an efficient and versatile dye-adsorbing material from waste-derived protein.
Maximilian P. Oppelt, Tobias S. Zech, Sarah H. Lorenz
et al.
We introduce a novel wearable textile-garment featuring an innovative electrode placement aimed at minimizing noise and motion artifacts, thereby enhancing signal fidelity in Electrocardiography (ECG) recordings. We present a comprehensive, sex-balanced evaluation involving 15 healthy males and 15 healthy female participants to ensure the device's suitability across anatomical and physiological variations. The assessment framework encompasses distinct evaluation approaches: quantitative signal quality indices to objectively benchmark device performance; rhythm-based analyzes of physiological parameters such as heart rate and heart rate variability; machine learning classification tasks to assess application-relevant predictive utility; morphological analysis of ECG features including amplitude and interval parameters; and investigations of the effects of electrode projection angle given by the textile / body shape, with all analyzes stratified by sex to elucidate sex-specific influences. Evaluations were conducted across various activity phases representing real-world conditions. The results demonstrate that the textile system achieves signal quality highly concordant with reference devices in both rhythm and morphological analyses, exhibits robust classification performance, and enables identification of key sex-specific determinants affecting signal acquisition. These findings underscore the practical viability of textile-based ECG garments for physiological monitoring as well as psychophysiological state detection. Moreover, we identify the importance of incorporating sex-specific design considerations to ensure equitable and reliable cardiac diagnostics in wearable health technologies.
Continuous, non-invasive pregnancy monitoring is crucial for minimising potential complications. The fetal electrocardiogram (fECG) represents a promising tool for assessing fetal health beyond clinical environments. Home-based monitoring necessitates the use of a minimal number of comfortable and durable electrodes, such as dry textile electrodes. However, this setup presents many challenges, including increased noise and motion artefacts, which complicate the accurate extraction of fECG signals. To overcome these challenges, we introduce a pioneering method for extracting fECG from single-channel recordings obtained using dry textile electrodes using AI techniques. We created a new dataset by simulating abdominal recordings, including noise closely resembling real-world characteristics of in-vivo recordings through dry textile electrodes, alongside mECG and fECG. To ensure the reliability of the extracted fECG, we propose an innovative pipeline based on a complex-valued denoising network, Complex UNet. Unlike previous approaches that focused solely on signal magnitude, our method processes both real and imaginary components of the spectrogram, addressing phase information and preventing incongruous predictions. We evaluated our novel pipeline against traditional, well-established approaches, on both simulated and real data in terms of fECG extraction and R-peak detection. The results showcase that our suggested method achieves new state-of-the-art results, enabling an accurate extraction of fECG morphology across all evaluated settings. This method is the first to effectively extract fECG signals from single-channel recordings using dry textile electrodes, making a significant advancement towards a fully non-invasive and self-administered fECG extraction solution.
Daiva Mikucioniene, Liudmyla Halavska, Ginta Laureckiene
et al.
Compression therapy can be successfully applied to the treatment of amputated limbs. Compression is known to speed healing and reduce the appearance of complex scars. This is particularly relevant as the number of amputations increases, especially during times of war, such as the current war in Ukraine. For the research presented in this article, compression knits of two pattern repeats and twelve structural variations each were created. We investigated how the compression generated by the knit is influenced by the main factors which theoretically could have an effect: knitting pattern, density of loops, speed of the wheel supplying elastomeric inlay-yarn into the knitting zone, and elongation resulting from the difference between the knitted limb cover and limb circumference. It was found that in the area of low elongations (up to 50%) of the investigated elastomeric knits, the speed of supply of the inlay-yarn does not have a significant influence on the compression. However, the effect of loop density and knitting elongation on the generated compression is significant and manifests linearly. In addition, the established equations can be used for compression prediction and knitting design according to the required compression class.
Chemicals: Manufacture, use, etc., Textile bleaching, dyeing, printing, etc.
Cedric W. Sanjon, Yuchen Leng, Marek Hauptmann
et al.
This study presents a novel transmission-based method for characterizing local structural features, including the grammage, thickness, and fiber orientation, of paper materials. Some non-destructive techniques, such as micro-computed tomography (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>μ</mi></semantics></math></inline-formula>-CT), microscopy, and radiation-based methods, are costly, time-consuming, and lack the ability to provide comprehensive local structural information within a single measurement. The proposed method utilizes a single light transmission measurement to assess local grammage and thickness through histogram matching with reference data obtained via <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>β</mi></semantics></math></inline-formula>-radiography and profilometry. The same light transmission images are also used to determine local fiber orientation, employing image analysis techniques. The structure tensor method, which analyzes gradients of light transmission images, provides detailed insight into the local fiber orientation. The results show that thickness and grammage measurements are independent of which side of the paper is evaluated, while the fiber orientation distribution varies between the front and back sides, reflecting differences in fiber arrangement due to manufacturing processes. Various distribution functions are compared, and the Pearson Type 3, log-normal, and gamma distributions are found to most accurately describe the grammage, thickness, and fiber orientation distributions. The study includes a variety of paper types, ensuring a robust and comprehensive analysis of material behavior, and confirms that the method can effectively infer the inhomogeneous features from a single light transmission measurement.
Chemicals: Manufacture, use, etc., Textile bleaching, dyeing, printing, etc.
To examine the impact of in situ water maceration in macerating ponds on the degumming process and fiber quality of freshly kenaf and jute whole plants. Different kenaf/jute fresh samples (whole plant, bast fresh hides) were subjected to distinct maceration treatments: padded film + cover film, cover film only, and no film. Water temperature, degumming bacterial colony counts, and fiber quality were assessed. Results revealed that composting pools with padded film + cover film maintained the highest water temperature. For colony count, padded film + cover film treatment displayed the highest colony count for kenaf, and no film treatment had the highest for jute. Kenaf whole fresh rods treated with padded film + cover film and cover film alone demonstrated the highest fiber strengths at 489.01 N and 494.85 N, respectively. Jute whole fresh rods macerated in padded film + cover film achieved the greatest strength at 392.32 N. Comparisons of fresh fiber strength between whole fresh rod and bastshowed a maximum difference of 150.69 N (kenaf) and 152.88 N (jute). Comprehensive analysis concluded, that the most effective degumming method involved using the whole fresh rods of red hemp/jute in maceration ponds equipped with padded film + cover film.
Science, Textile bleaching, dyeing, printing, etc.
This work presents a shear elastoplasticity model for textile fabrics within the theoretical framework of anisotropic Kirchhoff-Love shells with bending of embedded fibers proposed by Duong et al. (2023). The plasticity model aims at capturing the rotational inter-ply frictional sliding between fiber families in textile composites undergoing large deformation. Such effects are usually dominant in dry textile fabrics such as woven and non-crimp fabrics. The model explicitly uses relative angles between fiber families as strain measures for the kinematics. The plasticity model is formulated directly with surface invariants without resorting to thickness integration. Motivated by experimental observations from the picture frame test, a yield function is proposed with isotropic hardening and a simple evolution equation. A classical return mapping algorithm is employed to solve the elastoplastic problem within the isogeometric finite shell element formulation of Duong et al. (2022). The verification of the implementation is facilitated by the analytical solution for the picture frame test. The proposed plasticity model is calibrated from the picture frame test and is then validated by the bias extension test, considering available experimental data for different samples from the literature. Good agreement between model prediction and experimental data is obtained. Finally, the applicability of the elastoplasticity model to 3D shell problems is demonstrated.
Textile-reinforced concrete (TRC) is a reinforced concrete, where steel reinforcement is replaced with textiles or fibers. Textile reinforcement is a material consisting of natural or synthetic singular technical fibres processed into yarns or rovings which are woven into multi-axial textile fabrics having an open mesh or grid structure. In the paper an overview of tests results related to mechanical properties, deformation properties and durability characteristics of textile meshs are presented. Applications of different textiles as reinforcement in TRC is analyzed through some realized projects. TRC has been successfully employed for strengthening or repair of damaged structural elements and lightweight, thin structural elements (precast thin-walled elements, shells, tanks, pipes, pedestrian bridge, waterproofing structure, integrated cladding systems, external insulation system).
The elastic bands integrated using the ruffles technique proved to be effective in enhancing the performance of the soft robotic structures. In the actuator application, the elastic bands greatly increased the bending capability and force capability of the structure, while in the eversion robot cap application, the elastic bands improved the performance slightly by maintaining the sensory payload at the tip without restricting the eversion process. These findings demonstrate the potential of using elastic bands and textile techniques in soft robotics to create more efficient and adaptable structures.
The traditional pre-treatment of cotton fabric hardly meets the requirement of low carbon emissions due to its large energy consumption and wastewater discharge. In this study, a low-temperature and near-neutral strategy was designed by establishing a tetraacetylethylenediamine (TAED)-activated sodium percarbonate (SPC) system. First, the effects of SPC concentration, temperature and duration on the whiteness index (WI) and capillary effect of cotton fabrics were investigated. Particularly, excess SPC’s ability to create an additional bleaching effect was studied. The optimized activated pre-treatment was compared with the traditional pre-treatment in terms of the bleaching effect and energy consumption. Further, the degradation of morin, which is one of the natural pigments in cotton, was carried out in a homogeneous TAED/SPC system to reveal the bleaching mechanism. Lastly, the application performance of the treated cotton was evaluated by characterizing the dyeability, mechanical properties, morphology, etc. The research results showed that temperature had a significant influence on both the WI and capillary effect, followed by the SPC concentration and duration. The WI was positively correlated with the SPC concentration, but excess SPC could not produce an obvious additional effect. The WI of the fabric increased by 67.6% after the optimized activated bleaching using 10 mmol/L SPC and 15 mmol/L TAED at 70 °C for 30 min. Compared with the traditional process performed at 95 °C for 45 min, the activated process produced approximately 39.3% energy savings. Research on the bleaching mechanism indicated that the reactive species that participated in degrading the morin were the hydroxyl radical and superoxide radical, and the contribution degree of the former was larger than that of the latter. Two degradation components with molecular weights of 180 and 154 were detected using mass spectroscopy. Based on this, the bleaching mechanism of the TAED/SPC system was proposed. Moreover, the fabric after the activated pre-treatment had a suitable dyeability and strength, a lower wax residual and a smoother and cleaner fiber surface. The encouraging results showed that TAED/SPC is a promising bleaching system that is conducive to the sustainable advance of the textile industry.