The residual dyes from different sources (e.g., textile industries, paper and pulp industries, dye and dye intermediates industries, pharmaceutical industries, tannery, and Kraft bleaching industries, etc.) are considered a wide variety of organic pollutants introduced into the natural water resources or wastewater treatment systems. One of the main sources with severe pollution problems worldwide is the textile industry and its dye-containing wastewaters (i.e. 10,000 different textile dyes with an estimated annual production of 7.105 metric tonnes are commercially available worldwide; 30% of these dyes are used in excess of 1,000 tonnes per annum, and 90% of the textile products are used at the level of 100 tonnes per annum or less) (Baban et al., 2010; Robinson et al., 2001; Soloman et al., 2009). 10-25% of textile dyes are lost during the dyeing process, and 2-20% are directly discharged as aqueous effluents in different environmental components. In particular, the discharge of dye-containing effluents into the water environment is undesirable, not only because of their colour, but also because many of dyes released and their breakdown products are toxic, carcinogenic or mutagenic to life forms mainly because of carcinogens, such as benzidine, naphthalene and other aromatic compounds (Suteu et al., 2009; Zaharia et al., 2009). Without adequate treatment these dyes can remain in the environment for a long period of time. For instance, the half-life of hydrolysed Reactive Blue 19 is about 46 years at pH 7 and 25°C (Hao et al., 2000). In addition to the aforementioned problems, the textile industry consumes large amounts of potable and industrial water (Tables 1, 2 and Fig. 1) as processing water (90-94%) and a relatively low percentage as cooling water (6-10%) (in comparison with the chemical industry where only 20% is used as process water and the rest for cooling). The recycling of treated wastewater has been recommended due to the high levels of contamination in dyeing and finishing processes (i.e. dyes and their breakdown products, pigments, dye intermediates, auxiliary chemicals and heavy metals, etc.) (Tables 3, 4 and 5) (adapted from Bertea A. and Bertea A.P., 2008; Bisschops and Spanjers, 2003; Correia et al., 1994; Orhon et al., 2001).
Textile pattern generation (TPG) aims to synthesize fine-grained textile pattern images based on given clothing images. Although previous studies have not explicitly investigated TPG, existing image-to-image models appear to be natural candidates for this task. However, when applied directly, these methods often produce unfaithful results, failing to preserve fine-grained details due to feature confusion between complex textile patterns and the inherent non-rigid texture distortions in clothing images. In this paper, we propose a novel method, SLDDM-TPG, for faithful and high-fidelity TPG. Our method consists of two stages: (1) a latent disentangled network (LDN) that resolves feature confusion in clothing representations and constructs a multi-dimensional, independent clothing feature space; and (2) a semi-supervised latent diffusion model (S-LDM), which receives guidance signals from LDN and generates faithful results through semi-supervised diffusion training, combined with our designed fine-grained alignment strategy. Extensive evaluations show that SLDDM-TPG reduces FID by 4.1 and improves SSIM by up to 0.116 on our CTP-HD dataset, and also demonstrate good generalization on the VITON-HD dataset.
The potential application of non-thermal plasma in treating textile industrial wastewater motivates researchers to develop innovative techniques at a laboratory scale to achieve the goal of wastewater mineralization. In line with this objective, a dielectric barrier post-discharge plasma reactor with a liquid electrode has been built for the study of synthetic dye degradation. The plasma reactor was optimized by altering various operating conditions to achieve a higher degradation efficiency at given discharge conditions. The reaction kinetics of crystal violet degradation were studied, and the same plasma reactor was tested for other synthetic dyes (wastewater model samples). The results suggest that the proposed dielectric barrier post-discharge plasma reactor may offer a promising solution for treating dye effluents from the textile industry.
Textiles may be exposed to metal contamination during their production, functionalization and storage processes. While some of these metals and metallic compounds cause contamination in the final textile product through fiber production, pre-treatment processes such as boiling and bleaching, dyeing and some finishing processes, some of them which provide specific functional properties to the final textile product (anti-microbial property, self-cleaning property, UV protection feature, electromagnetic wave shielding feature, etc.) cause contamination in the final textile product during the functionalization process. Although a wide variety of antimicrobial substances are used in the production of antibacterial textiles, metal/metallic compounds and nano metal particles are also widely used as antibacterial substances. Studies on antibacterial textiles generally focus on the synthesis of antibacterial material, its application to fabric and its effectiveness against pathogenic microorganisms. However, more studies are needed on the effects of the metal content of antibacterial textile products on the user's skin and health throughout their lifetime. Because textile products are in direct and long-term contact with human skin. In this study, ICP-MS metal content analysis, time-dependent metal release amount analysis, antibacterial activity analysis and cytotoxicity test with cell culture were performed on antibacterial socks and the results were evaluated.
Background: Industrialization consumes a significant amount of water, and the textile sector rapidly expands globally using vast quantities of water. Textile products undergo various procedures such as bleaching, dyeing, printing, and stiffening. Dyeing factories are the major polluters in this industry, generating waste that contains unused organic compounds and colours. Dyes can pose a risk to environmental components and public health, potentially causing harm to vital human organs. Even in small amounts, reactive black 5 dye (RB5) can block light in water, reducing photosynthesis and affecting aquatic plant growth, possibly leading to eutrophication. Prolonged exposure to RB5 has been linked to serious health issues, including skin rashes, cancer, kidney and respiratory failures, and other severe conditions. Objectives: The current study aims to establish the effectiveness of using a new, affordable, and environmentally friendly adsorbent, namely kaolin filter cake (KFC), for the removal of reactive black 5 dye from textile wastewater. Methods: The prepared kaolin filter cake (KFC) activated carbon was characterized using Fourier Transform Infrared (FTIR), Scanning Electron Microscopy (SEM), X-ray diffraction (XRD), point of zero charge (pHpzc), and Brunauer–Emmett–Teller (BET) surface area. The effectiveness of KFC's decolorization was assessed by adsorption tests that looked at batch process variables, such as pH, adsorbent dosage, contact time, and beginning dye concentration. Response Surface Methodology (RSM) was employed to optimize the RB5 removal. Results: The adsorption data closely fit the Langmuir isotherm model, indicating a maximum adsorption capacity of 60.24 mg·g-1. Kinetic studies revealed that the adsorption process followed a pseudo-second-order model. Remarkably, KFC demonstrated excellent regeneration potential, retaining 60.52% of its adsorption capacity after five cycles. Conclusion: KFC is a highly promising adsorbent with significant potential for sustainable, cost-effective, environmentally friendly, and efficient applications in textile wastewater treatment.
Seoyoung Choi, Rashmi Balegar Mohan, Heather Jin Hee Kim
et al.
We present PileUp, a tufted pile e-textile sensing approach that offers unique affordances through the tactile expressiveness and richness of its continuous, threaded-volume construction. By integrating conductive yarns in looped or cut pile forms, PileUp transforms soft 3-dimensional textiles into multimodal sensors capable of detecting mechanical deformations such as pressure, bending, and strain, as well as environmental conditions like moisture. We propose a design space that outlines the relationships between texture, form factor, and sensing affordances of tufted textiles. We characterize electrical responses under compression, bending, and strain, reporting sensor behaviors. To demonstrate versatility, we present three application scenarios in which PileUp sensors are seamlessly integrated into soft fabrics: a meditation rug with multi-zone sensing, a fleece sleeve that detects arm motion, and a moisture-sensing wall art. Our results establish tufting as an accessible yet expressive fabrication method for creating integrated sensing textiles, distinguishing our work from traditional flat textile sensors.
Coral reefs support numerous marine organisms and are an important source of coastal protection from storms and floods, representing a major part of marine ecosystems. However coral reefs face increasing threats from pollution, ocean acidification, and sea temperature anomalies, making efficient protection and monitoring heavily urgent. Therefore, this study presents a novel machine-learning-based coral bleaching classification system based on a diverse global dataset with samples of healthy and bleached corals under varying environmental conditions, including deep seas, marshes, and coastal zones. We benchmarked and compared three state-of-the-art models: Residual Neural Network (ResNet), Vision Transformer (ViT), and Convolutional Neural Network (CNN). After comprehensive hyperparameter tuning, the CNN model achieved the highest accuracy of 88%, outperforming existing benchmarks. Our findings offer important insights into autonomous coral monitoring and present a comprehensive analysis of the most widely used computer vision models.
Gabriel Aeppli, Alexander V. Balatsky, Stefano Bonetti
et al.
We introduce the concept of quantum printing -- the imprinting of quantum states from photons and phonons onto quantum matter. The discussion is focusing on charged fluids (metals, superconductors, Hall fluids) and neutral systems (magnets, excitons). We demonstrate how structured light can generate topological excitations, including vortices in superconductors and skyrmions in magnets. We also discuss how quantum printing induces magnetization in quantum paraelectrics and strain-mediated magnetization in Dirac materials. Finally, we propose future applications, such as printing entangled photon states, creating entangled topological excitations, and discuss applications of quantum printing to light induced quantum turbulence in a charged fluid. This review represents the expanded version of the shorter review submitted to Nature Physics.
M. B. Üzümcü, E. Sarıoğlu, Tülin Nacarkahya
et al.
In the context of sustainable development goals, a diverse array of contributing studies has emerged within the textile sector. It is evident that the majority of these studies encompass both legal and customer obligations. The objective of contemporary businesses is to manufacture products that demonstrate a high level of environmental sensitivity. For instance, the objective is to reduce the quantity of waste products, to achieve energy-efficient production, to minimize the amount of chemicals employed, to reduce water consumption, to utilize energy derived from renewable sources, and thus to diminish the carbon footprint. From an environmental standpoint, the chemicals utilized in textile product manufacturing have emerged as a significant consideration. It is preferable that the chemicals employed in the dyeing process (dyestuffs, bleaching agents, softeners, etc.) are environmentally sensitive. Furthermore, the use of organic dyes in the dyeing process is also employed as a means of obtaining a more sustainable product. In the context of this study, the production of bamboo/cotton yarn was conducted at varying blend ratios (67/33%, 50/50%, and 33/67%) through the use of three distinct production methods (open end, vortex, and ring systems). Single jersey knitted fabrics were produced using these yarns with the same production parameters. Subsequently, the fabrics were dyed using acorn natural dyestuff. Pilling, fastness and CIELab analyses were performed on the fabric samples, and the results were subjected to statistical analysis.
This review focuses on the transformative applications of deep learning and artificial intelligence in textile dyeing, printing, and finishing. In textile dyeing, the topics span color prediction, color-based classification, dyeing recipe prediction, dyeing pattern recognition, and the nuanced domain of color fabric defect detection. In textile printing, applications of artificial intelligence and machine learning center around pattern detection in printed fabrics, the generation of novel patterns, and the critical task of detecting defects in printed textiles. In textile finishing the prediction of fabric thermosetting parameters is discussed. Artificial neural networks, diverse convolutional neural network variations like AlexNet, traditional machine learning approaches including support vector regression, principal component analysis, XGBoost, and generative artificial intelligence such as generative adversarial networks, as well as genetic algorithms all find application in this multifaceted exploration. At its core, the interest to use these methodologies is because of the need to minimize repetitive and time-consuming manual tasks, curtail prototyping costs, and promote process automation. The review unravels a plethora of innovative architectures and frameworks, each tailored to address specific challenges. However, a persistent hurdle looms – the scarcity of data, which remains a significant impediment. While unveiling a collection of research findings, the review also spotlights the inherent challenges in implementing artificial intelligence solutions in the textile dyeing and printing domain.
With the strengthening of the public awareness of food safety and environmental protection, functional food packaging materials have received widespread attention. Nanofibers are considered as promising packaging materials due to their unique one-dimensional structure (high aspect ratio, large specific surface area) and functional advantages. Electrospinning, as a commonly used simple and efficient method for preparing nanofibers, can obtain nanofibers with different structures such as aligned, core-shell, and porous structures by modifying the devices and adjusting the process parameters. The selection of raw materials and structural design of nanofibers can endow food packaging with different functions, including antimicrobial activity, antioxidation, ultraviolet protection, and response to pH. This paper aims to provide a comprehensive review of the application of electrospun nanofibers in functional food packaging. Advances in electrospinning technology and electrospun materials used for food packaging are introduced. Moreover, the progress and development prospects of electrospun nanofibers in functional food packaging are highlighted. Meanwhile, the application of functional packaging based on nanofibers in different foods is discussed in detail.
The modification method of grafting multi-walled carbon nanotubes (MWCNT, abbreviated as CNT in this paper) on the surface of flax fibers was investigated, i.e. CNT were grafted onto the surface of flax fibers by silane coupling agent under the action of ultrasonic waves to form covalent bonding. The tensile strength of CNT grafted flax fiber is 22% higher than that of untreated flax fiber monofilament. The tensile strength of FFRP composites after CNT grafting treatment increased by 14.2%; however, the tensile modulus of single fiber and composites did not show a significant increase, the interfacial shear strength of the fiber-resin is 38.3% higher than that of untreated filament. The improvement of the contact angle after grafting was investigated by observing the surface morphology, and the surface of flax filament was characterized by scanning electron microscopy and atomic force microscopy. Also the elemental changes of the flax single fiber surface before and after the treatment were analyzed using X-ray photoelectron spectroscopy. The results showed that the tensile strength of flax single fibers, its composites, and interfacial shear strength of fiber-matrix was improved after CNT grafting treatment but the increase of modulus was not obvious.
Science, Textile bleaching, dyeing, printing, etc.
The recycling of materials is in line with the policy of a closed-loop economy and is currently an option for managing waste in order to reuse it to create new products. To this end, 3D printing is being used to produce materials not only from pure polymers but also from their composites. Further development in this field seems interesting and necessary, and the use of recycled materials will help to reduce waste and energy consumption. This article deals with the use of degradable waste materials for the production of insulating materials by 3D printing. For the study, samples with different numbers of layers (one and five), composite thickness (20, 40, 60, 80, and 100 mm) and composition (including colored resins that were transparent, black, gray, and metallized, as well as resins that were colored gray using soybean oil and gray using natural fibers) were made. The role of natural fillers was played by glycerin and biomass ash with a weight ratio of 5%. The finished materials were tested, and the values of the coefficient of thermal resistance and heat transfer were determined. The best thermal properties among the tested materials were distinguished by a five-layer sample made of soybean-oil-based resin with a thickness of 100 mm. This sample’s heat transfer coefficient was: 0.16 W/m<sup>2</sup>K. As a material for thermal insulation in 3D printing technology, biodegradable components have great potential.
Chemicals: Manufacture, use, etc., Textile bleaching, dyeing, printing, etc.
Sisal fibers were extracted and treated in alkali solutions of varying pH concentrations to alter their physical properties for the study. The study explores the effect of the pH concentrations on the internal microstructure using computed tomography, the changes in fibers surface topography using laser confocal microscopy, and how the mechanical properties are affected regarding their surface topography and internal microstructure. The X-ray microscopy scans showed that the untreated fibers are hollow throughout their length, and when treated, these voids collapse and reduce the fibers’ diameter. Moreover, this also showed that treatment affects the complete structure of the fiber. Where a pronounced degradation was observed at 25%. This also affects the overall fibers’ surface topography and mechanical properties. Where optimal mechanical properties were reported at 1% alkali treatment, this is evidently supported by the change in surface topology at this concentration. This means optimal properties may be achieved at the alkali concentration range below 1% and not necessarily at higher concentrations.
Science, Textile bleaching, dyeing, printing, etc.
Ariharasudhan Subramanian, Senthil Kumar Selvaraj, Rajaram Mani
et al.
This study investigates the synthesis and characterization of composite materials, pigeon pea stem, and cotton fibers blended in different ratios such as 100/0, 70/30, 60/40, 50/50, 30/70, and 0/100. These composite materials were produced using a compression molding technique. According to ASTM standards, the acoustics, thermal conductivity, and physical characteristics of the composite samples were tested to assess their qualities. The impedance tube method detailed in ASTM E1050 was used to determine the sound absorption coefficients (SAC) for acoustics. The SAC values were measured at six frequencies such as 125, 250, 500, 1000, 2000, and 4000 Hz. The results showed that composite samples made from waste cotton and pigeon pea demonstrated sound absorption values of greater than 80%. Superior sound insulation and absorption, moisture absorption, fiber properties have also been demonstrated by waste composites. Especially, the waste cotton/pea stalk waste fiber composites achieved over 75% sound absorption, while the waste 28% composites performed well in terms of sound absorption, moisture absorption, and fiber properties. Even in humid conditions, the composite samples constructed from used cotton and pigeon pea stalks demonstrated good moisture resistance without reducing their insulating qualities. Soundproofing barriers are composite layers of foam or pigeon pea/cotton.
Science, Textile bleaching, dyeing, printing, etc.
Katarzyna Ewa Buczkowska, Petr Louda, Artem Sharko
et al.
This study focuses on the optimization of geopolymer composites, considering the parameters of composition and performance. The research explores the integration of algorithm-built hybrid implementations and a hybrid intelligent system to solve complex optimization problems in geopolymer composite materials. Firstly, an algorithm-built hybrid implementation is proposed, combining experimental results with various data processing methods. This approach enables the utilization of composite algorithms, offering several advantages, such as scalability and adaptability to different loads. The models developed in this study provide a flexible and extensible architecture, allowing for efficient problem-solving in optimization tasks. Secondly, a hybrid intelligent system is introduced, comprising statistical simulation models that combine different control and design problem-solving approaches. Markov chains are employed to address the quantitative aspects of loosely structured tasks and process performance evaluation. Criterion methods are utilized for quantitative conclusions, ensuring the optimal adaptation of the results from both applications. The research culminates in the identification of the optimal composition, denoted as G + FC + CFI, with specific weight content. This composition consists of cement, activator, fireclay, and carbon fiber I, with 100 g, 90 g, 100 g, and 2.5 g, respectively. The findings from this study provide valuable insights into the optimization of geopolymer composites, employing algorithm-built hybrid implementations and a hybrid intelligent system. The proposed approaches offer enhanced efficiency and accuracy in solving complex optimization problems in the field of geopolymer composite materials. The identified optimal composition demonstrates the potential for improving performance in composition and weight content.
Science, Textile bleaching, dyeing, printing, etc.
Cutler Phillippe, Francesco Panerai, Laura Villafane
Micro-mechanics of parachute fabrics under tensile loads is studied using in situ X-ray micro-tomography. Results are presented for two nylon textiles commonly used in parachute systems, MIL-C-7020H Type III and MIL-C-44378(GL) Type II. Textiles are subjected to incremental tension using a custom apparatus that loads the fabric radially, and the microstructure is imaged sequentially at steady load conditions. Micro-tomography images are processed using learning-aided segmentation and a custom processing pipeline that tracks the locations and morphological properties of individual tows on 3-D datasets. Results are used to reconstruct tow micro-scale properties and meso-scale strains. Our findings reveal a direct relation between the fabric architecture and the meso-scale mechanics. Warp tow pretensioning during manufacturing is found to affect decrimping and the anisotropy of the textile strains. Areal porosity increase with tension is quantified and a geometric model for pore opening under incremental load is validated.
Unsupervised texture anomaly detection has been a concerning topic in a vast amount of industrial processes. Patterned textures inspection, particularly in the context of fabric defect detection, is indeed a widely encountered use case. This task involves handling a diverse spectrum of colors and textile types, encompassing a wide range of fabrics. Given the extensive variability in colors, textures, and defect types, fabric defect detection poses a complex and challenging problem in the field of patterned textures inspection. In this article, we propose a knowledge distillation-based approach tailored specifically for addressing the challenge of unsupervised anomaly detection in textures resembling fabrics. Our method aims to redefine the recently introduced reverse distillation approach, which advocates for an encoder-decoder design to mitigate classifier bias and to prevent the student from reconstructing anomalies. In this study, we present a new reverse distillation technique for the specific task of fabric defect detection. Our approach involves a meticulous design selection that strategically highlights high-level features. To demonstrate the capabilities of our approach both in terms of performance and inference speed, we conducted a series of experiments on multiple texture datasets, including MVTEC AD, AITEX, and TILDA, alongside conducting experiments on a dataset acquired from a textile manufacturing facility. The main contributions of this paper are the following: a robust texture anomaly detector utilizing a reverse knowledge-distillation technique suitable for both anomaly detection and domain generalization and a novel dataset encompassing a diverse range of fabrics and defects.
Callum Vidler, Michael Halwes, Kirill Kolesnik
et al.
Additive manufacturing is an expanding multidisciplinary field encompassing applications including medical devices, aerospace components, microfabrication strategies, and artificial organs. Among additive manufacturing approaches, light-based printing technologies, including two-photon polymerization, projection micro stereolithography, and volumetric printing, have garnered significant attention due to their speed, resolution and/or potential applications for biofabrication. In this study, we introduce dynamic interface printing (DIP), a new 3D printing approach that leverages an acoustically modulated, constrained air-liquid boundary to rapidly generate cm-scale three-dimensional structures within tens of seconds. Distinct from volumetric approaches, this process eliminates the need for intricate feedback systems, specialized chemistry, or complex optics while maintaining rapid printing speeds. We demonstrate the versatility of this technique across a broad array of materials and intricate geometries, including those that would be impossible to print via conventional layer-by-layer methods. In doing so, we demonstrate the rapid fabrication of complex structures in-situ, overprinting, structural parallelisation, and biofabrication utility. Moreover, we showcase that the formation of surface waves at this boundary enables enhanced mass transport, material flexibility, and permits three-dimensional particle patterning. We therefore anticipate that this approach will be invaluable for applications where high resolution, scalable throughput, and biocompatible printing is required.
In this work heat transfer papers were loaded with a new core–shell pigment based on precipitating thin shell of titanium dioxide on a core of rice husk silica ash TiO_2/RHSA to be applied in dye sublimation printing of textile fabrics. Besides, 0.1% (w/w) cationic polyacrylamide (CPAM) and 1% (w/w) bentonite (Bt) were also added sequentially to improve drainage and filler retention of the paper hand-sheets made from bleached kraft bagasse pulps. The effect of the new core–shell pigment on the mechanical and barrier properties, thermal stability and surface morphology of modified paper sheets were investigated. In addition, the study of transfer printability and ease of dye release from paper to fabric in this heat transfer printing of polyester fabrics using silk-screen printing under different transfer parameters were studied. Also, fastness measurements including washing, light and perspiration of printing polyester fabric were also estimated.