Hasil untuk "Textile bleaching, dyeing, printing, etc."

Ana Vukoičić, Aleksandra Ivanovska, Marija Ćorović et al.

This study explored, for the first time, the simultaneous dyeing and functionalization of textiles using enzymatically synthesized mixtures of phloridzin and esculin oligomers. Initial screening using multifiber fabric containing diacetate, cotton, polyamide, polyester, polyacrylonitrile, silk, viscose, and wool revealed that the oligomers successfully imparted color and high antioxidant activity to cotton, polyamide, and viscose. These three materials were therefore selected for determination of key process parameters’ influence, including temperature (35 °C and 75 °C), reaction time (6 h and 19 h), and oligomers’ concentration (1.5 and 3.0 mg/mL). Treated fabrics were evaluated for color strength (K/S), antioxidant activity, and prebiotic capacity (in vitro <i>stratum corneum</i> model), with all properties assessed before and after washing. The results showed that several functionalized fabrics retained coloration and functionality after washing, while fabrics functionalized with esculin oligomers’ mixture showed strong prebiotic capacity. Overall, the polyamide that functionalized with 3.0 mg/mL esculin oligomers for 19 h at 35 °C was identified as a promising candidate for reusable colored textiles, including dermatology-oriented garments for sensitive or atopic skin, sportswear, protective workwear, and daily use functional items such as hygienic pads or cloth liners. These findings demonstrate the feasibility of developing textiles with targeted prebiotic functionality.

Jack Andrew Cottrell, Muhammad Ali, D. Brett Martinson et al.

This study investigates the behaviour of Compressed Earth Cylinders (CECs) and Compressed Earth Blocks (CEBs) during direct compression tests and examines the influence of aspect ratio and the effects of platen restraint. The experimental investigation utilises two soil types and examines the impact of jute fibre reinforcement on the failure mechanism of CECs with aspect ratios ranging from 0.50 to 2.00. Through experimental analysis and numerical modelling, the effects of platen restraint are examined, and a novel hypothesis of intersecting cones is presented. The results show that specimens with a lower aspect ratio exhibited higher compressive strength due to confinement caused by platen restraint. Moreover, this research has derived new aspect ratio correction factors that enable conversion from Apparent Compressive Strength (ACS) to Unconfined Compressive Strength (UCS) of unstabilised and fibre-reinforced CECs. The experimental results indicate that the derived conversion factor of 0.861 allows for the prediction of CEB strength from CEC specimens with an accuracy of 2.7%. Furthermore, the addition of jute fibres at a 0.25% dosage increased the Apparent Compressive Strength across all aspect ratios. The outcome of this research recommends a standard approach to the application of aspect ratio correction factors when interpreting and reporting the compressive strength of CECs and CEBs.

Seunghwan Lee, Gisoo Lee, Seounghee Yun et al.

3D-printed digital materials whose mechanical behavior travels between those from thermoplastic to rubbery polymers have become increasingly important. However, their mechanical functionalities have not been fully exploited due to intrinsic mechanical anisotropy resulting from microstructural heterogeneity. Here, we combine mechanical testing, microscopy analysis and micromechanical modeling for a comprehensive understanding of complex deformation mechanisms responsible for the printing-orientation-dependent nonlinear mechanical behavior of digital materials at small to large strains. Towards this end, we construct representative volume elements that account for highly anisotropic microstructural features resulting from the printing-orientation-dependent diffusion and mixing between photocurable base resins. We then demonstrate, through micromechanical analysis, that stable compressive deformation of well-aligned elliptical hard thermoplastic inclusions embedded within the surrounding soft rubbery matrix gives rise to initial elastic anisotropy. Our experimental and micromechanical modeling results also show that the interplay between buckling instability and plastic deformation of the high-aspect-ratio hard domains governs mechanical anisotropy at large strains as well as the printing-orientation-dependent resilience and energy dissipation capabilities in these digital materials.

Basavaraju Bennehalli, Santhosh Nagaraja, Suresh Subramanyam Poyil et al.

The present study investigates the effect of chemical surface modification on the mechanical and thermal properties of bio-derived areca sheath fiber-reinforced epoxy biocomposites. The primary objective was to enhance fiber-matrix interactions and improve biocomposite performance through alkaline, permanganate, acrylation, acetylation, and benzene diazonium chloride treatments. The chemical treatments were validated using FTIR, TGA, and XRD analyses, which confirmed structural modifications and improved thermal stability. The results showed significant enhancement in tensile, flexural, and impact strength, with peak performance observed at an optimized fiber loading of 36%. The treated fibers exhibited better interfacial bonding, leading to improved stress transfer mechanisms. These sustainable biocomposites demonstrate potential for applications in lightweight structural components, such as partition panels, roofing materials, and prefabricated structures, offering a promising solution for eco-friendly and high-performance materials in various applications.

Jacob Shauri Tlatlaa, George Muhamba Tryphone, Eliakira Kisetu Nassary

This study was conducted in Msilale Village, Chato District in Tanzania, to evaluate the influence of sowing dates and phosphorus levels on cotton fiber quality. The study was established according to a factorial trial, with varying sowing dates (25th November 2022, 15th December 2022 and 4th January 2023) and phosphorus levels (control, 20 kg P ha−1, 40 kg P ha−1, 60 kg P ha−1). Results revealed that early planting had a statistically significant (p < .001) effect on fiber cotton quality, including spinning coefficient index, fiber length, fiber strength, uniformity index, short fiber content, and grade/color. Early sowing dates (25th November 2022 and 15th December 2022) consistently produced superior fiber quality, including spinning coefficient index (156.5 and 148.4), moisture content of the fiber (7.8% and 7.7%), micronaire (3.5 μg/inch), upper half mean length (1.2 cm), uniformity index (84.6% and 84.2%) and shorter fiber (6.8% and 7.0%) relative to late sowing (4th January 2023). Conversely, phosphorus levels did not significantly (p > .05) impact these parameters within the tested range. This research underscores the critical role of selecting appropriate sowing dates for cotton cultivation to achieve better fiber quality.

Buradagunta Suvarna, Sivadi Balakrishna

Abstract With the rise of online shopping due to the COVID-19 pandemic, Recommender Systems have become increasingly important in providing personalized product recommendations. Recommender Systems face the challenge of efficiently extracting relevant items from vast data. Numerous methods using deep learning approaches have been developed to classify fashion images. However, those models are based on a single model that may or may not be reliable. We proposed a deep ensemble classifier that takes the probabilities obtained from five pre-trained models such as MobileNet, DenseNet, Xception, and the two varieties of VGG. The probabilities obtained from the five pre-trained models are then passed as inputs to a deep ensemble classifier for the prediction of the given item. Several similarity measures have been studied in this work and the cosine similarity metric is used to recommend the products for a classified product given by a deep ensemble classifier. The proposed method is trained and validated using benchmark datasets such as Fashion product images dataset and Shoe dataset, demonstrating superior accuracy compared to existing models. The results highlight the potential of leveraging transfer learning and deep ensemble techniques to enhance fashion recommendation systems. The proposed model achieves 96% accuracy compared to the existing models.

اخترالسادات موسوی, ایمان زکریایی کرمانی, علی حاجی غلام سریزدی

رنگرزی طبیعی جز جدایی‌‌ناپذیر فرش دستباف ایرانی از گذشته دور تا به امروز بوده است. اخیرا علاقمندی مجدد به استفاده از رنگزاهای طبیعی در رنگرزی منسوجات گسترش یافته است. در این راستا هدف از این پژوهش ارائه یک مدل پویا جهت توسعه فناوری استفاده از رنگزاهای طبیعی در صنعت فرش دستباف است. لذا در تحقیق حاضر با استفاده از رویکرد پویایی‌‌‌‌شناسی کیفی ‌‌سیستم و ترسیم نمودارهای علی حلقوی، متغیرهای تأثیرگذار بر توسعه فناوری استفاده از رنگزاهای طبیعی در صنعت فرش دستباف شناسایی شده و در نهایت با ایجاد یک مدل مفهومی عوامل و روابط بین متغیرهای تحقیق نشان داده شده است. نتایج نشان می‌دهد ارتباط پژوهشگاه‌ها و صنعت فرش دستباف در نهایت باعث بهره‌وری و سودآوری بازار فرش دستباف خواهد شد که همین امر تمایل بازار را جهت توسعه فناوری استفاده از رنگزاهای طبیعی در صنعت فرش دستباف افزایش خواهد داد.

Richard E. Neddo, Zander W. Blasingame, Chen Liu

Face morphing attacks pose an increasing threat to face recognition (FR) systems. A morphed photo contains biometric information from two different subjects to take advantage of vulnerabilities in FRs. These systems are particularly susceptible to attacks when the morphs are subjected to print-scanning to mask the artifacts generated during the morphing process. We investigate the impact of print-scanning on morphing attack detection through a series of evaluations on heterogeneous morphing attack scenarios. Our experiments show that we can increase the Mated Morph Presentation Match Rate (MMPMR) by up to 8.48%. Furthermore, when a Single-image Morphing Attack Detection (S-MAD) algorithm is not trained to detect print-scanned morphs the Morphing Attack Classification Error Rate (MACER) can increase by up to 96.12%, indicating significant vulnerability.

Marcelino Ferri, José M. Bravo, Javier Redondo et al.

The correction of transcranial focused ultrasound aberrations is a relevant topic for enhancing various non-invasive medical treatments. Nowadays, the most widely accepted method to improve focusing is the emission through multi-element phased arrays; however, a new disruptive technology, based on 3D printed holographic acoustic lenses, has recently been proposed overcoming the spatial limitations of phased arrays due to the submillimetric precision of the latest generation of 3D printers. This works aims to optimize this recent solution; particularly, the preferred acoustic properties of the polymers used for printing the lens are systematically analyzed, paying special attention to the effect of p-wave speed and its relationship to the achievable voxel size of 3D printers. Results from simulations and experiments clearly show that there are optimal ranges for lens thickness and p-wave speed, fairly independent of the emitted frequency, the transducer aperture, or the transducer-target distance, given a particular voxel size

Sayan Kumar Chaki, Zeynep Sonat Baltaci, Elliot Vincent et al.

This paper aims to develop the study of historical printed ornaments with modern unsupervised computer vision. We highlight three complex tasks that are of critical interest to book historians: clustering, element discovery, and unsupervised change localization. For each of these tasks, we introduce an evaluation benchmark, and we adapt and evaluate state-of-the-art models. Our Rey's Ornaments dataset is designed to be a representative example of a set of ornaments historians would be interested in. It focuses on an XVIIIth century bookseller, Marc-Michel Rey, providing a consistent set of ornaments with a wide diversity and representative challenges. Our results highlight the limitations of state-of-the-art models when faced with real data and show simple baselines such as k-means or congealing can outperform more sophisticated approaches on such data. Our dataset and code can be found at https://printed-ornaments.github.io/.

Moni Sankar Mondal, Syed Zubair Hussain

The objective of the current study is to develop a model employing a fuzzy logic expert system (FLES) for predicting the noise reduction coefficient (NRC) of a banana-glass fiber composite. Banana fiber has a strong ability to muffle sounds while having low tensile strength. Glass fiber, on the other hand, has a limited capacity for sound absorption despite having considerable tensile strength. A composite consisting of banana and glass fiber has been developed in order to increase noise reduction capability while keeping appropriate tensile strength. The sound adsorption test was done by passing sound through composites via an impedance tube. It was found that 25% banana and 75% glass hybrid composite having 5 mm thickness shows 375.96% more NRC than 100% glass fiber composite. Only a 25% increase of banana fiber content increased NRC incredibly. Different compositions of glass fiber, banana fiber, and thicknesses of the composites were taken as the input variables and the output, noise reduction coefficient. To better comprehend the relationship between these variables, a fuzzy logic-based model was created and the model’s coefficient of determination (R2) was found to be 0.9884. The model accurately anticipated the noise reduction coefficient of the composites with varying constituent percentages and thicknesses.

Ying-Jun Gao, Wen-Jie Jin, Bi-Qing Hu et al.

This study focuses on the synthesis of a reactive phosphorus-/nitrogen-based intumescent flame retardant (IFR) agent using diethyl phosphite, urea, and glutaraldehyde through Kabachnik-Fields reaction. We further studied the potential applications in IFR modification of cotton fabrics through surface coating approach. The chemical structure of IFR agent and its potential grafting action with cotton fibers were characterized. The thermal stability, smoke and heat release performance, flame retardancy, and durability of the IFR-coated cotton fabrics were explored. Char residue analyses were also performed to confirm the FR mechanism of IFR coating. The results revealed that IFR coating significantly inhibited the heat and smoke generation of cotton. The IFR coating showed high functional efficiency due to phosphorus/nitrogen synergism. The IFR-coated fabrics passed vertical burning B1 level and obtained an limiting oxygen index (LOI) value of higher than 32.0%. The introduction of IFR coating to cotton by covalent bonds imparted excellent washing resistance to cotton as indicated by the self-extinguishing action of the IFR-coated cotton fabrics after 10 launderings. In general, the present study offers a novel strategy to prepare reactive and efficient IFR coating for cellulose-based textiles.

Qianqian Liu, Yu Zhang, Zixing Ma et al.

Using chitosan as pretreatment agent, the dyeing properties of peanut skin extracts (PSE) to flax fabrics were improved. Flax fabrics have excellent comfort property and are loved by many people. However, flax is different to dye, especially with natural dye. In this research, chitosan was used to pretreat flax fabrics and PSE was used to dye the pretreated flax fabric. The optimal conditions of the chitosan pretreatment and dyeing conditions of PSE were investigated according to the K/S value of the dyed flax fabrics. Comparing the original flax fabric, the chitosan pretreated flax fabric significantly improved the absorption to PSE, and the dyed fabrics had an increased K/S value from 0.9 to 3.9, and had good color fastnesses. The main chemical constitution in PSE such as catechin, chitosan, and cellulose of flax fabrics may form hydrogen bond and ionic bond. Chitosan pretreated and dyed flax fabrics had a stronger ability to UV resistance and scavenging free radicals. The fluorescence intensity of the dyed flax fabrics was improved while it was decreased after chitosan pretreatment. Chitosan pretreatment combined PSE dyeing can be used to develop functional flax textiles without using metallic mordants.

Yu Zhao, Dahui Zhu, Feng Zhou et al.

An apparel product has a unique feature other than other products in that apparel product design must consider three categories of design requirements, namely function (governed by natural sciences), comfort (governed by ergonomics), and pleasure (governed by aesthetics and psychology). This paper proposes a general design theory for apparel products. The theory is based on Axiomatic Design Theory (ADT), which is for the functional aspect of products, particularly by adapting ADT to apparel product design, to which all the aspects (function, comfort, pleasure) need to be considered. The proposed theory is thus called the Axiomatic Design Theory For Apparel (ADT-FA). The ADT-FA has two axioms. Axiom 1 (apparel) concerns coupling in the design requirement, and Axiom 2 (apparel) concerns redundancy in the design parameter. The proposed theory is preliminarily validated with the Zoot suit, which is well known in the community of apparel design. The work opens an avenue for more validations in future.

Ahmmad A. Abbass, Sallal R. Abid, Ali I. Abed et al.

The ACI 544-2R repeated impact test is known as a low-cost and simple qualitative test to evaluate the impact strength of concrete. However, the test’s main deficiency is the high variability in its results. The effect of steel fibers and the compressive strength of concrete on the variability in repeated impact test results was investigated experimentally and statically in this study. Two batches from four mixtures were prepared and tested for this purpose. Hooked-end steel fibers were utilized in the fibrous mixtures. The mixtures NC, NC-SF0.5 and NC-SF1.0 were normal strength mixtures with 0, 0.5 and 1.0% of steel fibers, respectively, while HC was a plain high-strength mixture. The impact tests were conducted using an automatic testing machine following the setup of the ACI 544-2R repeated impact test. The impact numbers at cracking (N1) and at failure (N2) were recorded for both batches of the four mixtures. The results were also analyzed using the normal probability and Weibull distribution tests. The test results showed that the fibers increased the impact results at the cracking stage and significantly increased the failure impact resistance. Adding 0.5 and 1.0% of steel fibers increased the N1 by up to 66 and 111%, respectively, and increased the N2 by 114 and 374%, respectively. The test results also showed that duplicating the design compressive strength from 40 to 80 MPa increased the impact resistance by up to approximately 190%. The test results revealed no clear trend of an effect of steel fibers and compressive strength on the variability in the test results.

H C Meena, D B Shakyawar, R K Varshney et al.

Khadi is a handspun and handloom woven textile fabric made up of natural textile fibers, predominantly cotton and wool. Khadi mainly intended for apparel purposes. Hence, the thermo-physiological properties of wool-cotton blended khadi fabric are crucial in studying fabric comfort. In this study, the 18 types of wool-cotton blended khadi fabrics are produced on a handloom by using wool-cotton blended yarn as warp; and woolen yarn comprised of three different mixes of Australian Merino (AM) wool and JK crossbred (JKC) as weft yarn. Two different weft yarns of 41.7 and 31.2 Tex were prepared using these mixes. The thermo-physiological properties of fabric viz. air permeability, water vapor transmission, and thermal resistance were studied. The air and water vapor permeability, and thermal resistance of wool-rich blended fabrics were found higher compared to cotton-rich blends. The air permeability is negatively influenced by the fabric cover factor. The coarser weft yarn gives higher air permeability while lower water vapor permeability. The thermal resistance is found to have a positive relationship with fabric cover factor. The wool content in yarn and weft yarn linear density largely influences the thermo-physiological comfort properties of the khadi fabric.

Grażyna Silska, Tomasz Górecki

The flax and hemp genetic resources collection gathered by the IWNiRZ – PIB the Institute of Natural Fibres & Medicinal Plants – National Research Institute (iNNi R2) is very important for protection of biodiversity (http://www.biodiv.org). Presently, the flax collection of IWNiRZ Gene Bank comprises 829 accessions, including wild forms and landraces, primitive and advanced cultivars as well as varieties and breeding lines. Hemp collection holds about 150 accessions from various regions of the world. Genetic resources of flax and hemp are very important for health. The IWNiRZ is involved in the valorization of morphological biological features and economic traits of genetic resources of flax, hemp and herbal plants. This article characterizes two economic traits of 264 accessions of flax from many countries of the world: fiber content in stem and fiber yield. The IWNiRZ is involved also in developing The International Flax Data base, therefore the results are also presented in the form of a descriptive assessment, using special descriptors. The range of variability of the fiber content of 263 tested flax accessions ranges from 9.9% – Argentina 346 (INF00201) to 28.9% – Dacota C.I. 1072 (INF00026). The results of fiber content of 263 flax accessions according to the International Flax DataBase methodology are as follows: very low content of fiber – 27 accessions of flax (10.3% of evaluated accessions), low – 151 accessions of flax (57.4%), medium – 55 accessions of flax (20.9%), high – 28 accessions of flax (10.6%) and very high – 2 varieties (0.8%). The fiber yield results could not be prepared for the International Flax Database because the plot of the experiment was too small to be considered reliable. The IWNiRZ collection contributes as a valuable source for breeders when selecting useful parental components and also secures breeders’ achievements.

P. Venkateshwar Reddy, R. V. Saikumar Reddy, B. Veerabhadra Reddy et al.

The utilization of the plant-based fiber-reinforced composites is being increased in recent days. The plant-based fiber used in the present study was extracted from the Prosopis juliflora plant. Alkali treatment effects of the fiber-reinforced composites on the static and dynamic mechanical and dielectric properties were investigated and compared with the untreated fiber-reinforced composites in the current work. Tests like static and dynamic mechanical, dielectrical, scanning electron microscopy (SEM), X-ray diffraction (XRD), and thermogravimetric analysis (TGA) were carried out on both treated and untreated composite specimens. The temperature was varied from 25°C to a maximum temperature of 180°C to investigate the dynamic mechanical properties at a constant frequency of 2 Hz. Dielectric properties were also analyzed using impedance analyzer and compared the results of both treated and untreated composites. Characterization techniques like SEM, TGA, and XRD were carried out on both the treated and untreated composite specimens to probe the bonding and crystallinity among the composites. The results of SEM and XRD showed that the bonding and crystallinity improved with the fiber treatment such that the thermal stability also improved. The improved properties of the composite samples extend the applications in the field of automotive, packaging, construction, etc.

Mustafa Doga Dogan, Ahmad Taka, Michael Lu et al.

Existing approaches for embedding unobtrusive tags inside 3D objects require either complex fabrication or high-cost imaging equipment. We present InfraredTags, which are 2D markers and barcodes imperceptible to the naked eye that can be 3D printed as part of objects, and detected rapidly by low-cost near-infrared cameras. We achieve this by printing objects from an infrared-transmitting filament, which infrared cameras can see through, and by having air gaps inside for the tag's bits, which appear at a different intensity in the infrared image. We built a user interface that facilitates the integration of common tags (QR codes, ArUco markers) with the object geometry to make them 3D printable as InfraredTags. We also developed a low-cost infrared imaging module that augments existing mobile devices and decodes tags using our image processing pipeline. Our evaluation shows that the tags can be detected with little near-infrared illumination (0.2lux) and from distances as far as 250cm. We demonstrate how our method enables various applications, such as object tracking and embedding metadata for augmented reality and tangible interactions.

Mauricio Cruz Saldivar, Eugeni L. Doubrovski, Mohammad J. Mirzaali et al.

Bio-inspired composites are a great promise for mimicking the extraordinary and highly efficient properties of natural materials. Recent developments in voxel-by-voxel 3D printing have enabled extreme levels of control over the material deposition, yielding complex micro-architected materials. However, spatial complexity makes it a formidable challenge to find the optimal distribution of both hard and soft phases. To address this, a nonlinear coarse-graining approach is developed, where foam-based constitutive equations are used to predict the mechanics of biomimetic composites. The proposed approach is validated by comparing coarse-grained finite element predictions against full-field strain distributions measured using digital image correlation. To evaluate the degree of coarse-graining on model accuracy, pre-notched specimens decorated with a binarized version of a renowned painting were modeled. Subsequently, coarse-graining is used to predict the fracture behavior of bio-inspired composites incorporating complex designs, such as functional gradients and hierarchical organizations. Finally, as a showcase of the proposed approach, the inverse coarse-graining is combined with a theoretical model of bone tissue adaptation to optimize the microarchitecture of a 3D-printed femur. The predicted properties were in exceptionally good agreement with the corresponding experimental results. Therefore, the coarse-graining method allows the design of advanced architected materials with tunable and predictable properties.