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

Dajun Lin, Xiaofeng Chen, Connor O. Dea et al.

Additive manufacturing using light is commonly constrained by serial voxel-by-voxel or layer-by-layer processing, which fundamentally limits fabrication speed and scalability. Here, we introduce a single-exposure holographic three-dimensional (3D) printing approach that synthesizes an entire volumetric dose distribution optically in one step. The method combines inverse-designed microstructured phase masks with photopolymer resins engineered for controlled optical absorption. By precisely tailoring the phase-mask topography, we generate arbitrary 3D light-intensity distributions within the resin, including intentionally encoded dark regions that define hollow internal features. Simultaneously, the resin formulation is designed to balance optical penetration with sufficient local energy deposition to achieve high-fidelity polymerization throughout the volume. Using this approach, millimeter-scale architectures comprising more than $10^{6}$ addressable voxels are fabricated in a single 7.5~s exposure, corresponding to a volumetric throughput of $\sim$1~mm$^{3}$/s ($>10^{5}$~voxels/s). The demonstrated performance is presently limited by resin kinetics and illumination geometry rather than by the phase-mask framework itself. Because the volumetric information capacity scales with the space--bandwidth product of the phase mask, this approach provides a clear pathway toward substantially higher throughput, enabling scalable fabrication of micro-optical components, biomedical scaffolds, and other precision-engineered mesoscale systems.

Kencho Dekar

Aadhar A. Mandot, Sanjay Bambhaniya

Xu Huiya, Wang Ping, Xia Tian

As cultural heritage preservation and sustainable development concepts become increasingly integrated, China’s traditional textile dyeing protection and development gain heightened attention. This study focuses on tie-dyeing, a representative intangible cultural heritage (ICH) craft, to investigate the expectations of its current and potential consumers. The ultimate goal is to translate these expectations into actionable guidance that supports the long-term viability of the tie-dyeing industry. Through a combined methodology of grounded theory and the Kano model, the study initially identified demand indicators via grounded theory, yielding 4 dimensions and 26 demand items. The Kano model analysis was then applied to 239 valid responses. By combining the Better–Worse coefficient and quadrant analysis, the study established a classification system for consumer expectations and prioritized demand importance. The research indicates that the five primary consumer expectations for tie-dyed products are as follows: ease of maintenance, esthetic expression, natural materials, product diversity, and cultural symbolism. These elements represent core consumer demands and warrant primary consideration during product development. Based on these findings, the study presents targeted strategic recommendations for tie-dyeing enterprises regarding product development, market promotion, and brand building. This research contributes to the theoretical understanding of consumer expectations within the ICH domain while offering novel perspectives for promoting the sustainable inheritance and innovative development of tie-dyeing in contemporary markets.

Juneyoung Minn, Hyunjin Kim, Hye Rim Kim

Bacterial cellulose (BC) was crosslinked with citrus (Citrus junos and Citrus unshiu) peel to produce a colored, multifunctional leather substitute with enhanced mechanical strengths and flame retardancy. Surface characterization confirmed successful crosslinking between the citrus peel and BC. The citrus peel-crosslinked BC exhibited tensile strengths and elongations at break 1.9–2.1 times and 2.5–2.8 times greater than those of cowhide leather, respectively. Flame retardancy analysis confirmed that the citrus peel-crosslinked BCs formed compact, porous char layers during combustion, and retained final residual masses 10.9–11.8 times higher than that of original BC. Moreover, the citrus peel imparted a brown color to BC, with good fastness levels 5 and 4. Thus, this study demonstrates that citrus waste can be sustainably recycled to improve the mechanical strength and flame retardancy of BC while simultaneously imparting color.

Ilias Sertaridis, Spyridon Besias, Florentia Afentaki et al.

Printed Electronics (PE) technology has emerged as a promising alternative to silicon-based computing. It offers attractive properties such as on-demand ultra-low-cost fabrication, mechanical flexibility, and conformality. However, PE are governed by large feature sizes, prohibiting the realization of complex printed Machine Learning (ML) classifiers. Leveraging PE's ultra-low non-recurring engineering and fabrication costs, designers can fully customize hardware to a specific ML model and dataset, significantly reducing circuit complexity. Despite significant advancements, state-of-the-art solutions achieve area efficiency at the expense of considerable accuracy loss. Our work mitigates this by designing area- and power-efficient printed ML classifiers with little to no accuracy degradation. Specifically, we introduce the first sequential Support Vector Machine (SVM) classifiers, exploiting the hardware efficiency of bespoke control and storage units and a single Multiply-Accumulate compute engine. Our SVMs yield on average 6x lower area and 4.6% higher accuracy compared to the printed state of the art.

Adam Barr, Cinzia da Vià, Mosst Tasnim Binte Shawkat et al.

This work reports on the performance of a novel neutron-sensitive scintillating detector fabricated using Fused-Deposition Modelling (FDM) additive manufacturing. FDM is a cost-effective 3D-printing method employing flexible plastic filaments to create custom-shaped components. Scintillating filaments, based on polystyrene doped with \emph{p}-terphenyl and 1,4-bis (5-phenyloxazol-2-yl) benzene, and enriched with $^6$LiF to enable neutron sensitivity were manufactured in house and achieved visible scintillation with a light output of 30$\pm$5~photons per MeV. Printed scintillators were then integrated into a detector system consisting of an image intensified TimePix3 camera, offering high spatial and temporal resolution. The detector performance was compared with Geant4 simulations of the scintillating sensor's response to electrons, gamma-rays, and thermal neutrons. A novel event discrimination algorithm, using the properties of the TimePix3 camera, enabled the separation of neutron signatures from the gamma-ray background.

Ward van der Schoot, Niels M. P. Neumann

With a growing interest in quantum computing, the number of proposed quantum algorithms grows as well. The practical applicability of these algorithms differs: Some can be applied out-of-the-box, while others require black box oracles, which can not always be easily implemented. One of the first works to explicitly discuss these practical applicability aspects is by Aaronson discussing the \textit{fine print} of the HHL quantum algorithm that solves linear systems of equations. We extend this line of research by providing a similar fine print for the first analog quantum algorithm that computes the stationary distribution of Markov chains. We conclude that more focus should be put on this practical applicability of quantum algorithms, either through a separate line of research, or through more attention when introducing the algorithm.

Lami Amanuel Erana

This study investigates the mechanical properties of single and double-layer woven sisal mat-reinforced PP composite panels. Sisal fibers were extracted using the manual decortication method, resulting in fibers with a density of 1.43 g/cm3 and a diameter ranging from 0.4 mm to 0.6 mm. To improve the bonding between the sisal fibers and the matrix, the fibers were hand-spun into yarn and woven into mats. The study focuses on the unique material combination and the use of sisal as a natural fiber reinforcement. The 18 mm thick panels were tested for water absorption following ASTM D570, compression strength, and tensile strength following ASTM D3039 using the UTES-100 High Precision universal strength tester machine. Composite panels with single layers of 10% and 15% woven fabric mat, loaded with 8 kg and 10 kg, exhibited compressive strengths of 11.6KN and 12.5KN, respectively. Panels reinforced with two layers of 20% and 30% sisal woven fabric mat, loaded with 8 kg and 10 kg, had compression strengths of 12.2KN and 12.5KN, respectively. Moreover, composite samples with 15% single layer and 30% double-layer sisal woven fabric mat demonstrated a equal compression strength of 12.5KN, falling within the range recommended by ISO13006:2012. The tensile strength of 16.99MPa, although slightly below the recommended ISO13006 value of 20MPa for commercial-grade panels, indicates promising results. The study’s findings suggest that higher fiber content and additional reinforcement layers lead to increased compression and tensile strength. Furthermore, the moisture absorption rate of the developed composite panels was significantly lower than the 0.5% water absorption rate authorized by the American National Standard Institute.

Yingjie Cai, Xiaolong Huang, Mohammad Nazmul Ehsan et al.

A limited selection of natural dyes’ color impedes the development of textile dyeing with natural plant dyes. Inspiring by the conventional coloration of textiles with a combination of three synthetic dyes generally, the present work is to investigate the broadening color shade of dyed wool fiber with ternary natural dye combinations of madder red (MR), gardenia yellow (GY), and gardenia blue (GB) without mordants in a decamethylcyclopentasiloxane (D5) medium. The wool yarn was wetted in an aqueous solution of pH 3 to own a 300% pickup rate, followed by immersion in a D5 medium containing 2% of alcohol ethoxylate (AEO-3) and solid natural dyes at 90°C for 90 min for coloration. The colorfastness to washing was achieved at a 4–5 for fading and a 5 rating for staining for all colors. The XRD patterns and TGA analysis confirmed that the dyeing procedure did not affect the crystallinity nature and stable thermal tendency. SEM images and cross-sections showed that the dyeing procedure did not damage the morphological structure of the wool fiber surface, and the dyes were evenly distributed. Finally, many color shades of dyed fibers were prepared with various dyes’ ratios.

Hansadi Jayamaha, Isabel Schorn, Larissa M. Shepherd

Many adsorbent materials are being studied for dye and oil removal from the environment. Bio-based materials such as silk are promising candidates due to their enhanced affinity for dyes and intrinsic hydrophobicity. This work extensively studies various silk textiles as dye and oil adsorbents. For comparison, we use electrospun fiber mats and hollow silk microparticle-treated silk fabrics. Our work is motivated by two factors: (i) massive amounts of silk waste is being discarded annually from textile factories, and (ii) the limited studies on the adsorption phenomena of pristine silk textiles. Based on our findings, 12 mg of silk filament yarn has a 90% methylene blue (MB) removal efficiency within 10 min of exposure for concentrations up to 100 ppm and exhibits adsorption capacities of 145 mg/g for 800 ppm concentrations. The adsorption kinetics obey a pseudo-second order, where the rate-controlling step is chemisorption, and isotherms follow the Langmuir model with homogenous monolayer adsorption. Furthermore, noil woven fabrics with contact angles of 140⁰ have oil adsorbent capacities that are double the fabric weight. Our work confirms that silk waste textiles are efficient and reusable bio-adsorbents for MB dye and oil removal, outperforming materials made with additional and energy-intensive techniques such as silk dissolution and electrospinning.

Naouri Ladaci, Aziz Saadia, Ahmed Belaadi et al.

This study examined the water uptake (WU) behavior of recycled high-density polyethylene (RHDPE). The biocomposites made of palm waste Washingtonia (PWW) fibers were treated with 3% sodium bicarbonate (NaHCO3) for 24 h. Several RHDPE materials reinforced with different concentrations of PWW fibers (5 to 30 wt.%) until saturation, or roughly 25 days, were developed to investigate the WU kinetics and diffusion in biocomposites. An artificial neural network (ANN) and the response surface methodology (RSM) methods were applied to model the behavior of uptake measured in experiments and optimize the immersion period and PWW fiber content in RHDPE/PWW biocomposite WU. The WU moved swiftly during the first test phase and was completed after 400 h of soaking. The outcomes demonstrated a perfect fit between the observed and anticipated data. Findings showed that the ANN models’ training, test, and validation correlation coefficients were 0.9984, 0.9955, and 0.9723, respectively, for predicting WU. Concerning accuracy and reliability, the ANN model outperformed the RSM model, making it suitable for various industrial uses. The results offer helpful information for professionals to consider when developing and implementing PWW fiber biocomposites.

Amit Talukder, Charles Freeman, Caroline Kobia et al.

Wearable photovoltaic technology has been prominent in recent years because electronic devices need to be powered continuously without reliance on traditional methods. However, the practical adoption of wearable PV cells is hindered by the need for laundering, potentially degrading performance. This research compared PV cells’ maximum current and electrical resistance before and after laundering testing conditions. This study used eight samples of two types of PV panel cells and laundered them up to five cycles. The current and electrical resistance values were recorded before and after each laundering cycle. This study analyzed the data using a paired sample <i>t</i>-test and MANOVA. It was found that laundering cycles significantly affected the current values in both types of samples, with no differential impact between the types; on the other hand, laundering cycles did not significantly affect the electrical resistance values in both types of samples, with no differential impact between the types. These results are crucial for industries developing textile-based PV panels, where maintaining electrical performance after laundering is essential. These findings could pave the way for more sustainable, self-powered wearable PV technologies, ultimately transforming how users interact with electronic devices daily.

Vuković Milovan, Dašić Dejan, Vuković Aleksandra

The recent wave of crises caused by various factors, which began in 2020, affects all aspects of society, including economic activities. Many industries, including the fashion industry, are experiencing a number of unfavorable developments, chief among them being the reduction in demand for particular goods, damaged reputation etc. Business operations in the conditions of an economic crisis have forced many fashion industry companies to seek adequate mechanisms to face the consequences of this type of crisis. One potential solution to lessen the negative consequences of these occurrences is to implement crisis management in a firm in a systematic way. Crisis communication helps in crisis management, according to a review of businesses' experiences dealing with such an undesirable occurrence or a sequence of events. The subject of this paper is the role of crisis communication in crisis management, particularly from the perspective of companies that dominate the fashion industry. The first part of the paper addresses the various types of crises that all manufacturing companies must consider. The crisis management process, which includes an analysis of potential communication strategies, will be the central focus of the discussion. The final part of the paper examines the operation of companies under high-risk conditions.

Abdolmajid Alipour, Krishnan Jayaraman

Flax fibers have been shown to have comparable mechanical properties to some conventional synthetic fibers. Flax fabrics with different textile structures show differences in resistance against mechanical loads mainly rooted in fabric orientation and the resultant resin impregnation. Thus, in this study, flax fabrics with three different textile structures, fine twill weave, coarse twill weave and unidirectional, were used as reinforcements in an epoxy matrix. The surfaces of the fabrics were chemically treated using an alkaline treatment, and the alterations in fabric crystallinity index (CrI) were determined using X-ray diffraction (XRD). Experimental results confirmed that textile structures and CrI had significant effects on the mechanical properties of composites. Although an increment in CrI, resulting from chemical treatment, always enhanced tensile and flexural properties, it adversely affected damage development once composites were exposed to impact load. In terms of textile structures, unidirectional fabric outperformed woven fabrics in tensile and flexural properties while in impact properties, the latter had a better performance inducing less damage development. Finally, the mechanism of damage development in different composites was discussed in detail using Scanning Electron Microscopy (SEM) images. It is envisaged that the results of this study will provide an insight that will lead to the proper choice of the optimal kind of flax fabric for different applications.

Briony Forsberg, Dr Henry Williams, Prof Bruce MacDonald et al.

This paper develops an approach to classify instances of product failure in a complex textiles manufacturing dataset using explainable techniques. The dataset used in this study was obtained from a New Zealand manufacturer of woollen carpets and rugs. In investigating the trade-off between accuracy and explainability, three different tree-based classification algorithms were evaluated: a Decision Tree and two ensemble methods, Random Forest and XGBoost. Additionally, three feature selection methods were also evaluated: the SelectKBest method, using chi-squared as the scoring function, the Pearson Correlation Coefficient, and the Boruta algorithm. Not surprisingly, the ensemble methods typically produced better results than the Decision Tree model. The Random Forest model yielded the best results overall when combined with the Boruta feature selection technique. Finally, a tree ensemble explaining technique was used to extract rule lists to capture necessary and sufficient conditions for classification by a trained model that could be easily interpreted by a human. Notably, several features that were in the extracted rule lists were statistical features and calculated features that were added to the original dataset. This demonstrates the influence that bringing in additional information during the data preprocessing stages can have on the ultimate model performance.

Xueyu Hu, Kun Kuang, Jiankai Sun et al.

Large language models (LLMs) have made significant progress in code generation tasks, but their performance in tackling programming problems with complex data structures and algorithms remains suboptimal. To address this issue, we propose an in-context learning approach that guides LLMs to debug by using a "print debugging" method, which involves inserting print statements to trace and analysing logs for fixing the bug. We collect a Leetcode problem dataset and evaluate our method using the Leetcode online judging system. Experiments with GPT-4 demonstrate the effectiveness of our approach, outperforming rubber duck debugging in easy and medium-level Leetcode problems by 1.5% and 17.9%.

Hao Zhang, Yaoyao Zheng, Haitao Wang et al.

طاهره نوایی دیوا

امروزه به دلیل افزایش تولید مواد رنگزا، آلودگی محیط‌زیست افزایش یافته است. مطالعات اخیر  نشان داده که جاذب‌های قابل استفاده فراوانی از جمله پوست موز، سیب زمینی، جلبک و غیره در دسترس همگان است. سازمان غذا و دارو استفاده از رودامینB  را به دلیل سمی ‌بودن و اثرات مضر آن ممنوع کرده‌ است. بنابراین، این مطالعه طیف گسترده‌ای از جاذب‌های جایگزین غیر‌متعارف ولی کم هزینه را برای حذف ماده رنگزای رودامین  B از پساب ارائه می‌کند. مشاهدات نشان داده است که سازوکار جذب این ماده رنگزا بر روی مدل‌های سینتیک، ایزوترم و ترمودینامیک متمرکز است که به ماهیت شیمیایی مواد و شرایط مختلف  فیزیکی و شیمیایی مانند pH محلول، غلظت اولیه ماده رنگزا، دوز جاذب و دما نیز بستگی دارد. داده‌های سینتیکی جذب ماده رنگزای رودامین B معمولاً از مدل‌های سینتیکی شبه مرتبه اول و شبه مرتبه دوم پیروی می‌کند. چندین مطالعه نشان داد که مدل‌های ایزوترم جذب لانگمویر و فروندلیچ اغلب برای ارزیابی ظرفیت جذب جاذب‌ها استفاده می‌شوند. علاوه بر این، بررسی ترمودینامیکی حاکی از آن است که جذب رودامین B در طبیعت، گرماگیر و بدون محدودیت است. بنابراین، هر دو روش تجزیه کاتالیزوری نوری و جذب، برای حذف ماده رنگزا رودامین B از پساب‌های صنعتی قابلیت خوبی دارند. تحقیقات بیشتری برای ارزیابی امکان استفاده از زیست‌توده پسماندهای اصلاح شده دیگر برای کنترل آلودگی صنعتی در حال انجام است.

Ahmed Belaadi, Messaouda Boumaaza, Hassan Alshahrani et al.

The present research is an extension of a previous paper published by the authors. In the first part of the research, the flexural properties of Washingtonia filifera (WF) fiber-reinforced plaster composite treated with sodium bicarbonate were explored using response surface method statistics. In the current study, the data was analyzed using artificial neural network tool. The main objective of the current research is to model the flexural properties of an environmentally friendly gypsum biocomposite reinforced with treated and untreated WF fibers using response surface method and artificial neural networks. For this purpose, the study reports a comparative approach between models predicted by response surface methodology (RSM) and artificial neural networks (ANNs). The statistical results as root mean square error and coefficient of determination reveal that ANN and RSM are effective techniques for bending properties prediction of plaster/WF biocomposites. In addition, ANN and RSM models correlate highly with the experimental data. However, artificial neural network model displayed more accuracy.