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

Hisham Alabduljabbar, Irfan Ullah, Muhammad Faisal Javed et al.

This study employed hybrid machine learning models, known for their superior accuracy over traditional ML models, to develop a reliable framework for estimating the compressive strength (CS) of rice husk ash (RHA) concrete. This approach eliminates the reliance on time-consuming and resource-intensive physical experiments. To optimize the hyperparameters of the random forest (RF) model, six metaheuristic algorithms were employed. These include the differential evolution algorithm (DEA), human felicity algorithm (HFA), lightning search algorithm (LSA), nuclear reaction optimization (NRO), Harris hawk optimization (HHO), and tunicate swarm algorithm (TSA). To assess the efficacy of the suggested ML models, several statistical indicators were employed. To enhance the interpretability of the model predictions, the SHapley Additive exPlaination (SHAP) method and partial dependence plots (PDP) analysis were utilized. All six hybrid models showed strong performance, with LSA-RF proving to be the most effective. LSA-RF had the highest coefficient of determination (R2) value of 0.979, showcasing superior prediction accuracy in comparison to DEA-RF (0.972), HFA-RF (0.962), NRO-RF (0.960), TSA-RF (0.916), and HHO-RF (0.928). Furthermore, an intuitive user interface was designed for practical applications, enabling instant CS predictions for RHA concrete based on input parameters.

Sheila Naa Tetteorkor Clottey, Sylvia Ashley Gyampoh

Purpose: This study explored consumer buying behaviour towards Ghanaian fashion products in the Greater Accra Metropolis, focusing on demographic factors, fashion trends, and economic influences. Methodologies/Design: A quantitative cross-sectional survey was employed, utilising structured questionnaires to gather data. A sample of size of 366 respondents was obtained and used in the study. To ensure representativeness, the simple random sampling techniques were employed. Descriptive and inferential statistical analyses, including regression, were conducted. Findings: The study revealed that gender and age significantly influence consumer behaviour, with women and younger adults (aged 20-39) showing a higher inclination towards purchasing locally made fashion items. Fashion trends emerged as a key determinant, acknowledging their influence on buying decisions. Regression analysis confirmed a significant positive effect of fashion trends and working status on purchasing behaviour. Practical and Social Implications: The findings suggest that local fashion brands should target younger consumers through digital platforms and trend-driven marketing. Also, brands could benefit from tailoring products and promotions towards female consumers and employed individuals with greater purchasing power. Socially, the study shows the role of fashion as a form of cultural expression among urban youth while also identifying a niche market focused on quality and heritage. Originality: A novel understanding of consumer dynamics within the Ghanaian fashion industry is provided in this study, emphasising the interplay of trends, demographics, and economic factors, offering actionable recommendations for fashion marketers to optimise their strategies in a competitive market.

Xing Zheng, Xiaoyun Liu, Yunyun Hu et al.

The measurement of dynamic deformation and pressure distribution of the human body is crucial for advancements in 3D body measurement, modeling, and the optimization of clothing patternmaking for both fit and comfort This study focuses on assessing the dynamic changes in pressure and deformation of the waist-abdomen region during posture transitions in young women wearing tight-fitting pants of different sizes and compared the dynamic deformability of real human body and virtual simulated models. Clothing pressure was measured in both standing and sitting postures, while 3D models of the waist-abdomen region were generated using 3D body scanning to capture body deformation patterns. The research examined the relationship between pressure distribution, circumference, and volume, along with their dynamic variations under different levels of pressure. A novel under-clothing bump grid method was introduced to measure and analyze the horizontal and vertical skin deformation of the waist-abdomen. A dynamic virtual human body model was constructed to compare and analyze its dynamic deformation. The findings revealed that clothing pressure distribution on the waist-abdomen is closely related to the physiological morphology of the body. Notably, the skin’s vertical deformations are more significant when sitting, with clothing pressure playing a significant role in the elastic deformation of the waist-abdomen. Additionally, the changes in circumference and volume follow a consistent pattern. This research offers novel insights for optimizing clothing design, enhancing the functional design and comfort design, and contributes to improving the body and clothing simulation.

Qinhua Guo, Lizhou Yang, Yawen Gan et al.

Micro-transfer printing is an assembly technology that enables large-scale integration of diverse materials and components from micro- to nano-scale. However, traditional micro-transfer printing technologies lack dynamic selectivity, limiting capabilities in sorting and repairing materials and components for effective yield management during large-scale manufacturing and integration processes. In this work, we introduce a dynamically programmable micro-transfer printing system utilizing a sharp phase-changing polymer and an independently addressable microheater array to modulate adhesion through localized heating. The system demonstrates dynamically programmable capabilities for selective transfer of various materials including semiconductors, polymers and metals, handling geometries from micro-scale chiplets to nanometer-thick films and micro-spheres. It also exhibits exceptional capabilities in 3D stacking and heterogeneous materials integration, significantly advancing the manufacturability of complex microsystems. As a demonstration, we successfully perform dynamically programmable transfer of microLED chips to create arbitrarily specified patterns, offering a promising solution to the challenges of mass transfer and pixel repair in microLED display manufacturing.

David Sims, Benjamin Sims, Brian Wright et al.

3D-printing of radiofrequency (RF) cavity resonators could provide a cost-effective solution that enables rapid prototyping and design flexibility compared to traditional fabrication of full-metal cavities. In this work, the feasibility of fabrication of a useful multi-mode GHz cavity is explored. Two kinds of plastics, two slicing approaches and two metal coating techniques were used to build a series of clamped cavities with thin inner copper surface on otherwise 3D printed plastic surface. The cavities were then bench-tested to identify spatial field distributions, operating frequencies and quality factors (Q-factor). Pros and cons of the used fabrication approaches were identified and understood, and the performance of longitudinally sliced painted cavity design demonstrated considerable practicality of 3D-printing approach in designing rf systems.

Muhammad Waqas Shabbir, Sagor Biswas, Rohit Kajla et al.

Scattering and absorption are fundamental processes in optical engineering and applications. This study investigates the use of the food dye tartrazine to design refractive index fluids that enhance light propagation through scattering media. The optical properties of the solutions were carefully examined using spectrometry and ellipsometry under two extreme conditions, emphasizing the importance of a comprehensive understanding of dye solutions. Additionally, we demonstrated using dye molecules to control light propagation through scattering media. Our findings highlight the potential of food dyes as cost-effective, environmentally friendly alternatives for future advancements in biomedical imaging, optical communication, and photonic devices.

Okkyung Lee, Heeran Lee

Abstract Herein, we investigate the effects of 3D printed electrodes on electrophysiological signals and identify the important design elements required for manufacturing better electrodes for high body adhesion for smart wear. Ten electrodes of different shapes (plain, check, stripe, circular, radial cut-out) and thicknesses (0.5 mm and 1.0 mm) were manufactured. The electrodes were evaluated by testing on 20 healthy individuals (10 men and 10 women). To measure the electroencephalogram (EEG) of the participants, we used BIOS-S8 (BioBrain Inc., Korea), an 8-channel polygraph for multibody signal measurement. Data were analyzed using the SPSS 26.0 statistical program. The EEG values were significantly activated according to gender. For the male participants, relative alpha (RA), relative slow theta (RST), relative mid theta (RMT), and the ratio of SMR-mid beta to theta (RSMT) values were highly activated and for the female participants, RA, relative fast alpha (RFA), and relative slow theta (RSA) values were highly activated. There were no significant gendifferences in the EEG of both genders for the 10 types of electrodes. However, for the female participants, the ‘RA’ indices showed a significant difference based on electrode shape on the right temporal lobe (T4), but there was no significant difference based on the thickness. There was a significant difference in the subjective preference of the electrodes also. In the subjective evaluation, it was found that the differences based on the shape and thickness of the electrodes were sensitively recognized.

Nahyun Kwon, Tong Sun, Yuyang Gao et al.

The widespread consumer-grade 3D printers and learning resources online enable novices to self-train in remote settings. While troubleshooting plays an essential part of 3D printing, the process remains challenging for many remote novices even with the help of well-developed online sources, such as online troubleshooting archives and online community help. We conducted a formative study with 76 active 3D printing users to learn how remote novices leverage online resources in troubleshooting and their challenges. We found that remote novices cannot fully utilize online resources. For example, the online archives statically provide general information, making it hard to search and relate their unique cases with existing descriptions. Online communities can potentially ease their struggles by providing more targeted suggestions, but a helper who can provide custom help is rather scarce, making it hard to obtain timely assistance. We propose 3DPFIX, an interactive 3D troubleshooting system powered by the pipeline to facilitate Human-AI Collaboration, designed to improve novices' 3D printing experiences and thus help them easily accumulate their domain knowledge. We built 3DPFIX that supports automated diagnosis and solution-seeking. 3DPFIX was built upon shared dialogues about failure cases from Q&A discourses accumulated in online communities. We leverage social annotations (i.e., comments) to build an annotated failure image dataset for AI classifiers and extract a solution pool. Our summative study revealed that using 3DPFIX helped participants spend significantly less effort in diagnosing failures and finding a more accurate solution than relying on their common practice. We also found that 3DPFIX users learn about 3D printing domain-specific knowledge. We discuss the implications of leveraging community-driven data in developing future Human-AI Collaboration designs.

Md Manjurul Ahsan, Shivakumar Raman, Zahed Siddique

Additive manufacturing (AM), particularly 3D printing, has revolutionized the production of complex structures across various industries. However, ensuring quality and detecting defects in 3D-printed objects remain significant challenges. This study focuses on improving defect detection in 3D-printed cylinders by integrating novel pre-processing techniques such as Region of Interest (ROI) selection, Histogram Equalization (HE), and Details Enhancer (DE) with Convolutional Neural Networks (CNNs), specifically the modified VGG16 model. The approaches, ROIN, ROIHEN, and ROIHEDEN, demonstrated promising results, with the best model achieving an accuracy of 1.00 and an F1-score of 1.00 on the test set. The study also explored the models' interpretability through Local Interpretable Model-Agnostic Explanations and Gradient-weighted Class Activation Mapping, enhancing the understanding of the decision-making process. Furthermore, the modified VGG16 model showed superior computational efficiency with 30713M FLOPs and 15M parameters, the lowest among the compared models. These findings underscore the significance of tailored pre-processing and CNNs in enhancing defect detection in AM, offering a pathway to improve manufacturing precision and efficiency. This research not only contributes to the advancement of 3D printing technology but also highlights the potential of integrating machine learning with AM for superior quality control.

Dominique Almendariz , Nikolaj Munk Nielsen, Laura Deschl

Developments in textile and fiber engineering have allowed the development of functional clothing such as protective wear, sportswear, and medical clothing. Stimulating pressure points on the skin has a wide range of applications in manual therapy – both to eliminate functional disorders in the musculoskeletal system and to relieve pain. An acupressure-like effect can be achieved when the practitioner or the person pressures the skin with the thumb on specific pressure-points on the body. So far, there have not been any product solutions which combine (full)-body garments with an acupressure-like effect. Understanding textiles as a grid which holds pressure balls in place and making use of fiber and textile technologies for industrial knitting has enabled “trykk.” to develop four pressure-point-garments with different textile variables. The purpose of the garment is to substitute the mechanical stimulation of the acupressure-like thumb on the skin through a patent-pending 3-dimensional textile-body interface which consists of a flexible textile grid and small marble-sized semi-precious stone balls. This paper describes a study set-up where the four prototypes in five different haptic use-scenarios are compared to the average force applied in an acupressure-like intervention. Besides, data of the likeability (satisfaction) regarding the four distinctive textiles were obtained. Results demonstrated a comparable performance of the prototypes in four out of five use case scenarios. Textile variables significantly altered users’ interest in the garments, yet had no significant effect on the technical performance and the perceived intensity of stimulation.

Mojtaba Haghighat, Seyed Ehsan Samaei, Somayeh Amininasab et al.

Natural fibers obtained from the agricultural wastes are a promising source within the field of acoustic and have already shown favorable results for mitigating the noise pollution. Supported by the experimental data and via an eco-friendly approach, the current study evaluates the impact of fiber size on the sound absorption values of the samples fabricated from sugarcane bagasse (SCB) waste fibers. The samples were formed based on the fiber size and constant bulk densities and thicknesses. The empirical models such as Delany-Bazley (D-B model) along with Best-fit-Nelder-Mead method were also employed to predict the acoustic absorption coefficients of the samples. Therefore, the least-square fit procedure was taken to evaluate the results which is compatible with both the impedance test tube and prediction models. Hence, according to the analyses, the lowest fiber size measured the highest absorption performance (α≃0.63) and airflow resistivity (σ = 6750), indicating that the performance of the fibers reached peaks at lower frequency and slightly decreased at mid and high frequency ranges while the fiber size 0.29–0.37 mm saw a slight rise again. Also, airflow resistivity and sound absorption performance of the SCB fibers decreased with increased fiber sizes.

Aboalasaad A. R., Sirková B. K., Mansoor T. et al.

The objective of this paper is to report a study on the prediction of the steady-state thermal resistance of woven compression bandage (WCB) by using three different mathematical models. The experimental samples of WCB were 100% cotton, cotton–polyamide–polyurethane, and viscose–polyurethane. The bandage samples were evaluated at extensions ranging at 10–100%, with two- and three-layer bandaging techniques. Experimental thermal resistance was measured by thermal foot manikin (TFM) and ALAMBETA testing devices. The obtained results by TFM and ALAMBETA were validated and compared with the theoretical models (Maxwell–Eucken2, Schuhmeister, and Militky), and a reasonable correlation of approximately 78%, 92%, and 93% for ALAMBETA and 75%, 82%, and 83% for TFM, respectively, was observed.

Toufique Ahmed, Ramazan Tugrul Ogulata

Silver nanoparticles (AgNPs) and green synthesis have hegemony over their counterparts. This paper reviews- green synthesis mechanism, antimicrobial mechanism and, incorporation of AgNPs in textiles. Green synthesis is nontoxic, unlike chemical methods, cost-effective and precise, unlike physical techniques. In green synthesis, the reconversion of biomolecules from NADPH to NADP+releases electrons that reduce silver ions. Harmoniously, the functional groups of biomolecules act as polar-end to formulate steric stabilization. Green synthesized AgNPs are loaded on fabrics through different loading techniques such as pad-dry-cure, immersion, in situ, and others. This review also depicts the feasible mechanisms to explain the antimicrobial action of AgNPs. The antimicrobial activity of AgNPs is adequate for annihilating both gram-positive and gram-negative bacteria. The nanoparticle morphology depends on various constituents such as pH, temperature, concentration, and others. The acidic environment causes a larger nanoparticle size. Typically, the room temperature is enough for green synthesis. Whereas, high concentration of either plant extracts or metal precursors causes large nanoparticles. Hence, various shapes and sizes are possible by consolidating diverse concentrations of plants and metal precursors. Complicated connections may prevail amongst numerous concentrations, pH, temperature, and others with varying phytochemicals.

Zhe Jiang, Yiyi Zhang, Qiang Wang et al.

Research suggests that to eliminate undesirable effects of the scale layer, natural wool needs to be surface-modified before further application to textile manufacture, obtaining better properties of shrink-resistance, washing/felting and dyeing. However, previous methods exhibited some disadvantages, such as the adsorbable organic halogens (AOX) pollution from chloride treatment and severe fiber damage caused by enzyme treatment. Therefore, thiol-based ionic liquid was introduced onto the surface modification of wool to counter these defects. In this modification process, the surface modification was controlled on the wool surface using scanning electron microscopy (SEM) with evaluation of the effects of cleavage of disulfide bonds ascertained by the X-ray energy dispersive spectroscopy (EDS) results. The solubility in alkali and Fourier transform infrared spectroscopy (FTIR) spectra further indicated that the process could prevent main body damage of the fiber, the decreased content of the α-helix structure was evaluated from X-ray diffraction (XRD) and differential scanning calorimeter (DSC) curves. Furthermore, the hydrophilic performance of the modified wool, including wettability and the dye-ability, revealed an apparent enhancement compared to that of raw wool. In a summary, the thiol-based ionic liquid approach can efficiently improve hydrophilic properties of wool, and has the potential for large-scale production.

Fei Huang, Jiyong Hu, Xiong Yan

Flexible textile strain sensors that can be directly integrated into clothing have attracted much attention due to their great potential in wearable human health monitoring systems and human–computer interactions. Fiber- or yarn-based strain sensors are promising candidate materials for flexible and wearable electronics due to their light weights, good stretchability, high intrinsic and structural flexibility, and flexible integrability. This article investigates representative conductive materials, traditional and novel preparation methods and the structural design of fiber- or yarn-based resistive strain sensors as well as the interconnection and encapsulation of sensing fibers or yarns. In addition, this review summarizes the effects of the conductive materials, preparation strategy and structures on the crucial sensing performance. Discussions will be presented regarding the applications of fiber- or yarn-based resistive strain sensors. Finally, this article summarizes the bottleneck of current fiber- or yarn-based resistive strain sensors in terms of conductive materials, fabrication techniques, integration and performance, as well as scientific understanding, and proposes future research directions.

Fei Qian, Lei Zhao, Li Wei et al.

Four layers of glass fiber filaments with the fineness of 2400 tex were used as warp yarns, five layers of glass filaments with the fineness of 600 tex were used as weft yarns 110 tex and aramid fibers were used as Z yarns to process a three-dimensional woven reinforcement. Then, 307-3 unsaturated polyester resin was used as the matrix, and the three-dimensional woven reinforced composite was prepared by the VARTM method (resin transfer molding method). The bullet impact composite was modeled by ABAQUS (Finite element software). The starting conditions of the bullet incidence and the actual conditions were set consistently to analyze the change of the remaining velocity and acceleration of the bullet and the worth energy loss after the bullet impact. The results showed that the theoretical and experimental values of bullet incidence velocity and residual bullet velocity were linearly related. When the impact velocity of bullet incidence was higher, the slope of the straight line of the initial phase of bullet velocity decrease was larger, and the peak of the absolute value of acceleration after bullet impact was larger. The calculated value of energy loss after bullet impact simulation is basically consistent with the experimental value, This also fully proved that the bullet impact composite material model established was correct and effective.

Anand Sundararaju Perinbakannan, Muralidharan Karuppusamy, Karuppasamy Ramar

In this investigation, hybrid composites were prepared for structural applications using Indian almond and Banana fibers by hand layup method. Five types of composites were fabricated viz. I-I-I-I, I-B-B-I, I-B-I-B, B-I-I-B & B-B-B-B and the mechanical & moisture absorption characteristics were studied. The tensile and flexural studies showed that the I-I-I-I composite displayed the maximum tensile and flexural strength of 61 MPa and 53 MPa, respectively, due to the placing of high strength Indian almond fiber at outer skin. The impact study resulted that the B-B-B-B composite exhibited the maximum impact strength (6.2 kJ/m2) owing to the presence of more void content (6.83%) that absorbed more impact energy. The moisture absorption study reported that the B-B-B-B composite absorbed the maximum moisture percentage of 21% at 11 days due to more void content whereas the I-I-I-I composite showed least moisture absorption of 15% at 11 days because of low void percentage. Further, the biodegradation study revealed that the B-B-B-B composite exhibited the maximum weight loss of 38% at 60 days due to more moisture absorption that weakened the bonding strength of matrix and fiber and the microorganism accelerated the degradation.

Muhammad Mubashar Zafar, Amir Shakeel, Muhammad Haroon et al.

The production of cotton is negatively affected by salinity. For this purpose, 8 parents and their 16 F1 hybrids were evaluated under saline stress (15 dSm−1) in Line × Tester fashion. Mean values of plant height, number of bolls plant−1, boll weight, lint weight, seed cotton yield plant−1, seed index, no. of seeds boll−1, seed mass boll−1, lint mass boll−1, seed volume per 100 seeds, fiber strength, fiber length, lint%, K+, K+/Na+ ratio, CAT, TSP, chlorophyll a, b, and relative water contents decreased under salt stress whilst the values of lint index, seed density, fiber fineness, Na+, H2O2, SOD, POD carotenoids, malondialdehyde, phenolic contents, ascorbic acid, and flavonoids increased under saline conditions. Under saline MS-71× CRS-2007, MS-71× KAHKASHAN, and IUB-65 × FH-312 exhibited performed better than other genotypes for most traits. For fiber quality traits IUB-65× CRS-2007 and IUB-65× FH-312 showed the highest value under salt stress. Improved identified cotton genotypes can enhance our capacity to grow cotton in salt-affected soils and the key morpho-biochemical traits can potentially be exploited to obtain higher and more stable crops yield under stressed environments.

Gautam Basu, Mallika Datta, Surajit Sengupta et al.

Effect of pore size and its distribution on the noise reduction coefficient of jute felt were studied through capillary flow porometer and impedance tube. The inter-criteria correlation method was used to optimize the type of jute felts to obtain noise reduction coefficient of 0.5. The porometry study of the needle punched jute felt suggested the gradient pore structure of felt due to presence of needling induced inverted cone of pores within fibrous mass. The jute felt with an areal density 796.5 g/m2 with mean pore diameter 60.32 µm offered optimum noise reduction coefficient of 0.5. The percentage weight of pore distribution in the range of 45≥ ∅ <25 µm was 44.61%, indicated that to achieve an objective of NRC≥ 0.5 the most influential pore diameter range was 45≥ ∅ $$ \lt $$25.The increased number of jute fiber per unit area of felts from 55 to 430 resulted in narrowing of inter fiber spaces and consequently reduced the mean pore size. Further increase in number of fibers ultimately leads to blocking of spaces within fibers and get compacted like a solid fibrous mass.

Sepideh Hatamikia, Laszlo Jaksa, Gernot Kronreif et al.

Recently, 3D printing has been widely used to fabricate medical imaging phantoms. So far, various rigid 3D printable materials have been investigated for their radiological properties and efficiency in imaging phantom fabrication. However, flexible, soft tissue materials are also needed for imaging phantoms, which are used in various scenarios, such as anatomical deformations to improve dynamic treatments and various needle-based surgeries and training. Recently, various silicone additive manufacturing technologies have been used to produce anatomical models based on extrusion techniques that allow the fabrication of soft tissue materials. To date, there is no systematic study in the literature investigating the radiological properties of silicone rubber materials/fluids for imaging phantoms fabricated directly by extrusion using 3D printing techniques. The aim of this study was to investigate the radiological properties of 3D printed phantoms made of silicone in CT imaging. The radiodensity as described as Hounsfield Units (HU) of several test phantoms composed of three different silicone printing materials were evaluated by changing the infill density to adjust their radiological properties. A comparison of HU values with a Gammex Tissue Characterization Phantom was performed. A scaled down anatomical model derived from an abdominal CT was also fabricated and the resulting HU values were evaluated. For the three different silicone materials, a spectrum ranging from -639 to +780 HU was obtained on CT at a scan setting of 120 kVp. A good agreement was observed between the HU target values in abdominal CT and the HU values of the 3D-printed anatomical phantom in all tissues. Moreover, using different infill densities, the printed materials were able to achieve a similar radiodensity range as obtained in different tissue-equivalent inserts in the Gammex phantom (238 HU to -673 HU).