Fibers and Polymers最新文献

The dissolubility of electrospun chitosan nanofibers in aqueous environments is a matter of concern for the long-term water treatment application. In this study, chitosan was ionically crosslinked with a highly chemical stable polymer, sulfonated polyphenylsulfone (sPPSU), with aim of developing water stable electrospun nanofibers adsorbent for removal of an anionic dye, Congo red (CR). The morphology was characterized by electron microscopies, which showed high longitudinal uniformity nanofiber and fibrous orientation with no characteristic flaws on the surface of nanofibers. Additional studies for detecting changes in the surface wettability of the electrospun chitosan fibers by contact angle were performed, while TGA and DSC were used for determining the thermal stability and crosslinking phenomenon, respectively. To demonstrate the efficiency of the adsorbents, the dye removal rate is investigated as a function of pH, adsorbent dosage, and dye concentration. The optimal experimental conditions for achieving the best adsorptive behavior were 150 min for optimal time, 5 mg adsorbent dose, 10 ml dye solution volume, and 180 rpm shaker speed. The crosslinked chitosan nanofibers were regenerated over adsorption–desorption cycles to validate the favorable reusability. The obtained results revealed that the sPPSU crosslinked chitosan had excellent water-stability, and maximum anionic dye adsorption capacity (531.56 mg/g) according to the Langmuir model, and 371 mg/g was the actual adsorption ability. Additionally, the developed nanofibers showed an excellent reusability, exhibiting removal efficiency (~ 70%) after three consecutive adsorption–desorption cycles.

Poly(vinylidene fluoride) (PVDF) is widely used as a membrane material for applications such as filtration and water treatment due to its unique properties such as high mechanical strength, chemical resistance, ease of electrospinning, thermal stability, and high hydrophobicity. Using embedded organic and/or inorganic fillers, excellent separation efficiency and antifouling performance can be readily achieved. Among these fillers, metal–organic frameworks (MOFs) materials have drawn a lot of attention from researchers due to their variety and unique structures. These properties are further amplified when MOFs are at nanoscale. The synthesis of particles at this scale is challenging and only limited research has been published. With the help of electrospinning, nano-scaled ZIF-67 particles were grown on the surface of the PVDF fibers. In this work, the influence of solvents and ligand concentration on the morphology of the particles formed were evaluated. The morphology of the fibers was analyzed through SEM and the structural characterization was confirmed by XRD and FTIR, while the mass concentration of ZIF-67 was estimated by TGA. These materials are excellent candidates for applications such as textiles, filtration, and gas separation.

In this study, multiple-network hydrogels of polyacrylamide/gelatin/alginate were synthesized by photopolymerization method. In the study, the effect of the concentration of N,Nʹ-Methylenebisacrylamide, as a crosslinking agent, on hydrogels for use as wound dressings was investigated. For improving antibacterial, and wound-healing properties, salicylic acid was incorporated into the hydrogels. Results of this study showed that the novel multiple-network hydrogels exhibited adjustable mechanical properties, and desirable swelling capacities, making them good choices for wound dressing applications. Furthermore, the optimized formulation of the novel hydrogel, prepared with 0.025 gr of the crosslinking agent, revealed prominent characteristics including 2.93 ± 0.13 µm average pore size, 168.514% swelling percentage, 165 kPa tensile strength, 208 kPa Young’s modulus, and prolonged salicylic acid release. Finally, an antibacterial assay and cell scratch test of the optimized hydrogel showed a significant reduction in bacterial growth and complete closure of the wound within 24 h.

Hemp (Cannabis sativa L.) is an annual plant belonging to the Moraceae family. It is grown for its long and stronger fiber. Fabrics made from hemp fibers have obvious advantages over synthetic textiles. An effective attempt has been made to see the effect of scouring and bleaching on the physico-mechanical properties of the hemp fabric. In this study, sodium hydroxide was used for scouring and hydrogen peroxide was used for bleaching. After the scouring, it was found that the tensile strength of the fabric decreased, but elongation increased due to the removal of impurities and non-cellulosic components. Removal of non-cellulosic impurities enhanced the softness, compactness, and crease recovery angle of the fabric. After scouring, there was also a noticeable increase in the whiteness index. On the other hand, there was a significant increase in the whiteness index after bleaching, but the tensile strength and thickness decreased due to the acidic nature of hydrogen peroxide, which weakened and deteriorated the surface of the fabric, as confirmed by the result of Scanning electron microscopy. Furthermore, it was found that bleaching with a 5% concentration of H₂O₂ has an unfavorable impact on the physico-mechanical properties of the hemp fabric, whereas scouring with a 2% concentration of NaOH improves most of the physico-mechanical properties of the hemp fabric.

To address the low recognition accuracy and poor real-time performance of models in online fabric defect detection tasks, an efficient and compact fabric defect detection method, YOLOv7-tinier, is introduced in this paper. YOLOv7-tinier makes several key improvements to the YOLOv7-tiny model. First, it uses partial convolution to reconstruct the feature extraction module ELAN in the backbone network, reducing the number of parameters and extracting more diverse and hierarchical features and thus improving the detection accuracy and speed. Secondly, a new module called Dilated Spatial Pyramid Pooling Fast Cross Stage Partial Concat is proposed to replace the original Spatial Pyramid Pooling Cross Stage Partial Concat, further reducing the number of parameters and improving the computational efficiency. Finally, it introduces a convolution structure with attention mechanism SConv(Self-attentional convolution) to replace the ordinary convolution of the Neck part, and SBL and ELAN-S modules are constructed, which substantially enhances the network’s detection accuracy without significantly increasing the number of parameters. Extensive comparison and ablation experiments were conducted on the real fabric defect dataset. The experimental results show that under identical conditions, YOLOv7-tinier, our proposed model, achieved a 9.55% improvement in mean Average Precision (mAP) and a 10.81% reduction in parameters compared to the baseline YOLOv7 model, while maintaining a Frames Per Second (FPS) rate of 155.27 Hz. This model can meet both the accuracy and real-time requirements of fabric defect detection in textile manufacturing environments.

Advanced hybrid materials are in high demand across multiple engineering sectors like aviation, construction, automotive, and sports due to their improved specific strength, reduced weight, enhanced ductility, and favourable thermo-mechanical characteristics. The objective of this study is to improve the mechanical properties of fibre metal laminate (FML) using woven glass fibre and nano-alumina in a cost-effective hand layup process involving compressive action, which will result in a better interfacial mechanism between the laminates. The Final FML is comprised of woven glass fibre (GF) in quantities of 200, 400, and 610 GSM, combined with alumina (Al₂O₃) at 1, 3, and 5% weights, arranged in single, double, and triple layers bonded with epoxy resin, and then enclosed in aluminium alloy with a thickness of 0.8 mm. The actions of GF, Al₂O₃, and layering on tensile, flexural and impact strength of aluminium alloy-woven glass fibre-reinforced plastic (Al-GFRP) FML is studied. A triple layer makes the FML with 3 wt% of Al₂O₃ for 200, 400, and 610 GSM are recorded as maximum tensile, flexural and impact strength behaviour. More than 3 wt% of Al₂O₃ incorporated triple layer FML is recorded as reduced mechanical behaviour. Furthermore, the FML featuring triple-layer construction with 610 GSM glass fibre/3% Al₂O₃ and an aluminium alloy laminate demonstrates maximum tensile, impact, and flexural strength values of 258 MPa, 5.4 J, and 278 MPa, respectively. These conditions are conducive to the deep drawing process, which plays a crucial role in improving the formability and structural integrity of FMLs, thereby enhancing their overall performance and utilized for automotive roof frame applications.

Tires and conveyor belts are among the most prominent examples of cord-rubber composites in which, synthetic fibers are extensively used as reinforcing material. Although, it passes a long time from utilization of cord-rubber composites in rubber industry, yet, adhesion of cord to rubber remains an important challenge in this area, as it determines the quality of the final product. Accordingly, present work attempts to optimize adhesion of dipped Polyester/Polyamide 66 fabrics through identification and controlling of effective process parameters by the means of Design of Experiment (DoE). To accomplish this target, fractional factorial design, ({2}_{IV}^{7-2}), has been implemented with seven process parameters, namely, Styrene-Butadiene-Rubber (SBR) content, curing temperature and time, type and thickness of fabric, Dip Pick Up and type of adhesive in two variation levels. Subsequently, 32 experiments have been carried out through 4 blocks. Analyze of experiments showed that curing temperature and activation of fabrics/fibers before dip coating are the most important factors on adhesion of cord to rubber. The quality of fitting in applied model has been, eventually, checked using additional experiments. Pairwise Pearson Correlation coefficient demonstrated strong linear correlation between calculated data from the model and corresponding test results in laboratory.

The high prevalence of diabetes requires simple, continuous, and accurate monitoring of glucose level for diabetic patients in daily life. Recent researches have been geared toward flexible and wearable sensors to realize non-invasive detection and continuous glucose monitoring from body fluids, such as sweat, saliva, and tears. This review mainly summarizes the recent development of textile-based glucose sensors using silk, cotton, and synthetic polymers and fabrics as substrates and discusses their fabrication processes and working mechanism. In particular, the characteristics of these textile-based glucose sensors are analyzed and the sensing performances are compared. Based on this review, the challenges and prospects of textile-based glucose sensors are also proposed. Although the textile-based glucose sensors still have some problems, they show great application potential, which also presents new challenges and development directions for the application of the textiles.

In the present study, we fabricated nonwoven fabrics by melt-blowing (MB) with mixing polyethylene terephthalate (PET) and polypropylene (PP) fibers on a spinning line to improve the bulkiness and resistance under compression. That is, both PP and PET were simultaneously extruded from three nozzle holes laid down alternately, and they formed fiber state and then entangled each other during the whipping process. We investigated the effects of the MB manufacturing conditions, i.e., the hot air flow rate, the PET fiber fraction, and the presence or absence of annealing, on the compressibility of the obtained nonwovens. The fiber diameter histograms tended to split into two peaks as the PET fiber fraction increased. A larger PET fiber fraction produced a thicker nonwoven. Also, the compressibility increased, but the compression recovery rate did not. Annealing increased the thickness but decreased the compression recovery rate. Although thick fibers were increased by PET fiber mixing, they had insufficient rigid to resist compression. The decrease in the recovery rate can be explained by the brittleness of the PET fibers caused by crystallization of the non-oriented fibers during annealing.

Wearable electronics based on natural biocompatible fibers have attracted considerable interests due to the promising use for healthcare monitoring, human–machine interactions, and smart clothing. However, crucial challenges to design robust, flexible, and highly sensitive fiber sensors remain, to meet various requirements for practical application. Herein, Fischer esterification and in situ polymerization technologies were employed to produce conductive nanocelluloses (CNC–PEDOT), which possessed excellent mechanical stiffness and high conductivity (238 μS/cm). Then, silk yarns as supporting materials were functionalized by as-prepared conductive units to construct all-in-one fiber sensor (SCP) for multiple signals monitoring. Surprisingly, the resulted SCP fiber showed impressive mechanical performances (422.86 MPa at 18.44%), due to the strong hydrogen-bond interaction between SY substrate and CNC–PEDOT conductive units. More importantly, SCP fiber was employed a dual-function sensor for real-time monitoring of strain and temperature, illustrating remarkable sensitivities, i.e., gauge factor = 4.28 in a large strain range of 0–16%, and sensitivity = 1.55%/℃ in a broad temperature range of 25–60 ℃. The SCP fiber sensor with impressive mechanical performances and high sensitivity, can be applied for real-time health monitoring in wearable biosensors, smart healthcare, and on-demand therapy.