Electrical conductive and structural characterization of electrospun aligned carbon nanofibers membrane

In the paper, the membrane with aligned carbon nanofibers (CNFs) was prepared by electrospinning, stabilization and carbonization. The electrical conductivity of the membrane was examined. The effect of stabilization temperature and drum rotating speed on the conductivity of aligned CNFs membrane was discussed. The study on stabilization temperature showed that 250 °C was optimum parameter for preparing fibrous aligned CNFs membrane with uniform diameter, but 270 °C was benefit to fiber conglutination which could improve the electrical conductivity of the final CNFs membrane. The study on drum rotating speed showed that when drum rotating speed reached 2500 rpm, graphitic structures with parallel graphene sheets could be observed and 1000, 1500 and 2000 rpm CNFs membranes presented desirable conductivity with only 1.3 Ω·cm in the parallel directions and 2.0 Ω·cm in the perpendicular direction.     

Predicting the tensile strength of needle-punched nonwoven mats using X-ray computed tomography and a statistical model

As nonwoven mats are randomly oriented fiber assemblies, the tensile strength of nonwoven mats is determined by their microstructural factors, such as fiber orientation, fiber volume fraction, and fiber-fiber contact level. The complex microstructure of nonwoven mats must be reasonably simplified to properly predict their mechanical properties within affordable efforts. In this study, a new parameter, so called contact efficiency, is defined to describe the fiber-fiber contact level of nonwoven mats. Micro X-ray computer tomography (CT) is employed to characterize the microstructure of needlepunched nonwoven mats made of polypropylene short fibers. The fiber orientation and volume fraction are obtained by analyzing 2D sectional CT image of the nonwoven mat, while the contact efficiency is determined from 3D CT image. A statistical model, developed originally for staple yarns, is modified to predict the tensile strength of the nonwoven mat using the microstructural factors obtained from CT analysis. The prediction is then compared with experiments to validate that the current model incorporating the contact efficiency is highly suitable for predicting the tensile strength of nonwoven mats.     

Predicting tensile strength of yarns required for producing PET/Cotton blended woven fabrics of a pre-defined tensile strength

This study was aimed at developing statistical models for the prediction of tensile strength of warp and weft yarns required for attaining a pre-defined strength of PET/Cotton blended woven fabrics. The models were developed based on the empirical data obtained from carefully developed 234 fabric samples with different constructions using 15, 20, and 25 tex yarns in warp and weft directions. The prediction ability and accuracy of the developed models were assessed by correlation analyses of the predicted and actual warp and weft yarn strength values of another set of 36 fabric samples. The analyses showed a very strong ability and accuracy of the developed statistical prediction models.     

Empirical modelling of tensile strength of woven fabrics

Aesthetic properties of fabrics have been considered as the most important fabric attribute for years. However, recently there has been a paradigm shift in the domain of textile material applications and consequently more emphasis is now being given on the mechanical and functional properties of fabrics rather than its aesthetic appeal. Moreover, in certain woven fabrics used for technical applications, strength is a decisive quality parameter. In this work, tensile strength of plain woven fabrics has been predicted by using two empirical modelling methods namely artificial neural network (ANN) and linear regression. Warp yarn strength, warp yarn elongation, ends per inch (EPI), picks per inch (PPI) and weft count (Ne) were used as input parameters. Both the models were able to predict the fabric strength with reasonably good precision although ANN model demonstrated higher prediction accuracy and generalization ability than the regression model. The warp yarn strength and EPI were found to be the two most significant factors influencing fabric strength in warp direction.     

Fique fibers: Enhancement of the tensile strength of alkali treated fibers during tensile load application

Fique fibers were treated using Na(OH) solution at 5 w/v%, slack and under 1 N of tension, at room temperature, for 4 and 24 h respectively. Changes in their structure and composition were monitored using Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA) and X-ray diffraction (XRD). Additionally their mechanical properties were evaluated and analyzed. Results showed that tensile load application during alkali treatment improves their tensile strength and modulus. The most important change in mechanical properties was achieved in fibers treated for 24 h under tension. However, these fibers presented a high standard deviation; due to this treatment causing an important defibrillation. Moreover, fibers treated for 4 hours under tension, enhance their tensile strength around 56 %, while slack treated fibers improve only 38 %. When fibers were treated under tension, cellulose microfibrills were rearranged in the direction of tensile application and the spiral angle decreased, increasing the molecular orientation.     

Effect of hot-stretching on morphology and mechanical properties of electrospun PMIA nanofibers

Well-aligned PMIA nanofiber mats were fabricated by electrospinning and then hot-stretching along the fiber axis was used to improve the mechanical properties of nanofibers in this paper. Scanning electron microscopy (SEM), X-ray diffraction (XRD) and Differential scanning calorimetry (DSC) were used to characterize the morphology and properties of nanofibers. The results showed that the nanofibers became thinner and better alignment than the as-spun nanofibers after hotstretching, and the average diameter of the nanofibers decreased with the increasing of the tensile force. In the same time, hotstretching improved the crystallinity and T _g of the as-spun PMIA nanofibers. The tensile strength and modulus of the hotstretched nanofiber mats peaked at ca.50 % and ca.196 % respectively at the tensile force of 12 N compared with the as-spun nanofiber mats.     

Yarn formation of nanofibers prepared using electrospinning

In this study, the process of electrospinning was used on nanofiber yarn formation. The parameters in the study were flow rate and twist multiplier, which were discussed their effect on yarn formation. Further, a normal yarn was used as the core yarn, which was wrapped with nanofibers to form a new type of composite yarn. In this part of the experiment, the parameters were flow rate and collector width, which were discussed in terms of their effect on the yarn quality of nanofibrous composite yarn. The experiment result showed the diameter of the nanofiber was between 220 nm to 260 nm. When the collector width was 5 mm, there was a high quality wrapping resulting in good yarn, with the nanofiber composite yarn having a strength of 3.25 (cN/dtex).     

Predicting the tensile strength of polyester/cotton blended woven fabrics using feed forward back propagation artificial neural networks

Tensile strength plays a vital role in determining the mechanical behavior of woven fabrics. In this study, two artificial neural networks have been designed to predict the warp and weft wise tensile strength of polyester cotton blended fabrics. Various process and material related parameters have been considered for selection of vital few input parameters that significantly affect fabric tensile strength. A total of 270 fabric samples are woven with varying constructions. Application of nonlinear modeling technique and appreciable volume of data sets for training, testing and validating both prediction models resulted in best fitting of data and minimization of prediction error. Sensitivity analysis has been carried out for both models to determine the contribution percentage of input parameters and evaluating the most impacting variable on fabric strength.     

Weibull distribution analysis of the tensile strength of the kenaf bast fiber

This paper presents the influence of the gage length on the kenaf fiber Young’s modulus and the tensile strength characterization. Four different gage lengths of 10 mm, 15 mm, 20 mm and 25.4 mm are selected in this study and the tensile testing is performed at a quasi-static loading rate of 1 mm/min. The cross-sectional area of the fiber after failure is considered for the stress calculations. Weibull probability distribution is used to characterize the tensile strength of the kenaf fiber. The Weibull parameters are obtained for the two parameter, three parameter and Weibull of Weibull models and the average tensile strength of the fibers are evaluated. The predicted average tensile strength from all the three approaches are in good agreement with the experimental results for the obtained parameters.     

Selection of yarn for the predefined tensile strength of cotton woven fabrics

In order to meet the required strength of a fabric, selection of yarn is difficult because tensile strength of woven fabric depends upon a number of factors. Still, the manufacturers have to use hit and trial method in order to select the yarn for the required tensile strength of fabric. This study was carried out to develop regression equations for the prediction of yarn tensile strength suitable for the predefined strength of cotton woven fabrics. These equations were developed by using empirical data obtained from two hundred and thirty four fabric samples prepared under a systematic plan with different constructions. Prediction proficiency and precision of these regression equations were evaluated by correlation analysis of the predicted and actual warp and weft yarn strength values of another set of thirty six fabric samples. The results show a very strong prediction precision of the equations.     

Relationship between chemical composition,crystallinity, orientation and tensile strength of kenaf fiber

The physical properties of natural growth fibers such as chemical composition content and fiber diameter are highly affected by environmental issues such as environmental changes and fiber extraction methods. These irregularities of the natural fibers seriously affect its utilization in composite as reinforcements. In this study, taking into account the importance of the fiber tensile strength, the correlation degrees between the kenaf fiber tensile strength and the fiber chemical composition, crystallinity, orientation degree were analyzed by the grey relational analysis method. Both the kenaf single fiber and fiber bundle were used as XRD and tensile strength test sample. The chemical composition content and the FTIR were carried out to obtain a correct result of the chemical composition content. It found that for the different XRD and tensile strength test samples, the single fiber showed lower crystallinity, higher orientation degree and tensile strength compared with the fiber bundle. The cellulose content and the orientation degree got the higher correlation degree with single fiber tensile strength, which was 0.674 and 0.640. The highest factor associated with the fiber bundle tensile strength was the orientation degree, the correlation degree was 0.747. The hemicellulose content and the crystallinity also got high correlation degree with the fiber bundle strength, which was 0.687 and 0.640.     

Prediction of diameter in blended nanofibers of polycaprolactone-gelatin using ANN and RSM

Fabrication of nanofibers with a defined diameter is a primary purpose of the electrospinning process. The diameter of nanofiber is directly related to its individual features, such as mechanical property and porosity. The motivation to conduct the current study was to explore the diameter of hybrid nanofibers of polycaprolactone-gelatin (PCL-GT) as one of the most attractive scaffolds employed in various research fields, such as tissue engineering and industrial fields. We have developed two predictive models describing the electrospinning process of PCL-GT using response surface methodology (RSM) and artificial neural network (ANN). The effect of 4 variables on diameter was analyzed, including total polymer concentration, ratio of PCL to Gel, voltage, and tip-to-collector distance. The individual and interactive effects of the mentioned factors were analyzed using RSM. The total polymer concentration had the most significant individual effect on the diameter of PCL-Gel nanofiber, whereas the other three factors showed less strong individual effects, although, the interactive effects of these factors were more remarkable. It was demonstrated that both models, especially the ANN model, could accurately predict the diameter of PCL-GT nanofiber (regression coefficient > 0.92, mean absolute percentage error < 5.7). The represented predictive models could facilitate construction of electrospun nanofibers from PCL-Gel with wellcontrolled diameter required for any intended purpose.     

Fabrication of electrospun antimicrobial nanofibers containing metronidazole using nanospider technology

Nanospider technology as a modified electrospinning technique was used for the fabrication of electrospun nanofibers based on poly(vinyl alcohol) (PVA)/poly(ethylene oxide) (PEO) blend as drug delivery system (DDS) for metronidazole (MTZ) as an antimicrobial drug. Electrospun PVA/PEO/MTZ composite nanofibers were stabilized against disintegration in water by heating in oven at 110°C, or by soaking in isopropyl alcohol for 6 hrs. Incorporation of MTZ into electrospun nanofibers was confirmed by SEM, FT-IR spectra and TGA. The drug release results showed that the burst release was suppressed with stabilized electrospun nanofibers compared with non-stabilized ones. Electrospun PVA/PEO/MTZ composite nanofibers exhibited remarkable antimicrobial activity against Escherichia coli, Pseudomonas aeruginosa, Aspergillus niger, Penicillium notatum and Aspergillus flavus which varies with the species of the tested organisms.     

Synthesis,analysis and simulation of carbonized electrospun nanofibers infused carbon prepreg composites for improved mechanical and thermal properties

This paper reports the fabrication, characterization and simulation of electrospun polyacrylonitrile (PAN) nanofibers into pre-impregnated (prepreg) carbon fiber composites for different industrial applications. The electrospun PAN nanofibers were stabilized in air at 270 °C for one hour and then carbonized at 950 °C in an inert atmosphere (argon) for another hour before placing on the prepreg composites as top layers. The prepreg carbon fibers and carbonized PAN nanofibers were cured together following the prepreg composite curing cycles. Energy dispersive X-ray spectroscopy (EDX) was carried out to investigate the chemical compositions and elemental distribution of the carbonized PAN nanofibers. The EDX results revealed that the carbon weight % of approximately 66 (atomic % 72) was achieved in the PAN-derived carbon nanofibers along with nitrogen and lower amounts of nickel, oxygen and other impurities. Thermomechanical analysis (TMA) exhibited the glass transition regions in the prepreg nanocomposites and the significant dependence of coefficient of thermal expansion on the fiber directions. The highest value of coefficient of thermal expansion was observed in the temperature range of 118-139 °C (7.5×10^-8 1/°C) for 0 degree nanocomposite scheme. The highest value of coefficient of thermal expansion was observed in the temperature range of 50-80 °C (37.5×10^-6 1/°C) for 90 degree nanocomposite scheme. The test results were simulated using ANSYS software. The test results may be useful for the development of structural health monitoring of various composite materials for aircraft and wind turbine applications.     

Characterizing the tensile properties of spun yarns using bivariate normal distribution

The tensile properties of spun yarns decisively influence its performance in various mechanical processing stages. This study is primarily aimed at simultaneous analysis of two tensile properties of spun yarns namely tenacity and breaking strain, which play crucial role in determining the frequency of warping breaks. The threshold values of yarn tenacity and breaking strain required for 20’s Ne carded cotton yarn to sustain the imposed stresses and strains during warping process have been determined using a bivariate normal distribution model. This study opens up the possibility of minimizing end breakage rate in various manufacturing processes of textile industry by engineering of spun yarns devoid of potential weak spots which are responsible for breaks.     

Flexible VOC sensors using conductive polymers and porous membranes for application to textiles

In order to fabricate textile-based flexible VOC sensors, two conductive polymers such as polyaniline and poly(3,4-ethylenedioxythiophene)-poly(styrene-sulfonate) (PEDOT:PSS) were used as VOC-sensing materials, and various porous organic membranes were used as base substrates on which the conductive polymers were coated. Electrical resistance change of conductive polymers by adsorption of VOCs was measured. Polyaniline showed better sensitivity than PEDOT:PSS. Porous high density polyethylene membrane exhibited the most stable signal reproducibility and dimensional stability of membrane itself. Even after covering with additional high density polyethylene membrane to protect conductive polyaniline inside, the stable signals were still obtained during repeated measurement.     

Moisture absorption effect on thermal, dynamic mechanical and mechanical properties of injection-molded short glass-fiber/polyamide 6,6 composites

Polymer composites of polyamide 6,6 reinforced with short glass fiber were prepared by injection molding, conditioned under dry, 50 % relative humidity and wet. Investigations by DSC, DMA and tensile tests were conducted. FLD study showed that more fiber degradation occurred during processing of the composites with higher fiber loading. DSC analysis revealed that the incorporation of glass fiber and moisture into the PA 6,6 matrix resulted in a remarkable decrease in the degree of crystallinity. DMA results revealed the glass transition temperatures were sensitive to moisture absorption and their values moved to a lower temperature upon exposure to moisture. Incorporation of glass fiber into the polyamide 6,6 gave rise to a significant improvement in tensile modulus and tensile strength, while tensile strain was reduced. Exposure to different environments from dry to wet conditions resulted in a decrease in the strength and modulus, while tensile strains decreased.     

Influence of the core-sheath weight ratio and twist on the tensile strength of the ring core yarns with high tenacity filaments

Core spun yarns are applied for various purposes that especially require the multi-functional performance. This research reports on the core spinning effect on the yarn strength. We prepared various core yarns by combining different kinds of high tenacity filaments in core with cotton staples in sheath with various twist levels in the ring spin system. And the tensile strength was tested to investigate the contribution of the core-sheath structure to the core yarn strength. The influence of the twist level was also checked up on the relationship between the core-sheath structure and the yarn strength. Results turned out that the core-sheath weight ratio had influence on the tensile properties of the ring core-spun yarns in different ways according to the core filaments used for the yarn. Increasing the twists yielded a monotone decreasing strength for the aramid and the basalt core yarns, while the PET core yarns showed almost unchanged strength, which could be ascribed to the extensional property of the filaments.     

Mechanical properties,morphology and dynamic mechanical properties of LGF/TPU/SAN composites

A series of the long glass fiber reinforced thermoplastic polyurethane elastomers and poly (styrene-acrylonitrile) (LGF/TPU/SAN) composites with different contents of long glass fiber were prepared by using self-designed impregnation device. Dynamic mechanical properties of TPU/SAN matrix reinforced with 10, 20 and 30 % by weight long glass fibers have been investigated by using dynamic mechanical thermal analysis (DMA). The results indicated that the content of long glass fiber and scanning frequency had some influence on dynamic mechanical properties and glass transition of LGF/TPU/SAN composites. In addition, the Arrhenius relationship has been used to calculate the activation energy of a-transition of the LGF/TPU/SAN composites. SEM demonstrates the relatively good dispersion of the long glass fiber in the TPU/SAN matrix. In addition, Effects of the content of long glass fiber on mechanical properties of the LGF/TPU/SAN composites are investigated.     

The preparation and characterization of conductive poly(ethylene terephthalate)/polyaniline composite fibers using benzoyl peroxide

Conductive polyaniline (PAn)/poly(ethylene terephthalate) (PET) composite fibers were prepared by chemical polymerization of aniline in the presence of PET fibers using benzoyl peroxide (Bz₂O₂) in organic solvent/aqueous hydrochloric acid mixtures. The effects of polymerization conditions such as organic solvent/water ratio, oxidant, aniline and hydrochloric acid concentrations and temperature were investigated on the amount of PAn deposited on PET fiber and the electrical surface resistance of composite fibers. The maximum PAn content and the lowest electrical surface resistance of composite fibers were observed at HCl concentrations of 0.5 mol L⁻¹. The properties of PAn/PET composite fibers such as density, diameter, tensile strength and breaking elongation were also investigated in comparison with those of pure PET. Characterization of conductive composite fibers was carried out by FTIR, TGA, SEM techniques, surface resistance measurements, and cross section images taken by optical microscope.