Shape Of Yarn Research Articles

Characterization of 3D-printed filament yarns using various parameters

Smart clothing refers to clothing that is enhanced with technology to add functionality beyond its traditional use. It capable of perception and response it can mimic the characteristics of living systems. Conductivity in textiles is essential for smart clothing because electrical conductivity provides pathways for carrying information or energy for various functions. Textile conductivity can be imparted at various stages. Conductive polymers, fibers, yarns, fabrics, embroidery, and finishing are vital for the construction of smart clothes. most smart materials, electronic sensors or actuators are used to integrate the desired interactions with the environment. Typical textile methods, such as sewing, necessitate the adequate construction of electronic components, for example, by first soldering an electronic component on a flexible substrate with holes that can then be used for a sewn connection to a conductive yarn in a textile fabric. Most currently commercialized 3D printing processes involve fused deposition modeling (FDM) methods, which extrude thermoplastic filaments through nozzles. This process is similar to melt spinning, and modeling to print lines using one layer can yield a filament yarn shape. 3D printing outputs molten polymers by discharging thermoplastic filaments though a nozzle by an extrusion process. This method is similar to melt spinning. Currently, various types of materials are used in 3D Printing, However not all of these materials are suitable for textile applications. In addition, dogbone-type outputs were used to evaluate physical properties in previously reported studies in which the parameters of existing 3D printing were changed. but unlike filament-type outputs, dogbone-type outputs are composed of multiple layers rather than single layers. therefore, their properties are different from those of single-layer filament outputs. This study, as a basic study to develop smart textiles using 3D printing, herein we aimed measuring and analyzing the impact of conditions like printing speed and nozzle temperature on the surface structure, crystallinity, and mechanical properties of the outputs. Therefore, unlike dogbone-type sample forms, which have been used in many previous 3D-printing property evaluation studies, there is no adhesion between layers as the temperature increases. Therefore, the physical properties do not increase. This study entailed research to develop smart textiles using FDM-type 3D printing. A follow-up study that aims to evaluate the 3D printing spinning properties that combine extrusion 3D printing and melt spinning spools is underway.

Highly stretchable conductor with elastomeric passivation sheath enabling applications in harsh conditions

The rapid development of robotics requires stretchable electrical conductors capable of large deformations and having high operational stability in terms of electrical and mechanical characteristics. Carbon nanotubes (CNT) have been considered as the primary component of stretchable conductors, and mechanically drawn CNT sheets have shown their functionality when combined with various elastomeric materials in the shape of yarns. Herein, an electrically passivated stretchable conductor with an elastomer sheath and a spandex–CNT coiled-yarn core structure is reported. Based on the proven performance of spandex–CNT coiled-yarn, the electrical insulation by the Ecoflex elastomer enhances its applicability in an actual situation without degrading the stretchable conductor functionality. The experimental results show a substantial working deformation range (up to 350%), high durability, and low resistance variation during repetitive stretch and release cycles. Additionally, its stability is confirmed over a wide temperature range (up to 150 °C) and even inside an acidic liquid environment where the elastomeric sheath protects the conducting core. The perfect cooperation between the Ecoflex sheath and spandex–CNT core opens the possibility of deploying this stretchable conductor technology under harsh conditions.

Preparation and Lithium-Ion Capacitance Performance of Nitrogen and Sulfur Co-Doped Carbon Nanosheets with Limited Space via the Vermiculite Template Method.

Nitrogen and sulfur co-doped graphene-like carbon nanosheets (CNSs) with a two-dimensional structure are prepared by using methylene blue as a carbon source and expanded vermiculite as a template. After static negative pressure adsorption, high-temperature calcination, and etching in a vacuum oven, they are embedded in the limited space of the vermiculite template. The addition of an appropriate number of mixed elements can improve the performance of a battery. Via scanning electron microscopy, it is found that the prepared nitrogen-sulfur-co-doped carbon nanosheets exhibit a thin yarn shape. The XPS results show that there are four elements of C, N, O, and S in the carbon materials (CNS-600, CNS-700, CNS-800, CNS-900) prepared at different temperatures, and the N atom content shows a gradually decreasing trend. It is mainly doped into a graphene-like network in four ways (graphite nitrogen, pyridine nitrogen, pyrrole nitrogen, and pyridine nitrogen oxide), while the S element shows an increasing trend, mainly in the form of thiophene S and sulfur, which is covalently linked to oxygen. The results show that CNS-700 has a discharge-specific capacity of 460 mAh/g at a current density of 0.1 A/g, and it can still maintain a specific capacity of 200 mAh/g at a current density of 2 A/g. The assembled lithium-ion capacitor has excellent energy density and power density, with a maximum power density of 20,000 W/kg.

Rapid prediction model of effective thermal conductivity of plain weave fabric in space environment

The prediction of effective thermal conductivity of aerospace insulation materials is crucial for insulation design and radiation characteristics control of space targets. In this paper, a rapid and accurate prediction model is proposed for the effective thermal conductivity of plain weave fabrics in space environments. This model assumes that the cross-sectional shape and bending degree of yarns within aerospace fabrics remain unchanged. To represent the structural characteristics of the plain weave fabric, a dimensionless parameter called "f" is defined. Numerical simulations are conducted to investigate the effects of fabric structure, temperature, and yarn thermal properties on the effective thermal conductivity of multilayer fabrics. Three parameters are identified as the most influential factors for the effective thermal conductivity of plain weave fabrics: the structural parameter f, and the axial and radial thermal conductivities of yarns. Based on extensive simulation data, an empirical equation is proposed for the rapid prediction of the effective thermal conductivity of plain weave fabrics. Moreover, polyester, cotton, and wool plain weave fabric samples are tested for their thermal conductivity in a vacuum environment. The predicted results from the empirical equation proposed in this study exhibit a deviation of less than 6 % when compared to experimental measurements. This study can provide valuable insights for the design of plain weave fabrics used in aerospace insulation materials.

Visual similarity simulation of slub denim based on image processing

The slub denim has various appearance styles that attract consumers due to the irregular distribution and long cycle of the slubs in the slub yarn. This characteristic of the slub yarn makes the slub denim proofing that relies on artificial visual contrast time-consuming with a long design cycle. A visual similarity simulation method was proposed for slub denim based on slub yarn images to solve this problem. At first, the yarn images were pre-processed by grey-level transformation, image threshold segmentation, and morphological operations to obtain the yarn core images. Secondly, according to the elastic change of yarn in fabric structure, the elliptic and sine curve models were established to treat the string to obtain the actual yarn shape in the fabric. Then, a light intensity curve function, which consists of a radial curve model and an interlacing point curve model, was established to simulate the light intensity distribution on the yarn surface. Finally, the cover relation of warp and weft yarns was controlled by Boolean matrix, and mean filtering was used to adjust the fuzzy denim fabric images. The experimental results show that the slub denims simulated by the method proposed in this article have a high visual similarity with the actual slub denims. Meanwhile, multiple parameters of the simulation model established in this article can be adjusted to enhance the adaptability of the model and the accuracy of the simulation results.

Effect of weave structures and thread densities on the cover factor and mechanical properties of cotton spandex woven fabrics

The aim of this article is to investigate the effect of weave structures and thread densities on the cover factor and mechanical properties of cotton spandex woven fabrics. 98% cotton and 2% spandex poplin, twill, and sateen woven fabrics of different thread densities were used in this research for investigation. In this investigation, total samples of 15 types with miscellaneous textures such as plain (1/1), twill (1/4), and 7 ends sateen (1/6) were used. Yarns were assessed using microscope with its morphological views and outer shape views to confirm the existence of cotton fibers. In the microscopic observations, the outer shape of cotton yarn was seen with full of hairy fibers at the slope which guaranteed the existence of cotton content in these cellulosic fabrics. The stretching behaviors such as stretch, growth and recovery were measured in agreement with the test method provided by ASTM D3107 Standard along with apposite equations as mentioned underneath the paper. Using weave coefficient, the values of cover factors were measured with suitable equations. The fabrics of plain weave exposed the highest values of cover factors due to having higher interlacement points than any other weave structures conducted in this research. The fabrics of sateen weave exposed excellent mechanical properties with its stretch, growth and recovery values due to having fewer binding points in its repeat size, than any other weave structures carried out in this research. This research is practice based and it opens possible ways for the scholars to further study in this field.

Real meso-scale model reconstruction and tensile failure prediction of 3D braided PIP-SiCf/SiC composites considering pore defects

• A combination of parametric and statistical methods is proposed for the real meso-scale model reconstruction. • The finite element model of 3D6d braided SiCf/SiC composite considering yarn shape and pore defects is established. • To predict well the material tensile properties and failure mechanisms, the effect of the fiber damage and pore defects is considered. • The simulation values and damage modes are consistent with the experimental ones when the damage factor of the fiber bundle is 0.8. This paper presents the real meso-scale model reconstruction and tensile failure prediction of three-dimensional six-directional (3D6d) braided precursor impregnation and pyrolysis (PIP) SiC f /SiC composites. A combination of parametric and statistical methods is proposed, and the real meso-scale finite element model considering yarn shape and pore defects is built. The damage factor is introduced into the mixing law and the progressive damage model is developed. The results reveal that the simulation values and damage modes are consistent with the experimental ones when the damage factor is 0.8. In detail, the predicted errors of modulus, stress and strain are 3%, 9% and 5%, respectively. The main damage modes of 3D6d braided SiC f /SiC composites are braiding yarn shear fracture, fifth yarn tensile fracture, and matrix cracking. Furthermore, the initial damage firstly appears in the braiding yarn, and when the load is near the maximum value, the fifth yarn and matrix also occur the damage.

A mesoscale tensile model for woven fabrics based on Timoshenko beam theory

The yarn weave architectures highly influence the mechanical response of woven fabrics. To provide an accurate prediction of the mechanical behaviors of woven fabrics under tension, a mesoscale model is developed. The model takes into account yarn properties, yarn weaving pattern, and interactions between yarns. The yarn properties such as tensile modulus and yarn strength of yarns are considered as random variables. Each yarn in fabric is modeled as a Timoshenko beam with a weaving shape modeled by a parabolic function. The yarn shape evolution and mechanical response of undulated yarn under tension are computed based on Castigliano’s second theorem. The damage initiation and propagation of a yarn in fabric is introduced through a damage variable. The model is demonstrated on woven jute fabrics. Analytical and numerical analyses are carried out and show good prediction on the macroscopic tensile response of woven jute fabric. The model provides a quantitative understanding between yarn geometrical parameters and the expected material response, and makes it helpful for designing woven structural composites with high performance.

Changing the shape of wool yarns via laccase-mediated grafting of tyrosine

The shape of wool yarns was changed by laccase-assisted grafting of tyrosine. Prior to tyrosine grafting a cysteine pre-treatment was optimized aiming to increase the amount of thiol reaction groups available. The best operational conditions for laccase-assisted tyrosine grafting were: i) pre-treatment with cysteine (2.2 mM) in a solution of 20 % ethanol, 15 % propylene glycol and 0.5 % benzyl alcohol, pH = 10, 40 °C; ii) tyrosine grafting with 3.0 mM tyrosine, 18 U/mL laccase, pH = 5, 40 °C. The shape modification was evaluated by number of curly twists determination on the grafted yarn samples. The thermal and mechanical properties of the grafted wool yarns was evaluated by TGA, DSC and breaking strength determination. The amount of free thiols and weight gain were assessed aiming to infer the role of the cysteine pre-treatment on the final tyrosine grafting and shape modification. The laccase-assisted grafting of tyrosine onto wool yarns have influenced the thermal and mechanical properties of the yarns however without compromising their structural integrity for the final application purposes. The developed methodology to impart new shape to wool yarns is presented herein as an environmentally friendly alternative to chemical methods. The new findings revealed great potentialities for application in similar fibers like hair.

Modeling method of irregular cross section annular axis braided preform based on finite element simulation

The irregular cross section annular axis braided preform is modeled by using finite element simulation instead of geometric modeling. The braiding process is simulated by using a finite element software to obtain the yarn path. And the braided preform is modeled by using nine virtual fibers to form irregular cross section shape of yarn. Meanwhile, a modified vertical braiding machine is used to braid the actual preform, to compare with results from the simulation model. The results show that the simulation model is consistent with the actual braided preform, braiding angle is about 36°, and yarn spacing is about 6 mm. The finite element method can predict the yarn path more accurately without the need of complex analysis and derivation, especially when the irregular mandrel is used for braiding. In addition, the cross-section shape of yarn composed of virtual fibers can be used to achieve a more realistic simulation result. FEM is an efficient simulation method, and can also provide an effective basis in studies of the actual cross-sectional shape of yarn and the properties of its composite reinforcements.

Flat Yarn Fabric Substrates for Screen‐Printed Conductive Textiles

Herein, flat yarn‐based polyethylene terephthalate (PET) fabrics as substrates for screen printing conductive inks are described. The effect of the screen‐printing parameters, such as the screen mesh size (70 or 120 pixels in.−1) and the number of printing cycles, is investigated. The uniformity of the screen‐printed layers and their electrical properties are directly related to the yarn shape, substrate roughness, and printing conditions. Minimum average sheet resistance of 16 ± 3 mΩ sq−1 is achieved on the flat yarn PET fabrics, and there is little change in the electrical performance after 1000 bending cycles. To demonstrate the impact of yarn shape on an E‐textile application, wearable antennas are fabricated using the screen‐printed PET fabrics. The antennas are designed to operate at 2.4 GHz, which is a widely used unlicensed frequency for public wireless local area network services, Bluetooth, and radio frequency identification (RFID) services. The effects of the uniformity and conductivity of the printed layers on the antenna performance are analyzed. In open‐area field tests, the textile antennas show better performance than commercial antennas. The results of this study will help improve the understanding of how the ink/substrate interface affects the screen‐printing process and to advance the manufacturing technology for conductive patterns.

Meshfree-based micromechanical modelling of twill woven composites

This paper presents a novel, meshfree-based micromechanical model for homogenising the elastic properties and analysing the deformation and microscopic strains/stresses of twill woven composites. The proposed model was based on a minimum unit cell (mUC) whose internal features such as the cross-sectional shape and waviness of yarns were described by using sophisticated functions. The boundary conditions imposed on the mUC were derived by applying an equivalence approach, which converts the standard form of periodic boundary conditions into a generic set of fixed and relative displacement constraints. Theoretical formulations were developed to implement the micromechanical model within the framework of the moving kriging (MK)-based element-free Galerkin (EFG) method. An in-house computer program implementing the proposed model was developed for analysing a typical twill woven composite. Good agreements were found between the meshfree-based predictions and the reference results, highlighting the proposed model capable of homogenising twill woven composites and meanwhile avoiding the commonly required pre-processing tasks such as building an explicit geometry model and generating identical meshes on the mapping surfaces to enforce boundary conditions. Three case studies were also performed to identify the sensitivities of the predicted results to three numerical parameters, i.e. the total number of field nodes, the total number of background cells, and the support domain scaling factor. The results of these studies suggest that the numbers of field nodes and background cells used must be sufficiently large, while the support domain scaling factor in an appropriate range (e.g. 2.0−3.25) to achieve convergent results.

Spatial modelling of 3D woven variable thickness composite plate at the mesoscopic scale

The geometric details of variable thickness 3D woven composite plate, which features varying weft yarn cross section shapes and sizes at each layer and resulting diverse warp yarn path orientations, are quite different from the structure in constant thickness plate. A geometric model to handle these variances is presented in this paper which no doubt can also be used in constant thickness plate. Based on the idealized assumptions that the cross section shape of weft yarn is lenticular and warp yarn is rectangular, the inner structure details of variable thickness plate are illustrated in the efficient geometric model with weaving parameters and some measurements as input data. Two 3D woven sample materials are produced to confirm the accuracy of the proposed geometric model. Even though the idealizations in geometric model lead to some over predictions, the model still captures the majority of details in corresponding real sample architectures.

Effects of spinning process and core yarn contents on yarn shape retention

Purpose In order to develop high shape retention yarn and investigate the effects of spinning process and core yarn contents on the shape retention of yarn, in this paper, three kinds of yarns, JC/T400 18.5tex (55.6dtex) core-spun yarn, JC/T400 18.5tex (44.4dtex) core-spun yarn and JC18.5tex pure cotton yarn were spun by using the complete condensing Siro-spinning technology. The paper aims to discuss these issues. Design/methodology/approach In this paper, the core-spun yarns were spun by using the complete condensing spinning and Siro-spinning technology. Two key spinning processes, yarn twist factor and core yarn pre-draft ratio, were optimized by using the orthogonal test method first. Then, via the variable control method, the position of the core yarn, the position of the bell mouth and the center distance between two bell mouths were optimized, respectively, and corresponding optimal spinning process of the three yarns was determined. Finally, the yarns were spun under the optimal process, and the performance of the spun yarns was tested and compared. Findings Results show that the yarn twist factor affects yarn strength and hairiness, the position of bell mouth affects the evenness and hairiness of the yarn mainly, and the position of the core yarn affects the coverage and hairiness of the yarn. For the Z-twist spinning, the core yarn enters the front roller from the left side of two strands center, which is beneficial to improve the covering effect of core yarn, and reduce the pilling phenomenon of the yarn. The contents of core yarn affect indicators of the yarn shape retention, such as yarn strength, elastic recovery and abrasion resistance. Originality/value The shape retention of yarns affects the shape retention of fabrics, and the production of yarn with high shape retention is a key step in achieving shape retention of fabrics. At present, there are little studies on the shape retention of yarns, most researchers shave focused on shape retention of fabrics. Using the complete condensing Siro-spinning method to spin the core-spun yarn can improve the quality of the yarn. Compared with traditional ring-spinning yarns, the addition of the core yarn can improve the shape retention of the yarn.

Study on Interlaminar Shear Properties of SiO2f/SiO2 Composites Based on Different Braided Structures

The interlaminar shear properties of SiO2f/SiO2 composites reinforced by needle-punched and 2.5D braided preforms are studied and analyzed. The effects of different temperatures and braiding structures on the interlaminar shear strength were investigated by analyzing the stress curves, macrostructure and microstructure of the composites. The increase of temperature, in a certain range, will change sintering condition of matrix and the bonding between matrix and interface, and thus increase the interlaminar shear strength. Because of the different shape of warp and weft yarn, there is a considerable discrepancy in the interlaminar shear strength of different direction. The interlaminar shear strength of needle-punched braided SiO2f/SiO2 composites is a little higher than the warp direction of 2.5D braided SiO2f/SiO2 composites. The interlaminar shear strength, time and economic cost should be considered comprehensively to select a more suitable braiding structure.

Synergetic design of enlarged surface area and pseudo-capacitance for fiber-shaped supercapacitor yarn

In various wearable energy storage devices, the shape of fiber or yarn has many advantages owing to their compatibility with the environment in which they are deployed. We present a systematic approach to maximizing the capacitance of a supercapacitor yarn by significantly increasing the yarn's surface area by growing a high density of nanorods around the yarn, followed by coating the surface with a pseudo-capacitive material. The two-step strategy is implemented using a dry-spun carbon nanotube yarn-based electrode, which is surrounded by a zinc oxide nanorod forest that is coated by a pseudo-capacitive nickel-cobalt layered double hydroxide material. The flexible as-prepared electrode exhibits a maximum capacitance of 1065 mF cm−2 (1278 F g−1) at a scan rate of 5 mV s−1 and an excellent capacitance retention of 60.5% over 7000 cycles at a current density of 30 mA cm−2. The outstanding performance of the composite yarn supercapacitor can be ascribed to the enhanced ion accessibility to the deep surface of the nickel-cobalt layered double hydroxide layer through the porous carbon nanotube yarn. Furthermore, the symmetric supercapacitor configuration demonstrated nearly 100% capacity retention at a bending angle of 150°.

Stochastic modeling techniques for textile yarn distortion and waviness with 1D random fields

Within the concept of simulation approaches for manufacturing-induced imperfections of composite structures, this work proposes modeling frameworks for the consideration of stochastic deviations concerning the yarns of textile composite materials. The random distortion of a yarn’s cross-section, is addressed by flexible 1D Fourier-based random fields, with the potential to be calibated from measurements of the deviations from the nominal yarn shape and their statistical characteristics. Furthermore, a Kriging-based modeling approach is presented, able to randomize any nominal yarn path in short or long range problems, considering data for the correlation and variance in a straightforward manner. The effects of defects due to stochastic yarn distortion and waviness, are investigated by simulating a forward uncertainty propagation problem of a triaxially braided composite material. The response variability concerning stiffness and strength for different uncertainty levels is highlighted, while several comments are offered regarding numerical issues and potential surrogate modeling techniques.

Automatic Construction of Digital Woven Fabric by Using Sequential Yarn Images

Abstract In this article, a computerized method is proposed for simulating digital woven fabric (DWF) based on sequential yarn images captured from a moving yarn. A mathematical model of woven fabric structure is established by assuming that the crimped shape of yarns in weave structure is elastica, and the cross-sections of yarn in sequence image and fabric are circular and ellipse, respectively. The sequential yarn images, which are preprocessed and stitched first by image processing methods, are resized based on the mathematical model. Then a light intensity curve, which consists of radial curve model and axial curve model, is used to simulate the gray texture distribution of interlacing points in radial and axial directions. Finally, a Boole Matrix model is used to control the woven pattern. In the experiment, a slub yarn and a normal yarn samples with same count are applied to simulate gray texture fabrics. Then the gray fabrics are transformed to color fabrics based on three color maps. The fabric simulations are confined to single fabrics of plain, 2/2 matt, and 1/3 twill weaves.

A study on the suitability of which yarn number to use for recycle polyester fiber

Recycling and reuse of materials is not new to the textile and apparel industry. Recycling refers to the breakdown of product into its raw materials in order for the raw material to be reclaimed and used in new products. The aim of the study is that the examining the usage of recycle polyester fiber (rPET) in different yarn count and blend ratio and so to determine which count and blend ratio is more suitable for rPET usage. For this aim, 24 yarns containing recycle polyester fiber, virgin polyester fiber and viscose fiber as raw material were obtained in different yarn counts which are Ne 10, Ne 20, Ne 30 and Ne 40, and in different blend ratios. Yarn diameter, density, shape (roundness), unevenness, imperfection, hairiness, and yarn tensile tests were applied to the obtained yarns. The findings obtained by experimental and statistical study show that rPET fiber has usually negative effects on the yarn properties in especially fine yarns due to physical and chemical deterioration caused by contaminants of during re-processing of recycle polyester fiber. Based on the findings it is revealed that the values of unevenness, imperfection, and density increase whereas the values of diameter, hairiness, and tensile decrease from coarse yarns to fine yarns. As a conclusion it is possible to say that rPET fiber is suitable for thick yarns which are especially Ne 10 and Ne 20 as pure and in all blend ratios, and rPET fiber is suitable if it is used in lower ratios than 65% for Ne 30 yarns, whereas it is suitable if it is used in lower ratios than 35% for Ne 40 yarns.

Yarn Shape in Twisting Part of Disc Friction False Twister

Yarn Shape in Twisting Part of Disc Friction False Twister