Fiber-based artificial muscles with excellent actuation performance are gaining great attention as soft materials for flexible actuators; however, current advances in fiber-based artificial muscles generally suffer from high cost, harsh stimulation regimes, limiting deformations, chemical toxicity, or complex manufacturing processing, which hinder the widespread application of those artificial muscles in engineering and practical usage. Herein, a facile cross-scale processing strategy is presented to construct commercially available nontoxic viscose fibers into fast responsive and humidity-driven yarn artificial muscles with a recorded torsional stroke of 1752°cm −1 and a maximum rotation speed up to 2100 rpm, which are comparable to certain artificial muscles made from carbon-based composite materials. The underlying mechanism of such outstanding actuation performance that begins to form at a mesoscale is discussed by theoretical modeling and microstructure characterization. The as-prepared yarn artificial muscles are further scaled up to large-sized fabric muscles through topological weaving structures by integrating different textile technologies. These fabric muscles extend the simple motion of yarn muscles into higher-level diverse deformations without any composite system, complex synthetic processing, and component design, which enables the development of new fiber-based artificial muscles for versatile applications, such as smart textiles and intelligent systems.
The aim of this work is to explore a new method for producing color-alternation fancy yarn on a modified compact spinning machine. Color-alternation fancy yarn is a new kind of fancy yarn with varying color effects along the yarn axis. The modified compact spinning machine produces double-channel compact spinning, which has two coaxial back rollers in a drafting unit. In this spinning process, two different colored rovings are alternately fed into each back roller to produce alternant color effects along the yarn axis. The mean length of the connecting piece between of two different solid color pieces of this yarn is the key research subject. Mathematical equations have been derived to describe the relationship between the mean length of the connecting pieces, the mean length of the wedged broken end of roving, the mean overfeeding length of the roving and the total draft ratio. The effect of the total draft ratio and overfeeding length on yarn properties, such as tenacity, elongation and yarn evenness, was studied. The results indicate that a relatively small total draft ratio is beneficial to shorten the mean length of the connecting pieces, enhance the tensile property and improve yarn evenness.
The main aim of this paper is to investigate the fiber distribution on the surface of a kind of novel two-color yarn spun by regulating the feeding ratio of two colored rovings on a modified ring spinning frame, which is named the double-channel spinning frame. The surface distribution ratio ( SDR) and the coefficient of variation of surface distribution evenness ( CV sd) of the two colored fiber strands in the yarns was used to quantify the fiber distribution feature along the yarns based on a purpose-made image acquisition device and the corresponding image processing method. The effect of the weight ratio, roving feeding position and spinning method on the mean SDR and CV sd were studied, and the testing results of the Z-twist and S-twist two-color yarns spun by a modified traditional ring spinning frame as well as the yarns spun by a modified compact spinning frame were compared with each other. The fibers of the left-hand roving are more likely to distribute in the surface of Z-twist yarn, while the fibers of the right-hand roving tend to distribute in the surface of S-twist yarn. Four linear fitting equations of the 19.4 tex Z-twist and S-twist two-color ring spun yarns and two-color compact spun yarns were developed to predict the relationships between the mean SDR and weight ratio of two colored fibers.
An agent-aided system (AAS) for improving comprehensive properties of ring spun yarns with the aid of viscosity and surface tension of the agent is reported in this paper. The mechanism of the humidification and friction process of the AAS was investigated, and related experiments were also carried out to verify the mechanism of analysis. The results confirm that the AAS can attach the fiber ends protruding out of a yarn body on the yarn surface and assist in twisting the fiber ends back into the interior of the yarn body, resulting in a significant reduction of the modified ring spun yarn hairiness. Moreover, the yarn hairiness is prominently reduced after the winding process. The experimental results also show that a speed ratio of 1.3 between the rotating speed of the cylinder and the output speed of the yarn leads to the greatest extent of harmful hairiness reduction (34%), which also corresponds to optimal modified yarn tenacity. Meanwhile, the modified ring spun yarns show a tight and smooth appearance, and the yarn evenness has no deterioration. In addition, the AAS is applicable to both cotton and viscose yarns with different yarn counts. Therefore, the AAS can potentially be used to reduce yarn hairiness for ring spun yarns and enhance the quality of ring spun yarns in the textile industry.
Fabrics with good shape-retention properties are strongly expected to improve the aesthetic feeling, comfort and easy-care performance of clothing in daily life, and the efficient characterization of the wrinkle recovery property of fabrics is a necessary approach to facilitate the development of garments with good shape retention. Here, a double extraction method was presented to evaluate fabric wrinkling based on the wrinkling-induced residual force–displacement curves. The correlation analysis was used to determine applicable evaluation indices in order to cluster the wrinkle recovery property of fabrics based on a K-means clustering algorithm. Moreover, subjective judgements were conducted and compared with the objective K-means cluster method. The results show that there is good consistency between objective K-means clustering and subjective judgements, indicating that the indices featured from wrinkling-induced residual force–displacement curves can be used to evaluate the wrinkle recovery of fabrics. Therefore, the double extraction method is a starting point for the rapid identification of wrinkle recovery of fabrics by the mechanical performance of textiles.
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