Knitted Fabrics Research Articles

Study evaluating the curling property of weft knitted fabrics based on pixel analysis

Curling is a common phenomenon observed in knitted fabrics. Curling poses many problems for fabric and clothing production, especially for digital devices, where it can affect the production quality and efficiency, while there is still no accurate method for evaluating it. This study established an evaluation method for the curling properties of knitted fabrics based on pixel statistics. Weft knitted fabric samples were created using a fabric cutter and a piece of paper was placed underneath the fabric. The fabric sample curls, whereas the paper represents a non-curling state. Subsequently, a scanner was used to scan the projections of the circular samples and paper to obtain digital images. The pixel amounts of the curled fabric and paper digital images were measured using the Photoshop 2020 software. The ratio between the fabric and paper projection pixels can be calculated by subtracting from 100% and converting the curling area ratio to the curling distance ratio. This can be used to represent the curling properties of knitted fabrics. The error between the theoretical and measured values is <0.1%, indicating a high level of accuracy. Ten knitted fabrics were validated for analysis. The sample with the maximum deviation between the left, middle, and right positions was 5.9%, whereas that with the minimum deviation was 0.3%. Subsequently, the fabrics were retested on the 7th and 14th days to assess reproducibility. The maximum deviation for each fabric on the 1st, 7th, and 14th days was 4.1%, and the minimum deviation was 0%. Therefore, it can be concluded that the method described in this study can accurately quantify the curling properties of knitted fabrics.

Investigation of effect of recycled polyester ratio and draw frame passages on flame retardancy of chenille fabric properties

PurposeIn this study, both flame retardancy and sustainability properties were combined in the chenille yarn so that functional and sustainable upholstery fabrics can be produced with optimum energy consumption. The chenille yarn samples were produced from recycled polyester (rPET)-blended binder yarns and fully drawn yarn (FDY) polyester pile yarn. While the pile component of the chenille samples was kept constant, the lock yarns were manufactured as 50% r-PET-50% virgin polyester (PES), 100% r-PET and 100% PES. The binder yarns were also produced in two groups. In the first group, a 2-passage draw frame was used, while a 3-passage draw frame was used in the second group. The chenille yarn samples were applied flame-retardant (FR) finishing.Design/methodology/approachThe knitted upholstery fabric samples were produced from chenille yarn samples via flat knitting machines. The knitted fabrics were applied flame retardancy, bursting strength and abrasion resistance tests according to related standards.FindingsThe test results were analysed, and so the effect of r-PET ratio and draw frame passage number on upholstery fabric flame retardancy, bursting strength and abrasion resistance performance properties were revealed. It was concluded that the number of draw frame passages and the recycled fibre content have no important effect on the flame retardancy. On the other hand, it has been observed that the bursting strength decreases as the recycled fibre content increases and bursting distention results are close to each other. It was seen that the draw frame passage number has no significant effect on both bursting strength and distention. It was revealed that both r-PET fibre content and draw frame passage number have significant effect on abrasion resistance. The samples with 2 draw frame passages provide higher abrasion resistance compared to those with 3 draw frame passage. The lowest abrasion resistance was obtained with 100% r-PET fibre content and the highest abrasion resistance was obtained with 50% r-PET-50% PES.Originality/valueThe results will provide enough knowledge for sustainable chenille yarn design. The recycled fibre content and draw frame passage number can be optimised, and so sustainable chenille yarns can be produced with less energy consumption. Future studies will involve producing chenille yarns with different linear densities and varying draw frame combinations, such as 1, 2 and 3 passages.

The dynamic of cooling heat flow of simple jersey polyester fabric

The dynamic of cooling heat flow during evaporation of the simple jersey polyester fabrics was investigated in this study. The holding period as a new parameter was introduced to study the dynamic of cooling heat flow during evaporation from the skin through the jersey knitted fabric. The holding period intervals were chosen as follows: 0, 30, 60, 90, 120, 180, 240 and 300 seconds. The Permetest skin model was used to study and visualize the dynamic of the cooling heat flow at different holding periods. Results demonstrated that adding elastane makes fabrics less cool. Three different stages were noticed concerning the cooling heat flow dynamic: the first with a maximum heat flow (Qmax) indicating the first contact properties of a textile material with the skin. The second is a transition phase where the cooling heat flow decreases to the minimum heat flow (Qmin), and then it reaches the equilibrium (Qeq) mentioning the beginning of the third stage with a constant heat flow. It was found that the holding period does not affect the measured water vapour resistance, in the case of polyester jersey fabrics.

Superior filaments-based fabric with thermal-mechanical-electrical coupling properties for remote temperature alarm

The safeguarding fabrics featuring good thermal insulation, flame retardancy, and force dissipation simultaneously remain challenging due to the current filaments with limited properties. Herein, a novel and flame-retardant filament (F-filament) is developed by hot-extruding the mixture of shear stiffening gel/thermoplastic polyurethane (SSG/TPU) and microencapsulated ammonium polyphosphate (MHAPP), which is conducive to knitting protective fabrics. The conductive F-filament (cF-filament) is further prepared by incorporating with MXene. The F-filament-based fabrics present better anti-impact properties than commercial fabrics and can dissipate 6.32 kN impacting force to 1.89 kN. The patterned knitted fabric also facilitates heat exchange, reducing the contact temperature of the body surface to approximately 37 °C when exposed to an 80 °C heat source, effectively avoiding thermal damage through its porous structure. Moreover, the F-filament-based fabrics are intact even after 19 s of continuous burning. Notably, the cF-filament is demonstrated for use as a sensor for real-time multimodal monitoring, such as detecting external mechanical loadings and temperature stimuli. The cF-filament sensor can be integrated into the F-filament-based knitted fabrics, which accurately realizes environmental monitoring and explores the best-escaping route through a remote temperature alarm system.

Analysis of Liquid Transport Performance of Cotton Knitted Fabric Made by the TransDry Technology

ABSTRACT In order to improve a competitiveness of cotton in textile market, an innovative TransDry® technology has been developed. The aim of the work was to investigate the liquid moisture transport in cotton knitted fabrics: standard and made using TransDry® technology. The measurement has been performed using Moisture Management Tester. Additionally, fabrics have been measured in the range of water-vapor permeability and thermal insulation using Permetest and Alambeta. Results showed that both calculated parameters: R – accumulative one-way transport index and OMMC – overall moisture management capacity do not reflect the advantages of the TransDry® technology. The advantages of TransDry® technology have been demonstrated in values of the following parameters: WTT – wetting time for top surface, MWRB – maximum wetted radius for the bottom surface, SST and SSB – spreading speed on both sides of fabric. Results showed that only an in-depth analysis of results of individual parameters and graphs from the MMT software allowed for a detailed examination of movement of liquid moisture in tested fabrics and demonstration of the advantages of TransDry® technology. It has been also concluded that the changes of the structure of knitted fabrics cause the changes of moisture transport properties of the fabrics.

Rapid simulation of knitted fabrics based on a ribbon yarn model

In the study, an innovative three-dimensional ribbon-based yarn model simulation technique is introduced, aimed at significantly enhancing the realism and speed of knitted fabric simulation through efficient model construction and rendering processes. The method successfully overcomes the limitations of traditional two-dimensional loop models and tubular yarn models, accurately capturing the textural details of knitted fabrics with a vivid three-dimensional representation. Experimental results demonstrate the outstanding performance of this simulation system in simulating the fuzz effects of yarn and in processing speed. This technology offers significant potential in textile design and production, notably in boosting design efficiency and accelerating new product development. By employing low-cost image capture methods, the study effectively reduces technical and financial barriers in knitted fabric simulation, enhancing its practical and industrial applicability.

Optimizing textile dyeing and finishing for improved energy efficiency and sustainability in fleece knitted fabrics

In the industrial range, optimizing dyeing and finishing energy is important to control environmental pollution. In the Dyeing stage to finishing of textiles gas, electricity, steam, and water are used 260 m3/hour, 591 kWh, 1.2 pounds/hour, and 8.69 tons/hour respectively. If textile professionals do not match the desired shade and quality of fabrics with the use of minimal resources the energy cost will be multiple times higher. This study investigates the change in the shade of fleece knitted fabrics from the dyeing unload to the finish stage and assumes a dyeing recipe adjustment, focusing on the impact of optimized dyeing and finishing processes. Also, it focuses on qualitative changes in properties across various color variations. Identical dyeing recipes for light, medium, and dark shades of red, blue, and navy. Properties such as GSM (grams per square meter), width, color strength, shade (darker/lighter, red/green, blue/yellow), shrinkage, spirality, pilling, bursting strength, and color fastness were analyzed. Dyeing to post-finishing, an increase in color strength (K/S) values was observed, with examples including minimum increases from 2.9 to 3.18 for light red and maximum from 19.3 to 22.9 for dark navy shade. Darker shades (DL*) were observed after stenter 1st pass (among all variants, red: 1.2 % to 8.1 %, blue: 4.5 % to 6.7 %, navy: 1.6 % to 2 %), while lighter shades (DL*) were observed following sueding and napping (among all variants, red: 3.1 % to 19.7 %, blue: 11.8 % to 19.7 %, navy: 14.8 % to 27.6 %). Greenish (Da*) and yellowish (Db*) tones are prominent across all colors in the finishing stages. Besides, other properties shrinkage, spirality, pilling, bursting strength, and color fastness significantly changed. These findings offer valuable guidance for dyeing professionals aiming to achieve the desired adjustment of shades that match the quality standard and produce sustainable fleece fabrics. To compensate for the shade lightening that occurs during the finishing process, it is recommended to keep the fabric shade slightly darker (5.70 % to 23.10 %) at the dyeing stage.

Research on constant tension yarn transfer control technology based on AGA-PID and FOC algorithm

To solve the problems of poor real-time tension tracking, large overshoot, long adjustment time, and large tension fluctuation error that exist in the current control system for yarn feeding in the circular weft knitting machine, this paper presents an optimized and improved adaptive genetic algorithm (AGA) for adjusting the PID (Proportional Integral Derivative) parameters of the tension control part of the yarn-conveying system (AGA-PID). The algorithm is combined with the field-oriented control technology of the permanent magnet synchronous motor to design a closed-loop control strategy for the yarn-conveying system of a circular weft knitting machine. The MATLAB-Simulink simulation model was used to analyze the external tension loop-based AGA-PID controller and permanent magnet synchronous motor dual closed-loop control strategy of the yarn transport control system. The experimental verification was conducted by constructing an experimental platform that simulates the real process of yarn transportation. The outcomes of system simulations and experiments have consistently demonstrated that the AGA-PID control algorithm outperforms the GA-PID and PID control algorithms in terms of overshooting, response speed, stability, and anti-jamming ability. The yarn transport control system, which is designed to operate based on an AGA-PID control algorithm, is capable of reducing the fluctuations in tension that occur during the transportation of yarn and exhibits enhanced control accuracy, effectively stabilizing yarn tension control during the conveying process. The application of this algorithm can enhance the overall elasticity uniformity and surface flatness of knitted fabrics, thereby facilitating the realization of adjustable and controllable local elasticity in fabrics.

Life Cycle Assessment (LCA) of Single Jersey Knitted Fabrics Containing Recycled Cotton Fiber and Fabric Performance

This study investigates the life cycle assesment of single jersey knitted fabrics containing recycled cotton and their some performance properties. In the yarn production stage fibers obtained from waste through mechanical recycling (pre-consumer recycle) were used in blends at 10%, 15%, and 20% to produce knitted fabrics. Some performance properties such as fabric stiffness, air permeability, and dimensional change, which are important in the usage properties of jersey knitted fabrics, were compared. Within the scope of the study, the environmental impact of the use of recycled raw materials was evaluated with LCA. According to the Life Cycle Analysis (LCA) results, the use of recycled cotton with contributions ranging from 10% to 20% instead of 100% original cotton demonstrated significant improvements in resource depletion (fossil fuels), global warming, ozone layer depletion, toxic impact on human life, toxic impact on freshwater life, toxic impact on terrestrial life, and total water usage.

A novel drying process for knitted fabrics based on heat-wet coupling model

The characteristics of high elasticity and easy deformation of knitted fabrics present challenges for traditional continuous flat drying processes. Shrinkage, uneven drying and dye migration are common problems with these processes. To address those problem, a novel dual-heat-supply drying process for knitted fabrics is proposed, which combines the characteristics of hot air drying and cylinder drying. By establishing a mechanical model of the fabric microelement, the force conditions of the fabric during the drying process are analyzed to prevent the occurrence of shrinkage. Consider the structural attributes of knitted fabrics and the diverse forms of water, a foundational unit model for single-sided weft knitted fabrics is proposed. The effective thermal conductivity of wet knitted fabrics in three directions is calculated through numerical simulation, and the validity of this method is preliminarily verified by comparison with literature experiments. The thermal-humidity coupling model is utilized to develop finite element models of cylinder drying and dual-heat-supply drying, which are then employed to conduct a comparative analysis of the two drying processes. The accuracy of the simulation results is verified through experiments, with the maximum deviation being less than 3.3 %. The results demonstrate that in comparison to cylinder drying, the temperature differential between the upper and lower surfaces of the fabric(ΔT) in dual-heat-supply drying is diminished by approximately 5 K. Additionally, the critical saturation point is reached approximately 10 s earlier, which effectively reduces the proclivity of dye migration and enhances the efficiency of the drying process. Finally, three process parameters (v, Tout and Th) is optimized for the dual-heat-supply drying process, 63.68 % reduction in ΔT, thereby further enhancing the quality of the drying process. The dual-heat-supply drying process represents an effective and significant improvement in the quality of knitted fabrics.

Automated model discovery for textile structures: The unique mechanical signature of warp knitted fabrics

Textile fabrics have unique mechanical properties, which make them ideal candidates for many engineering and medical applications: They are initially flexible, nonlinearly stiffening, and ultra-anisotropic. Various studies have characterized the response of textile structures to mechanical loading; yet, our understanding of their exceptional properties and functions remains incomplete. Here we integrate biaxial testing and constitutive neural networks to automatically discover the best model and parameters to characterize warp knitted polypropylene fabrics. We use experiments from different mounting orientations, and discover interpretable anisotropic models that perform well during both training and testing. Our study shows that constitutive models for warp knitted fabrics are highly sensitive to an accurate representation of the textile microstructure, and that models with three microstructural directions outperform classical orthotropic models with only two in-plane directions. Strikingly, out of 214=16,384 possible combinations of terms, we consistently discover models with two exponential linear fourth invariant terms that inherently capture the initial flexibility of the virgin mesh and the pronounced nonlinear stiffening as the loops of the mesh tighten. We anticipate that the tools we have developed and prototyped here will generalize naturally to other textile fabrics–woven or knitted, weft knit or warp knit, polymeric or metallic–and, ultimately, will enable the robust discovery of anisotropic constitutive models for a wide variety of textile structures. Beyond discovering constitutive models, we envision to exploit automated model discovery for the generative material design of wearable devices, stretchable electronics, and smart fabrics, as programmable textile metamaterials with tunable properties and functions. Our source code, data, and examples are available at https://github.com/LivingMatterLab/CANN. Statement of significanceTextile structures are rapidly gaining popularity in many biomedical applications including tissue engineering, wound healing, and surgical repair. A precise understanding of their unique mechanical properties is critical to tailor them to their specific functions. Here we integrate mechanical testing and machine learning to automatically discover the best models for knitted polypropylene fabrics. We show that warp knitted fabrics possess a complex symmetry with three distinct microstructural directions. Along these, the behavior is dominated by an exponential linear term that characterize the initial flexibility of the virgin mesh and the nonlinear stiffening as the loops of the fabric tighten. We expect that our technology will generalize naturally to other fabrics and enable the robust discovery of complex anisotropic models for a wide variety of textile structures.

Design of nature-inspired patterns on knitted fabrics for directional transportation of sweat and study of their performances

The human body in a hot environment or during intense training will sweat a lot. Traditional cotton fabrics are soft and breathable, but they tend to absorb moisture easily and evaporate it slowly, which makes people feel cold and wet. Sweat staying on fabrics for a long time could also cause bacteria to grow. Thus, it is necessary to transport the excessive sweat from the gathering section to the collection points along the surface paths in time to minimize such problems. The mechanism of directional water transport of desert beetles, cacti, nepenthes, and river meanders was referenced in this paper. The paths in dot, tree, V-shape, and river meander patterns were designed and manufactured from the inspiration of these natural architectures. The paths were coated on the surfaces of selected knitted fabrics with different structures through a one-step coating process. The optimal recipe of hydrophobic solution was determined when 0.1 g hydroxyethyl-cellulose (HEC) was added into MS-S002 solution. The results showed that sweat movement is mainly influenced by FL, FWD, FG, and knitted structure. The continuous and enclosed paths such as tree and river contribute to a better sweat moving track than those of dot and V-shape ones. Terry structure is more suitable for surface sweat transport than plain and pique. The highest movement speed of the terry structure with a tree pattern reaches 0.43 cm/s, followed by that of the terry structure with river pattern 0.35 cm/s. The coated fabrics also have ideal moisture and air permeability for wearing.

The superior ballistic performance of highly stretchable and flexible double-face knitted fabrics (DFKF): An experimental investigation

When the protective and protected systems are detached, the former can be allowed to absorb the kinetic energy of the impacting projectile through large deformation without considering the back face signature of the latter. This paper presents a novel double-face knitted fabric (DFKF) designed for this very impacting scenario. Shooting tests equipped with high-speed camera were used to characterize the ballistic performance with the impact velocities ranging from 100∼450 m/s. The results showed that the ballistic limits (Vbl) of DFKF are approximately triple and double that of its counterpart UD and plain fabrics, respectively. For mass-normalized metrics, the specific energy absorption (SEA) is 250% and 350% greater than the UD and plain fabrics at their corresponding Vbls. The quasi-static tests showed that the DFKF displayed greater resilience, crease recovery properties, and flexibility, which also made it an especially better candidate than UD and plain weaves for the design of umbrella surface cloth. It was also found that DFKF is dependent on yarn count and the incorporation of spandex. A prototype anti-ballistic umbrella is manufactured using DFKF made of 200D multi-filament yarn. The ballistic performance is also sensitive to the impact site when the umbrella is subjected to impact.

Wearing Quality of Ribbed Knits Made from Viscose and Lyocell Fibers for Underwear

As an alternative to cotton, viscose and lyocell fibers are suitable for the production of knitted next-to-skin underwear. Despite the advantages of a more environmentally friendly production process and valuable properties, the consumption of lyocell fibers is significantly lower compared to viscose fibers. The applicability of viscose and lyocell fibers in the production of ribbed knits for underwear is insufficiently researched, as is the influence of unconventionally spun yarns on their wearing properties. This study, therefore, investigates the possibilities of using lyocell fibers in the production of novel knitwear with improved properties compared to viscose and conventional cotton knitwear and determines their wearing quality. In this context, two sets of circular 1 × 1 rib jersey fabrics were produced from three types of differently spun viscose and lyocell yarns. The quality of the dry relaxed and wet processed knitted fabrics was evaluated by determining their structure, absorbency, air permeability, and dimensional stability, as well as their tensile, abrasion, and pilling properties, all in comparison to cotton knitted fabric produced under the same conditions. The results showed that lyocell rib knits have better structural uniformity, tensile properties, dimensional stability, air permeability, lower abrasion resistance, and comparable moisture absorbency and pilling propensity compared to viscose knits.

Effects of finishing processes on physical properties of knitted fabrics produced by recycled cotton fibers

This study examines conventional wet-finishing processes applicable to fabrics containing recycled cotton fibers. The knitted fabrics were produced using open-end and compact yarns, with up to 80% of the cotton fibers being obtained from mechanical recycling of pre-consumer textile wastes. The study evaluated the effects of these finishing processes on the physical properties of the fabrics based on the recycled fiber ratio, yarn type, and yarn count. After determining the parameters for enzymatic bio-polishing, scouring, and color removal processes, two sequential finishing routes were designed: using the fabrics as mélange without a dyeing process (F1) or coloring them with color stripping and subsequent dyeing (F2). The resulting fabrics were tested for bursting strength, pilling resistance, weight, thickness, air permeability, and abrasion resistance, and the results were evaluated statistically. The study demonstrated that compact yarns provide superior strength, particularly when the F2 process was employed. The F2 process resulted in high pilling resistance and increased breathability of recycled knitted fabrics. The study concluded that the quality of fabrics containing recycled cotton fibers could be optimized by the selection of the appropriate finishing processes.

The Effects of Polyester Filament Number and Accompanying Hydrophilic Fiber Type on Moisture Management and Drying of Double-Layered Knitted Fabrics

This study aims to investigate the moisture transfer and drying behavior of the double-layered fabrics knitted using polyester yarns with a combination of cotton and viscose yarns. As well as the fiber type on both faces, the effect of the number of filaments of the polyester yarns was also researched. For this purpose, double-layered interlock fabrics were knitted, and the resultant samples were characterized by moisture management, drying, water vapor permeability, and heat conduction tests. It was indicated that the fabrics knitted by polyester yarns on the inner side and cotton fabrics on the outer side resulted in a very good overall moisture-management capacity. The same applied to the drying speed; even faster drying was achieved than the 100% polyester double-layered samples. The increase in the filament number led to a decrease in both moisture management and drying rate. Moreover, it was determined that the use of viscose yarn was not suitable.

A review of deep learning within the framework of artificial intelligence for enhanced fiber and yarn quality

In the textile production chain, fibers serve as the foundational units for yarn, and yarn, in turn, acts as a fundamental component for woven or knitted fabrics. The quality control of fabrics is intricately tied to the management of fibers and yarns. Traditional laboratory methods have been utilized to assess their quality, but the advent of machine learning and deep learning introduces a transformative approach. This review explores the application of machine learning methods such as principal component analysis, support vector machine, and deep learning methods such as artificial neural networks, convolutional neural networks, you look only once, and genetic algorithms to predict various properties of fibers and yarns. In the context of fibers, the review delves into topics such as cotton fiber grading based on color, characterization of jute fiber, and the identification of medullation in alpaca fibers. For yarns, the focus shifts to predicting parameters such as yarn tenacity, evenness, abrasion index of spun yarns, inspection of false twist textured yarn packages, breaking elongation of ring-spun cotton yarns, tensile properties of cotton/spandex yarns, yarn thickness, and yarn hairiness. The review also provides insights into the advantages and limitations of the discussed studies. Despite the comprehensiveness of this review, it is acknowledged that there might be additional relevant work not covered. The review encourages the sharing of data to expedite the integration of these technologies in future applications within the field.

An eco-friendly droplet-wet spinning technology for producing high-quality hemp/cotton blend yarn

In recent years, hemp textiles have gained attention as a sustainable alternative to cotton. However, the uneven fineness and length of hemp fibers, along with their stiffness, adversely affect spinnability and exacerbate yarn evenness and hairiness, particularly due to short fibers. This study introduces a modified sustainable droplet-wet spinning technology aimed at enhancing hemp yarn quality, with a primary focus on reducing yarn hairiness. Implemented on a ring spinning machine, the technology utilizes a syringe connected to an adjustable-speed pump, delivering water onto the front top roller. This innovative approach enhances hemp yarn in two ways: firstly, the cohesive force of water promotes the consolidation of short fibers on both sides of the fiber bundle towards the center, thereby condensing the spinning triangle. Consequently, the fibers on both sides of the fiber bundle are more readily drawn into the spinning triangle and twisted to form yarn; secondly, wet hemp fibers possess a lower modulus, rendering them softer and more deformable, facilitating their embedding into the yarn, thereby enhancing yarn tenacity and reducing yarn hairiness. The study systematically investigates the relationship between droplet-wet spinning parameters (water droplet rate, hemp fiber content of the roving, and yarn twist multiplier) and hemp yarn quality. Experimental results reveals that optimal droplet-wet spinning lead to a 22% increase in yarn tenacity and about 50% reduction in hairiness. A higher hemp fiber content in the roving contributes to better performance of droplet-wet spinning technology in enhancing yarn quality. Moreover, droplet-wet spinning enables the production of high-quality hemp yarn at lower twist multipliers, thereby reducing electricity consumption during yarn production. Subsequently, the performance of knitted fabrics made from conventional ring-spun yarn and droplet-wet spun yarn was compared and analyzed. The results indicate that fabric made from droplet-wet spun yarn exhibits an approximately 8% increase in bursting strength and a one-level improvement in pilling resistance. This research highlights the potential of droplet-wet spinning technology to enhance hemp yarn quality and promote sustainable textile production.

Study on the thermo-physiological comfort properties of cotton/polyester combination yarn-based double-layer knitted fabrics

In this study, a cotton/polyester combination yarn with a hydrophobic–hydrophilic gradient across the yarn cross-section was developed using twinning and twisting technologies, and the hermos-physiological comfort properties of the cotton/polyester combination yarn-based double-layer knitted fabrics, prepared from the cotton/polyester combination yarn together with cotton yarn and polyester filaments, were systematically investigated and compared with the cotton (outer)–polyester filaments (inner) fabric. The results show that the cotton/polyester fabric has a better one-way transfer capacity and drying property due to the hydrophobic–hydrophilic gradient from inside to outside, as well as a lower thermal resistance. The cotton/polyester (outer)–polyester filaments (inner) fabric exhibits a weaker hydrophobic–hydrophilic gradient than the cotton/polyester fabric, offering superior water vapor permeability and dynamic cooling property. Although the cotton (outer)–cotton/polyester (inner) fabric with a hydrophilic gradient shows a higher thermal resistance and a weaker dynamic cooling property, it also has a higher air permeability, thermal conductivity and qmax, and its drying rate is second only to the cotton/polyester fabric. The use of the cotton/polyester combination yarn in the inner layer significantly improves the fabrics’ wettability, wickability, and tactile comfort. Furthermore, the combination yarn-based fabrics also have very good water transfer ability. As a result, the combination yarn can take advantage of both fibers in the preparation of fabrics that meet different comfort requirements.

Moisture-wicking Janus-structure electronic knitted fabric for multimodal wearable mechanical sensing

Multimodal mechanical sensors that can recognize bending direction and exhibit excellent wearable performance are crucial for the fields of physical exercise and healthcare. This study fabricated a knitted multimodal sensor with porous and wetting gradients using hydrophobic core-spun yarns and hydrophilic CNT/WPU conductive yarns in plain stitch and partial tuck stitch. The electronic fabric demonstrated reliable strain sensing unaffected by compression disturbances and displayed a selective response to directional bending. The sensor exhibits a 50% sensing range with a GFmax of −4.41 during strain deformation detection. In terms of bending detection, one side achieves a 10% sensing range (−51.68°) with a GFmax of −6.89, while the other side achieves a 20% sensing range (73.72°) with a GFmax of 8.64. Encouragingly, deep learning incorporated with the sensor achieves an impressive recognition rate of 98.16% for mixed signals with different force levels. Furthermore, it possesses excellent wearable properties such as breathability, moisture permeability, perspiration remove, quick-drying and washability, suitable for applications like activity monitoring, medical rehabilitation evaluation, and gesture recognition. This work presents a promising pathway for the advancement of next-generation multifunctional electronic textiles.