Band 21, Heft 1

This study is to investigate the role of the coating of TiO 2 nanoparticles deposited on wool fibers against high-intensity ultraviolet B (UVB), ultraviolet A (UVA), and visible light irradiation. The properties of tensile and yellowness and whiteness indices of irradiated TiO 2 -coated wool fibers are measured. The changes of TiO 2 -coated wool fibers in optical property, thermal stability, surface morphology, composition, molecular structure, crystallinity, and orientation degree are characterized using diffuse reflectance spectroscopy, thermogravimetric analysis, scanning electronic microscopy, energy-dispersive X-ray spectroscopy, Fourier-transform infrared spectroscopy, and X-ray diffraction techniques. Experimental results show that the tensile properties of anatase TiO 2 -coated wool fibers can be degraded under the high-intensity UVB, UVA, and visible light irradiation for a certain time, resulting in the loss of the postyield region of stress–strain curve for wool fibers. The coating of TiO 2 nanoparticles makes a certain contribution to the tensile property, yellowness and whiteness indices, thermal stability, and surface morphology of wool fibers against high-intensity UVB, UVA, and visible light irradiation. The high-intensity UVB, UVA, and visible light can result in the photo-oxidation deterioration of the secondary structure of TiO 2 -coated wool fibers to a more or less degree. Meanwhile, the crystallinity and orientation degree of TiO 2 coated wool fibers decrease too.

Heated gloves have been gaining popularity due to increasing work safety demands. The objective of the present work was to evaluate the effects of the presence of chemical hand warmers in protective gloves. The study involved three types of gloves appropriate for work activities performed in cold environments. Several hand warmer variants were designed, differing in terms of shape and location within the glove, which are of great relevance to the comfort of use. Manual dexterity tests were designed to approximate real conditions of the work environment, allow for simulation of occupational activities, and involve various aspects of manipulation.

The dye production and its use in textile and related industries resulted in discharge of dye to wastewater. Adsorption for color removal is known as equilibrium separation process, and the resultant decolorization is influenced by physicochemical factors such as adsorbent surface area. The nanofiber membranes prepared by the electrospinning method have controllable nanofiber diameter and pore size distribution (PSD) with a high surface area to volume or mass ratio. In this study, polyvinyl alcohol (PVA) nanofibrous membranes were prepared by the electrospinning method at different collection times such as 3, 5 and 10 h and heat fixated at 130, 150 and 170°C for 10 min, and then, the adsorption capability of PVA nanofiber membranes for Reactive Red 141 from aqueous solution was investigated. In order to make PVA nanofibers stable to water, the nanofibrous membranes were chemically cross-linked by a polycarboxylic acid (1,2,3,4 butanetetracarboxylic acid (BTCA)). PVA nanofibrous membranes were characterized by scanning electron microscopy, thermogravimetric analysis, swelling tests and pore size analysis. The results indicated that BTCA crosslinking improved the thermal and water stability of the nanofibrous structure but has no significant effect on the pore sizes of the membranes. Adsorption of Reactive Red 141 was studied by the batch technique, and it was observed that PVA nanofibers removed approximately >80% of the dye.

Protective and sport clothing is governed by protection requirements, performance, and comfort of the user. The comfort and impact performance of protective and sport clothing are typically subjectively measured, and this is a multifactorial and dynamic process. The aim of this review paper is to review the contemporary methodologies and approaches for measuring ergonomic wear comfort, including objective and subjective techniques. Special emphasis is given to the discussion of different methods, such as objective techniques, subjective techniques, and a combination of techniques, as well as a new biomechanical approach called modeling of skin. Literature indicates that there are four main techniques to measure wear comfort: subjective evaluation, objective measurements, a combination of subjective and objective techniques, and computer modeling of human–textile interaction. In objective measurement methods, the repeatability of results is excellent, and quantified results are obtained, but in some cases, such quantified results are quite different from the real perception of human comfort. Studies indicate that subjective analysis of comfort is less reliable than objective analysis because human subjects vary among themselves. Therefore, it can be concluded that a combination of objective and subjective measuring techniques could be the valid approach to model the comfort of textile materials.

The purposes of the current research were to deposit the silver nanoparticles on the surface of a textile woven fabric and evaluate their dyeing performance and antibacterial activity. The synthesis of silver nanoparticle (Ag°) is done by the in situ method. Strong alkali is used to improve functionality of cellulose before the application of silver nitrate salt (AgNO 3 ). The silver nanoparticle is formed by reduction of ascorbic acid. Various instrumental analyses are done to prove the formation of nanoparticles on the fabric surface. The morphology of nanodeposited fabric is characterized by using scanning electron microscope (SEM), elemental composition is done by energy dispersive spectroscopy, and crystallinity of nanoparticles is obtained by X-ray diffraction (XRD). Nanodeposited fabric is then dyed with direct dyestuff (Direct Red-89). Fourier transform infrared spectroscopy analysis is done to explore the bonding phenomena of un-dyed and dyed fabrics. The dyeing performance and antibacterial activity are examined on the colored fabric to investigate the dyed fabric quality after nanoparticle deposition. Results demonstrate the improvement of 54% of color strength and 11% of dye exhaustion with excellent antibacterial activity.

This work deals with determination of rapid and precise methods to predict the amount of sewing thread needed to sew a garment using different chain stitches of the class 400 (from 401 to 407 chain stitches). At first, to avoid unused stocks, sewing consumption value was determined using a geometrical method (based on different chain stitch shapes). The prediction of the sewing thread consumption was proposed as a function of the studied input parameters, which are fabric thickness, stitch density, yarn linear density, and stitch width. Then, a statistical method based on the multilinear regression was studied. Geometrical and statistical results were discussed. Based on the R 2 range, we concluded that the geometrical method is more accurate than the statistical one (from 98.16 to 99.19% and from 97.30 to 98.51%, respectively). Thus, this result encourages industrialists to use geometrical models to predict thread consumption. Also, all studied parameters, contributing to the sewing thread consumption behavior, were investigated and analyzed. The result shows that the most important parameters affecting thread consumption are stitch density followed by stitch width and fabric thickness. The yarn density has a low contribution on the thread consumption value.

Electroencephalogram (EEG) is the biopotential recording of electrical signals generated by brain activity. It is useful for monitoring sleep quality and alertness, clinical applications, diagnosis, and treatment of patients with epilepsy, disease of Parkinson and other neurological disorders, as well as continuous monitoring of tiredness/alertness in the field. We provide a review of textile-based EEG. Most of the developed textile-based EEGs remain on shelves only as published research results due to a limitation of flexibility, stickability, and washability, although the respective authors of the works reported that signals were obtained comparable to standard EEG. In addition, nearly all published works were not quantitatively compared and contrasted with conventional wet electrodes to prove feasibility for the actual application. This scenario would probably continue to give a publication credit, but does not add to the growth of the specific field, unless otherwise new integration approaches and new conductive polymer composites are evolved to make the application of textile-based EEG happen for bio-potential monitoring.

This research aims to evaluate the properties of cotton single jersey knitted fabrics (SJKF) produced from cotton/spandex yarns at different Lycra states. So, four different SJKF were produced, namely 100% cotton, cotton with additional Lycra (full-platted), core, and dual-core-spun (DCS) yarns with the same loop length. The thermal comfort properties, fabric recovery, total hand value (THV), moisture management parameters, and air permeability were measured. The experimental results showed that the use of DCS yarns in the SJKF improves the fabric elastic recovery by 100%. The obtained values of air permeability, THV, and overall moisture management capacity of stretched SJKF are lower than 100% cotton fabric sample. Thermal absorptivity of core and dual-core samples increased by 27% and the water vapor permeability decreased by 18% compared to 100% cotton fabric sample.

Softener application on fabric surface facilitates the process and wear abilities of the fabric. However, the application of softeners and other functional finishes influence the color of dyed fabrics, which results in shade change in the final finished fabrics. This article presents the method of intelligent prediction of the shade change of dyed knitted fabrics after finishing application by using artificial neural networks (ANNs). Individual neural networks are trained for the prediction of delta values (ΔL, Δa, Δb, Δc, and Δh) of finished samples with the help of reflectance values of the knitted dyed samples along with color, shade percentage, and finishing concentrations, which were selected as input parameters. The trained ANNs were validated through “holdout” and “cross-validation” techniques. The trained ANNs were combined to develop the model for shade prediction. The developed system can predict the shade change with >90% accuracy and help to decrease the rework and reprocessing in the wet processing industries.

Friction is defined as a force resisting a relative motion between two bodies in contact. The friction of a fabric on itself or on another fabric influences significantly a fabric’s performance and user’s utility comfort, especially the so-called sensorial comfort. Generally, the coefficient of friction is determined for a given pair of materials. The aim of the present work was to investigate the influence of the structure of the seersucker woven fabrics on their frictional properties. Three variants of the seersucker woven fabrics of different repeat of the seersucker effect were the objects of the investigations. Three measuring elements were applied: made of aluminum and steel and covered with silicone. The obtained results confirmed the influence of the pattern of the seersucker effect on the values of friction coefficient. It was also stated that there are differences between the friction coefficients measured in the warp and weft directions of the seersucker woven fabrics. Values of friction coefficient between the seersucker woven fabrics and measuring elements were the highest for the measuring element covered by silicone. These values were several times higher than the values of friction coefficient measured using the measuring elements made of aluminum and steel.

Cochlospermum vitifolium flowers were evaluated as a raw material of natural dye on different fabrics, natural and synthetic. The dyeing process evaluation was performed by CIELa * b * color coordinates analysis. Color fastness was evaluated using the AATCC 61-1B and AATCC 116 methods. The chemical identification of the compounds in the color fraction was carried out by HPLC–MS/MS. The naringenin was determined to be the color compound. Among the natural textiles, the wool presented the best uniformity of dyeing and fixation of color, achieving the best hue when a pre-mordant treatment was used. The combination of sodium and potassium tartrate dye resulted in the best final hue, between the yellow and red regions of the CIELa * b * space (L = 49.84, a * = 5.41, b * = 45.52). The dyeing of the wool by the sodium and potassium tartrate pretreatment showed the best fastness properties to the laundering test (ΔE ab = 54.56), as well as in the rub test (ΔE ab = 67.36). The extract of C. vitifolium could be considered as an alternative natural dye for textiles with a protein base (e.g., wool fabrics), obtaining the best results when mordant pretreatment is used.

This study discusses the effect of corona pretreatment and subsequent loading of titanium dioxide nanoparticles on self-cleaning and antibacterial properties of cellulosic fabric. The corona-pretreated cellulosic fabrics were characterized by field emission scanning electron microscopy, and X-ray mapping techniques revealed that layers of the titania deposited on cellulose fibers were more uniform than the sample without pre-corona treatment. The self-cleaning property of treated fabrics was evaluated through discoloring dye stain under sunlight irradiation. The antibacterial activities of the samples against two common pathogenic bacteria including Escherichia coli and Staphylococcus aureus were also assessed. The results indicated that self-cleaning and antibacterial properties of the corona-pretreated fabrics were superior compared to the sample treated with TiO 2 alone. Moreover, using corona pretreatment leads to samples with good washing fastness.

The paper presents the numerical modeling of large deflections of a flat textile structure subjected to a constant force acting on the free end. It was assumed that the examined structure is inextensible. The effect of the structure's own weight was also taken into account. In order to solve the problem, the flat textile structure was modeled using the heavy elastica theory. An important element of the analysis involves taking into account the variable bending rigidity of the examined textile structure along its length, which is often found in this type of products. The function of variable bending rigidity was assumed in advance. Numerical calculations were carried out in the Mathematica environment using the shooting method for the boundary value problem. The obtained results were verified using the finite element method.

Thermal performance of aerogel-embedded polyester/polyethylene nonwoven fabrics in cross airflow was experimentally studied by using a laboratory-built dynamic heat transfer measuring device in which the fabric could be applied on a heating rod. Experiments were performed with different airflow velocities and heating conditions. The temperature–time histories of different materials were collected and compared. The temperature difference and convective heat transfer coefficient under continuous heating were analyzed and discussed. Results showed that under preheated conditions, the aerogel-embedded nonwoven fabrics had very small decrease in temperature and good ability to prevent against heat loss in cross flow. As for the continuous heating conditions, the heat transfer rate of each material showed an increasing trend with increase in the Reynolds number. The aerogel-treated nonwoven fabric with the least fabric thickness and aerogel content delivered a significantly increased heat transfer rate at higher Reynolds number. Thicker fabrics with higher aerogel content could provide better insulation ability in cross flow.

Traditional patterns are widely used in the modern design due to their long history, rich connotation, and beautiful form. However, the current application of traditional patterns in the modern design is mostly based on the designer's subjective preferences, not from the perspective of consumers, to explore their feelings about traditional patterns, and which design factors have an impact on consumers, which is the main reason why modern applications of traditional patterns cannot meet the esthetic needs of modern consumers. Therefore, to make better inheritance of the traditional pattern and meet the needs of contemporary consumers, this article takes the caisson lotus pattern of Mogao Cave in the Tang dynasty as an example and first, using the theory of Kansei engineering to investigate the perceptual cognition of the young consumers aged 20–35 years old on the lotus pattern, then use SPSS 24.0 software to analyze the perceptual evaluation data, find the design element combination code corresponding to the perceptual vocabulary, and establish a mathematical model that can predict consumers’ emotional imagery of the lotus pattern of the caisson in the Tang dynasty. Through the verification of the model, the test results show that the model has a high degree of credibility; designers can use this model to quickly evaluate and redesign the lotus pattern to better meet the needs of modern consumers. At the same time, the method of this paper can also be applied to other design fields with user-centered concerns.