Cotton Blend Research Articles

Performance of Jute Cotton and Viscose Blended Woven Fabrics Compared to Hundred Percent Cotton Woven Fabrics: Regarding Mechanical and Comfort Properties.

Performance of Jute Cotton and Viscose Blended Woven Fabrics Compared to Hundred Percent Cotton Woven Fabrics: Regarding Mechanical and Comfort Properties.

A comparative study on physical and mechanical properties of 100% cotton denim and blended cotton denim after industrial washing

This research work was conducted to examine the effects of two types of washing procedures e.g., stone enzyme wash, and bleach wash on the physical and mechanical properties of 95% cotton (CTN), 5% recycled CTN denim, and blended CTN denim containing 80% cotton, 18% polyester, 2% spandex. Two fabrics were dyed with medium brand shade indigo dyes. The fabric weight, EPI and PPI, tear strength, breaking strength, color fastness to accelerated laundering, color fastness to water, color fastness to perspiration, and color fastness to crocking were carried out to key changes of physical and mechanical properties in two fabrics. This study has demonstrated the changes in two fabrics before washing (A) and after washing (B) accordingly. In the case of color fastness results ratings were similar in both fabrics. In contrast, the color fastness to crocking or rubbing showed different results. This research was carried out to investigate the parameter variations and choose which fabric exhibits the best or not.

A Novel and Integrated Approach to Dyeing Recycled Cotton and Chitosan Yarns Blended Fabrics with Innovative Nanobubble Technology

A Novel and Integrated Approach to Dyeing Recycled Cotton and Chitosan Yarns Blended Fabrics with Innovative Nanobubble Technology

Assessment of the Barrier Performance of the Flourosilicone Treated Fabric Exposed to Pesticides Spraying to Chilli Crop at Laboratory Conditions

In this study, in view of development of protective clothing for pesticide sprayers in chilli crop, the suitable fabric polyester 67/cotton 37 with weight 157.7 GSM was selected. BOND-WR-12-A RTU was aqueous fluorosilicone durable water and oil repellent emulsion was used to treat the fabric by using different application parameters at the rate of 5 per cent concentration. As per Chowdhury, 2018 water repellent finish type and concentrations were very important parameters to obtain water repellent fabric having acceptable use properties. Later, the treated fabric was exposed to the selected pesticides like Phosphamidon, Monocrotophos and Dimethoate for for three exposures. By estimating the absorption and penetration behaviour of the treated and untreated fabrics, the performance of silicon finish was determined by using four factor with CRD and Heuristic method. From this result, the treated fabric had restricted the absorbency over control fabric and the Studies on barrier clothing, [1,2] suggested that blends of polyester cotton and polyester viscose showed better barrier performance with minimum penetration of pesticides than other blended fabrics. Hence it can be used in development of protective clothing for pesticide applicators in chilli crop or any other field crops where ever pesticides are used.

Superhydrophobic Surface Modification for Enhanced Fabric Face Masks: The Impact of Varying HDTMS Concentrations

The widespread use of disposable surgical masks and N95 respirators has led to concerning environmental pollutions. As a result, there has been a growing demand for fabric face masks that are not only reusable and environmentally friendly, but also effective in preventing virus transmission. However, traditional fabric masks have a drawback: their hydrophilic nature increases the risk of virus transmission. To address this challenge, an innovative solution for achieving superhydrophobic surface on cotton, microfiber, and microfiber blend materials was investigated. The key focus of this investigation revolvesaround the impact of varying concentration of hexadecyltrimethoxysilane (HDTMS) on the hydrophobicity of different fabrics. Consequently, all cotton fabric samples treated with 5%, 10% and 20% HDTMS concentration exhibit water contact angles (WCA) surpassing 150o, effortlessly achieving a state of superhydrophobicity. The modified cotton and microfiber materials proudly display not only enhanced water repellency but also boast exceptional self-cleaning and stain resistant properties.

30 Engineered Nanoparticle Resuspension Contributing to Inhalation Exposure from Contaminated Protective Clothing

Abstract In this study, we investigated engineered nanoparticle (ENP) release associated with the contamination of personal protective clothing during the simulated motion of the human wearing the ENP-contaminated protective clothing and evaluated the relative ENP retention on the fabric. The release of airborne ENPs can contribute to inhalation exposure, which is the route of exposure of most concern to cause adverse health effects in the pulmonary system. The evaluation focuses on four popular fabric materials making the laboratory coats (cotton, polypropylene, polyester cotton blend, and Tyvek®) and three types of ENPs (Al2O3, carbon black and CNT). The magnitudes of particle contamination and resuspension were investigated by measuring the number concentration increase of airborne particles in sizes of 10 nm to 10 μm and the weight changes on fabric pieces. Collected aerosol particles and contaminated fabric surfaces were further characterized for understanding particle morphology, elements, agglomeration and surface contamination status. The particle resuspension from contaminated lab coat fabric was found to vary by the type of fabric material. Cotton fabric showed the highest level of particle resuspension for all three tested ENPs. Data were evaluated to determine the dominant forces responsible for ENP adhesion on the surface of the fabric. Tyvek® fabric was determined as the best fabric for trapping Al2O3 and carbon black ENPs indicating less resuspension of particles meaning lower subsequent release, but not durable enough to wear for the long term compared with other fabrics.

Effect of Lubrication in Cotton Blended Air-Vortex Sewing Thread

ABSTRACT Attempts have been made to use air-vortex cotton-blended spun yarn of 30s and 40s count as sewing thread by using 2.9% and 5.9% concentrations of lubricant. No systematic study has been conducted as of now for vortex because all the sewing threads used in the garment industry are produced from ring yarn. Yarn strength, elongation, hairiness, dry heat shrinkage, yarn abrasion, snarling of yarn after heat setting, loop strength, and knot strength of air-vortex-spun sewing threads have been studied. It is observed that the sewing thread made with 5.9% concentration of lubricant performs better in comparison to that made with a 2.9% lubrication level. Seam strength and efficiency of different types of seams made by air-vortex sewing threads have also been studied. Flat and lapped seams are found to produce higher seam strength and seam efficiency. Seam strength and efficiency improve with an increase in the concentration of lubricant in both 30S and 40S yarn.

Optimization of Textile Waste Blends of Cotton and PET by Enzymatic Hydrolysis with Reusable Chemical Pretreatment.

Textile waste usually ends up in landfills and causes environmental pollution. In this study, pretreatment methods for textile recycling, including autoclaving, freezing alkali/urea soaking, and alkaline pretreatment, were applied to textile waste with various cotton/polyester blending ratios. The best condition for enzymatic hydrolysis was a 60/40 textile waste blend of cotton/polyethylene terephthalate (PET) with a reusable chemical pretreatment (15% NaOH) at 121 °C for 15 min. The hydrolysis of pretreated textile waste by cellulase was optimized using response surface methodology (RSM) based on central composite design (CCD). The optimized conditions were 30 FPU/g of enzyme loading and 7% of substrate loading, which resulted in a maximum observed value of hydrolysis yield at 89.7%, corresponding to the predicted value of 87.8% after 96 h of incubation. The findings of this study suggest an optimistic solution for textile waste recycling.

Investigating how the dye colour is impacted when chemically separating polyester-cotton blends

Blended textile fabrics with dyed cotton and polyester (PET) fibres intimately mixed are extensively used in the textile industry. Separating and recycling these blends cannot be performed by conventional mechanical or chemical recycling processes, and this is contributing significantly to the global textile waste problem. Here we demonstrate an approach to separate coloured cotton and polyester blends, and the dye is retained in the separated polyester and cotton components. The separation was achieved via chemical dissolution of cotton using a co-solvent system of ionic liquid and dimethyl sulfoxide, from which regenerated cellulose fibres could be directly wet spun. The polyester component was left intact and recovered via filtration. The recovered products were characterised for thermal, chemical, mechanical, colour strength, and morphological properties.

Development of insecticide-impregnated polyester/cotton blend fabric and assessment of their repellent characteristics against Cimex lectularius and dengue vectors Aedes albopictus and Aedes aegypti

BackgroundPersonal protection measures using insecticide-treated fabric is one of the most effective strategies to prevent the bites of hematophagous insects. Many countries have had success treating fabrics with pyrethroids on an individual level.MethodsIn the current study, a new combination of insecticides, alpha-cypermethrin (ACP) and deltamethrin (DET), has been impregnated on fabric composed of a 50:50 blend of polyester and cotton. Residual and morphological analysis was performed along with the evaluation of physical parameters. Biological evaluations were performed to check the repellency, knockdown, and mortality of insecticide-impregnated fabric (IIF) against bed bugs (Cimex lectularius) using Petri plate assay and mosquitoes (Aedes aegypti and Aedes albopictus) using cone bioassay.ResultsThe results showed the repellency of IIF to be 56.6% for C. lectularius and a knockdown percentage of 53.3% and 63.3% for Ae. aegypti and Ae. albopictus, respectively. A > 80% mortality was found for both species of mosquitoes up to 20 cycles of washing with no significant difference (P > 0.05). From high-performance liquid chromatography (HPLC) analysis, the reduction in the contents of ACP and DET after subsequent washes can be correlated with the overall decrease in bioefficacy. ACP and DET remaining in unit gram of fabric after 20 wash cycles were found to be 5.4 mg and 3.1 mg, respectively. By examining the fabric’s surface morphology using scanning electron microscope (SEM) and utilizing energy-dispersive x-ray (EDX) analysis, it was possible to identify the presence of insecticides that were adhered to the fabric. Differential scanning calorimetry (DSC) showed distinctive endothermic peak of insecticide at 98.3 ºC, whereas no change in thermal behavior was observed from thermo-gravimetric analysis (TGA). Furthermore, the physical attributes of IIF provide conclusive evidence for its firmness.ConclusionAll experimental findings were consistent with the potential use of IIF as a bed bug- and mosquito-repellent fabric to be used against hematophagous infestations. This fabric can serve as a potential strategy to control vector-borne diseases like dengue, malaria, trench fever, etc.Graphical

Eco-Friendly and Facile Integrated Intumescent Polyelectrolyte Complex Coating with Universal Flame Retardancy and Smoke Suppression for Cotton and its Blending Fabrics

Cotton and its blended fabrics are widely used textile materials in daily life; however, their high flammability brings serious fire hazards. It remains a huge challenge to endow cotton and its blended fabrics through simple and universal technology. In this work, a novel water-based polyelectrolyte complex (PEC) coating was developed from chitosan and a water treatment agent (amino trimethylphosphonic acid). By controlling the degree of ion pair aggregation through pH adjustment, the intumescent and stable PEC coating can be constructed quickly via facile blading coating and curing processes. High transparency allows for the deposition of the coating with little effect on the original pattern of the coated fabric. Additionally, when the coated fabrics were exposed to flame, the PEC coating underwent a quick self-char-forming reaction in advance and formed a protective char layer covered on the fibers. Thus, the PEC coating with low adding-on (11.5–21.5 wt %) shows universally high flame retardancy for cotton, polyester/cotton blends, and polyester/poly(vinyl alcohol)/cotton blends. The coated fabrics show excellent extinguishing performances, high limiting oxygen index values of 27.5%–28.5%, and total release smoke inhibition of 42%. This work provides a promising universal technology for manufacturing fire-safety cotton and its blends in a simple and eco-friendly way.

Influence of Stretching on Liquid Transport in Knitted Fabrics

The transport of liquid sweat in clothing worn close to human skin is very important from the point of view of the thermo-physiological comfort of clothing users. It ensures the drainage of sweat secreted by the human body and condensed on the human skin. In the presented work, knitted fabrics made of cotton and cotton blends with other fibers (elastane, viscose, polyester) were measured in the range of liquid moisture transport using the Moisture Management Tester MMT M290. The fabrics were measured in unstretched form and stretched to 15%. Stretching of the fabrics was performed using the MMT Stretch Fabric Fixture. Obtained results confirmed that stretching significantly changed the values of parameters characterizing the liquid moisture transport in the fabrics. Before stretching, the best liquid sweat transport performance was stated for the KF5 knitted fabric made of 54% cotton and 46% polyester. For this, the greatest value (10 mm) of maximum wetted radius for the bottom surface was obtained. The Overall Moisture Management Capacity (OMMC) of the KF5 fabric was 0.76. This was the highest value among all values obtained for the unstretched fabrics. The lowest value of the OMMC parameter (0.18) was stated for the KF3 knitted fabric. After stretching, the KF4 fabric variant was assessed as the best one. Its OMMC improved from 0.71 before stretching to 0.80 after stretching. The value of the OMMC for the KF5 fabric remained after stretching at the same level (0.77) than before stretching. The most significant improvement was observed for the KF2 fabric. Before stretching, the value of the OMMC parameter for the KF2 fabric was 0.27. After stretching, the OMMC value increased to 0.72. It was also stated that the changes in the liquid moisture transport performance of the investigated knitted fabrics were different for the particular fabrics being investigated. Generally, in all cases, the ability of the investigated knitted fabrics to transfer liquid sweat was improved after stretching.

Comparative Effect of Fabric Type on the Protection and Comfort Properties of Fabric Face Mask: A Contribution to Surveillance Against Covid-19

The purpose of this study was to investigate the effect of fabric type on the protection and comfort properties of fabric face masks against covid -19. Five different fabrics; Cotton, Poly-cotton blend, Light Neoprene, Polyester, Neoprene were purchased from Gashua market and 500 fabric face masks were produced. Three parameters; air permeability, elongation, and tensile strength were used to determine its fabric functional and quality properties. Laboratory tests as well as structured questionnaires were used as instruments for data collection. Polyester has the highest tensile strength of 1214.02N, followed by poly-cotton blends and the lowest being cotton 714.80N. Neoprene has the highest elongation of 78.81%, followed by light Neoprene and the least is 20.29%. Cotton has the highest air permeability of 118.36 ft3/ft2min, followed by Neoprene and light Neoprene respectively; the lowest is poly cotton blends. The cotton face mask has the best characteristics in terms of ease of breathability, can easily be washed and does not fog on the glass of the wearer. Poly-cotton blends face masks follow cotton in all the three characteristics stated above and it was adjudged to be the best in fitness for wearing. Polyester face mask produces the lowest result in breathability and fog production in the glasses.

Impact of Variant Fibre Blend Ratios, pH Levels and Finishing Types on Comfort Properties of Polyester/Cotton Knitted Fabric

Today is the era of value added textiles. The people like to have comfortable dressing in addition to have aesthetic quality. Comfort is the key factor of all kinds of fabrics especially for knitted fabric and has a significant role in their selection. Generally the comfort properties of the knitted fabric are related to its thermal and moisture transmission behavior. The comfort of knitted fabric depends upon many factors like fibre types and their blend ratios; pretreatment, dyeing and finishing processes, various pH levels during dyeing and processing. The application of synthetic fibres with natural ones is carried out for some kind of value addition in the resultant product. Polyester and Cotton (P/C) blend is the most popular blend in the textile sector. Both fibres play significant role in the comfort related characteristics of the manufactured fabric. The variant blend ratios of these fibres significantly affect the comfort of the resulted fabric. Hence keeping in view all this the present research study was planned to have a comprehensive observation on the comfort of the P/C blended knitted fabric under variant blend ratios, pH levels and finishing types. The study revealed a significant impact of all designated factors on the comfort properties of the knitted fabric.

Analysis of the Effect of Sizing Add-on% and Sizing Process Parameters on the Average Warp Breakage Rate for 30Ne 100% Cotton Warp Yarn

Sizing is one of the essential steps in fabric manufacturing for increasing weaving production efficiency in the case of cotton and cotton blend fabrics by providing a protective coating to warp yarn that does not add any functional value. This research aimed to analyze the effects of size add-on% and two sizing process parameters, such as sizing machine speed and squeezing roller pressure, on the average warp yarn breakage rate during weaving. The sizing experiments have been conducted based on the size add-on% (8.93 %, 9.94%, 11.23%), sizing machine speed (35 yards/min, 38 yards/min, 40 yards/min), and squeezing roller pressure (2.2 kg, 3.3 kg, 3.5 kg) on the 30Ne 100% cotton warp yarn. It was found from the experimental results that the warp yarn breakage rate was increased with the rise in sizing machine speed and squeezing roller pressure. In contrast, the lowest warp yarn breakage rate was exhibited in size add-on% 9.94 in the loom during weaving. Based on the research, promising industrial application is highlighted for future fabric production. Journal of Engineering Science 13(2), 2022, 111-115

Converting textile waste into value-added chemicals: An integrated bio-refinery process

The rate of textile waste generation worldwide has increased dramatically due to a rise in clothing consumption and production. Here, conversion of cotton-based, colored cotton-based, and blended cotton-polyethylene terephthalate (PET) textile waste materials into value-added chemicals (bioethanol, sorbitol, lactic acid, terephthalic acid (TPA), and ethylene glycol (EG)) via enzymatic hydrolysis and fermentation was investigated. In order to enhance the efficiency of enzymatic saccharification, effective pretreatment methods for each type of textile waste were developed, respectively. A high glucose yield of 99.1% was obtained from white cotton-based textile waste after NaOH pretreatment. Furthermore, the digestibility of the cellulose in colored cotton-based textile wastes was increased 1.38–1.75 times because of the removal of dye materials by HPAC-NaOH pretreatment. The blended cotton−PET samples showed good hydrolysis efficiency following PET removal via NaOH–ethanol pretreatment, with a glucose yield of 92.49%. The sugar content produced via enzymatic hydrolysis was then converted into key platform chemicals (bioethanol, sorbitol, and lactic acid) via fermentation or hydrogenation. The maximum ethanol yield was achieved with the white T-shirt sample (537 mL/kg substrate), which was 3.2, 2.1, and 2.6 times higher than those obtained with rice straw, pine wood, and oak wood, respectively. Glucose was selectively converted into sorbitol and LA at a yield of 70% and 83.67%, respectively. TPA and EG were produced from blended cotton−PET via NaOH–ethanol pretreatment. The integrated biorefinery process proposed here demonstrates significant potential for valorization of textile waste.

A sustainable approach to oil spill cleanup by kapok and waste cotton needle punched nonwoven blends

Natural materials that can absorb a large amount of oil have recently received a lot of interest as sorbents to clean up oil spills in seawater. In this work, kapok fibre was blended with different proportions of cotton fibres obtained as blow room waste from the textile industry to prepare nonwovens using carding and needle-punching techniques. The potential for oil sorption, oil retention, and water sorption of kapok/waste cotton nonwovens was investigated. FTIR, SEM, and surface contact angle of the fibres were determined since oil sorption depends on the fibres' physical and chemical properties. The effect of waste cotton and kapok fibre blend ratio on oil sorption and oil retention behaviour of kapok/cotton nonwoven was studied. The maximum oil sorption capacity of blended nonwoven (90/10, kapok/cotton) with areal density (150 GSM or g/m 2 ) was 45.36 g/g, 43.97 g/g, and 39.92 g/g for engine oil, vegetable oil, and diesel oil, respectively. Reusability test results suggest that after ten cycles, the oil absorbency of 150K/C 90/10 was 42.55 g/g, 40.61 g/g, and 36.45 g/g against engine oil, vegetable oil, and diesel oil, respectively. A comparison of the oil sorption capacity of kapok/waste cotton blends with other synthetic (Polypropylene) sorbents was also presented. According to our findings, kapok/waste cotton nonwovens could become an important sorbent for oil spill clean-up. • Sustainable oil sorbent was made from blends of kapok and waste cotton fibres. • The oil-to-pore volume occupied by fibre was explored for oil sorption capacity. • After ten cycles, K/C blend sorbents retained 76 % of engine oil. • The sorbents can be used as biofuel even after 10th cycle.

Assessment of comfort property of jute-cotton blend denim trousers after repetitive laundering

In this analysis jute cotton blend denims performance at enzyme wash to 35 times respective laundering, in friction and roughness properties where 5 times laundered sample showed smoother surface in both inner and outer surface. In bending properties, 5 times laundered sample was found second lowest Bending Average Rigidity (BAR) and Bending Work (BW). In compression, highest Compression Average Rigidity (CAR), Recovery Average Rigidity(RAR) and less energy requirement Compression work (CW) to compress in both inner and outer surface was found in 5 times laundered sample. In Sensorial Comfort Aspect (SCA), 5 times laundered sample was found smoother surface property, quite higher bending property and higher compression average rigidity. Therefore, 5 times laundered sample was good sensorial comfort among all the samples. In Maximum Thermal Flux (MTF), 20 times laundered sample gives most warm feeling at inner surface because it provides minimum heat flux which ensure warmness in skin-garment micro environment. For thermo physiological comfort aspect, only 20 times repetitive laundered sample found maximum thermo physiological comfort among all samples. Thus, Jute-Cotton blend denims performance at enzyme wash to 35 times repetitive laundering up to 20 times repetitive laundering sample reported good results and the protruding fibre of jute was visible excessively on the surface.

Evaluation of Air Permeability of Knitted Fabrics at Various Washing Intervals

The air permeability of fabrics is one of the most important factors to be considered in making comfortable clothing for consumers. It helps to transport moisture in the form of vapours from the inner skin to the outer environment. This study aims at determining the rate of airflow through the prepared knitted fabrics after various washing intervals. Circular knitted fabrics with 100% cotton and a blend of cotton and polyester having a ratio of 70% / 30% were made by setting different construction parameters. Prepared fabrics were evaluated for their air permeability by following the ASTM D737-1996 test procedure. Then these fabrics were laundered with standard procedure and evaluated after various intervals. It was concluded from the obtained results that construction parameters such as kind of polymer, loop length, hairiness, yarn count, number and size of pores and their distribution play a major role in determining the air permeability of knitted fabrics. Moreover, an increase in washing cycles also reduces the airflow through the fabric.

A big-data-driven matching model based on deep reinforcement learning for cotton blending

ABSTRACT China’s cotton textile industry is undergoing a critical period of digital transformation and upgrading to cope with pressure and challenges such as rising labour costs and large fluctuations in raw material prices. Developing a cost-based competitive advantage while ensuring a high-quality product is a critical problem in intelligent manufacturing. From the perspective of big data and reinforcement learning, the authors designed a reward value combining transaction, interaction, and measurement data by combining the reward mechanism and Markov decision for a combination of different raw materials in the intelligent textile factory. The authors propose a big data-driven application to the depth of the reinforcement learning to solve problems and build a big-data-driven matching model based on deep reinforcement learning to cotton matching. The offline strategy is designed to construct a memory bank and neural network, and the incentive mechanism of reinforcement learning is used to iterate the optimal yarn matching scheme to achieve the goal of intelligent cotton matching. The results show that deep reinforcement learning can be optimised using big data on the premise of quality assurance. Manufacturing costs can be optimised using a matching model of big data based on a deep reinforcement learning model.