Fabric Samples Research Articles

Proteomics for forensic identification of saliva and vomit in a case of alleged rape.

In crime investigations, the unambiguous identification of biological traces can be decisive for framing the events. In this study, we applied proteomics to analyze scant amounts of biological residues in the context of an alleged rape case, focusing on the detection of traces of vomit. We used high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) and two distinct proteomic workflows to identify proteins and possible proteolytic peptides in biological residues from clothing, bedding, and car upholstery from the alleged crime scene. Specifically, a fragment of pillowcase contained a protein pattern indicative of human saliva and a complex panel of peptides resulting from extensive hydrolysis of salivary proteins. The presence of partly digested proteins from bovine meat, wheat, and eggs, along with salivary and gastric enzymes, demonstrated the presence of vomit on the alleged victim's trousers, also providing insights into the recently consumed meal. A drop of cow's milk on the seat of the suspect's car was likely irrelevant to the criminal act. Other fabric samples showed only common contaminants, excluding significant biological traces or food-derived proteins. These findings support the judicial decision regarding consent to sexual intercourse, for which DNA individualization lacks evidentiary power, and establish a reference for annotating saliva and vomit traces in forensic investigations.

Spectrophotometric and calculative determination methods of textile color-difference threshold considering the observing condition

Purpose This study aims to investigate the varying color-difference thresholds for textiles under various illuminants. Design/methodology/approach To determine color-difference thresholds, 108 fabric samples with widely ranging colors were spectrophotometrically measured and visually assessed under four illumination conditions (correlated color temperatures of 2,856 K and 6,504 K; illuminances of 100 lx and 2,000 lx). Findings The mean spectrophotometric color-difference threshold (solely based on the textile’s physical color attributes in machine vision) was 4.22 ΔE*ab; thus, a mechanically measured color difference between two textiles (regardless of illuminant) of less than 4.22 ΔE*ab indicated individuals’ inability to differentiate between two textiles. The calculated color-difference thresholds, which reflected the color differences perceived by people considering textiles’ physical color attributes and the environmental factors in which they were observed, were higher than the spectrophotometric thresholds. This meant that under various illuminants, people had greater difficulty perceiving color differences than mechanically measured spectrophotometric thresholds. Particularly, larger discrepancies between the two threshold types occurred under reddish illuminants of 2,856 K than under bluish-white illuminants of 6,504 K. Furthermore, the extent to which people perceived color differences as distinct from actual differences under illumination was larger for greenish-blue textiles than for textiles of other hues. Originality/value The determined spectrophotometric and calculative color-difference thresholds for textiles can help fashion companies predict consumers’ perceptions of the colors of their textile products under various illuminants and, accordingly, appropriately plan colors of products and create standards for color quality control.

Rapid Antibacterial Assessments for Plastic and Textile Materials Against Escherichia coli

Background: Standard test methods for evaluating the antibacterial performance of plastic (non-porous) and textile (porous) materials are accurate and reliable, but completing a standard assessment generally requires at least several days to a week. Well-trained and experienced technicians are also required to conduct the standard tests consistently and analyse the samples and test results systemically. These costs are often not favourable for the performance assurance of antimicrobial products in industrial production, nor for meeting the fast-return demands in research and development of antimicrobial materials nowadays. Methods: In this study, “Rapid Tests” are developed to evaluate the antibacterial activities of plastic and textile materials. Results: The assessment results from Rapid Tests for plastics and textiles are highly correlated to those from the ISO 22196 and the AATCC Test Method 100, respectively, whereas the evaluation operation can be completed within one day. Based on bioluminescence technology, colony-forming units of E. coli from the inoculated specimens are determined via luminometry. Antibacterial efficacy of the treated plastic and textile samples can be examined effectively. Conclusions: By analysing antimicrobial artificial leather samples composed of hydrophilic polyurethane polymer using Rapid Tests for plastics and textiles, the applicability and scope of these tests were remarkedly recognised and verified.

Modeling of the Stress-Strain Quality of Hydroentangled Nonwoven Fabrics

Hydroentanglement is a mechanical bonding process designed to produce nonwoven fabrics with appearances and textures that resemble woven and knitted fabrics. Eleven samples of hydroentangled nonwoven fabrics with different compositions and weights were subjected to a series of uniaxial stress-strain tests. Models, ranging from the simple Kelvin to the more complicated Kelvin–Vangheluwe, were fitted to the experimental data to find a generalized and universal model. In this model, a nonwoven fabric was considered a nonlinear viscoelastic material. The combination of Kelvin and Vangheluwe models resulted in an excellent fit to the uniaxial stress-strain curves. The model-predicted results almost overlapped with the experimental data, an indication of its excellent accuracy in predicting the mechanical behavior of nonwoven fabrics.

Thermophysiological Comfort Behaviour of Cut Protective Workwear Consisting of Filament Twisted Multicomponent Hybrid Yarn

Current cut protective gear is subject to several difficulties, such as the use of heavy fabric, complicated donning processes, lack of comfort and limited movement. When selecting the most comfortable cut protective fabric, it is important to consider the end users' specific needs. The aim of this study was to enhance the comprehension and optimisation of protective apparel for superior occupational safety and protection by exploring the intricate link between material composition, yarn structure and comfort parameters. Various combinations of filament twisted core sheath yarn consisting of stainless-steel/glass with high-performance polyethylene and polyester wraps were used to fabricate thermo-physiological comfortable cut protective workwear fabric. Twelve cut protective fabrics with the same areal density (200 g/m2) were prepared with 6-end satin weave using filament twisted core sheath yarn of five distinct linear densities (98.4 tex, 73.8 tex, 59.1 tex, 49.2 tex and 39.4 tex). These fabric samples were used to evaluate thermophysiological characteristics, including air permeability, dry and evaporative heat resistance, thermal conductivity, moisture permeability, wettability and moisture wicking according to the established standard. The cut protection of each sample was also measured according to EN 13997. The cut protection and thermo-physiological comfort attributes of cut-resistant clothing are greatly influenced by the proportion of core material (stainless-steel/glass) and yarn structural parameters (linear density and twist direction), which was observed by analysing the results. An increased core material percentage (stainless-steel/glass) contributes to increased fabric thickness and reduced bulk density, which influences the thermophysiological comfort attributes of the developed cut protective workwear fabric. Fabric made from a higher proportion of core material (stainless-steel/glass) with a lower bulk density exhibited an acceptable cut protection level and performed better in terms of thermo-physiological comfort attributes.

New family of type V natural hydrophobic deep eutectic solvents based on thymol-acetamide/acetanilide: Characteristics, intermolecular interactions and applications in liquid–liquid extraction

To develop type V hydrophobic thymol-based Deep Eutectic Solvents (DESs) with low viscosity for liquid–liquid extraction, this work briefly reviews the thymol-based DESs reported in the literature, along with their various applications, and investigates the potential for DES formation between thymol and new materials. For this purpose, 39 combinations of thymol with different amino acids (5), acids (10), carbohydrates (13), amides (2), alkylammonium halides (4), and other compounds (5) were screened, resulting in the preparation of two new thymol-acetamide and thymol-acetanilide-based DESs. To identify the optimal molar ratios for DES formation, various combinations of thymol with acetamide and acetanilide were prepared, and their abilities to form stable liquids at room temperature, along with their thermal properties, were evaluated. Based on the solid–liquid equilibria (SLE) phase diagrams, it was found that stable liquids at ambient temperature were formed within the composition ranges of xACM = 0.29–0.40 (2.5:1–1.5:1) for THY:ACM and xACN = 0.29–0.33 (2.5:1 – 2:1) for THY:ACN. The mixtures with a molar ratio 2:1 were selected for further study, and their intermolecular interactions, characteristics, and applications in dye extraction were analyzed. FT-IR and NMR analyses were performed to investigate the structure and hydrogen bond formation between the DES components. Additionally, molecular dynamic (MD) simulations were conducted to examine the molecular structure and formation mechanisms of these DESs. The results indicated that hydrogen bonds are formed between the hydroxyl group (OH) of thymol and the carbonyl group (CO) of acetamide/acetanilide. Thermodynamic models, including regular solutions, NRTL, and Wilson, were employed to correlate the SLE phase diagrams of the studied mixtures, as determined by the DSC method. The physical properties of the prepared DESs, such as melting point, density, speed of sound, refractive index and viscosity, were measured at different temperatures. Due to their hydrophobic nature, the DESs demonstrated stability in aqueous solutions and thus can be used to extract various analytes from aqueous environments. The obtained solvents were applied for the extraction of methylene blue, methyl orange, and rhodamine B from aqueous solutions, as well as from real textile wastewater samples. Finally, to achieve optimal extraction conditions, the effects of various factors on extraction efficiency were investigated.

Mercury (II) sensor based on nanosilver/chitosan modified screen-printed carbon electrode

This study introduces a highly sensitive platform for ultratrace mercury [Hg (II)] detection, utilizing a screen-printed carbon electrode (SPCE) modified with silver nanoparticles (AgNPs), chitosan (CS), and carbon nanotubes (CNTs). The AgNPs were synthesized using a green method incorporating CS and CNT hybrids, leading to their immobilization on the CNT sidewalls, resulting in nanoscale silver electrode arrays on the SPCE. Detection of Hg (II) involved the formation of Hg/Ag amalgam on the AgNPs/CS/CNT-modified SPCE surface by depositing mercury species onto elemental mercury. Hg (II) detection successfully occurred through the stripping of both Hg0 and Ag0 at a potential of +0.16 V in a supporting electrolyte (0.10 M HCl and 0.10 M KCl). This newly established detection method demonstrates exceptional selectivity and sensitivity, featuring a remarkable linear range for Hg (II) concentration from 1.0 nM to 12.6 nM, with an impressive correlation coefficient (R2) of 0.982 (n = 13) and a low detection limit of 0.4 nM. The designed electrode effectively measured Hg (II) levels in textile samples, yielding acceptable recovery results, while also exhibiting remarkable reproducibility and precision. This work presents a novel, highly sensitive, and selective approach for ultratrace Hg (II) detection, with promising applications in environmental monitoring and analytical chemistry.

Plaid fabric image retrieval based on hand-crafted features and relevant feedback

Common fabric image retrieval methods ignore the diversity and dynamism of user demands, the results are determined by the query image and cannot be dynamically adjusted. To solve this problem, this study proposes a novel image retrieval method for plaid fabrics based on hand-crafted features and relevant feedback. First, local texture descriptors are extracted by the local binary pattern on the separated images which are processed by Fourier transform. Global texture descriptors are extracted by scale-invariant feature transform (SIFT) and vector of locally aggregated descriptors (VLAD). Second, color moments with image partitioning are extracted to characterize spatial color information of plaid fabric images. Third, the extracted features are fused by the weight allocation for similarity measurement. Finally, the relevant feedback based on meta learning is involved to realize personalized adjustment and optimization of retrieval results. An image retrieval database is built as the benchmark by collecting over 44, 000 plaid fabric samples from the factory. Experiments show that precision and recall at rank eight reach to 70.6% and 62.6%, respectively, and mAP reaches to 0.690. Results prove that the proposed strategy is feasible and effective, which can realize plaid fabric image retrieval fast and efficiently.

Nonlinear large strain mechanics and failure of 45° woven CFRP laminates characterized by Full-Field measurements

The nonlinear mechanical response of 45° woven composites is studied using full-field strain measurements. First, carbon fabric samples without an epoxy matrix are prepared and tested to evaluate the deformation response of the fiber tows in the absence of internal resistance imposed by the epoxy matrix. Next, the effect of the epoxy matrix is examined by fabricating and testing 45° single-ply carbon fiber reinforced composite laminas. Homogeneous strain fields with minimal resistance against external loads are observed in fabric samples without epoxy. The in-plane rotation of fiber tows in the carbon fabric samples varies linearly with the applied global strain. On the other hand, the development of scissoring action in single-ply composite laminas is shown to cause severe shearing of the epoxy entrapped between the orthogonal fiber tows, leading to the outward protrusion of epoxy from the surface of the lamina. The scissoring effect is correlated with different stages of deformation in a highly nonlinear stress–strain response. Finally, similar tests performed on three-ply laminates reveal that the abovementioned matrix protrusion leads to accelerated delamination in 45° laminates at global strains lower than those in single-ply laminas. The underlying mechanisms for scissoring-induced matrix protrusion are discussed using a simple analytical model.

Evaluation of Electrical Properties and Uniformity of Single Wall Carbon Nanotube Dip-Coated Conductive Fabrics Using Convolutional Neural Network-Based Image Analysis

This study proposes a convolutional neural network (CNN)-based image analysis method to evaluate the electrical properties and uniformity of conductive fabrics treated with single-walled carbon nanotube (SWCNT) dip-coating. The conductive fabric was produced by dip-coating cotton-blended spandex with SWCNT, and the surface images were scanned and preprocessed to obtain image data, while resistance measurements were conducted to obtain labels and build the dataset. SEM analysis revealed that as the number of dip-coating cycles increased, particle density and path formation improved. The CNN model learned the relationship between surface images and resistance values, achieving a high predictive performance, with an R-squared (R²) value of 0.9422. The model demonstrated prediction accuracies of 99.1792% for the coefficient of variation (CV) of uniformly coated fabrics and 96.8877% for non-uniformly coated fabrics. Additionally, p-value analysis of all fabric samples yielded a result of 0.96044, indicating no statistically significant difference between the predicted and actual values. The proposed CNN-based model can accurately evaluate the electrical uniformity of conductive fabrics, showing potential for contributing to quality control and process optimization in production.

Eco-friendly dyestuffs prepared with Curcuma Longa L. extracts and their antimicrobial activities

In this study, wool, cotton, polyester fabrics and wood samples were dyed with Curcuma longa (turmeric) extracts using CuSO4, FeSO4 and AlK(SO4)2 mordants. Dyeing processes were carried out using pre-, meta-, post- mordant and without-mordant dyeing methods. Yellow, mustard yellow, brown, greenish and light yellow color tones were obtained in samples dyed with turmeric. Rubbing fastness, washing fastness and light fastness of all dyed samples were evaluated. K/S and L* a* b* values of the dyed samples were determined by color measurement spectrophotometer. The highest K/S value was measured as 31.05 for CuSO4 with meta-mordanting method for dyed wool using turmeric extract. The antimicrobial properties of the dyed textile products were determined by the disk diffusion method against Staphylococcus aureus, Proteus mirabilis and Pseudomonas aeroginosa. According to the antimicrobial activity test results, it was determined that the fabric samples dyed with turmeric have moderate antimicrobial activity.

Developing computational and experimental models of heat transfer through multi-layered textile structures

Object signature management is a critical and urgent task that helps conceal and restrict the detection of contemporary optoelectronic systems. The design of thermal camouflage textiles and material solutions constitute a significant scientific area, however publications in this area are restricted because of military competitiveness and technological secrecy. Research on thermal camouflage materials has drawn interest both domestically and internationally for a variety of purposes, especially in military applications. Multi-layered Textile Structures (MTS) is a material with several advantages, such as its simple structure, capacity to combine many different materials with many different qualities, and great applicability. The article includes a model of computation and simulation of heat transfer through multi-layer textiles, as well as tests to assess the heat shielding effect and heat radiation energy of some samples of multi-layer textiles made of domestic materials. The initial computational and experimental results constitute an important foundation for further research and application of multi-layered textile structures.

Evaluation of polyester high-tenacity fabric and carbon nanotube reinforcements for improving flexural response in concrete beams.

This research scrutinized the effectiveness of utilizing polyester high tenacity fabrics to enhance the functionality of concrete panels. Two distinct woven fabrics with comparable strength resistance were fabricated and assessed. Concrete beams were compared in their original form and those reinforced with woven fabrics, along with beams reinforced with carbon nanotubes (CNTs) (B, BC2, BC4, BS1, and BS2). Results indicated that the textile-reinforced concrete panels displayed notably greater energy absorption capabilities post-failure under flexural loads in comparison to the control and CNT-reinforced panels. This enhanced performance was credited to the development of multiple cracking patterns in the textile-reinforced panels. The flexural behavior of the textile-reinforced panels was characterized by four discernible phases: a linearly increasing segment, a crack propagation phase featuring multiple cracking, a post-cracking phase with reduced stiffness, and ultimately, failure due to fabric rupture or debonding. Conversely, the control and CNT-reinforced panels exhibited a more brittle response post-initial cracking, with a limited number of cracks and reduced deformation capacity. The performance of the textile samples was largely unaffected by their specific characteristics, except for the fabric wrapping angle. The introduction of 0.04% CNTs marginally enhanced crack flexural resistance compared to the control and 0.02% CNT panels, owing to the varied distribution of CNTs within the matrix. Overall, the textile-reinforced concrete panels demonstrated superior load-bearing capacity, ductility, and energy absorption when compared to the other reinforcement techniques examined.

Digitized Identification of Indigo Natural Dyeing on Batik and Non-Batik Fabrics

Natural coloring in textiles has regained favor as the sustainable fashion movement grows. Fabric colour digitisation can help with data inventory of natural dyed textiles because digital data could endure longer than physical sample artifacts. In this research, digitization was performed on standardized fabric samples: cotton fabric dyed with indigo natural dyestuff and processed with batik and non-batik treatment. Indigo dye is made from the indigo plant (Indigofera tinctoria) and is fixed with quicklime (Calcium Oxide), which serves as both the initial and final mordant. Fabric dyeing was repeated three, six and nine times until the desired hue is reached. The final fabric samples were then scanned to produce discrete color values in RGB format. Color digitization of batik and non-batik fabrics produces content which can be used in digital mediums.

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.

Optimization Analysis of Clothing Fabric Design Based on Autoencoder and Generative Adversarial Neural Network

In order to meet the challenges of increasingly diverse clothing styles and consumer demands in the market, traditional fabric design methods have become difficult to meet the needs of rapid iteration and innovation due to their time-consuming, costly, and subjective preferences of designers. In view of this, we propose an innovative fabric design optimization simulation strategy aimed at breaking through these bottlenecks through technological means. This strategy cleverly integrates advanced technologies of variational autoencoder (VAE) and generative adversarial network (GAN). First, VAE is used to capture and learn the complex distribution characteristics of existing clothing fabric designs, which include key information such as fabric texture, color matching, and structural details. Subsequently, GAN uses the hidden vectors obtained from VAE as input to generate brand new fabric design samples. During the training phase, GAN continuously iterates and optimizes, engaging in intense “adversarial” interactions between its generator and discriminator. The generator is dedicated to creating new samples that are as close to real fabric designs as possible, while the discriminator is responsible for identifying the authenticity of these samples. This process is implemented through backpropagation (BP) loss function, ensuring that the generated fabric design can visually simulate real fabrics. Experimental verification shows that this method can not only effectively generate high-quality and realistic clothing fabric designs, but also greatly shorten the design cycle and reduce costs.

Synthesis of Stearyl Alcohol/Polyethylene Glycol Hybrids as Water-Repellent Finishes for Cotton/Polyester Blended Fabric

Nowadays, developing and innovation of new finishing agents that are cost effective, efficient, durable, and safe for the consumer as well as the environment are greatly required by the textile manufactures. In that concern, new stearyl alcohol/polyethylene glycol (SA/PEG) hybrids were synthesized, characterized, and applied as textile finishes to impart cotton/polyester fabric with water repellency. Such hybrids were synthesized by reaction of SA with PEG of molecular weight 1000 or 4000 Da in the presence of ammonium persulfate (APS) as initiator. The optimum conditions of the synthesis reaction are: APS/PEG, 20%; PEG/SA, 15%; reaction temperature, 80 °C and reaction time, 45 min. The synthesized hybrids are self-water dispersible that form oil-in-water stable emulsions. The results indicated that treating cotton/polyester fabric with easy-care finishing formulation containing 60 g/L of dimethyloldihydroxyethylene urea as a cross-linker, and 60 g/L of any of such hybrids emulsions imparts the treated fabric with water repellency, softness, and stiffness properties. Moreover, increasing the PEG molecular weight from 1000 to 4000 Da leads to a reduction in extents of softness and contact angle along with an enhancement in stiffness of treated fabric. Furthermore, the prepared hybrids emulsions-treated fabric samples are durable up to five washing cycles. The FTIR analysis confirmed the chemical structure of the synthesized SA/PEG1000 hybrid. The transmission electron microscope (TEM) revealed that the particles size of SA/PEG4000 hybrid emulsion is in the range of 34–70 nm and reaches to 185 nm in case of the SA/PEG4000 hybrid emulsion. The surface of SA/PEG1000 hybrid emulsion-treated fabric was characterized via scanning electron microscope (SEM).

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 comparative analysis of energy dissipation behaviour of woven and UD para-aramid fabrics

This research examines how impact energy spreads across para-aramid fabrics, comparing woven and unidirectional types, using 2-D Thin Plate Spline analysis. The experiment involved dropping a weighted hemisphere onto fabric samples and measuring their deformation across different layer counts. To assess how yarn orientation affects energy dispersion, panels with 0º/90º and 0º/90º/±45º configurations were tested. By analysing the fabric's shape changes under impact, the study revealed patterns of energy propagation. Calculations of bending energy and expansion factors provided insights into this behaviour. The findings indicate that unidirectional fabrics outperform woven structures in distributing impact energy across their surface. Moreover, incorporating ±45º fibre reinforcements in both fabric types enhances energy dispersion and mitigates impact effects.

Improved Adhesion of Bacterial Cellulose on Plasma-Treated Cotton Fabric for Development of All-Cellulose Biocomposites.

Cellulose produced by bacteria (BC) is considered a promising material for the textile industry, but the fragile and sensitive nature of BC membranes limits their broad applicability. Production of all-cellulose biocomposites, in which the BC is cultivated in situ on a cotton fabric, could solve this problem, but here a new issue arises, namely poor adhesion. To overcome this challenge, cotton fabric was modified with low-pressure oxygen plasma in either afterglow, E-mode, or H-mode. All-cellulose biocomposites were prepared in situ by placing the samples of cotton fabric in BC culture medium and incubating for 7 days to allow BC microfibril networks to form on the fabric. Modification of cotton fabric with oxygen plasma afterglow led to additional functionalization with polar groups, and modification with oxygen plasma in H-mode led also to etching and surface roughening of the cotton fibers, which improved the adhesion within the biocomposite. In addition, these biocomposites showed higher deformation capacities. Modification of the cotton fabric over a longer period in E-mode was found to be unsuitable, as this caused strong etching, which led to the defibrillation of cotton fibers and poor adhesion of BC. This study highlights the potential of low-pressure plasma treatment as an environmentally friendly method to improve the performance of cellulose-based biocomposites.