Search Results (96)

This paper presents research in the field of computer-aided 3D clothing design, focusing on an investigation of three methods for determining the mechanical properties of woven fabrics and their impact on 3D clothing simulations in the context of sustainable apparel development. Five mechanical parameters were analyzed: tensile elongation in the warp and weft directions, shear stiffness, bending stiffness, specific weight, and fabric thickness. These parameters were integrated into the CLO3D CAD software v.2025.0.408, using data obtained via the KES-FB system, the Fabric Kit protocol, and the AI-based tool, SEDDI Textura 2024. Simulations of women’s blouse and trousers were evaluated using dynamic tests and validated by real prototypes measured with the ARAMIS optical 3D system. Results show average differences between digital and real prototype deformation data up to 6% with an 8% standard deviation, confirming the high accuracy of 3D simulations based on the determined mechanical parameters of the real fabric sample. Notably, the AI-based method demonstrated excellent simulation results compared with real garments, highlighting its potential for accessible, sustainable, and scalable fabric digitization. Presented research is entirely in line with the current trends of digitization and sustainability in the textile industry. It contributes to the advancement of efficient digital prototyping workflows and emphasizes the importance of reliable mechanical characterization for predictive garment modeling. Full article

The fashion industry is widely recognized for its environmental challenges, but the health impacts related to textile toxicity remain significantly underexplored. Beyond the well-known issues of pollution and resource depletion, modern clothing often harbors a hidden threat: hazardous chemicals embedded within fabrics. These include dyes containing heavy metals, antimicrobial agents that foster bacterial resistance, and synthetic fibers that release microplastics. Unlike environmental discussions, the dialogue around the direct and long-term health effects of these substances is still limited. This entry addresses critical yet often-overlooked concerns, such as how chemicals in textiles contribute to chronic skin conditions, hormonal disruptions, and even carcinogenic risks. It also examines the proliferation of bacteria in synthetic garments, leading to dermatological infections and rapid fabric degradation. Furthermore, the globalized nature of production masks the contamination risks transferred from producer to consumer countries. Through an interdisciplinary approach, this entry highlights the urgent need for integrating scientific innovation, stringent regulation, and consumer awareness to mitigate health hazards in fashion. It calls for the adoption of safer textile technologies, sustainable materials, and transparent production practices, paving the way for a fashion future that prioritizes human health as much as environmental sustainability. Full article

Advancements in thermoregulating textiles have been propelled by innovations in nanotechnology, composite materials, and smart fiber engineering. This article reviews recent scholarly papers on experimental passive and active thermoregulating textiles to present the latest advancements in these fabrics, their mechanisms of thermoregulation, and their feasibility for use. The review underscores that phase-change materials enhanced with graphene, boron nitride, and carbon nanofibers offer superior thermal conductivity, phase stability, and flexibility, making them ideal for wearable applications. Shape-stabilized phase-change materials and aerogel-infused fibers have shown promising results in outdoor, industrial, and emergency settings due to their durability and high insulation efficiency. Radiative cooling textiles, engineered with hierarchical nanostructures and Janus wettability, demonstrate passive temperature regulation through selective solar reflection and infrared emission, achieving substantial cooling effects without external energy input. Thermo-responsive, shape-memory materials, and moisture-sensitive polymers enable dynamic insulation and actuation. Liquid-cooling garments and thermoelectric hybrids deliver precise temperature control but face challenges in portability and power consumption. While thermoregulating textiles show promise, the main challenges include achieving scalable manufacturing, ensuring material flexibility, and integrating multiple functions without sacrificing comfort. Future research should focus on hybrid systems combining passive and active mechanisms, user-centric wearability studies, and cost-effective fabrication methods. These innovations hold significant potential for applications in extreme environments, athletic wear, military uniforms, and smart clothing, contributing to energy efficiency, health, and comfort in a warming climate. Full article

Artificial intelligence (AI) is revolutionizing the fashion, textile, and clothing industries by enabling automated assessment of garment quality, condition, and recyclability, addressing key challenges in sustainability. This systematic review explores the applications of AI in evaluating clothing quality and condition within the framework of a circular economy, with a focus on supporting second-hand clothing resale, charitable donations by NGOs, and sustainable recycling practices. A total of 135 research resources were identified through searching academic databases including Google Scholar, Springer, ScienceDirect, IEEE, Taylor and Francis, and Sage journals. These publications were subsequently refined down to 49 based on selected inclusion criteria. The selection of these sources from diverse databases was undertaken to mitigate any potential bias in the selection process. By analyzing the effectiveness and challenges of related peer-reviewed articles, conference papers, and technical reports, this study highlights state-of-the-art methodologies such as convolutional neural networks (CNNs), hybrid models, and other machine vision systems. A critical aspect of this review is the examination and analysis of datasets used for model development, categorized and detailed in a comprehensive table to guide future research. Whilst the findings emphasize the potential of AI to enhance quality assurance in second-hand clothing markets, streamline textile sorting for donations and recycling, and reduce waste in the fashion industry, they also highlight gaps in the available datasets, often due to limited size and scope. The types of textiles captured were most commonly swatches of fabric, with 20 studies examining these, whereas whole garments were less frequently studied, with only 7 instances. This review concludes with insights into future research directions and the promising use of AI within fashion and textiles to facilitate a transition to a circular economy. This project was supported through RMIT University’s School of Fashion and Textiles internal seed funding (2024). Full article

Overconsumption and unplanned disposal of garments result in millions of tons of textile products going to landfills. Understanding the environmental benefits and impact of various recycling options is crucial for integrating recycling into the apparel waste stream. This study aims to assess the environmental impacts of products made from post-consumer textile waste fibers, highlighting the importance of closed-loop textile supply chains in developing countries. Using Open LCA software, the cradle-to-gate approach for life cycle assessment is used to calculate the environmental impacts of post-consumer textile waste, virgin cotton, virgin polyester fibers, and their blends in two different scenarios. The life cycle inventory data for functional units (1000 kg apparel) has been collected from the industrial units and the Ecoinvent v3.0 database. The results of 16 environmental impact categories are computed, showing that textile products made from virgin cotton fiber have 60% more global warming potential than those made from post-consumer textile waste fibers. Hence, the environmental impact of textile products can be controlled by recycling them. Consumption of post-consumer textile waste fiber is the key to reducing the new material needs in the textile supply chain. The closed-loop apparel supply chain can help developing countries generate maximum financial value with minimal environmental damage. In developing countries, value extraction from post-consumer textile waste recycling is essential to meet international consumer demands for cleaner production. Full article

Nowadays, the emphasis on sustainable performance highlights the necessity for resilience and innovation in tackling environmental and economic concerns within supply chain operations. Therefore, this study investigates the impact of six supply chain management practices (SCMPs) on organizational performance (OP) and environmental sustainability performance (ESP), along with the moderating role of supply chain dynamism. This research was conducted within medium and large export manufacturing firms in Jordan’s Garment, Textile, and Leather (GTL) sector, a pivotal export industry critical to the country’s economy. Data were gathered from 204 managers, employing an online self-administered questionnaire, using a quantitative research approach. The hypotheses were examined via structural equation modeling (SEM) through the SmartPLS software4. The findings reveal that ESP was significantly influenced by strategic supplier partnership and postponement. Additionally, the level of information sharing and internal lean practices were found to have a dual impact on both OP and ESP. Supply chain dynamism acted as a significant moderator only in the relationship between postponement and both OP and ESP. This study fills a significant gap in the GTL context in developing economies for export manufacturing firms that contribute to the current literature. What makes it original is its consideration of supply chain dynamism as a moderating variable and its context in an important sector for Jordan’s economy. In conclusion, the results present valuable implications for practitioners on developing custom SCMPs for sustainable and operational performance objectives in the dynamic supply chain context. Future studies should adopt probability sampling methods to improve the generalizability of the findings. Further, the findings should be confirmed by conducting a study on other exporting sectors or geographical areas to gain additional perspectives on the relationships between SCMPs, OP, and ESP. Full article

The significant waste generated by the fashion industry necessitates sustainable textile recycling strategies. Polyester, made from poly(ethylene terephthalate) (PET), is abundant in post-consumer textiles. Technologies have been developed to convert low-density garment waste into flakes, but the role of color sorting in achieving uniform aesthetics in injection-moldable plastics remains underexplored. This study compares materials extruded from dark color-sorted polyester garment flakes with those from light-color flakes in terms of processability in extrusion and injection molding. The properties examined include melt fluidity, injection molding shrinkage, and mechanical and thermal properties. Commercial chain extenders with anhydride, oxazoline, or epoxide reactive groups were added during extrusion. Interestingly, only dark-colored extruded pellets showed significant degradation, but all the chain extenders allowed melt fluidity to be controlled during reprocessing. The bisoxazoline-based additive was the most promising, due to the highly improved ductility of the samples, regardless of whether they were dark-colored or light-colored. The results indicate significant potential for the industrial recycling of post-consumer textiles and highlight the industrial feasibility of repurposing post-consumer polyester garments. This approach not only supports initiatives of circular economy but also offers a viable solution for managing textile waste, particularly in the fashion industry. Additionally, the suggested recycling route combats the production of microplastics. Full article

With the rapid development of wearable technology, multifunctional sensors have demonstrated immense application potential. However, the limitations of traditional rigid materials restrict the flexibility and widespread adoption of such sensors. Hydrogels, as flexible materials, provide an effective solution to this challenge due to their excellent stretchability, biocompatibility, and adaptability. This study developed a multifunctional flexible sensor based on a composite hydrogel of polyvinyl alcohol (PVA) and sodium alginate (SA), using poly(3,4-ethylenedioxythiophene)/polystyrene sulfonate (PEDOT:PSS) as the conductive material to achieve multifunctional detection of strain, temperature, and physiological signals. The sensor features a simple fabrication process, low cost, and low impedance. Experimental results show that the prepared hydrogel exhibits outstanding mechanical properties and conductivity, with a strength of 118.8 kPa, an elongation of 334%, and a conductivity of 256 mS/m. In strain sensing, the sensor demonstrates a rapid response to minor strains (4%), high sensitivity (gauge factors of 0.39 for 0–120% and 0.73 for 120–200% strain ranges), short response time (2.2 s), low hysteresis, and excellent cyclic stability (over 500 cycles). For temperature sensing, the sensor achieves high sensitivities of −27.43 Ω/K (resistance mode) and 0.729 mV/K (voltage mode), along with stable performance across varying temperature ranges. Furthermore, the sensor has been successfully applied to monitor human motion (e.g., finger bending, wrist movement) and physiological signals such as electrocardiogram (ECG), electromyogram (EMG), and electroencephalogram (EEG), highlighting its significant potential in wearable health monitoring. By employing a simple and efficient fabrication method, this study presents a high-performance multifunctional flexible sensor, offering novel insights and technical support for the advancement of wearable devices. Full article

Graphene quantum dots (GQDs) represent a class of promising nanomaterials characterized by adjustable optical properties, making them well suited for applications in biosensing and chemical detection. However, challenges persist in achieving scalable, cost-effective synthesis and enhancing detection sensitivity. In this study, we have developed a simple and environmentally friendly method to prepare blue graphene quantum dots, c-GQDs, using nitronaphthalene as a precursor, and yellow graphene quantum dots, y-GQDs, using nitronaphthalene doped acid. The quantum yield is 29.75%, and the average thickness is 2.08 nm and 3.95 nm, respectively. The synthesized c-GQDs exhibit a prominent cyan fluorescence at a wavelength of 490 nm under excitation at 380 nm, while the y-GQDs show a distinct yellow fluorescence at a wavelength of 540 nm under excitation at 494 nm. The introduction of p-aminobenzoic acid (PABA) introduced a marked red shift in fluorescence, attributed to the electron-withdrawing effect of the carboxyl groups on PABA. This key finding significantly enhanced the sensitivity of GQDs for detecting trace copper(II) ions (Cu²⁺), a heavy metal contaminant posing serious environmental risks. The fluorescence of the GQDs was selectively quenched in the presence of Cu²⁺, facilitating accurate and sensitive detection even in complex ion matrices. Mechanistic studies revealed that the quenching effect is driven by strong static quenching interactions, which inhibit non-radiative transitions. This work not only introduces a scalable method for producing high-performance GQDs but also highlights their potential as effective fluorescent probes for environmental monitoring and heavy metal ion detection. Full article

Methyl orange (MO) is an organic synthetic dye widely used in laboratory and industrial applications. In laboratory settings, it serves as an acid–base indicator due to its distinct color change in both acidic and alkaline environments. Industrially, it is primarily utilized in the textile industry for its ultraviolet (UV) absorption properties. However, the discharge and leakage of methyl orange into the environment can cause severe ecological damage and pose potential carcinogenic and teratogenic risks to human health. Therefore, detecting and quantifying the concentration of methyl orange in various matrices is crucial. This study reports the synthesis of graphene quantum dots (GQDs) from orange peel as a precursor, using ethanol and dimethylformamide (DMF) as solvents. Cyan (c-GQDs) and yellow (y-GQDs) graphene quantum dots were synthesized through a bottom-up hydrothermal method. The difference in color is attributed to the redshift caused by the varying ratio of pyridine nitrogen to pyrrole nitrogen. These GQDs exhibited notable optical properties, with c-GQDs emitting cyan fluorescence and y-GQDs emitting yellow fluorescence under UV light. To investigate fluorescence quenching effects, nine commonly used dyes were tested, and all were found to quench the fluorescence of y-GQDs, with methyl orange having the most significant effect. The fluorescence quenching of orange peel-derived GQDs in the presence of methyl orange is attributed to poor dispersion in DMF solution. Additionally, the GQDs possess high specific surface area, abundant surface functional groups, and excellent electronic conductivity, which contribute to their effective fluorescence quenching performance. The average thickness of y-GQDs (the vertical dimension from the substrate upwards) was 3.51 nm, confirming their graphene-like structure. They emitted yellow fluorescence within the wavelength range of 450–530 nm. Notably, a significant linear correlation was found between the concentration of methyl orange and the fluorescence intensity of y-GQDs (regression coefficient = 0.9954), indicating the potential of GQDs as effective sensing materials for organic pollutant detection. Full article

The goal of 3D simulation in the apparel industry is highly relevant in terms of sustainability, as the realistic visualization of textile drape and the drapability of textile surfaces plays a crucial role in reducing textile waste and optimizing resource use. It is a matter not only of generating photo-realistic images in 3D garment simulations, but also of making reliable predictions about the physical behavior of textile materials in order to achieve realistic outcomes. The prerequisite for 3D garment simulation is the correct application of standardized simulation programs, which is rarely accomplished in practice because the providers of 3D simulation software do not disclose their simulation algorithms, making accurate analysis difficult. In this study, an objective image comparison is carried out using the VStitcher simulation program as an example, which allows an assessment of the value of the relevant material parameters. A drape test is used as a validation method and the drape coefficient is calculated. Depending on the material and parameter settings, drape coefficients between 0.1 and 10% and between 0.7 and 70% are determined. By modifying the bending stiffness, the drape coefficient increases the most. By systematically varying and comparing these parameters, a deeper understanding of their influence can be obtained. The most significant effect on the drape coefficient (DC) is seen with increased bending stiffness, while changes in thickness, elongation, and shear stiffness have a minimal effect. Increased fabric thickness has a greater effect on appearance than on deformation. The digital parameters affect the simulation in much the same way as the physical textile parameters affect the real material. With VStitcher, the desired fabric changes are more effectively achieved by adjusting the bending stiffness and mass per area, while changes in thickness, elongation, and shear stiffness have little effect. Full article

The textile and garment care industries significantly impact ecological conditions and resources worldwide. Possible ways of minimizing the harmful influence on the environment include giving a preference to natural textiles; reducing the consumption rate by extending the lifespan of clothes, e.g., preserving colors and fibers; and using biodegradable garment care products. Wool is a natural fabric that must be washed with special laundry care products to preserve its initial appearance. Currently, there are no approaches that focus not only on preserving but also restoring wool fibers. To investigate the efficacy of biodegradable technology, consisting of natural-derived shikimic acid and L-arginine, in the restoration of wool fabric, SEM was applied. To analyze the obtained data, a novel three-point scale was suggested. In comparison with untreated samples, the composition promoted a smoothing of the scale structure of wool fibers of up to 34.87%. The system has shown efficacy in both the low pH (fabric softener) and high pH (laundry gel) systems. To further investigate biodegradable technology, the color retention of dark-colored cotton fabric was tested. It was shown that the composition promotes 96.15% color preservation after 10 laundry cycles when used in the fabric softener. Biodegradable technology is a promising solution for the maintenance of wool fabrics and color preservation solutions. Full article

Aloe vera is well known for its biological properties as a bioflavonoid anti-inflammatory and antibacterial agent. It has been used frequently in the food sector as a food coating due to its hygroscopic properties and as an ingredient in the lucrative cosmetic industry. Studies have also included aloe vera as an eco-friendly green solution based on these properties. The current research focuses on the use of aloe vera gel in printing pastes as an alternative sustainable solution to synthetic thickeners, evaluating its wet performance and ease of fabric stitching, and has been inspired by studies that similarly used this substance and measured its effect on the fabric’s coefficient of friction and antimicrobial action. In the current study, printing pastes with natural colourants, such as saffron, curcumin, and annatto, and aloe vera gel thickener derived from natural leaves from Crete increased the fabric’s mechanical resistance to abrasion compared to the untreated pastes. The measured performance did not differ substantially from prints with traditional synthetic pastes, hence tolerating the substitution with the non-contaminant variant. The enhanced resistance to abrasion and wear extends the fabric’s serviceable life and resulting garments, decreasing the need for high industry processing volumes and, as a result, reducing pollution. The resistance to wear was evaluated using the dominant method in textile testing of the Martindale apparatus, which measured the cycles to failure, weight loss, and general appearance deterioration using the official photographic standards. Full article

Regenerated cellulose fibers are a highly adaptable biomaterial with numerous medical applications owing to their inherent biocompatibility, biodegradability, and robust mechanical properties. In the domain of wound care, regenerated cellulose fibers facilitate a moist environment conducive to healing, minimize infection risk, and adapt to wound topographies, making it ideal for different types of dressings. In tissue engineering, cellulose scaffolds provide a matrix for cell attachment and proliferation, supporting the development of artificial skin, cartilage, and other tissues. Furthermore, regenerated cellulose fibers, used as absorbable sutures, degrade within the body, eliminating the need for removal and proving advantageous for internal suturing. The medical textile industry relies heavily on regenerated cellulose fibers because of their unique properties that make them suitable for various applications, including wound care, surgical garments, and diagnostic materials. Regenerated cellulose fibers are produced by dissolving cellulose from natural sources and reconstituting it into fiber form, which can be customized for specific medical uses. This paper will explore the various types, properties, and applications of regenerated cellulose fibers in medical contexts, alongside an examination of its manufacturing processes and technologies, as well as associated challenges. Full article

As economic growth and societal shifts reshape urban environments, cultural and creative industrial parks are emerging as vital contributors to sustainable urban development. The design of these landscapes plays a pivotal role in enhancing user satisfaction, increasing spatial attractiveness, and promoting eco-friendly urban practices. This study examines visitor landscape perception preferences in the Textile and Garment Cultural and Creative Industrial Park, located in Haizhu District, Guangzhou, through a novel methodology combining user-generated content (UGC), deep learning models, outdoor electrodermal activity (EDA) measurements, and questionnaire surveys. The UGC-based landscape recognition model achieved an accuracy of 86.8% and was validated against user preferences captured through questionnaires. Results demonstrate that visitors prefer areas featuring cultural landmarks and natural elements, while spaces dominated by human activity and transportation infrastructure are less favored. Key landscape elements, such as signage, thematic sculptures, brand logos, and trees, were identified as highly preferred features within the park. While EDA experiments revealed significant variations in physiological responses across different spatial settings, no strong correlation was observed between EDA indicators and subjective questionnaire scores. This integrative approach enables a comprehensive, objective assessment of landscape perception, providing a data-driven, user-centered framework for improving landscape design in cultural and creative industrial parks. Full article