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Flame-retardant finishing of cotton fabrics using DOPO functionalized alkoxy- and amido alkoxysilane
(2023)
In the present study, DOPO-based alkoxysilane (DOPO-ETES) and amido alkoxysilane (DOPO-AmdPTES) were synthesized by one-step and without by-products as halogen-free flame retardants. The flame retardants were applied on cotton fabric utilizing sol–gel method and pad-dry-cure finishing process. The flame retardancy, the thermal stability and the combustion ehaviour of treated cotton were evaluated by surface and bottom edge ignition flame test (according to EN ISO 15025), thermogravimetric analysis (TGA) and micro-scale combustion calorimeter (MCC). Unlike CO/DOPO-ETES sample, cotton treated with DOPO-AmdPTES nanosols exhibits self-extinguishing ehaviour with high char residue, an improvement of the LOI value and a significant reduction of the PHRR, HRC and THR compared to pristine cotton. Cotton finished with DOPO-AmdPTES reveals a semi-durability after ten laundering cycles keeping the flame-retardant properties unchanged. According to the results obtained from TGA-FTIR, Py-GC/MS and XPS, the major activity of flame retardant occurs in the condensed phase via catalytic induced char formation as physical barrier along with the activity in the gas phase derived mainly from the dilution effect. The early degradation of CO/DOPO-AmdPTES compared to CO/DOPO-ETES, triggered by the cleavage of the weak bond between P and C=O, as the DFT study indicated, provides the beneficial effect of this flame retardant on the fire resistance of cellulose.
It is widely recognized that Education for Sustainable Development (ESD) plays a critical role in creating a more sustainable world by fostering the development of the knowledge, skills, understanding, values, and actions necessary for such change (UNESCO, 2020). In this context, ESD represents a holistic approach that focuses on lifelong learning to create informed people who can make decisions today and in the future. Related to the textile and fashion industry, ESD is an appropriate approach to continuously implement sustainability aspects in education and training. To achieve this goal, the European project "Sustainable Fashion Curriculum at Textile Universities in Europe - Development, Implementation and Evaluation of a Teaching Module for Educators" (Fashion DIET) has developed a digital teaching module in a partnership between a University of Education and universities with textile departments. The main objective of the project is to elaborate an ESD module for university lecturers in order to introduce a sustainable fashion curriculum in textile universities in Europe and implement it in educational systems. The project therefore aims to train educators along the textile supply chain, to inform the young generation about the latest aspects of sustainability and raise awareness by implementing ESD in textile education. This paper presents the learning outcomes of the modules on sustainable fashion design and related production technologies developed by the technical university partners, as part of the total of 42 courses covering didactic-methodological approaches and the sustainable orientation of the fashion market, offered at the consortium level. The project content is made available as Open Educational Resources through Glocal Campus, an open-access e-learning platform that enables virtual collaboration between universities.
Patterns are virtually simulated in 3D CAD programs before production to check the fit. However, achieving lifelike representations of human avatars, especially regarding soft tissue dynamics, remains challenging. This is mainly since conventional avatars in garment CAD programs are simulated with a continuous hard surface and not corresponding to the human physical and mechanical body properties of soft tissue. In the real world, the human body’s natural shape is affected by the contact pressure of tight-fitting textiles. To verify the fit of a simulated garment, the interactions between the individual body shape and the garment must be considered. This paper introduces an innovative approach to digitising the softness of human tissue using 4D scanning technology. The primary objective of this research is to explore the interactions between tissue softness and different compression levels of apparel, exerting pressure on the tissue to capture the changes in the natural shape. Therefore, to generate data and model an avatar with soft body physics, it is essential to capture the deform ability and elasticity of the soft tissue and map it into the modification options for a simulation. To aim this, various methods from different fields were researched and compared to evaluate 4D scanning as the most suitable method for capturing tissue deformability in vivo. In particular, it should be considered that the human body has different deformation capabilities depending on age, the amount of muscle and body fat. In addition, different tissue zones have different mechanical properties, so it is essential to identify and classify them to back up these properties for the simulation. It has been shown that by digitising the obtained data of the different defined applied pressure levels, a prediction of the deformation of the tissue of the exact person becomes possible. As technology advances and data sets grow, this approach has the potential to reshape how we verify fit digitally with soft avatars and leverage their realistic soft tissue properties for various practical purposes.
In recent years, the demand for accurate and efficient 3D body scanning technologies has increased, driven by the growing interest in personalised textile development and health care. This position paper presents the implementation of a novel 3D body scanner that integrates multiple RGB cameras and image stitching techniques to generate detailed point clouds and 3D mesh models. Our system significantly enhances the scanning process, achieving higher resolution and fidelity while reducing the cost, time and effort required for data acquisition and processing. Furthermore, we evaluate the potential use cases and applications of our 3D body scanner, focusing on the textile technology and health sectors. In textile development, the 3D scanner contributes to bespoke clothing production, allowing designers to construct made-to-measure garments, thus minimising waste and enhancing customer satisfaction through fitting clothing. In mental health care, the 3D body scanner can be employed as a tool for body image analysis, providing valuable insights into the psychological and emotional aspects of self-perception. By exploring the synergy between the 3D body scanner and these fields, we aim to foster interdisciplinary collaborations that drive advancements in personalisation, sustainability, and well-being.
Der pH-Wert der menschlichen Haut liegt nicht im neutralen Bereich, sondern ist mit Werten von 3,5-6 – je nach Körperstelle – leicht Sauer. Das bietet der Kommensalen Hautflora einen geeigneten Lebensraum, wirkt jedoch abtötend auf einige pathogene Mikroorganismen und inaktivierend auf einige Viren. Dieser Säureschutzmantel der Haut stellt somit eine erste äußere Schutzschicht vor dem Befall von Krankheitserregern dar. Ein entsprechender Oberflächen-pH-Wert auf Textilien kann dazu beitragen, die Übertragung von Krankheitserregern durch die Kleidung von Mitarbeitern im Gesundheitswesen zu minimieren und gleichzeitig keinen negativen Einfluss auf die hauteigene Flora auszuüben. Zudem kann die Besiedlung von z.B. Bettwäsche durch pathogene Mikroorganismen vermindert werden. Einen positiven Einfluss kann dies zudem auf die bakterienassoziierte Geruchsbildung auf Funktionskleidung haben.
The pH value of the human skin is not in the neutral range but is slightly acidic with values of – depending on the body part – 3.5 to 6. This provides a suitable habitat for the commensal skin floral but has a killing effect on some pathogenic micro-organisms and an inactivating effect on some viruses. This protective acid mantle of the skin thus represents a first external protective layer against infestation by pathogens. An appropriate surface pH on textiles can help to minimize the transmission of pathogens through the clothing of healthcare workers while at the same time not exerting a negative influence on the skin’s own flora. In addition, the colonization of e.g. bed linen by pathogenic microorganisms can be reduced. This can also have a positive influence on bacteria-associated odor formation on functional clothing.
The pH value of the human skin is not in the neutral range but is slightly acidic with values of – depending on the body part – 3.5 to 6. This provides a suitable habitat for the commensal skin floral but has a killing effect on some pathogenic micro-organisms and an inactivating effect on some viruses. This protective acid mantle of the skin thus represents a first external protective layer against infestation by pathogens. An appropriate surface pH on textiles can help to minimize the transmission of pathogens through the clothing of healthcare workers while at the same time not exerting a negative influence on the skin’s own flora. In addition, the colonization of e.g. bed linen by pathogenic microorganisms can be reduced. This can also have a positive influence on bacteria-associated odor formation on functional clothing.
Der pH-Wert der menschlichen Haut liegt nicht im neutralen Bereich, sondern ist mit Werten von 3,5-6 – je nach Körperstelle – leicht Sauer. Das bietet der Kommensalen Hautflora einen geeigneten Lebensraum, wirkt jedoch abtötend auf einige pathogene Mikroorganismen und inaktivierend auf einige Viren. Dieser Säureschutzmantel der Haut stellt somit eine erste äußere Schutzschicht vor dem Befall von Krankheitserregern dar. Ein entsprechender Oberflächen-pH-Wert auf Textilien kann dazu beitragen, die Übertragung von Krankheitserregern durch die Kleidung von Mitarbeitern im Gesundheitswesen zu minimieren und gleichzeitig keinen negativen Einfluss auf die hauteigene Flora auszuüben. Zudem kann die Besiedlung von z.B. Bettwäsche durch pathogene Mikroorganismen vermindert werden. Einen positiven Einfluss kann dies zudem auf die bakterienassoziierte Geruchsbildung auf Funktionskleidung haben.
Cotton contamination by honeydew is considered one of the significant problems for quality in textiles as it causes stickiness during manufacturing. Therefore, millions of dollars in losses are attributed to honeydew contamination each year. This work presents the use of UV hyperspectral imaging (225–300 nm) to characterize honeydew contamination on raw cotton samples. As reference samples, cotton samples were soaked in solutions containing sugar and proteins at different concentrations to mimic honeydew. Multivariate techniques such as a principal component analysis (PCA) and partial least squares regression (PLS-R) were used to predict and classify the amount of honeydew at each pixel of a hyperspectral image of raw cotton samples. The results show that the PCA model was able to differentiate cotton samples based on their sugar concentrations. The first two principal components (PCs) explain nearly 91.0% of the total variance. A PLS-R model was built, showing a performance with a coefficient of determination for the validation (R2cv) = 0.91 and root mean square error of cross-validation (RMSECV) = 0.036 g. This PLS-R model was able to predict the honeydew content in grams on raw cotton samples for each pixel. In conclusion, UV hyperspectral imaging, in combination with multivariate data analysis, shows high potential for quality control in textiles.