Hasil untuk "Textile bleaching, dyeing, printing, etc."

Md. Belal Uddin Rabbi, Sultana Bedoura

Kunal Singha, Anjali Agrawal

Manisha Yadav, Nagender Singh, Shelly Khanna

Shipra Agarwal, Aahana Sharma, Abhilasha Mishra

Shelly Khanna, Manisha Yadav, Nagender Singh et al.

Mahmuda Akter, Aiasha Siddiqua, Maitree Howlader et al.

Akanksha Nautiyal, Sandeep Kidile, Shruti Ghadge et al.

Kumar Ghosh, Chandra Jeet Singh, Harun Venkatesan et al.

Danmei Sun, Madiha Ahmad, Muhammad Owais Raza Siddiqui et al.

Subhadeep Paul, Sourav Banerjee, S. Wazed Ali et al.

Chintan R. Madhu

Juro Živičnjak, Antoneta Tomljenović, Igor Zjakić

During use, the surface of textile fabrics is prone to wear, which can cause changes such as pilling. Pilling (entanglement of fibers) is primarily assessed using the standard visual method EN ISO 12945-4:2020, but it can also be quantitatively measured by instrumental methods with image analysis software. Due to non-uniform digital imaging conditions, such as variations in magnification and analyzed surface area, the assessed area is often inconsistent. As a result, the total percentage of the fabric specimen surface area covered with pills is often omitted. To ensure uniform digital imaging, an innovative apparatus was designed and constructed in this research and applied to woven fabrics made from 100% cotton, wool, viscose, polyamide 6.6, polyester, and acrylic fiber. Pilling in the fabric specimens was induced by rubbing with the Martindale pilling tester (EN ISO 12945-2:2020) using two different abradant materials, through predefined pilling rubs ranging from 125 to 30,000. Pilling assessment was conducted using both the visual method and the improved instrumental method, following established grading classes based on the total percentage of the fabric specimen surface area covered with pills. The research results highlight the importance of uniform digital imaging and digital grading, as these demonstrate the high comparability of pilling grades assigned by the standard visual method while providing better distinction between consecutive grades.

T. Nageshkumar, Prateek Shrivastava, L. Ammayapan et al.

Machine learning model coupled with graphical user interface was developed to predict mechanical properties of flax fiber. The experiment was conducted using test setup which applies constant rate of loading (CRL). Flax fiber was tested under five independent parameters i.e, type of fiber (Tf), moisture content (Mc), weight of sample (Ws), gauge length (Gl) and loading rate (Lr) with response variables, i.e., breaking load and elongation. In this study, a total of 432 patterns of input and output parameters obtained from laboratory experiments were used to develop machine learning algorithms (Random forest, support vector, and XGBoost). Among the machine learning models, random forest regressor yielded high R2 value, low mean squared error (MSE), and mean absolute error (MAE). The SHapley Additive exPlanations (SHAP) analysis was performed and found sample weight and gauge length were the most influential features for breaking load and elongation, respectively. The developed GUI, integrated with a random forest regressor, predicted breaking load and elongation with an error range of −2.5% to 2.3% for raw fiber and 1.5% to 6.5% for cleaned fiber. The developed GUI coupled random forest regressor can be used to predict the mechanical properties of fibers with ease.

José Augusto de la Fuente León, Ma. Alejandrina Martínez Gámez, José Luis Lucio Martinez et al.

In this study, we demonstrate a proof of principle of an all-fiber random laser due to the plasmonic effect. This was achieved with a fiber co-doped with bismuth/aluminum/yttria/silver in which a microsphere (microcavity) at the fiber’s tip was made using a splicing machine. The presence of bismuth and silver nanoparticles in the fiber along with bismuth–aluminum phototropic centers stands behind the observed phenomenon. The effect can be attributed to the in-pair functioning of this unit as an active medium and volumetric plasmonic feedback, resulting in lasing at 807 nm under 532 nm pumping with a notably low (~2 mW) threshold.

علیرضا طاهری مقدم, سمانه کاظم نژاد

گنبد سبز مشهد یکی از بناهای تاریخی دوره صفویه و تزیینات اصلی این آرامگاه شامل کاشی‌کاری‌های بیرونی متعلق به دوره پهلوی است. هدف از این پژوهش، شناسایی پالت رنگی کاشی‌کاری‌های گنبد سبز و تطبیق کمّی رنگ‌ها براساس سیستم رنگی NCS است. نظر به اهمیت و نقش محوری عنصر رنگ در هنر کاشی‌کاری ایرانی، این پژوهش در پی پاسخ به دو پرسش اساسی است: نخست آنکه معادل‌سازی کمّی پالت رنگی کاشی‌های بنای گنبد سبز براساس سیستم استاندارد رنگی NCS چیست؟ و دوم اینکه میزان فراوانی و قدرت رنگی در پالت کاشی‌کاری بنای گنبد سبز چگونه است و رنگ‌های غالب آن کدام هستند؟ روش گردآوری داده‌ها بر اساس مطالعات میدانی میدانی و از طریق انطباق سیستم رنگ NCS با کاشی‌های اصیل بنا است. در نتیجه تطبیق رنگ‌ها، ۱۲۲ کد رنگی از ۷ خانواده رنگی به دست آمد و با روش توصیفی-تحلیلی مورد بررسی و ارزیابی قرار گرفت. علاوه بر این، رنگ های غالب، قدرت رنگی و درصد تنوع رنگی نیز مشخص شد. نتایج نشان می‌دهد که هر چه رنگ‌ها روشن‌تر باشند، دامنه رنگی آن‌ها گسترده‌تر می‌شود و هر چه به سمت رنگ‌های تیره نزدیک می‌شویم، تنوع رنگی آن‌ها کاهش یافته و رنگ‌ها یکنواخت‌تر می‌شوند.

Katarzyna Grabowska, Łukasz Januszkiewicz, Ewelina Pabjańczyk-Wlazło

This study explores the electromagnetic properties of flat textile products enhanced with carbon nanotube (CNT) threads used as the weft. CNT threads, fabricated via dry-spinning, were integrated into fabrics by wrapping them around steel threads to form a solenoid-like structure. To further improve electromagnetic attenuation, the CNT yarn was coated with graphene oxide and silver nanoparticles. The research assessed the impact of these modifications on the fabric’s ability to attenuate alternating electromagnetic fields across a range of frequencies. Results showed enhanced attenuation at 30 MHz and 500 MHz. CNT yarn wrapped around steel threads achieved attenuation efficiencies of 18 dB at 30 MHz and 22 dB at 500 MHz, with a notable 10 dB improvement at 30 MHz over the reference. Fabrics with CNT yarn coated with graphene oxide demonstrated similar performance to the reference fabric at 500 MHz and an 8 dB increase at 30 MHz. Similarly, CNT yarn with silver nanoparticles showed comparable performance at higher frequencies but matched the reference at 30 MHz. These results indicate significant enhancement at lower frequencies, with benefits diminishing at higher. This study underscores the potential of integrating CNTs and metal nanoparticles into textiles to improve electromagnetic shielding, especially across specific frequencies.

Zheng Yong, Qi Yexiong, Qi Xiaoling et al.

The helmet shell material featuring a gradient in bending is urgently required for the next-generation integrated helmet system. However, achieving a bending gradient design for orthogonal woven composites on a 3D shell surface is a significant challenge. Here, nonorthogonal woven composites at 30°, 45°, and 60° were fabricated, and their bending properties are discussed. Furthermore, their bending properties are compared to those of plain off-axis woven composites, which indicates that the bending linearity trend of nonorthogonal woven composites is evident. Notably, the bending strength of the 30° and 60° nonorthogonal woven composites is 66.9 and 67.4% higher, respectively, than that of the plain off-axis woven composites, and the bending modulus is 169.8 and 196.9% higher, respectively. Finally, a finite element analysis of the bending properties of nonorthogonal woven composites was conducted, and a stress analysis of the inner layers was also conducted. This work paves the way for designing gradient materials for helmet shells.

Silas M. Mbeche, Paul M. Wambua, David N. Githinji

Human hair (HH) is considered a waste material generated in salons and barbershops in most societies, especially highly populated cities, where it is produced in large quantities, thus rekindling the interests of academics. Several studies are ongoing on the possibility of utilizing it as a reinforcement in polymer composites, either in its raw form or as extracted keratin nanoparticles, due to its unique features and the current global emphasis on circular economy. The present review seeks to provide a synopsis of recent developments in the utilization of HH and keratin in polymer composites. Composites from different HH loading, length, and chemical treatments were made using hand lay-up and hot compression molding methods. HH has been investigated in diverse composite systems, encompassing HH/natural fiber composites, HH/synthetic fiber composites, and keratin-reinforced composites. Our study revealed that these innovative materials exhibit enhanced energy absorption capacity, mechanical strength, hardness, and thermal properties, positioning them as promising choices for a wide range of engineering applications. The review further revealed that keratin nano-particles can be extracted from waste HH using various methods such as reduction alkaline hydrolysis and can be used as reinforcement in polymer composites.