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  • Open Access


    Fabrication of High Toughness Silk Fibroin/Tungsten Disulfide Nanoparticles Hybrid Fiber and Self-Heating Textile by Wet Spinning

    Jianjun Guo1,2, Lingling Jia3, Sandra Senyo Fometu4, Qiang Ma5, Jinjin Wang1, Hang Li1, Lei Jiang5, Guohua Wu1,*

    Journal of Renewable Materials, Vol.10, No.12, pp. 3373-3389, 2022, DOI:10.32604/jrm.2022.021087

    Abstract Traditionally, silkworm silk has been used to make high-quality textiles. Nevertheless, various wastes from silkworm silk textiles that are no longer used are increasing, which is also causing considerable waste and contamination. This issue is causing widespread concern in countries that use more silk. Regenerated silk fibroin (RSF) fibers have been shown to be fragile and tender, which prohibits RSF from being widely used as a structural component. Therefore, enriching the function of silk and enhancing the RSF mechanical properties are important directions to expand the comprehensive utilization of silk products. In the present research, wet spinning was used to… More >

  • Open Access


    Machine Learning-Based Predictions on the Self-Heating Characteristics of Nanocomposites with Hybrid Fillers

    Taegeon Kil1, D. I. Jang1, H. N. Yoon1, Beomjoo Yang2,*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4487-4502, 2022, DOI:10.32604/cmc.2022.020940

    Abstract A machine learning-based prediction of the self-heating characteristics and the negative temperature coefficient (NTC) effect detection of nanocomposites incorporating carbon nanotube (CNT) and carbon fiber (CF) is proposed. The CNT content was fixed at 4.0 wt.%, and CFs having three different lengths (0.1, 3 and 6 mm) at dosage of 1.0 wt.% were added to fabricate the specimens. The self-heating properties of the specimens were evaluated via self-heating tests. Based on the experiment results, two types of artificial neural network (ANN) models were constructed to predict the surface temperature and electrical resistance, and to detect a severe NTC effect. The… More >

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