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Comparative evaluation of fiber treatments on the creep behavior of jute/green epoxy composites

机译:纤维处理对黄麻/绿色环氧复合材料蠕变行为的比较评估

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摘要

This work presents the short term creep behavior of novel treated jute fabric reinforced green epoxy composites. Jute fabric was treated with CO2 pulsed infrared laser, ozone, enzyme and plasma. The treated jute fibers were characterized by scanning electron microscopy (SEM). Composites were prepared by hand layup method and compression molding technique. The creep and dynamic mechanical tests were performed in three-point bending mode by dynamic mechanical analyzer (DMA). The creep strain was experiential to increase with temperature. The treated composites exhibited less creep strain than untreated one at all temperatures. The best result in terms of creep deformation is presented by laser treated composite which dominantly exhibited elastic behavior rather than viscous behavior, especially at higher temperatures. The Burgers four parameters model was used to fit the experimental creep data using R statistical computing software. A good agreement between experimental data and theoretical curves were obtained. Dynamic mechanical analysis results revealed the reduction in the tangent delta peak height of treated composites, might be due to improvement in fiber/matrix interfacial adhesion. The degree of interfacial adhesion between the jute fiber and green epoxy was also anticipated using adhesion factor obtained through DMA data and laser treated composite revealed the better interlocking of fibers and matrix at the interface. (C) 2015 Elsevier Ltd. All rights reserved.
机译:这项工作提出了新型经处理的黄麻织物增强的绿色环氧复合材料的短期蠕变行为。黄麻织物经过CO2脉冲红外激光,臭氧,酶和等离子体处理。经处理的黄麻纤维通过扫描电子显微镜(SEM)表征。通过手工铺层法和压塑技术制备复合材料。蠕变和动态力学测试是通过动态力学分析仪(DMA)在三点弯曲模式下进行的。蠕变应变随温度增加而增大。在所有温度下,经过处理的复合材料均表现出比未经处理的复合材料更低的蠕变应变。蠕变变形方面的最佳结果是通过激光处理的复合材料呈现的,该复合材料主要表现出弹性行为而不是粘性行为,尤其是在较高温度下。使用R统计计算软件,使用Burgers四参数模型拟合实验蠕变数据。实验数据和理论曲线之间取得了很好的一致性。动态力学分析结果表明,处理后的复合材料的切线δ峰高降低,可能是由于纤维/基质界面粘合力的提高。黄麻纤维和绿色环氧树脂之间的界面粘合程度也可以通过使用DMA数据获得的粘合因子来预测,激光处理的复合材料显示出纤维和基质在界面处的更好的互锁。 (C)2015 Elsevier Ltd.保留所有权利。

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