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首页> 外文期刊>Journal of Macromolecular Science. Physics >Predictions of Young's Modulus of Polymer Composites Reinforced with Short Natural Fibers
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Predictions of Young's Modulus of Polymer Composites Reinforced with Short Natural Fibers

机译:天然短纤维增强的聚合物复合材料的杨氏模量的预测

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摘要

Polymers reinforced with natural fibers are beneficial to prepare biodegradable composite materials. A new expression for the Young's modulus of short, natural fiber (SNF) reinforced polymer composites was derived based on a micro-mechanical model. The Young's moduli of poly(lactic acid) reinforced with reed fibers and low-density polyethylene (LDPE) reinforced with sisal fibers, from literature data, were estimated in the fiber weight fraction range from 0 to 50% using the equation and both the compounding rule and the Halpin-Tsai equation, and the estimations were compared with the reported measured data. The results showed that the predictions of the Young's moduli by means of the new Young's modulus equation were close to the measured data from the low density polyethylene/sisal fiber composites, as well as the poly(lactic acid)/reed composites at high fiber concentration. Comparing with other Young's modulus equations, the new Young's modulus equation would be more convenient to use owing to the parameters in the equation being easily determined.
机译:用天然纤维增强的聚合物有利于制备可生物降解的复合材料。基于微机械模型,推导了短天然纤维(SNF)增强聚合物复合材料的杨氏模量的新表达式。用文献数据估计,用芦苇纤维增强的聚乳酸和剑麻纤维增强的低密度聚乙烯(LDPE)的杨氏模量在0至50%的纤维重量分数范围内使用规则和Halpin-Tsai方程,并将估计值与报告的测量数据进行比较。结果表明,通过新的杨氏模量方程对杨氏模量的预测接近于低密度聚乙烯/剑麻纤维复合材料以及高纤维浓度下的聚乳酸/芦苇复合材料的测量数据。 。与其他杨氏模量方程相比,新的杨氏模量方程将更易于使用,因为该方程中的参数易于确定。

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