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Experimental Numerical and Analytical Study on The Effect of Graphene Oxide in The Mechanical Properties of a Solvent-Free Reinforced Epoxy Resin

机译:氧化石墨烯对无溶剂增强环氧树脂力学性能影响的实验数值和分析研究

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摘要

This paper presents a methodology for manufacturing nanocomposites from an epoxy resin reinforced with graphene oxide (GO) nanoparticles. A scalable and sustainable fabrication process, based on a solvent-free method, is proposed with the objective of achieving a high level of GO dispersion, while maintaining matrix performance. The results of three-point bending tests are examined by means of an analytical technique which allows determining the mechanical response of the material under tension and compression from flexural data. As result, an increase of 39% in the compressive elastic modulus of the nanocomposite is found with the addition of 0.3 wt % GO. In parallel, we described how the strain distribution and the failure modes vary with the amount of reinforcement based on digital image correlation (DIC) techniques and scanning electron microscopy (SEM). A novel analytical model, capable of predicting the influence of GO content on the elastic properties of the material, is obtained. Numerical simulations considering the experimental conditions are carried out. the full strain field given by the DIC system is successfully reproduced by means of the finite element method (FEM). While, the experimental failure is explained by the crack growth simulations using the eXtended finite element method (XFEM).
机译:本文提出了一种由用氧化石墨烯(GO)纳米颗粒增强的环氧树脂制造纳米复合材料的方法。提出了一种基于无溶剂方法的可扩展且可持续的制造工艺,目的是在保持基质性能的同时实现高水平的GO分散性。通过分析技术检查三点弯曲测试的结果,该分析技术可以根据弯曲数据确定材料在拉伸和压缩状态下的机械响应。结果发现,通过添加0.3重量%的GO,纳米复合材料的压缩弹性模量增加了39%。并行地,我们基于数字图像相关(DIC)技术和扫描电子显微镜(SEM)描述了应变分布和破坏模式如何随钢筋数量的变化而变化。获得了一种新颖的分析模型,该模型能够预测GO含量对材料弹性性能的影响。进行了考虑实验条件的数值模拟。 DIC系统给出的完整应变场可以通过有限元方法(FEM)成功复制。同时,通过使用扩展有限元方法(XFEM)进行的裂纹扩展模拟来解释实验失败。

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