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Multiscale Modeling: Thermal Conductivity of Graphene/Cycloaliphatic Epoxy Composites

机译:多尺度建模:石墨烯/脂环族环氧复合材料的导热系数

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摘要

The thermal property of epoxy as the binder in the Carbon Fiber (CF) composites, especially thermal conductivity is important to achieve the advance technology and to improve the performance of materials. Multiscale modeling including molecular dynamic (MD) modeling and micromechanical modeling is used to study the properties of neat Cycloaliphatic Epoxies (CE) and Graphene nanoplatelet (GNP)/CE with and without covalent functionalization.;The thermal properties (glass-transition temperature, thermal expansion coefficient, and thermal conductivity) and mechanical properties of CE system are investigated by MD modeling using OPLS-All Atom force field. A unique crosslinking technique is developed to achieve the cured CE models which has the complex curing mechanism. The thermal conductivity and elastic modulus of CF/CE models are further calculated by using micromechanical modeling. The results are validated with the experiments which are in good agreement.;GNP/CE nanocomposites models are established by MD with four different levels of GNP dispersion, namely, 1, 2, 3, and 4 layer(s) of graphene. The thermal conductivities of GNP/CE nanocomposites models are determined by Equilibrium MD (EMD) method. The thermal conductivities are randomized by arithmetic average and varied GNP volume fractions using micromechanics. The resultant thermal conductivities increase with the GNP volume fraction and the better dispersion which compared well with experiments. The 1-layered GNP/CE (perfectly dispersed) model gives the highest thermal conductivity.;The covalently functionalized GNP (fGNP)/CE models are created by functionalizing carboxyl groups onto the single-layered GNP surfaces by MD modeling. The similar method for the pristine GNP/CE models is applied to obtain the effective thermal conductivities fGNP/CE composites. The predicted values suggest that the thermal conductivity decreases with increased functionalization on GNP due to the GNP defect. However, the thermal conductivities of fGNP/CE models are higher than the thermal conductivities of 2, 3, and 4-layer GNP/CE models which the experiment found that the functionalization improves the dispersion.;The coefficients of linear thermal expansion (CLTE) of GNP/EPON862 system are studied with the similar work flow which the results show the improvement of CLTE regarding to GNP dispersion. Finally, the GNP aspect ratio is included to improve the micromechanical modeling for thermal conductivity.
机译:环氧作为碳纤维(CF)复合材料中的粘合剂的热性能,特别是导热性对于实现先进技术和改善材料性能非常重要。多尺度建模包括分子动力学(MD)建模和微机械建模,用于研究具有和不具有共价官能化的纯脂环族环氧树脂(CE)和石墨烯纳米片(GNP)/ CE的特性;热特性(玻璃化转变温度,热通过使用OPLS-All Atom力场的MD建模,研究了CE系统的热膨胀系数,导热系数和机械性能。开发了一种独特的交联技术以实现具有复杂固化机制的固化CE模型。 CF / CE模型的导热系数和弹性模量通过使用微机械模型进一步计算。实验结果吻合良好。;通过MD建立GNP / CE纳米复合材料模型,该模型具有四种不同水平的GNP分散度,分别为1、2、3和4层石墨烯。 GNP / CE纳米复合材料模型的热导率通过平衡MD(EMD)方法确定。使用微力学,通过算术平均值和变化的GNP体积分数将热导率随机化。与实验相比,所得的热导率随GNP体积分数和更好的分散性而增加。 1层GNP / CE(完全分散)模型具有最高的导热性。通过MD建模,通过将羧基官能化到单层GNP表面上来创建共价官能化GNP(fGNP)/ CE模型。将原始GNP / CE模型的相似方法应用于获得有效的热导率fGNP / CE复合材料。预测值表明,由于GNP缺陷,导热率随GNP官能度的增加而降低。然而,fGNP / CE模型的热导率高于2层,3层和4层GNP / CE模型的热导率,实验发现功能化可以改善分散性。;线性热膨胀系数(CLTE)以相似的工作流程对GNP / EPON862系统进行了研究,结果表明CLTE在GNP色散方面得到了改善。最后,包括GNP纵横比以改善导热系数的微机械建模。

著录项

  • 作者

    Chinkanjanarot, Sorayot.;

  • 作者单位

    Michigan Technological University.;

  • 授予单位 Michigan Technological University.;
  • 学科 Mechanical engineering.;Computational chemistry.
  • 学位 Ph.D.
  • 年度 2017
  • 页码 131 p.
  • 总页数 131
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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