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Parametric characterization of nano-hybrid wood polymer composites using ANOVA and regression analysis
Structures ( IF 3.9 ) Pub Date : 2020-12-11 , DOI: 10.1016/j.istruc.2020.11.069
Abraham Elmushyakhi

The need to reduce waste is driving the development of new materials and technologies that support the transition of societies towards a more environmentally sustainable world. Wood-polymer composites (WPCs) can be produced by using waste products deriving from wood and plastic manufacturing industries. Enhanced mechanical and physical properties of WPCs also allow for these materials to substitute their conventional counterparts, especially the ones intended to be used in dry and hot environments. This paper examined how the addition of various reinforcements influenced the properties of polymer matrix-based WPC. More closely, this paper focused on assessing the mechanical properties of Polymethylmethacrylate (PMMA) and date palm leaves-based composite samples with different reinforcement types of recycled Polyethylene Terephthalate (PETE) fibers and nano-Aluminum Oxide (nano-Al2O3) particles. A two-way ANOVA and multivariate linear regression models are developed to predict and examine the effects and the interaction between the effect of batches and series on density, absorption, strength, modulus and absorbed energy before and after aging. The results suggest that combining the PMMA with recycled date palm leaves and including a mixture of commercially available PETE fiber reinforcements along with nano-Al2O3 particles produces samples that show enhanced mechanical and water resistance properties compared to composites without such reinforcements. The analysis used to detect the WPC combination and reinforcements embedded in the composite structure indicated that the reinforcements limited the absorption of water. The mechanical tests conducted on the reinforced WPC samples showed an improvement of mechanical characteristics. Adding both recycled PETE fibers and nano-Al2O3 particles to the samples increases the flexural characteristics and shows the largest capacity to absorb energy at impact followed by single reinforcement samples. For samples that underwent aging in chloride solution (offshore simulation), the enhanced capabilities were reduced by 8 and 15%.



中文翻译:

基于ANOVA和回归分析的纳米杂化木材聚合物复合材料的参数表征

减少浪费的需求正在推动新材料和新技术的发展,这些新材料和技术将支持社会向更加环境可持续的世界过渡。木质聚合物复合材料(WPC)可以通过使用木材和塑料制造业的废品来生产。WPC增强的机械和物理性能也使这些材料可以替代其传统的对应材料,尤其是打算用于干燥和高温环境的材料。本文研究了各种增强材料的添加如何影响基于聚合物基质的WPC的性能。更紧密,2 O 3)颗粒。建立了双向ANOVA和多元线性回归模型,以预测和检查老化前后批次和系列对密度,吸收率,强度,模量和吸收能的影响以及它们之间的相互作用。结果表明,将PMMA与可回收的枣椰子叶结合使用,并包括市售PETE纤维增强材料与纳米Al 2 O 3的混合物与没有这种增强材料的复合材料相比,这种颗粒所产生的样品显示出增强的机械和耐水性。用于检测WPC组合和嵌入复合结构的增强材料的分析表明,增强材料限制了水的吸收。对增强的WPC样品进行的机械测试显示出机械特性的改善。将回收的PETE纤维和纳米Al 2 O 3颗粒都添加到样品中可提高弯曲特性,并显示最大的冲击吸收能量的能力,其次是单个增强样品。对于在氯化物溶液中经过老化的样品(海上模拟),增强的功能分别降低了8%和15%。

更新日期:2020-12-12
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