Parametric characterization of nano-hybrid wood polymer composites using ANOVA and regression analysis

Abstract

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%.