Optimization of Fabrication Technique to Prepare Acacia Wood Reinforced Bio-Composites

Md Rezaur, Rahman and Hamdan, Sinin and Siti Noor Linda, Taib and Rubiyah, Baini (2019) Optimization of Fabrication Technique to Prepare Acacia Wood Reinforced Bio-Composites. In: Acacia Wood Bio-composites. Springer International Publishing, pp. 49-102. ISBN 978-030-29627-8

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Abstract

This chapter discuss the preparation and optimization of wood polymer composites based on the impregnation by polymer and nanoclay. Wood impregnation is one of the basic and most frequently used techniques to enhance the wood properties. This fabrication technique offers a wide range of applications depending on type of impregnants applied. Impregnation could make the wood less flammable, more dimensionally stable, more resistant to decay, harder, stronger, and more stable against UV rays. Softwood (Acacia) was impregnated with acrylonitrile, poly(vinyl) alcohol and organically nanoclay. The specimen preparation was carried out using the vacuum-chamber in a laboratory scale. The physical and mechanical properties of the modified wood were analyzed through Tensile and Flexural tests, SEM, FTIR, TGA and DSC. Mechanical test results shown that Tensile and Flexural strength have improvements with the addition of the nanofillers. The FTIR test shown that the chemical bonding between PVA into the wood cell would certainly enhance the matrix adhesion and contribute to its property enhancement. SEM illustrate the samples surface morphology which confirm the impregnation of the specimen. TGA results shown the additives impregnate into the wood component increase the thermal stability compared to the raw wood. DSC results indicate the impregnate wood has a higher melting temperature compared to the raw wood, due to existing of the polymer and nanoclay interfacial bonding among cell wall of the wood. Response surface methodology (RSM) was used to optimize the conditions for the preparation of wood composites. The design experiment was carried out using Design Expert 11.

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