Morphological characterization of wood plastic composite (WPC) with advanced\ud imaging tools : developing methodologies for reliable phase and internal damage\ud characterization

Graduation date: 2008Wood plastic composites (WPCs) are composite materials made from thermoplastic polymers, wood flour, and a small amount of process- and property-enhancing additives; they are principally used in the automotive industry and as secondary building materials. Although the WPC market is expected to keep growing, it is still relatively small when compared with other building materials. Challenges for increasing the market share of WPCs include relatively low tensile strength and stiffness, significant long-term creep deformations and weak creep rupture properties. A significant barrier to obtain better understanding of the composite performance and internal bond durability is the lack of reliable tools and procedures for direct quantitative measurement of the micro-mechanical response of this heterogeneous material. The objective of this study was to use advanced imaging tools, including X-ray computed tomography (CT) and conventional microscopy for quantitative morphological characterization of WPCs, with the focus on developing methodologies for reliable characterization of component phases and internal damage generated by accelerated weathering and cyclic loading.\ud \ud One of the primary concerns in X-ray CT scanning of WPCs is the poor contrast\ud between the wood and polyethylene, which is the most common polymer for the WPC matrix. The objective of the first part of the thesis was to investigate the applicability\ud of fine gold particles as contrast agent. Specifically, the effects of adding gold nano- and micro-particles, and commonly used surfactant on the mechanical properties of\ud WPCs was assessed. Technically pure gold micro-particles was found to be an effective contrast agent for X-ray CT scanning of wood/HDPE composites. When used without surfactant, the addition of 1% gold particles did not impair the tensile\ud properties of the composites.\ud \ud In order to establish effective experimental methodologies for morphological characterization of WPCs in the second part of the project, various imaging tools,\ud including X-ray CT scanning, optical and electron microscopy were applied to examine wood particles embedded in the polymer matrix. Scans and images of uncompounded wood particles were used for reference. Such a combination of the imaging tools assisted in confirmation of the existence of an extensive wood/polymer interphase within the wood particles. Using the X-ray CT scanning, the combined volume of the interphase was quantitatively determined to be about 56% of the wood particle volume. This knowledge is critically needed for the proper assessment of the wood particle content from the CT scans.\ud \ud The third part of the thesis reports on a research which is not part of the original MS\ud project, and is still in progress. This part was included to demonstrate how the\ud conclusions and methods derived in the previous two parts are applied in further\ud research. Here, the X-ray CT scanning technique is applied to examine the\ud morphological changes in WPCs resulting from accelerated weathering treatment and cyclic loading. It was found that significant initial tensile modulus loss in wood/PVC\ud composites may be induced by the relatively low number of accelerated soak-dry and\ud freeze-thaw weathering cycles. Although no significant modulus loss was observed for\ud the specimens subjected to cyclic tensile loading, the reduced residual strength\ud indicated a significant damage accumulation.\ud \ud In summary, X-ray CT scanning was found to be a promising and effective nondestructive technique for 3D in situ examination and morphological characterization of WPCs. The experimental methodologies employing various\ud imaging tools (including X-ray CT scanning and 2D microscopy) and digital image processing methods are capable of characterizing WPCs, its component phases and the interphase returning statistically meaningful quantitative data