Microscale X-ray computed tomography (XCT) is discussed as a technique for identifying 3D adhesive distribution in wood-adhesive bondlines. Visualization and material segmentation of the adhesives from the surrounding cellular structures require sufficient gray-scale contrast in the reconstructed XCT data. Commercial wood-adhesive polymers have similar chemical characteristics and density to wood cell wall polymers and therefore do not provide good XCT attenuation contrast in their native form. Here, three different adhesive types, namely phenol formaldehyde, polymeric diphenylmethane diisocyanate, and a hybrid polyvinyl acetate, are tagged with iodine such that they yield sufficient X-ray attenuation contrast. However, phase-contrast effects at material edges complicate image quality and segmentation in XCT data reconstructed with conventional filtered backprojection absorption contrast algorithms. A quantitative phase retrieval algorithm, which isolates and removes the phase-contrast effect, was demonstrated. The article discusses and illustrates the balance between material X-ray attenuation and phase-contrast effects in all quantitative XCT analyses of wood-adhesive bondlines.
By combining advanced imaging tools with morphology-based numerical modelling, a methodology has been proposed to measure the wood-adhesive bond performance at the micro level. Through this integration of multi-modal and multi-scale tools, this methodology provides a tool to understand the complex interactions between wood and adhesive phases at a microscale. Focusing all measurements and modelling on matched physical specimens avoided many simplifying assumptions. Direct measurement of strain development validated that the model was capable of representing the effects of cellular structure and adhesive penetration. With this measurement tool one can analyse stress and strain distribution patterns throughout adhesively bonded materials and virtually experiment with a range of variables like adhesive properties, wood species, compression levels, processing parameters, penetration patters, etc.
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