Image credit: THE ROYAL SOCIETYAbstract
For wood to be used to its full potential as an engineering material, it is necessary to quantify links between its cell geometry and the properties it exhibits at bulk scale. Doing so will make it possible to predict timber properties crucial to engineering, such as mechanical strength and stiffness, and the resistance to fluid flow, and to inform strategies to improve those properties as required, as well as to measure the effects of interventions such as genetic manipulation and chemical modification. Strength, stiffness and permeability of timber all derive from the geometry of its cells, and yet current practice is to predict them based on properties, such as bulk density, that do not directly describe the cell structure. This work explores links between micro-computed tomography data for structural-size pieces of wood, which show the variation of porosity across the wood’s ring structure, and high-resolution tomography showing the geometry of the cells, from which we measure cell length, lumen area, porosity, cell wall thickness and the number density of cells. High-resolution scans, while informative, are time-consuming and expensive to run on a large number of samples at the scale of building components. By scanning the same volume of timber at both low and high resolutions (high-resolution scans over a near-continuous volume of timber of approx. 20 mm$^3$ at 15 μm$^3$ per voxel), we are able to demonstrate correlations between the measurements at the two different resolutions, reveal the physical basis for these correlations, and demonstrate that the data from the low-resolution scan can be used to estimate the variation in (small-scale) cell geometry throughout a structural-size piece of wood.
Guanglu Wu
Principal Investigator
Research interests: multi-component functional assemblies, noncovalent dimerization, supramolecular catalysis, and smart soft matter