RESUMO
Timber is the only widely used construction material we can grow. The wood from which it comes has evolved to provide structural support for the tree and to act as a conduit for fluid flow. These flow paths are crucial for engineers to exploit the full potential of timber, by allowing impregnation with liquids that modify the properties or resilience of this natural material. Accurately predicting the transport of these liquids enables more efficient industrial timber treatment processes to be developed, thereby extending the scope to use this sustainable construction material; moreover, it is of fundamental scientific value - as a fluid flow within a natural porous medium. Both structural and transport properties of wood depend on its micro-structure but, while a substantial body of research relates the structural performance of wood to its detailed architecture, no such knowledge exists for the transport properties. We present a model, based on increasingly refined geometric parameters, that accurately predicts the time-dependent ingress of liquids within softwood timber, thereby addressing this long-standing scientific challenge. Moreover, we show that for the minimalistic parameterisation the model predicts ingress with a square-root-of-time behaviour. However, experimental data show a potentially significant departure from this [Formula: see text] behaviour - a departure which is successfully predicted by our more advanced parametrisation. Our parameterisation of the timber microstructure was informed by computed tomographic measurements; model predictions were validated by comparison with experimental data. We show that accurate predictions require statistical representation of the variability in the timber pore space. The collapse of our dimensionless experimental data demonstrates clear potential for our results to be up-scaled to industrial treatment processes.
RESUMO
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 mm3 at 15 µm3 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.
Assuntos
Picea/anatomia & histologia , Madeira/anatomia & histologia , Microtomografia por Raio-X , PorosidadeRESUMO
The combination of potent chemical moieties with biologically active proteins is key to some of today's most innovative therapeutic drugs. In order to obviate any chemical modification of the proteins, we present a novel and powerful strategy for the selective conjugation of recombinant protein domains with synthetically derived peptides via a cucurbit[8]uril host-guest chemistry approach.