SYSTEMATIC COMPUTATIONAL INVESTIGATION OF THERMAL BARRIER COATINGS FOR CELLULOSE SUBSTRATES

A statistical central composite design (CCD) was employed to investigate the effects of cellulose nanocrystal (CNC) and cellulose nanofiber (CNF) volume fractions, as well as relative free volume fraction, on the thermal barrier properties of a pigment-based coating for cellulosic substrates composed of calcium carbonate (CaCO3) and a copolymer binder, poly(styrene-co-methacrylic acid). Average room-temperature thermal conductivity (based on three replicates) was selected as a response and calculated for the different coating formulations using reverse non-equilibrium molecular dynamics (RNEMD) simulation with the Müller-Plathe algorithm. A reduced quadratic response surface model was fitted to the response data and analysis of variance (ANOVA) was performed. The effects of CNC and relative free volume fractions on the average thermal conductivity of the coatings were found to be significant, while the CNF volume fraction was insignificant. Overall, relative free volume fraction, which is representative of the porosity in the coating, showed a much larger impact on the average thermal conductivity than that of CNC volume fraction. Moreover, a weak interaction was observed between the two significant factors. Specifically, at low relative free volume fractions, addition of CNC to the formulation lowered the average thermal conductivity more than that of high relative free volume fractions. The pore size distribution analysis and average pore size calculation for the coatings (~5.25 Å for low and ~6.50 Å for high relative free volume fractions) did not reveal any significant effect of CNC on these properties at either low or high relative free volume fractions. However, the larger average pore size in the coatings associated with larger relative free volume fractions correlated well between the increase in pore size and reduced thermal conductivity in these coatings. IV Consequently, a larger CaCO3-CNC interfacial phonon scattering at low relative free volume fractions is believed to be the reason behind the above observations. The lowest thermal conductivity (0.075 W m-1 K-1), corresponding to highest thermal barrier property, was obtained for the coating with 2.50 vol.% CNC at a relative free volume fraction of 30%. Since CNF volume fraction was not a significant factor, its level was set at 0 vol.%. The results of this study provide a framework for a systematic design and optimization of pigment-based thermal barrier coatings for cellulosic substrates

MRI quantification of blood-brain barrier leakage in the ageing brain

Cerebral small vessel disease, or SVD, refers to processes that lead to dysfunction and damage in cerebral microvessels, and is implicated in ischaemic stroke and vascular dementia. Although the pathophysiology is poorly understood, a subtle breakdown in the blood-brain barrier (BBB) has been implicated as a potential underlying mechanism. BBB breakdown is difficult to measure in-vivo however - Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) is the dominant technique for assessing BBB integrity in clinical populations and is the focus of the work presented in this thesis. In this work, there are two main objectives: 1. Assess and optimise current DCE-MRI processing methods to provide accurate measurements of BBB breakdown. 2. Relate BBB breakdown to other features of SVD: clinical outcomes, imaging markers, and risk factors. To achieve the first objective, simulations were used to estimate the effects of various technical and modelling errors in measured BBB breakdown. By generating a realistic simulation of biological processes during a DCE-MRI sequence, sources of systematic error could be identified along with potential solutions. The implementation of MRI processing recommendations (a slow injection of contrast agent, exclusion of first-pass data from model fitting, and the use of a novel fitting method that better represents underlying biophysics) was found to reduce the sensitivity of calculated DCE-MRI parameters to the effects of variable blood plasma flow, variable water exchange rates, and injection delay by over 90%. Additionally, correction for field inhomogeneities was also found to reduce the error of calculated DCE-MRI parameters. Combining all the suggested processing methods was found to reduce the systematic error of calculated DCE-MRI parameters by up to 97%. These simulations form the basis of an open access framework and include an accessible GUI (1). For the second objective data was obtained from a prospective cohort study of mild stroke patients, and multiple linear regression was used to investigate how regional BBB breakdown is related to various patient factors. Regression models were controlled for several potential confounds and were implemented for both cross-sectional and longitudinal data. It was found that areas of hyperintensity on MRI images (which are indicative of vascular damage) presented lesser BBB breakdown when the severity of imaging markers was greater. Additionally, greater breakdown in the BBB of the basal ganglia is associated with greater disability scores, suggesting that vascular damage in this region may affect motor function and cognition. Risk factors associated with greater BBB breakdown include: age, a diagnosis of hypertension, and a diagnosis of diabetes, although the causality of these relationships is unclear. In summary, this thesis aims to improve the measurement of subtle BBB breakdown using DCE-MRI, and then use the optimised methods to investigate how BBB breakdown relates to clinical outcomes, imaging markers, and risk factors associated with SVD