In this dissertation, a reversible system with a well controlled degree of particle aggregation was developed. By surface modification of colloidal silica with aminosilanes, interactions among the particles were tuned in a controlled way to produce stable sized clusters at different pH values ranges from well-disposed to a colloidal gel. N-[3-(trimethoxysilyl)propyl]ethylenediamine (TMPE) monolayer on particle surface not only removes all the reactive sites to prevent chemical aggregation, also provides steric stabilization in the absence of any repulsion. After surface modification, electrokinetic behavior of silica particles were changed to that of amino groups, positive in acidic pH and neutral at basic pH values. By tuning the pH, the balance between electrostatic repulsion and hydrophobic interactions was reversibly controlled. As a result, clusters with different sizes were developed.;The effect of clustering on the thermal conductivity of colloidal dispersions was quantified using silane-treated silica, a system engineered to exhibit reversible clustering under well-controlled conditions. Thermal conductivity of this system was measured by transient hot wire, the standard method of thermal conductivity measurements in liquids. We show that the thermal conductivity increases monotonically with cluster size and spans the entire range between the two limits of Maxwell's theory. The results, corroborated by numerical simulation, demonstrate that large increases of the thermal conductivity of colloidal dispersions are possible, yet fully within the predictions of classical theory.;Numerical calculations were performed to evaluate the importance of structural properties of particles/aggregates on thermal conduction in colloidal particles. Thermal conductivity of non-spherical particles including hollow particles, cubic particles and rods was studied using a Monte Carlo algorithm. We show that anisotropic shapes, increase conductivity above that of isotropic particles where Maxwell's theory is reliable. This method also provides an accurate tool for evaluation of conductivity in colloidal suspensions between Maxwell's limits where theory is inadequate and experiments are limited due to colloidal difficulties. The effect of cluster configuration and degree of aggregation was investigated and showed that clusters of about the same size, but with different structures increases conductivity by different degree. We also showed that even small structural details such as the size of the neck that particles form during aggregation, can change the enhancement significantly.;Colloidal clusters conduct heat more efficiently compared to fully dispersed particles at the same volume fraction. We present a predictive model to calculate the thermal conductivity of clusters by extending Maxwell's theory to non-spherical particles. We treat the clusters as spheres with effective thermal conductivity kc and volume fraction &phis;c. We calculate conductivity of the cluster from the upper bound of Maxwell's theory, and the conductivity of a dispersion of such clusters from the lower limit of the theory. We show that structural effects can be represented by a single parameter and a method was provided to obtain this parameter from numerical simulations. We test the theory against simulations as well as dispersions of colloidal cluster and find it to be in very good agreement with both. The results suggest that the variability of literature data and the unusually high values of thermal conductivity that have been reported in the literature can be fully accounted by the presence of clusters. (Abstract shortened by ProQuest.).
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