Atom transfer radical polymerization (ATRP) is a dynamic technique that possesses tremendous potential for the synthesis of novel polymeric materials not possible through conventional free radical polymerization. However, its use on an industrial scale has been limited by the high level of transition metal complex required. Significant advances have been made in the last 5 years towards lowering the level of copper complexes used in ATRP, resulting in novel variants called “activator regenerated by electron transfer” (ARGET) and “single electron transfer-living radical polymerization” (SET-LRP). To fully realize the potential of ATRP, its use in industrially relevant processes must be studied. Continuous processes such as tubular flow reactors and stirred tank reactors (CSTR) can reduce waste, improve productivity and facilitate process scale-up when compared to common batch reactors. The combination of low copper concentration ATRP techniques and continuous processes are especially attractive towards the design of a commercially viable process. This thesis presents a study into ARGET ATRP and SET-LRP as applied to continuous tubular and stirred tank reactors for the production of acrylic and methacrylic polymers. The equilibrium which governs polymerization rate and control over molecular architecture is studied through batch ARGET ATRP experiments. The improved understanding of ARGET ATRP enabled the reduction of ligand from a 3 to 10 fold excess used previously down to a stoichiometric ratio to copper salts. ARGET ATRP was then adapted to a continuous tubular reactor, as well as to a semi-automated CSTR. The design of the reactors and the effect of reaction conditions such as reducing agent concentration and residence time are discussed. The use of common elemental copper(0) such as copper wire and copper tubing is also investigated with SET-LRP for room temperature polymerization of methyl acrylate. SET-LRP is adapted to a CSTR to observe the effects of residence time on reaction rate, molecular weight control as well as copper consumption rate. The use of copper tubing as a catalyst source for SET-LRP is demonstrated and the design of a continuous tubular reactor using a combination of copper and stainless steel tubing is discussed. / Thesis (Ph.D, Chemical Engineering) -- Queen's University, 2012-04-30 16:01:28.916

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abstract: Geographically Weighted Regression (GWR) has been broadly used in various fields to model spatially non-stationary relationships. Classic GWR is considered as a single-scale model that is based on one bandwidth parameter which controls the amount of distance-decay in weighting neighboring data around each location. The single bandwidth in GWR assumes that processes (relationships between the response variable and the predictor variables) all operate at the same scale. However, this posits a limitation in modeling potentially multi-scale processes which are more often seen in the real world. For example, the measured ambient temperature of a location is affected by the built environment, regional weather and global warming, all of which operate at different scales. A recent advancement to GWR termed Multiscale GWR (MGWR) removes the single bandwidth assumption and allows the bandwidths for each covariate to vary. This results in each parameter surface being allowed to have a different degree of spatial variation, reflecting variation across covariate-specific processes. In this way, MGWR has the capability to differentiate local, regional and global processes by using varying bandwidths for covariates. Additionally, bandwidths in MGWR become explicit indicators of the scale at various processes operate. The proposed dissertation covers three perspectives centering on MGWR: Computation; Inference; and Application. The first component focuses on addressing computational issues in MGWR to allow MGWR models to be calibrated more efficiently and to be applied on large datasets. The second component aims to statistically differentiate the spatial scales at which different processes operate by quantifying the uncertainty associated with each bandwidth obtained from MGWR. In the third component, an empirical study will be conducted to model the changing relationships between county-level socio-economic factors and voter preferences in the 2008-2016 United States presidential elections using MGWR. / Dissertation/Thesis / Doctoral Dissertation Geography 2020