(376e) Selection of Particles with Optimal Material Properties for Advanced Oxidation Process Applications

In this paper we present a mathematical model that describes the transport behavior of large particles in Pressure-regulated Circulating Riser (PCR) systems; and captures the overall process performance of these particles in advanced oxidation process (AOP) applications. For the purpose of this study, process performance is defined as a particle's ability to adsorb, to transport, and to facilitate the catalytic destruction of a given contaminant chemical species in an aqueous environment. Here we employ mathematical programming to explore the parameter search space of our model to identify particle properties that maximize process performance in a continuous AOP configuration, namely substrate selection, optimal loadings of adsorbent and catalyst, and catalytic shell thickness. A variety of case studies are used to illustrate the application of our modeling approach to the optimal design of a composite particle consisting of an activated carbon-TiO$_2$ coating on various substrates for the degradation of the organic dye methyl orange in water. A sensitivity analysis is performed to identify qualitative trends implicit in the proposed mathematical model and to determine the effect that these parameters have on the annular bed height and the equilibrium between the rich and lean phase.