Optimal Particle Parameters for CLC and CLR Processes – Predictions by Intra-Particle Transport Models and Experimental Validation

Validated models for predicting oxidation and reduction kinetics of multi-component porous particles in chemical looping combustion (CLC) and chemical looping reforming (CLR) processes are of key importance to identify the rate limiting step in these processes. Since particle properties (i.e., their composition, porosity, pore size, grain size, etc.) can be adjusted by modern synthesis techniques, there is an open question on the optimal set of these properties that would lead to the most economic process. We introduce a general open-source simulation environment, called ParScale that can be used to simulate models relevant for CLC and CLR processes, and hence can be used for their optimization. Most important, ParScale features a generalized one-dimensional spherical discretization which enables the user to predict an arbitrary number of reactions within non-isothermal porous particles consisting of multiple solid (reactive or inert) species. We perform an optimization study (constrained by typical process requirements like the maximum reaction time) for an isothermal first-order reaction, as well as for an n-th order reaction typical for hematite reduction. Finally, materials consisting of active nanoparticles embedded in a matrix of a different composition are synthesized and analyzed.