A computational method to optimize the distribution of a catalytically active material inside a nano-scale pore

Paper in proceeding, 2015

Catalysis is a key phenomenon in a great number of energy processes, including feedstock conversion, tar cracking, emission abatement and optimizations of energy use. Within heterogeneous, catalytic nano-scale systems, the chemical reactions typically proceed at very high rates at a gas-solid interface. The present work investigates the performance of a Direct Simulation Monte Carlo (DSMC) code with a stochastic optimization heuristic for optimizations of such nano-scale systems. The DSMC code is able to treat molecular motion with homogeneous and heterogeneous chemical reactions in wall-bounded systems with a prescribed pressure difference between an inlet and an outlet. An algorithm has been devised and implemented that allows optimization of the distribution of a catalytically active material within a three-dimensional pore where the flow field is described by the code. The objective function is the outlet concentration of computational molecules that have interacted with the catalytically active surface, and the optimization method used is simulated annealing. The application of a stochastic optimization heuristic is shown to be more efficient within the present DSMC framework than using a macroscopic overlay method. Furthermore, it is shown that the performance of the developed method is superior to that of a gradient search method for the current class of problems.