REPRESENTATION OF POROUS CATALYSTS USING RANDOM PORE NETWORKS

Stochastic pore networks are increasingly being used to represent porous media and model transport processes occurring in them. Most frequently, square or cubic regular grids of pores are employed. It has been shown recently that regular and random networks give significantly different tortuosities both under conditions of diffusion-only and diffusion with simultaneous reaction. In this study the relationship between random and regular topologies is more formally investigated using percolation and finite-size scaling theories. Critical properties of the random model are determined from Monte Carlo simulations on large networks and these are compared with the results for regular lattices. Percolation thresholds are greater in the random models; it is observed that the greatest difference occurs at low pore connectivities. The critical exponents were determined by finite-size scaling and found to be independent of topology and connectivity. Further, at low connectivities the cluster size distribution is markedly different between regular and random topologies. The random model is also used to represent the bi-disperse porous structures which arise in commonly used catalyst supports. It is demonstrated that unreasonable results are obtained if macro-pores and micro-pores are assigned from two distributions in an uncorrelated manner. Using an appropriate random model, anomalously high tortuosities obtained by other workers are avoided. This demonstrates the importance of using a model which is a realistic representation of the porous structure.