Characterization and comparison of pore landscapes in crystalline porous materials

Abstract

Crystalline porous materials have many applications, including catalysis and separations. Identifying suitable materials for a given application can be achieved by screening material databases. Such a screening requires automated high-throughput analysis tools that characterize and represent pore landscapes with descriptors, which can be compared using similarity measures in order to select, group and classify materials. Here, we discuss algorithms for the calculation of two types of pore landscape descriptors: pore size distributions and stochastic rays. These descriptors provide histogram representations that encode the geometrical properties of pore landscapes. Their calculation involves the Voronoi decomposition as a technique to map and characterize accessible void space inside porous materials. Moreover, we demonstrate pore landscape comparisons for materials from the International Zeolite Association (IZA) database of zeolite frameworks, and illustrate how the choice of pore descriptor and similarity measure affects the perspective of material similarity exhibiting a particular emphasis and sensitivity to certain aspects of structures.

Keywords: Pore shape similarity; Pore size distribution; Porous materials; Stochastic rays.