Mathematical tools for discovery of nanoporous materials for energy applications

Abstract

Porous materials such as zeolites and metal organic frameworks have been of growing importance as materials for energy-related applications such as CO2 capture, hydrogen and methane storage, and catalysis. The current state-of-the-art molecular simulations allow for accurate in silico prediction of materials' properties but the computational cost of such calculations prohibits their application in the characterisation of very large sets of structures, which would be required to perform brute-force screening. Our work focuses on the development of novel methodologies to efficiently characterize and explore this complex materials space. In particular, we have been developing algorithms and tools for enumeration and characterisation of porous material databases as well as efficient screening approaches. Our methodology represents a ensemble of mathematical methods. We have used Voronoi tessellation-based techniques to enable high-throughput structure characterisation, statistical techniques to perform comparison and screening, and continuous optimisation to design materials. This article outlines our developments in material design.