We summarize the recent advancements in material discovery facilitated by the application of cheminformatics concepts to crystalline porous materials. We discuss challenges involved in developing descriptors and comparison techniques for these structures, and comment on the role of the similar property principle in material analysis. Our approach is to focus on void space, rather than the overall structure � this allows us to describe a material from the point of view of a guest molecule. We perform the Voronoi decomposition to obtain a periodic graph representation of a material's void space, and construct novel descriptors � Voronoi holograms � by automatically inspecting the graph. Through application of a modified Tanimoto similarity coefficient and MaxMin diversity selection, we illustrate the calculation of (dis)similarity using this descriptor, and the retrieval of a diverse and representative subset of promising candidate materials for CO2 capture not obtainable through the use of existing structural descriptors.

Cheminformatics for material discovery: Representation, searching and screening of porous materials

243rd National Meeting (2012)

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.