Digital navigation of energy–structure–function maps for hydrogen-bonded porous molecular crystals

Abstract

Porous molecular crystals are a promising class of functional materials, but their a priori design is challenging. We demonstrated recently that energy–structure–function (ESF) maps can aid in the targeted discovery of porous molecular crystals via prediction of the stable crystalline arrangements along with their functions of interest. Here, we compute ESF maps for a series of molecules that comprise either a triptycene or a spiro-biphenyl core, functionalized with six different hydrogen-bonding moieties. By quantifying the intermolecular hydrogen bonding and intermolecular stacking for the structures on the ESF maps, we show that the positioning of the hydrogen bonding sites, as well as their number, has a profound influence on the shape of the resulting ESF maps. This reveals promising structure–function spaces for future experimental efforts. To assist with the navigation and interpretation of these ESF maps, we developed an interactive browser-based visualization tool (https://www.interactive-esf-maps.app) for interrogating the correlations, dependencies, and relationships between the various dimensions of the data. We also demonstrate a simple and general approach to representing and inspecting the high-dimensional data of an ESF map; this involves learning two-dimensional embeddings of the high-dimensional ESF data by applying unsupervised learning to engineered descriptors, or to numerical representations, that encode the crystal structures. Within this unified framework, ESF maps can be efficiently navigated to identify ‘landmark’ structures that are energetically favourable or functionally interesting. This is a step toward the automated analysis of ESF maps, which is an important goal for closed-loop, autonomous searches for molecular crystals with useful functions.

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Identifiers

ORCID for Graeme M. Day: orcid.org/0000-0001-8396-2771

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