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Energy–Structure–Function Maps: Cartography for Materials Discovery
Author(s) -
Day Graeme M.,
Cooper Andrew I.
Publication year - 2018
Publication title -
advanced materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 10.707
H-Index - 527
eISSN - 1521-4095
pISSN - 0935-9648
DOI - 10.1002/adma.201704944
Subject(s) - crystal engineering , materials science , crystal (programming language) , molecular solid , computation , function (biology) , predictability , nanotechnology , molecule , crystal structure , supramolecular chemistry , computer science , crystallography , algorithm , physics , chemistry , organic chemistry , programming language , quantum mechanics , evolutionary biology , biology
Some of the most successful approaches to structural design in materials chemistry have exploited strong directional bonds, whose geometric reliability lends predictability to solid‐state assembly. For example, metal–organic frameworks are an important design platform in materials chemistry. By contrast, the structure of molecular crystals is defined by a balance of weaker intermolecular forces, and small changes to the molecular building blocks can lead to large changes in crystal packing. Hence, empirical rules are inherently less reliable for engineering the structures of molecular solids. Energy–structure–function (ESF) maps are a new approach for the discovery of functional organic crystals. These maps fuse crystal‐structure prediction with the computation of physical properties to allow researchers to choose the most promising molecule for a given application, prior to its synthesis. ESF maps were used recently to discover a highly porous molecular crystal that has a high methane deliverable capacity and the lowest density molecular crystal reported to date (r = 0.41 g cm −3 , SA BET = 3425 m 2 g −1 ). Progress in this field is reviewed, with emphasis on the future opportunities and challenges for a design strategy based on computed ESF maps.