Functional materials discovery using energy–structure–function maps

Abstract

Molecular crystals cannot be designed like macroscopic objects because they do not assemble according to simple, intuitive rules. Their structure results from the balance of many weak interactions, unlike the strong and predictable bonding patterns found in metal–organic frameworks and covalent organic frameworks. Hence, design strategies that assume a topology or other structural blueprint will often fail. Here, we combine computational crystal structure prediction and property prediction to build energy–structure–function maps describing the possible structures and properties available to a candidate molecule. Using these maps, we identify a highly porous solid with the lowest density reported for a molecular crystal. Both crystal structure and physical properties, such as the methane storage capacity and guest selectivity, are predicted using the molecular diagram as the only input. More generally, energy–structure–function maps could be used to guide the experimental discovery of materials with any target function that can be calculated from predicted crystal structures, such as electronic structure or mechanical properties.

A zeolitic vanadotungstate family with structural diversity and ultrahigh porosity for catalysis

“…The structures were optimized by density functional theory (DFT) calculations, and the energies and densities of the structures were obtained and plotted, which is useful in structural predictions 31 . VT-1 showed the lowest energy and highest density among all the VT members, indicating that VT-1 was the thermodynamically most stable structure (Fig.…”

Efficient Screening for Ternary Molecular Ionic Cocrystals Using a Complementary Mechanosynthesis and Computational Structure Prediction Approach

“…Despite the proven value of computational crystal structure prediction (CSP) methods in facilitating the discovery of previously unknown solid forms, molecular solids comprising three or more chemical entities are not routinely studied in such work. This reflects the demands on computing resources and the complexity of the search space, which scales exponentially with the degrees of freedom.…”

Application of computational methods to the design and characterisation of porous molecular materials

“…30 In addition, crystal structure prediction algorithms have afforded significant steps towards rationalising empirical data and show promise for the design of new functional materials. 31,32 This review will cover the application of computational approaches to the research of PMMs. In particular, simulations that produce structural models of these materials in crystalline, amorphous and liquid states will be canvassed and the novel methods of modelling porosity and gas adsorption in these systems will be discussed.…”