Convergence Properties of Crystal Structure Prediction by Quasi-Random Sampling

Case, David H.; Campbell, Josh E.; Bygrave, Peter J.; Day, Graeme M.

doi:10.1021/acs.jctc.5b01112

Cited by 99 publications

(137 citation statements)

References 73 publications

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“…What is consistent between methods is the need to perform calculations on many thousands of trial structures to fully explore the lattice energy landscape. 35 The final list of possible crystal structures is usually ranked using their calculated lattice energies, under the assumption that the lowest energy computer-generated structures are the most likely to be observed experimentally, illustrated in Fig. 4.…”

Section: Crystalline Phasementioning

confidence: 99%

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

et al. 2017

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Composed from discete units, porous molecular materials (PMMs) possess unique properties not observed for conventional, extended, solids, such as solution processibility and permanent porosity in the liquid phase. However, identifying the origin of porosity is not a trivial process, especially for amorphous or liquid phases. Furthermore, the assembly of molecular components is typically governed by a subtle balance of weak intermolecular forces that makes structure prediction challenging. Accordingly, in this review we canvass the crucial role of molecular simulations in the characterisation and design of PMMs. We will outline strategies for modelling porosity in crystalline, amorphous and liquid phases and also describe the state-of-the-art methods used for high-throughput screening of large datasets to identify materials that exhibit novel performance characteristics.

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Section: Crystalline Phasementioning

confidence: 99%

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

et al. 2017

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“…Crystal structure prediction was performed using quasi-random structure generation using the Global Lattice Energy Explorer software, 39 followed by lattice energy minimisation using an atom-atom intermolecular force field with empirically parameterised repulsiondispersion interactions and an atomic multipole electrostatic model. All lattice energy minimisations were performed using the crystal structure modelling software DMACRYS.…”

Section: Density Functional Theory (Dft) Calculations For Isolated Camentioning

confidence: 99%

“…25) where the nanotubes are preserved, but where collapse of the cage occurs. The bulk TCC2-R/TCC2-S material was insufficiently crystalline to determine whether the loss of porosity was due to this cage collapse, to a loss of crystallinity, or to both.We also calculated the landscapes of possible crystal structures of enantiopure and racemic TCC1-TCC3 using crystal structure prediction (CSP) 21,39,40,41,42 methods (Fig. 5, Supplementary Information, Section 4.6).…”

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Reticular synthesis of porous molecular 1D nanotubes and 3D networks

et al. 2016

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Synthetic control over pore size and pore connectivity is the crowning achievement for porous metal-organic frameworks. The same level of control has not been achieved for molecular crystals, which are not defined by strong, directional intermolecular coordination bonds. Hence, molecular crystallization is inherently less controllable than framework crystallization, and there are fewer examples of 'reticular synthesis'-where multiple building blocks can be assembled according to a common assembly motif.Here, we apply a chiral recognition strategy to a new family of tubular covalent cages, to create both 1-D porous nanotubes and 3-D diamondoid pillared porous networks.The diamondoid networks are analogous to metal-organic frameworks prepared from tetrahedral metal nodes and linear, ditopic organic linkers. The crystal structures can be rationalized by computational lattice energy searches, which provide an in silico screening method to evaluate candidate molecular building blocks. These results are a blueprint for applying the 'node and strut' principles of reticular synthesis to molecular crystals.Despite many advances in supramolecular chemistry, it is still challenging to control molecular crystallization to create a specific, useful property. 1,2 This is important in the emerging area of porous molecular solids, 3 which have practical advantages such as solution processability. The crystal packing in porous molecular crystals defines the pore dimensions, which in turn define properties such as guest selectivity. 4,5 The same challenge-control over solid state structure-applies to all 2 functional molecular crystals because crystal packing defines physical properties such as electronic band gap and thermal or electrical conductivity.A central paradigm in crystal engineering is to synthesize building blocks, or 'tectons', with strong, directional interactions, such as hydrogen bonding 6 or metal-ligand binding, 7 which direct assembly into a targeted three-dimensional superstructure (Fig. 1). 1,2,8,9 For metal-organic frameworks (MOFs) and porous coordination polymers (PCPs), directional metal-ligand bonds are used to do this (Fig. 1a). [10][11][12][13][14] Likewise, hydrogen bonding can be used to create organic molecular crystals with defined network structures (Fig. 1b). 9,15,16 We have used chiral recognition to assemble porous organic cages 3 (POCs) into structures with 3-D pore channels (Fig. 1c). 3 POCs are rigid molecules with a permanent internal void that is accessible to guests via 'windows' in the cage. [17][18][19] Control of structure and function for POCs can be difficult, however, because slight changes in the molecular structure 19 or the crystallization solvent 20 can cause a profound change in the crystal packing. Chiral window-towindow interactions (Fig. 1e,f) can direct these POCs to assemble into 3-D pore networks in several cases, 19,21,22 but this is not ubiquitous. For example, some cages require specific solvents to template the window-to-window packing. 20 The chiral cage CC3-S (...

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“…Applications of CSP to functional materials have been less common, at least for molecular crystals, aside from a relatively small number of studies for small‐molecule organic semiconductors, pigments, fluorescent molecules, and explosives . However, the development of efficient, accurate force fields, coupled with highly parallelized structure searching methods and rapid improvements in computational hardware mean that it is now possible to apply CSP in screening applications for the discovery of functional organic materials (Figure b) and to couple this with property predictions. Recently, this has led to materials with unprecedented properties, such as the lowest density molecular solid …”

Section: Introductionmentioning

confidence: 99%

Energy–Structure–Function Maps: Cartography for Materials Discovery

Day

Cooper²

2017

Advanced Materials

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bonding motif that dominates the lattice energy of the framework: that is, directional coordination bonds in the case of PCPs and MOFs, or covalent bonds for COFs. The dominance of a particular arrangement of interactions allows families of structurally related or "isoreticular" [4] frameworks to be prepared because the same bonding pattern can be assumed for multiple linkers. Hence, MOFs and COFs have become enormously popular platforms for a wide variety of materials applications, enabled by the relative ease with which one can explore the available "structure-function space." The importance of this transcends specific materials functions, such as porosity: isoreticular assembly is a powerful, generalizable tool to assemble molecular subunits in the solid state. [5] The situation is different for molecular crystals, which lack extended networks of coordination or covalent bonds. Despite much progress in the field of crystal engineering, [6] it is still rather challenging to program the assembly of molecules in crystalline solids. This is because the intermolecular forces that define molecular crystals-van der Waals and electrostatic interactions-are typically weaker and span a smaller energy range. Consequently, the lattice energies of molecular crystals are more evenly composed of various weak interactions and so the structure-directing forces are a more subtle balance than for PCPs, MOFs, and COFs. Strategies to make molecules crystallize more systematically, such as introducing strong hydrogen-bond donors and acceptors, can succeed but this may also introduce synthetic complexity. Moreover, the addition of such groups to create directional molecular building blocks, or "tectons," [7] can profoundly change the nature of the moleculefor example, by affecting its solubility or polarity-in ways that might not be aligned with the intended function. This can also be true for extended frameworks: in some PCPs and MOFs, the metal serves a specific chemical function, for example, as a catalyst, while in others, the metal is mostly there to hold the framework together-it serves no explicit chemical role.The introduction of directional functional groups such as carboxylic acids into organic tectons exemplifies the strategy of purposeful crystal engineering, whether this be in a hydrogenbonded molecular organic framework or in the organic linker of a MOF. Arguably, such intuitive design strategies will be defeated by complexity for molecular crystals, and even "wellbehaved" isoreticular extended frameworks might carry an unacknowledged overhead in terms of incorporating directing 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 b...

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Convergence Properties of Crystal Structure Prediction by Quasi-Random Sampling

Cited by 99 publications

References 73 publications

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

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

Reticular synthesis of porous molecular 1D nanotubes and 3D networks

Energy–Structure–Function Maps: Cartography for Materials Discovery

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