Predicted crystal energy landscapes of porous organic cages

Pyzer‐Knapp, Edward O.; Thompson, Hugh P. G.; Schiffmann, Florian; Jelfs, Kim E.; Chong, Samantha Y.; Little, Marc A.; Cooper, Andrew I.; Day, Graeme M.

doi:10.1039/c4sc00095a

Cited by 80 publications

(107 citation statements)

References 39 publications

Supporting

Mentioning

101

Contrasting

Order By: Relevance

“…43 Quinacridone finds use in the pigment and semiconductor industries 44 and has known polymorphism. The third molecule investigated, hereafter referred to as CC1, is one of a series of porous organic cages that we have studied previously using simulated annealing; 21,45 these cages are of interest as solution processable porous materials, and CC1 has the interesting behavior of switching between porous and nonporous polymorphs. 46 These three molecules not only exemplify the relevance of CSP in various application areas but also test and demonstrate the performance of the Glee code in cases with a range of known experimental polymorphs, molecular geometries, and intermolecular interactions.…”

Section: Introductionmentioning

confidence: 99%

Convergence Properties of Crystal Structure Prediction by Quasi-Random Sampling

Case

Campbell

Bygrave

et al. 2016

J. Chem. Theory Comput.

Self Cite

101

135

View full text Add to dashboard Cite

Generating sets of trial structures that sample the configurational space of crystal packing possibilities is an essential step in the process of ab initio crystal structure prediction (CSP). One effective methodology for performing such a search relies on low-discrepancy, quasi-random sampling, and our implementation of such a search for molecular crystals is described in this paper. Herein we restrict ourselves to rigid organic molecules and, by considering their geometric properties, build trial crystal packings as starting points for local lattice energy minimization. We also describe a method to match instances of the same structure, which we use to measure the convergence of our packing search toward completeness. The use of these tools is demonstrated for a set of molecules with diverse molecular characteristics and as representative of areas of application where CSP has been applied. An important finding is that the lowest energy crystal structures are typically located early and frequently during a quasi-random search of phase space. It is usually the complete sampling of higher energy structures that requires extended sampling. We show how the procedure can first be refined, through targetting the volume of the generated crystal structures, and then extended across a range of space groups to make a full CSP search and locate experimentally observed and lists of hypothetical polymorphs. As the described method has also been created to lie at the base of more involved approaches to CSP, which are being developed within the Global Lattice Energy Explorer (Glee) software, a few of these extensions are briefly discussed.

show abstract

Section: Introductionmentioning

confidence: 99%

Convergence Properties of Crystal Structure Prediction by Quasi-Random Sampling

Case

Campbell

Bygrave

et al. 2016

J. Chem. Theory Comput.

Self Cite

101

135

View full text Add to dashboard Cite

show abstract

“…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).…”

mentioning

confidence: 99%

“…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).…”

mentioning

confidence: 99%

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

et al. 2016

View full text Add to dashboard Cite

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 (...

show abstract

“…This work was followed up recently by Day to provide more weight to the use of CSP methods for POCs. 39 The authors evaluated the crystal energy landscapes of POCs possessing small changes in chemical structure but notably different porous structures. They observed that the crystal structures and concomitant porosity could be predicted in silico, and thereby CSP of similar compounds should be possible, but provided a point of caution in that such predictions are not intuitively obvious from the molecular structure.…”

Section: ¹1mentioning

confidence: 99%

“…Some important advances have been made in this area, especially with respect to mapping the crystal structure energy landscapes. 39 However, further development is required before in silico screening of potential structures can be applied to novel cages. Indeed, this would be a significant breakthrough, as the synthesis of new cages can be challenging and may be considered a "bottle-neck" to realizing new POC materials.…”

Section: ¹1mentioning

confidence: 99%

Synthesis and Applications of Porous Organic Cages

2015

View full text Add to dashboard Cite

Solids composed of shape-persistent organic cage molecules are an emerging class of porous materials. Research in this area has recently progressed from understanding the nature of porosity in these materials to finding applications suited to their unique properties. For example, given that the cages are held together in the solid state by relatively weak (compared to covalent interactions) dispersion forces, the resultant materials are structurally flexible and thus physical properties, such as porosity, that can be modulated according to the adsorbate to which it is exposed. Moreover, discrete cages are soluble and can thus be reprecipitated as structural polymorphs that possess different properties, or processed into thin layers or composite materials such as mixed matrix membranes. In this review, we highlight the synthetic strategies that have been employed to produce porous organic cages and discuss recent advances in design concepts that have led to ultraporous solids. We will also canvass recent applications of these materials and posit potential areas of development.

show abstract

Predicted crystal energy landscapes of porous organic cages

Abstract: Computational methods predict the crystal packing of porous organic cage molecules, allowing crystal structure and porosity to be predicted starting from the chemical diagram alone.

Cited by 80 publications

References 39 publications

Convergence Properties of Crystal Structure Prediction by Quasi-Random Sampling

Convergence Properties of Crystal Structure Prediction by Quasi-Random Sampling

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

Synthesis and Applications of Porous Organic Cages

Contact Info

Product

Resources

About