Heterogeneous Interactions Promote Crystallization and Spontaneous Resolution of Chiral Molecules

Thermodynamic Stability Is a Poor Indicator of Cocrystallization in Models of Organic Molecules

Cocrystallizing a given molecule with another can be useful for adjusting the physical properties of molecules in the solid state. However, most combinations of molecules do not readily cocrystallize but form either one-component crystals or amorphous solids. Computational methods of crystal structure prediction can, in principle, identify the thermodynamically stable cocrystal and thus predict if molecules will cocrystallize or not. However, the pronounced polymorphism and tendency of many organic molecules to form disordered solids suggest that kinetic factors can play an important role in cocrystallization. The question remains: if a binary system of molecules has a thermodynamically stable cocrystal, will it indeed cocrystallize? To address this question, we simulate the crystallization of more than 2600 distinct pairs of chiral model molecules of similar size in 2D and calculate accurate crystal energy landscapes for all of them. Our analysis shows that thermodynamic criteria alone are unreliable in the prediction of cocrystallization. While the vast majority of cocrystals that form in our simulations are thermodynamically favorable, most coformer systems that have a thermodynamically stable cocrystal do not cocrystallize. We furthermore show that cocrystallization rates increase 3-fold when coformers are used that do not form well-ordered single-component crystals. Our results suggest that kinetic factors of cocrystallization are decisive in many cases.

Anisotropic functionalized platelets: percolation, porosity and network properties

Anisotropic functionalized platelets are able to model the assembly behaviour of molecular systems in two dimensions thanks to the unique combination of steric and bonding constraints. The assembly scenarios can vary from open to close-packed crystals, finite clusters and chains, according to the features of the imposed constraints. In this work, we focus on the assembly of equilibrium networks. These networks can be seen as disordered, porous monolayers and can be of interest for instance in nano-filtration and optical applications. We investigate the formation and properties of two dimensional networks from shape anisotropic colloids functionalized with four patches. We characterize the connectivity properties, the typical local bonding motives, as well as the geometric features of the emerging networks for a large variety of different systems. Our results show that networks of shape anisotropic colloids assemble into highly versatile network topologies, that may be utilized for applications at the nanoscale.

Strategies for chiral separation: from racemate to enantiomer

Chiral separation has become a crucial topic for effectively utilizing superfluous racemates synthesized by chemical means and satisfying the growing requirements for producing enantiopure chiral compounds. However, the remarkably close physical and chemical properties of enantiomers present significant obstacles, making it necessary to develop novel enantioseparation methods. This review comprehensively summaries the latest developments in the main enantioseparation methods, including preparative-scale chromatography, enantioselective liquid-liquid extraction, crystallization-based methods for chiral separation, deracemization process coupling racemization and crystallization, porous material method and membrane resolution method, focusing on significant cases involving crystallization, deracemization and membranes. Notably, potential trends and future directions are suggested based on the state-of-art "coupling" strategy, which may greatly reinvigorate the existing individual methods and facilitate the emergence of cross-cutting ideas among researchers from different enantioseparation domains.

Semirigid discotic dimers: flexible but not flexible enough?

Two diastereomeric dibenzo[a,c]phenazine 1,2-cyclohexyl bridged diesters were prepared and their phase properties examined. While the trans dimer exhibited a broad columnar liquid crystal phase, the cis dimer was amorphous at all temperatures studied. This difference was attributed to the conformational dynamics of the two systems. NMR and DFT studies indicate that both dimers adopt folded and unfolded conformers in solution. While their folded geometries were similar, the trans dimer adopts an extended, largely planar structure, whereas the cis dimer is limited to non-planar unfolded structures and likely disrupts columnar ordering. Geometric constraints imposed by the cylcic linker were also important for columnar stability, with the trans dimer clearing 40 °C lower than the corresponding acyclic 2R,3R-butyl linked dimer, likely because the cyclohexyl group hinders π-π stacking in the unfolded conformation of the former.

Hierarchical Materials from High Information Content Macromolecular Building Blocks: Construction, Dynamic Interventions, and Prediction

Hierarchical materials that exhibit order over multiple length scales are ubiquitous in nature. Because hierarchy gives rise to unique properties and functions, many have sought inspiration from nature when designing and fabricating hierarchical matter. More and more, however, nature's own high-information content building blocks, proteins, peptides, and peptidomimetics, are being coopted to build hierarchy because the information that determines structure, function, and interfacial interactions can be readily encoded in these versatile macromolecules. Here, we take stock of recent progress in the rational design and characterization of hierarchical materials produced from high-information content blocks with a focus on stimuli-responsive and "smart" architectures. We also review advances in the use of computational simulations and data-driven predictions to shed light on how the side chain chemistry and conformational flexibility of macromolecular blocks drive the emergence of order and the acquisition of hierarchy and also on how ionic, solvent, and surface effects influence the outcomes of assembly. Continued progress in the above areas will ultimately usher in an era where an understanding of designed interactions, surface effects, and solution conditions can be harnessed to achieve predictive materials synthesis across scale and drive emergent phenomena in the self-assembly and reconfiguration of high-information content building blocks.

Predictive Theoretical Framework for Dynamic Control of Bioinspired Hybrid Nanoparticle Self-Assembly

At-will tailoring of the formation and reconfiguration of hierarchical structures is a key goal of modern nanomaterial design. Bioinspired systems comprising biomacromolecules and inorganic nanoparticles have potential for new functional material structures. Yet, consequential challenges remain because we lack a detailed understanding of the temporal and spatial interplay between participants when it is mediated by fundamental physicochemical interactions over a wide range of scales. Motivated by a system in which silica nanoparticles are reversibly and repeatedly assembled using a homobifunctional solid-binding protein and single-unit pH changes under near-neutral solution conditions, we develop a theoretical framework where interactions at the molecular and macroscopic scales are rigorously coupled based on colloidal theory and atomistic molecular dynamics simulations. We integrate these interactions into a predictive coarse-grained model that captures the pH-dependent reversibility and accurately matches small-angle X-ray scattering experiments at collective scales. The framework lays a foundation to connect microscopic details with the macroscopic behavior of complex bioinspired material systems and to control their behavior through an understanding of both equilibrium and nonequilibrium characteristics.

Pre-Nucleation Clusters Predict Crystal Structures in Models of Chiral Molecules

Kinetics can play an important role in the crystallization of molecules and can give rise to polymorphism, the tendency of molecules to form more than one crystal structure. Current computational methods of crystal structure prediction, however, focus almost exclusively on identifying the thermodynamically stable polymorph. Kinetic factors of nucleation and growth are often neglected because the underlying microscopic processes can be complex and accurate rate calculations are numerically cumbersome. In this work, we use molecular dynamics computer simulations to study simple molecular models that reproduce the crystallization behavior of real chiral molecules, including the formation of enantiopure and racemic crystals, as well as polymorphism. A significant fraction of these molecules forms crystals that do not have the lowest free energy. We demonstrate that at high supersaturation crystal formation can be accurately predicted by considering the similarities between oligomeric species in solution and molecular motifs in the crystal structure. For the case of racemic mixtures, we even find that knowledge of crystal free energies is not necessary and kinetic considerations are sufficient to determine if the system will undergo spontaneous chiral separation. Our results suggest conceptually simple ways of improving current crystal structure prediction methods.

Neuroevolutionary Learning of Particles and Protocols for Self-Assembly

Within simulations of molecules deposited on a surface we show that neuroevolutionary learning can design particles and time-dependent protocols to promote self-assembly, without input from physical concepts such as thermal equilibrium or mechanical stability and without prior knowledge of candidate or competing structures. The learning algorithm is capable of both directed and exploratory design: it can assemble a material with a user-defined property, or search for novelty in the space of specified order parameters. In the latter mode it explores the space of what can be made, rather than the space of structures that are low in energy but not necessarily kinetically accessible.

A Matter of Size and Placement: Varying the Patch Size of Anisotropic Patchy Colloids

Non-spherical colloids provided with well-defined bonding sites—often referred to as patches—are increasingly attracting the attention of materials scientists due to their ability to spontaneously assemble into tunable surface structures. The emergence of two-dimensional patterns with well-defined architectures is often controlled by the properties of the self-assembling building blocks, which can be either colloidal particles at the nano- and micro-scale or even molecules and macromolecules. In particular, the interplay between the particle shape and the patch topology gives rise to a plethora of tilings, from close-packed to porous monolayers with pores of tunable shapes and sizes. The control over the resulting surface structures is provided by the directionality of the bonding mechanism, which mostly relies on the selective nature of the patches. In the present contribution, we investigate the effect of the patch size on the assembly of a class of anisotropic patchy colloids—namely, rhombic platelets with four identical patches placed in different arrangements along the particle edges. Larger patches are expected to enhance the bond flexibility, while simultaneously reducing the bond selectivity as the single bond per patch condition—which would guarantee a straightforward mapping between local bonding arrangements and long-range pattern formation—is not always enforced. We find that the non-trivial interplay between the patch size and the patch position can either promote a parallel particle arrangement with respect to a non-parallel bonding scenario or give rise to a variety a bonded patterns, which destroy the order of the tilings. We rationalize the occurrence of these two different regimes in terms of single versus multiple bonds between pairs of particles and/or patches.

Solving the COF trilemma: towards crystalline, stable and functional covalent organic frameworks

Strategies in covalent organic frameworks and adjacent fields are highlighted for designing stable, ordered and functional materials.