Sustainable inverse-vulcanised sulfur polymers (vol 8, pg 27892, 2018)

Correction for ‘Sustainable inverse-vulcanised sulfur polymers’ by Douglas J. Parker et al., RSC Adv., 2018, 8, 27892–27899

Rapid Screening of Calcium Carbonate Precipitation in the Presence of Amino Acids: Kinetics, Structure, and Composition

Soluble additives are widely used to control crystallization, leading to a definition of properties including size, morphology, polymorph, and composition. However, because of the number of potential variables in these experiments, it is typically extremely difficult to identify reaction conditions—as defined by solution compositions, temperatures, and combinations of additives—that give the desired product. This article introduces a high-throughput methodology which addresses this challenge and enables the streamlined preparation and characterization of crystalline materials. Using calcium carbonate precipitated in the presence of selected amino acids as a model system, we use well plates as microvolume crystallizers, and an accurate liquid-handling pipetting workstation for sample preparation. Following changes in the solution turbidity using a plate reader delivers information about the reaction kinetics, while semiautomated scanning electron microscopy, powder X-ray diffraction, and Raman microscopy provide structural information about the library of crystalline products. Of particular interest for the CaCO3 system is the development of fluorescence-based protocols which rapidly evaluate the amounts of the additives occluded within the crystals. Together, these methods provide a strategy for efficiently screening a broad reaction space, where this can both accelerate the ability to generate crystalline materials with target properties and develop our understanding of additive-directed crystallization

Computational modelling of solvent effects in a prolific solvatomorphic porous organic cage

Crystal structure prediction methods can enable the in silico design of functional molecular crystals, but solvent effects can have a major influence on relative lattice energies sometimes thwarting predictions. This is particularly true for porous solids, where solvent included in the pores can have an important energetic contribution. Here we present a Monte Carlo solvent insertion procedure for predicting the solvent filling of porous structures from crystal structure prediction landscapes, tested using a highly solvatomorphic porous organic cage molecule, CC1. We use this method to rationalise the fact that the predicted global energy minimum structure for CC1 is never observed from solvent crystallisation. We also explain the formation of three different solvatomorphs of CC1 from three structurally-similar chlorinated solvents. Calculated solvent stabilisation energies are found to correlate with experimental results from thermogravimetric analysis, suggesting a future computational framework for a priori materials design that includes solvation effects

Powder-Bot: A Modular Autonomous Multi-Robot Workflow for Powder X-Ray Diffraction

Powder X-ray diffraction (PXRD) is a key technique for the structural characterisation of solid-state materials, but compared with tasks such as liquid handling, its end-to-end automation is highly challenging. This is because coupling PXRD experiments with crystallisation comprises multiple solid handling steps that include sample recovery, sample preparation by grinding, sample mounting and, finally, collection of X-ray diffraction data. Each of these steps has individual technical challenges from an automation perspective, and hence no commercial instrument exists that can grow crystals, process them into a powder, mount them in a diffractometer, and collect PXRD data in an autonomous, closed-loop way. Here we present an automated robotic workflow to carry out autonomous PXRD experiments. The PXRD data collected for polymorphs of small organic compounds is comparable to that collected under the same conditions manually. Beyond accelerating PXRD experiments, this workflow involves 13 component steps and integrates three different types of robots, each from a separate supplier, illustrating the power of flexible, modular automation in complex, multitask laboratories.Comment: 11 pages, 4 figures plus Supporting Information (2 videos, 13 supporting figures and one table

Porous organic cages for sulfur hexafluoride separation

A series of porous organic cages is examined for the selective adsorption of sulfur hexafluoride (SF6) over nitrogen. Despite lacking any metal sites, a porous cage, CC3, shows the highest SF6/N2 selectivity reported for any material at ambient temperature and pressure, which translates to real separations in a gas breakthrough column. The SF6 uptake of these materials is considerably higher than would be expected from the static pore structures. The location of SF6 within these materials is elucidated by X-ray crystallography, and it is shown that cooperative diffusion and structural rearrangements in these molecular crystals can rationalize their superior SF6/N2 selectivity

Sulfone-containing covalent organic frameworks for photocatalytic hydrogen evolution from water

Nature uses organic molecules for light harvesting and photosynthesis, but most man-made water splitting catalysts are inorganic semiconductors. Organic photocatalysts, while attractive because of their synthetic tunability, tend to have low quantum efficiencies for water splitting. Here we present a crystalline covalent organic framework (COF) based on a benzo-bis(benzothiophene sulfone) moiety that shows a much higher activity for photochemical hydrogen evolution than its amorphous or semicrystalline counterparts. The COF is stable under long-term visible irradiation and shows steady photochemical hydrogen evolution with a sacrificial electron donor for at least 50 hours. We attribute the high quantum efficiency of fused-sulfone-COF to its crystallinity, its strong visible light absorption, and its wettable, hydrophilic 3.2 nm mesopores. These pores allow the framework to be dye-sensitized, leading to a further 61% enhancement in the hydrogen evolution rate up to 16.3 mmol g −1 h −1 . The COF also retained its photocatalytic activity when cast as a thin film onto a support

Modular and predictable assembly of porous organic molecular crystals

Nanoporous molecular frameworks are important in applications such as separation, storage and catalysis. Empirical rules exist for their assembly but it is still challenging to place and segregate functionality in three-dimensional porous solids in a predictable way. Indeed, recent studies of mixed crystalline frameworks suggest a preference for the statistical distribution of functionalities throughout the pores rather than, for example, the functional group localization found in the reactive sites of enzymes. This is a potential limitation for 'one-pot' chemical syntheses of porous frameworks from simple starting materials. An alternative strategy is to prepare porous solids from synthetically preorganized molecular pores. In principle, functional organic pore modules could be covalently prefabricated and then assembled to produce materials with specific properties. However, this vision of mix-and-match assembly is far from being realized, not least because of the challenge in reliably predicting three-dimensional structures for molecular crystals, which lack the strong directional bonding found in networks. Here we show that highly porous crystalline solids can be produced by mixing different organic cage modules that self-assemble by means of chiral recognition. The structures of the resulting materials can be predicted computationally, allowing in silico materials design strategies. The constituent pore modules are synthesized in high yields on gram scales in a one-step reaction. Assembly of the porous co-crystals is as simple as combining the modules in solution and removing the solvent. In some cases, the chiral recognition between modules can be exploited to produce porous organic nanoparticles. We show that the method is valid for four different cage modules and can in principle be generalized in a computationally predictable manner based on a lock-and-key assembly between modules

Core-Shell Crystals of Porous Organic Cages

The first examples of core–shell porous molecular crystals are described. The physical properties of the core–shell crystals, such as surface hydrophobicity, CO2 /CH4 selectivity, are controlled by the chemical composition of the shell. This shows that porous core–shell molecular crystals can exhibit synergistic properties that out-perform materials built from the individual, constituent molecules

Oriented Two-Dimensional Porous Organic Cage Crystals

The formation of two-dimensional (2D) oriented porous organic cage crystals (consisting of imine-based tetrahedral molecules) on various substrates (such as silicon wafers and glass) by solution-processing is reported. Insight into the crystallinity, preferred orientation, and cage crystal growth was obtained by experimental and computational techniques. For the first time, structural defects in porous molecular materials were observed directly and the defect concentration could be correlated with crystal growth rate. These oriented crystals suggest potential for future applications, such as solution-processable molecular crystalline 2D membranes for molecular separations