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The thermal distillation of crude oil mixtures is an energy-intensive process, accounting for nearly 1% of global energy consumption. Membrane-based separations are an appealing alternative or tandem process to distillation due to intrinsic energy efficiency advantages. We developed a family of spirocyclic polytriazoles from structurally diverse monomers for membrane applications. The resulting polymers were prepared by a convenient step-growth method using copper-catalysed azide-alkyne cycloaddition, providing very fast reaction rates, high molecular weights and solubilities in common organic solvents and non-interconnected microporosity. Fractionation of whole Arabian light crude oil and atmospheric tower bottom feeds using these materials enriched the low-boiling-point components and removed trace heteroatom and metal impurities (comparable performance with the lighter feed as the commercial polyimide, Matrimid), demonstrating opportunities to reduce the energy cost of crude oil distillation with tandem membrane processes. Membrane-based molecular separation under these demanding conditions is made possible by high thermal stability and a moderate level of dynamic chain mobility, leading to transient interconnections between micropores, as revealed by the calculations of static and swollen pore structures.
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Metal-organic cages (MOCs) are popular host architectures assembled from ligands and metal ions/nodes. Assembling structurally complex, low-symmetry MOCs with anisotropic cavities can be limited by the formation of statistical isomer libraries. We set out to investigate the use of primary coordination-sphere engineering (CSE) to bias isomer selectivity within homo- and heteroleptic Pdn L2n cages. Unexpected differences in selectivities between alternative donor groups led us to recognise the significant impact of the second coordination sphere on isomer stabilities. From this, molecular-level insight into the origins of selectivity between cis and trans diastereoisomers was gained, highlighting the importance of both host-guest and host-solvent interactions, in addition to ligand design. This detailed understanding allows precision engineering of low-symmetry MOC assemblies without wholesale redesign of the ligand framework, and fundamentally provides a theoretical scaffold for the development of stimuli-responsive, shape-shifting MOCs.
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We derive design principles for the assembly of rectangular tetramines into Zn8 L6 pseudo-cubic coordination cages. Because of the rectangular, as opposed to square, geometry of the ligand panels, and the possibility of either Δ or Λ handedness of each metal center at the eight corners of the pseudo-cube, many different cage diastereomers are possible. Each of the six tetra-aniline subcomponents investigated in this work assembled with zinc(II) and 2-formylpyridine in acetonitrile into a single Zn8 L6 pseudo-cube diastereomer, however. Each product corresponded to one of four diastereomeric configurations, with T, Th , S6 or D3 symmetry. The preferred diastereomer for a given tetra-aniline subcomponent was shown to be dependent on its aspect ratio and conformational flexibility. Analysis of computationally modeled individual faces or whole pseudo-cubes provided insight as to why the observed diastereomers were favored.
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Novel functional materials are urgently needed to help combat the major global challenges facing humanity, such as climate change and resource scarcity. Yet, the traditional experimental materials discovery process is slow and the material space at our disposal is too vast to effectively explore using intuition-guided experimentation alone. Most experimental materials discovery programs necessarily focus on exploring the local space of known materials, so we are not fully exploiting the enormous potential material space, where more novel materials with unique properties may exist. Computation, facilitated by improvements in open-source software and databases, as well as computer hardware has the potential to significantly accelerate the rational development of materials, but all too often is only used to postrationalize experimental observations. Thus, the true predictive power of computation, where theory leads experimentation, is not fully utilized. Here, we discuss the challenges to successful implementation of computation-driven materials discovery workflows, and then focus on the progress of the field, with a particular emphasis on the challenges to reaching novel materials.
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Programas Informáticos , TecnologíaRESUMEN
Redox-active organic materials have emerged as promising alternatives to conventional inorganic electrode materials in electrochemical devices for energy storage. However, the deployment of redox-active organic materials in practical lithium-ion battery devices is hindered by their undesired solubility in electrolyte solvents, sluggish charge transfer and mass transport, as well as processing complexity. Here, we report a new molecular engineering approach to prepare redox-active polymers of intrinsic microporosity (PIMs) that possess an open network of subnanometer pores and abundant accessible carbonyl-based redox sites for fast lithium-ion transport and storage. Redox-active PIMs can be solution-processed into thin films and polymer-carbon composites with a homogeneously dispersed microstructure while remaining insoluble in electrolyte solvents. Solution-processed redox-active PIM electrodes demonstrate improved cycling performance in lithium-ion batteries with no apparent capacity decay. Redox-active PIMs with combined properties of intrinsic microporosity, reversible redox activity, and solution processability may have broad utility in a variety of electrochemical devices for energy storage, sensors, and electronic applications.
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Redox flow batteries (RFBs) based on aqueous organic electrolytes are a promising technology for safe and cost-effective large-scale electrical energy storage. Membrane separators are a key component in RFBs, allowing fast conduction of charge-carrier ions but minimizing the cross-over of redox-active species. Here, we report the molecular engineering of amidoxime-functionalized Polymers of Intrinsic Microporosity (AO-PIMs) by tuning their polymer chain topology and pore architecture to optimize membrane ion transport functions. AO-PIM membranes are integrated with three emerging aqueous organic flow battery chemistries, and the synergetic integration of ion-selective membranes with molecular engineered organic molecules in neutral-pH electrolytes leads to significantly enhanced cycling stability.
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Here we demonstrate how the hydrogen-bonding ability of a BINOL-based dialdehyde subcomponent dictated the stereochemical outcome of its subsequent self-assembly into one diastereomeric helicate form when bearing free hydroxy groups, and another in the case of its methylated congener. The presence of methyl groups also altered the self-sorting behavior when mixed with another, short linear dialdehyde subcomponent, switching the outcome of the system from narcissistic to integrative self-sorting. In all cases, the axial chirality of the BINOL building block also dictated helicate metal center handedness during stereospecific self-assembly. A new family of stereochemically pure heteroleptic helicates were thus prepared using the new knowledge gained. We also found that switching from FeII to ZnII, or the incorporation of a longer linear ligand, favored heteroleptic structure formation.
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Membranes with fast and selective ion transport are widely used for water purification and devices for energy conversion and storage including fuel cells, redox flow batteries and electrochemical reactors. However, it remains challenging to design cost-effective, easily processed ion-conductive membranes with well-defined pore architectures. Here, we report a new approach to designing membranes with narrow molecular-sized channels and hydrophilic functionality that enable fast transport of salt ions and high size-exclusion selectivity towards small organic molecules. These membranes, based on polymers of intrinsic microporosity containing Tröger's base or amidoxime groups, demonstrate that exquisite control over subnanometre pore structure, the introduction of hydrophilic functional groups and thickness control all play important roles in achieving fast ion transport combined with high molecular selectivity. These membranes enable aqueous organic flow batteries with high energy efficiency and high capacity retention, suggesting their utility for a variety of energy-related devices and water purification processes.
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An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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Computation is increasingly being used to try to accelerate the discovery of new materials. One specific example of this is porous molecular materials, specifically porous organic cages, where the porosity of the materials predominantly comes from the internal cavities of the molecules themselves. The computational discovery of novel structures with useful properties is currently hindered by the difficulty in transitioning from a computational prediction to synthetic realization. Attempts at experimental validation are often time-consuming, expensive, and frequently, the key bottleneck of material discovery. In this work, we developed a computational screening workflow for porous molecules that includes consideration of the synthetic difficulty of material precursors, aimed at easing the transition between computational prediction and experimental realization. We trained a machine learning model by first collecting data on 12,553 molecules categorized either as "easy-to-synthesize" or "difficult-to-synthesize" by expert chemists with years of experience in organic synthesis. We used an approach to address the class imbalance present in our data set, producing a binary classifier able to categorize easy-to-synthesize molecules with few false positives. We then used our model during computational screening for porous organic molecules to bias toward precursors whose easier synthesis requirements would make them promising candidates for experimental realization and material development. We found that even by limiting precursors to those that are easier-to-synthesize, we are still able to identify cages with favorable, and even some rare, properties.
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Intuición , Aprendizaje Automático , Técnicas de Química Sintética , PorosidadRESUMEN
Computational software workflows are emerging as all-in-one solutions to speed up the discovery of new materials. Many computational approaches require the generation of realistic structural models for property prediction and candidate screening. However, molecular and supramolecular materials represent classes of materials with many potential applications for which there is no go-to database of existing structures or general protocol for generating structures. Here, we report a new version of the supramolecular toolkit, stk, an open-source, extendable, and modular Python framework for general structure generation of (supra)molecular structures. Our construction approach works on arbitrary building blocks and topologies and minimizes the input required from the user, making stk user-friendly and applicable to many material classes. This version of stk includes metal-containing structures and rotaxanes as well as general implementation and interface improvements. Additionally, this version includes built-in tools for exploring chemical space with an evolutionary algorithm and tools for database generation and visualization. The latest version of stk is freely available at github.com/lukasturcani/stk.
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Unsymmetrical ditopic ligands can self-assemble into reduced-symmetry Pd2 L4 metallo-cages with anisotropic cavities, with implications for high specificity and affinity guest-binding. Mixtures of cage isomers can form, however, resulting in undesirable system heterogeneity. It is paramount to be able to design components that preferentially form a single isomer. Previous data suggested that computational methods could predict with reasonable accuracy whether unsymmetrical ligands would preferentially self-assemble into single cage isomers under constraints of geometrical mismatch. We successfully apply a collaborative computational and experimental workflow to mitigate costly trial-and-error synthetic approaches. Our rapid computational workflow constructs unsymmetrical ligands and their Pd2 L4 cage isomers, ranking the likelihood for exclusively forming cis-Pd2 L4 assemblies. From this narrowed search space, we successfully synthesised four new, low-symmetry, cis-Pd2 L4 cages.
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We designed a straightforward synthetic route towards a full-fledged family of π-extended helicenes: superhelicenes. They have two hexa-peri-hexabenzocoronenes (HBCs) in common that are connected via a central five-membered ring. By means of structurally altering this 5-membered ring, we realized a versatile library of molecular building blocks. Not only the superhelicene structure, but also their features are tuned with ease. In-depth physico-chemical characterizations served as a proof of concept thereof. The superhelicene enantiomers were separated, their circular dichroism was measured in preliminary studies and concluded with an enantiomeric assignment. Our work was rounded-off by crystal structure analyses. Mixed stacks of M- and P-isomers led to twisted molecular wires. Using such stacks, charge-carrier mobilities were calculated, giving reason to expect outstanding hole transporting properties.
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Molecular dumbbells with organic cage capping units were synthesised via a multi-component imine condensation between a tri-topic amine and di- and tetra-topic aldehydes. This is an example of self-sorting, which can be rationalised by computational modelling.
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Aromatic organic compounds can be used as electrode materials in rechargeable batteries and are expected to advance the development of both anode and cathode materials for sodium-ion batteries (SIBs). However, most aromatic organic compounds assessed as anode materials in SIBs to date exhibit significant degradation issues under fast-charge/discharge conditions and unsatisfying long-term cycling performance. Now, a molecular design concept is presented for improving the stability of organic compounds for battery electrodes. The molecular design of the investigated compound, [2.2.2.2]paracyclophane-1,9,17,25-tetraene (PCT), can stabilize the neutral state by local aromaticity and the doubly reduced state by global aromaticity, resulting in an anode material with extraordinarily stable cycling performance and outstanding performance under fast-charge/discharge conditions, demonstrating an exciting new path for the development of electrode materials for SIBs and other types of batteries.
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Many interesting target guest molecules have low symmetry, yet most methods for synthesising hosts result in highly symmetrical capsules. Methods of generating lower symmetry pores are thus required to maximise the binding affinity in host-guest complexes. Herein, we use mixtures of tetraaldehyde building blocks with cyclohexanediamine to access low-symmetry imine cages. Whether a low-energy cage is isolated can be correctly predicted from the thermodynamic preference observed in computational models. The stability of the observed structures depends on the geometrical match of the aldehyde building blocks. One bent aldehyde stands out as unable to assemble into high-symmetry cages-and the same aldehyde generates low-symmetry socially self-sorted cages when combined with a linear aldehyde. We exploit this finding to synthesise a family of low-symmetry cages containing heteroatoms, illustrating that pores of varying geometries and surface chemistries may be reliably accessed through computational prediction and self-sorting.
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The properties of an organic semiconductor are dependent on both the chemical structure of the molecule involved, and how it is arranged in the solid-state. It is challenging to extract the influence of each individual factor, as small changes in the molecular structure often dramatically change the crystal packing and hence solid-state structure. Here, we use calculations to explore the influence of the nitrogen position on the charge mobility of a chiral organic molecule when the crystal packing is kept constant. The transfer integrals for a series of enantiopure aza[6]helicene crystals sharing the same packing were analysed in order to identify the best supramolecular motifs to promote charge carrier mobility. The regioisomers considered differ only in the positioning of the nitrogen atom in the aromatic scaffold. The simulations showed that even this small change in the chemical structure has a strong effect on the charge transport in the crystal, leading to differences in charge mobility of up to one order of magnitude. Some aza[6]helicene isomers that were packed interlocked with each other showed high HOMO-HOMO integrals (up to 70 meV), whilst molecules arranged with translational symmetry generally afforded the highest LUMO-LUMO integrals (40-70 meV). As many of the results are not intuitively obvious, a computational approach provides additional insight into the design of new semiconducting organic materials.
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We describe the a priori computational prediction and realization of multi-component cage pots, starting with molecular predictions based on candidate precursors through to crystal structure prediction and synthesis using robotic screening. The molecules were formed by the social self-sorting of a tri-topic aldehyde with both a tri-topic amine and di-topic amine, without using orthogonal reactivity or precursors of the same topicity. Crystal structure prediction suggested a rich polymorphic landscape, where there was an overall preference for chiral recognition to form heterochiral rather than homochiral packings, with heterochiral pairs being more likely to pack window-to-window to form two-component capsules. These crystal packing preferences were then observed in experimental crystal structures.
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A tool for the automated assembly, molecular optimization and property calculation of supramolecular materials is presented. stk is a modular, extensible and open-source Python library that provides a simple Python API and integration with third party computational codes. stk currently supports the construction of linear polymers, small linear oligomers, organic cages in multiple topologies and covalent organic frameworks (COFs) in multiple framework topologies, but is designed to be easy to extend to new, unrelated, supramolecules or new topologies. Extension to metal-organic frameworks (MOFs), metallocycles or supramolecules, such as catenanes, would be straightforward. Through integration with third party codes, stk offers the user the opportunity to explore the potential energy landscape of the assembled supramolecule and then calculate the supramolecule's structural features and properties. stk provides support for high-throughput screening of large batches of supramolecules at a time. The source code of the program can be found at https://github.com/supramolecular-toolkit/stk. © 2018 Wiley Periodicals, Inc.
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Structural analysis of molecular pores can yield important information on their behavior in solution and in the solid state. We developed pywindow, a python package that enables the automated analysis of structural features of porous molecular materials, such as molecular cages. Our analysis includes the cavity diameter, number of windows, window diameters, and average molecular diameter. Molecular dynamics trajectories of molecular pores can also be analyzed to explore the influence of flexibility. We present the methodology, validation, and application of pywindow for the analysis of molecular pores, metal-organic polyhedra, and some instances of framework materials. pywindow is freely available from github.com/JelfsMaterialsGroup/pywindow .