Publications
155 results found
Kearsey RJ, Tarzia A, Little MA, et al., 2023, Competitive aminal formation during the synthesis of a highly soluble, isopropyl-decorated imine porous organic cage., Chem Commun (Camb)
The synthesis of a new porous organic cage decorated with isopropyl moieties (CC21) was achieved from the reaction of triformylbenzene and an isopropyl functionalised diamine. Unlike structurally analogous porous organic cages, its synthesis proved challenging due to competitive aminal formation, rationalised using control experiments and computational modelling. The use of an additional amine was found to increase conversion to the desired cage.
Davies JA, Tarzia A, Ronson TK, et al., 2023, Tetramine Aspect Ratio and Flexibility Determine Framework Symmetry for Zn8L6 Self-Assembled Structures, ANGEWANDTE CHEMIE-INTERNATIONAL EDITION, ISSN: 1433-7851
Anipa V, Tarzia A, Jelfs KE, et al., 2023, Pore topology analysis in porous molecular systems., R Soc Open Sci, Vol: 10, ISSN: 2054-5703
Porous molecular materials are constructed from molecules that assemble in the solid-state such that there are cavities or an interconnected pore network. It is challenging to control the assembly of these systems, as the interactions between the molecules are generally weak, and subtle changes in the molecular structure can lead to vastly different intermolecular interactions and subsequently different crystal packing arrangements. Similarly, the use of different solvents for crystallization, or the introduction of solvent vapour, can result in different polymorphs and pore networks being formed. It is difficult to uniquely describe the pore networks formed, and thus we analyse 1033 crystal structures of porous molecular systems to determine the underlying topology of their void spaces and potential guest diffusion networks. Material-agnostic topology definitions are applied. We use the underlying topological nets to examine whether it is possible to apply isoreticular design principles to porous molecular materials. Overall, our automatic analysis of a large dataset gives a general insight into the relationships between molecular topologies and the topological nets of their pore network. We show that while porous molecular systems tend to pack similarly to non-porous molecules, the topologies of their pore distributions resemble those of more prominent porous materials, such as metal-organic frameworks and covalent organic frameworks.
Wang A, Tan R, Liu D, et al., 2023, Ion-selective microporous polymer membranes with hydrogen-bond and salt-bridge networks for aqueous organic redox flow batteries., Advanced Materials, Pages: e2210098-e2210098, ISSN: 0935-9648
Redox flow batteries (RFBs) have great potential for long-duration grid-scale energy storage. Ion conducting membranes are a crucial component in RFBs, allowing charge-carrying ions to transport while preventing the cross-mixing of redox couples. Commercial Nafion membranes are widely used in RFBs, but their unsatisfactory ionic and molecular selectivity as well as high costs limit the performance and the widespread deployment of this technology. To extend the longevity and reduce the cost of RFB systems, inexpensive ion-selective membranes are highly desired that concurrently deliver low ionic resistance and high selectivity towards redox-active species. In this work, high-performance RFB membranes are fabricated from blends of carboxylate- and amidoxime-functionalized polymers of intrinsic microporosity (PIMs) that exploit the beneficial properties of both polymers. The enthalpy-driven formation of cohesive interchain interactions, including hydrogen bonds and salt bridges, facilitates the microscopic miscibility of the blends, while ionizable functional groups within the sub-nanometer pores allow optimization of membrane ion transport functions. The resulting microporous membranes demonstrate fast cation conduction with low crossover of redox-active molecular species, enabling improved power ratings and reduced capacity fade in aqueous RFBs using anthraquinone and ferrocyanide as redox couples. This article is protected by copyright. All rights reserved.
Wade J, Salerno F, Kilbride R, et al., 2022, Controlling anisotropic properties by manipulating the orientation of chiral small molecules, Nature Chemistry, Vol: 14, Pages: 1383-1389, ISSN: 1755-4330
Chiral π-conjugated molecules bring new functionality to technological applications and represent an exciting, rapidly expanding area of research. Their functional properties, such as the absorption and emission of circularly polarised light or the transport of spin-polarised electrons, are highly anisotropic. As a result, the orientation of chiral molecules criticallydetermines the functionality and efficiency of chiral devices. Here we present a strategy to control the orientation of a small chiral molecule (2,2’-dicyano[6]helicene, CN6H): the use of organic and inorganic templating layers. Such templating layers can either force CN6H molecules to adopt a face-on orientation and self-assemble into upright supramolecular columns oriented with their helical axis perpendicular to the substrate, or an edge-onorientation with parallel-lying supramolecular columns. Through such control, we show that low- and high-energy chiroptical responses can be independently ‘turned on’ or ‘turned off’. The templating methodologies described here provide a simple way to engineer orientational control, and by association, anisotropic functional properties of chiral molecular systems for a range of emerging technologies.
Wolpert EHH, Jelfs KEE, 2022, Coarse-grained modelling to predict the packing of porous organic cages, CHEMICAL SCIENCE, Vol: 13, Pages: 13588-13599, ISSN: 2041-6520
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- Citations: 1
Jelfs KE, 2022, Computational modeling to assist in the discovery of supramolecular materials, ANNALS OF THE NEW YORK ACADEMY OF SCIENCES, ISSN: 0077-8923
Bechis I, Sapnik AF, Tarzia A, et al., 2022, Modeling the Effect of Defects and Disorder in Amorphous Metal-Organic Frameworks, CHEMISTRY OF MATERIALS, ISSN: 0897-4756
Mroz AM, Posligua V, Tarzia A, et al., 2022, Into the Unknown: How Computation Can Help Explore Uncharted Material Space, JOURNAL OF THE AMERICAN CHEMICAL SOCIETY, Vol: 144, Pages: 18730-18743, ISSN: 0002-7863
Li R-J, Tarzia A, Posligua V, et al., 2022, Orientational self-sorting in cuboctahedral Pd cages, CHEMICAL SCIENCE, Vol: 13, Pages: 11912-11917, ISSN: 2041-6520
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- Citations: 1
Ess DH, Jelfs KE, Kulik HJ, 2022, Chemical design by artificial intelligence, JOURNAL OF CHEMICAL PHYSICS, Vol: 157, ISSN: 0021-9606
Wang A, Tan R, Breakwell C, et al., 2022, Solution-processable redox-active polymers of intrinsic microporosity for electrochemical energy storage, Journal of the American Chemical Society, Vol: 144, Pages: 17198-17208, ISSN: 0002-7863
Redox-active organic materials have emerged as promising alternatives to conventional inorganicelectrode materials in electrochemical devices for energy storage. However, the deployment of redoxactive organic materials in practical lithium-ion battery devices is hindered by their undesired solubilityin 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 intrinsicmicroporosity (PIMs) that possess an open network of sub-nanometer pores and abundant accessiblecarbonyl-based redox sites for fast lithium-ion transport and storage. Redox-active PIMs can be solutionprocessed into thin films and polymer-carbon composites with a homogeneously dispersedmicrostructure, while remaining insoluble in electrolyte solvents. Solution-processed redox-active PIMelectrodes demonstrate improved cycling performance in lithium-ion batteries with no apparent capacitydecay. Redox-active PIMs with combined properties of intrinsic microporosity, reversible redox activityand solution processability may have broad utility in a variety of electrochemical devices for energystorage, sensors and electronic applications.
Ye C, Tan R, Wang A, et al., 2022, Long-life aqueous organic redox flow batteries enabled by amidoxime-functionalized ion-selective polymer membranes, Angewandte Chemie International Edition, Vol: 61, ISSN: 1433-7851
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 selectivity. 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.
Perez NH, Sherin PS, Posligua V, et al., 2022, Emerging properties from mechanical tethering within a post-synthetically functionalised catenane scaffold, Chemical Science, Vol: 13, Pages: 11368-11375, ISSN: 2041-6520
Maintaining close spatial proximity of functional moieties within molecular systems can result in fascinating emergent properties. Whilst much work has been done on covalent tethering of functional units for myriad applications, investigations into mechanically linked systems are relatively rare. Formation of the mechanical bond is usually the final step in the synthesis of interlocked molecules, placing limits on the throughput of functionalised architectures. Herein we present the synthesis of a bis-azide [2]catenane scaffold that can be post-synthetically modified using CuAAC ‘click’ chemistry. In this manner we have been able to access functionalised catenanes from a common precursor and study the properties of electrochemically active, emissive and photodimerisable units within the mechanically interlocked system in comparison to non-interlocked analogues. Our data demonstrates that the greater (co-)conformational flexibility that can be obtained with mechanically interlocked systems compared to traditional covalent tethers paves the way for developing new functional molecules with exciting properties.
Ye C, Wang A, Breakwell C, et al., 2022, Development of efficient aqueous organic redox flow batteries using ion-sieving sulfonated polymer membranes, Nature Communications, Vol: 13, ISSN: 2041-1723
Redox flow batteries using aqueous organic-based electrolytes are promising candidates for developing cost-effective grid-scale energy storage devices. However, a significant drawback of these batteries is the cross-mixing of active species through the membrane, which causes battery performance degradation. To overcome this issue, here we report size-selective ion-exchange membranes prepared by sulfonation of a spirobifluorene-based microporous polymer and demonstrate their efficient ion sieving functions in flow batteries. The spirobifluorene unit allows control over the degree of sulfonation to optimize the transport of cations, whilst the microporous structure inhibits the crossover of organic molecules via molecular sieving. Furthermore, the enhanced membrane selectivity mitigates the crossover-induced capacity decay whilst maintaining good ionic conductivity for aqueous electrolyte solution at pH 9, where the redox-active organic molecules show long-term stability. We also prove the boosting effect of the membranes on the energy efficiency and peak power density of the aqueous redox flow battery, which shows stable operation for about 120 h (i.e., 2100 charge-discharge cycles at 100 mA cm−2) in a laboratory-scale cell.
Egleston BD, Mroz A, Jelfs KE, et al., 2022, Porous liquids - the future is looking emptier, CHEMICAL SCIENCE, Vol: 13, Pages: 5042-5054, ISSN: 2041-6520
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- Citations: 2
Sapnik AF, Bechis I, Bumstead AM, et al., 2022, Multivariate analysis of disorder in metal-organic frameworks, NATURE COMMUNICATIONS, Vol: 13
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- Citations: 2
Yuan Q, Szczypiński FT, Jelfs KE, 2022, Explainable graph neural networks for organic cages., Digit Discov, Vol: 1, Pages: 127-138
The development of accurate and explicable machine learning models to predict the properties of topologically complex systems is a challenge in materials science. Porous organic cages, a class of polycyclic molecular materials, have potential application in molecular separations, catalysis and encapsulation. For most applications of porous organic cages, having a permanent internal cavity in the absence of solvent, a property termed "shape persistence" is critical. Here, we report the development of Graph Neural Networks (GNNs) to predict the shape persistence of organic cages. Graph neural networks are a class of neural networks where the data, in our case that of organic cages, are represented by graphs. The performance of the GNN models was measured against a previously reported computational database of organic cages formed through a range of [4 + 6] reactions with a variety of reaction chemistries. The reported GNNs have an improved prediction accuracy and transferability compared to random forest predictions. Apart from the improvement in predictive power, we explored the explicability of the GNNs by computing the integrated gradient of the GNN input. The contribution of monomers and molecular fragments to the shape persistence of the organic cages could be quantitatively evaluated with integrated gradients. With the added explicability of the GNNs, it was possible not only to accurately predict the property of organic materials, but also to interpret the predictions of the deep learning models and provide structural insights for the discovery of future materials.
Tarzia A, Jelfs K, 2022, Unlocking the computational design of metal-organic cages, Chemical Communications, Vol: 58, Pages: 3717-3730, ISSN: 1359-7345
Metal–organic cages are macrocyclic structures that can possess an intrinsic void that can hold molecules for encapsulation, adsorption, sensing, and catalysis applications. As metal–organic cages may be comprised from nearly any combination of organic and metal-containing components, cages can form with diverse shapes and sizes, allowing for tuning toward targeted properties. Therefore, their near-infinite design space is almost impossible to explore through experimentation alone and computational design can play a crucial role in exploring new systems. Although high-throughput computational design and screening workflows have long been known as powerful tools in drug and materials discovery, their application in exploring metal–organic cages is more recent. We show examples of structure prediction and host–guest/catalytic property evaluation of metal–organic cages. These examples are facilitated by advances in methods that handle metal-containing systems with improved accuracy and are the beginning of the development of automated cage design workflows. We finally outline a scope for how high-throughput computational methods can assist and drive experimental decisions as the field pushes toward functional and complex metal–organic cages. In particular, we highlight the importance of considering realistic, flexible systems.
Ning G-H, Cui P, Sazanovich I, et al., 2021, Organic cage inclusion crystals exhibiting guest-enhanced multiphoton harvesting, CHEM, Vol: 7, Pages: 3157-3170, ISSN: 2451-9294
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- Citations: 3
Bennett S, Szczypiński F, Turcani L, et al., 2021, Materials precursor score: modelling chemists' intuition for the synthetic accessibility of porous organic cage precursors, Journal of Chemical Information and Modeling, Vol: 61, Pages: 4342-4356, ISSN: 1549-9596
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 realisation. 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 realisation. We trained a machine learning model by first collecting data on 12,553 molecules categorised either as `easy-to-synthesise' or `difficult-to-synthesise' by expert chemists with years of experience in organic synthesis. We used an approach to address the class imbalance present in our dataset, producing a binary classifier able to categorise easy-to-synthesise molecules with few false positives. We then used our model during computational screening for porous organic molecules to bias towards precursors whose easier synthesis requirements would make them promising candidates for experimental realisation and material development. We found that even by limiting precursors to those that are easier-to-synthesise, we are still able to identify cages with favourable, and even some rare, properties.
Kai A, Egleston BD, Tarzia A, et al., 2021, Modular Type III Porous Liquids Based on Porous Organic Cage Microparticles, ADVANCED FUNCTIONAL MATERIALS, Vol: 31, ISSN: 1616-301X
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- Citations: 11
Tarzia A, Lewis JEM, Jelfs KE, 2021, High‐throughput computational evaluation of low symmetry Pd <sub>2</sub> L <sub>4</sub> Cages to Aid in System Design**, Angewandte Chemie, Vol: 133, Pages: 21047-21055, ISSN: 0044-8249
Unsymmetrical ditopic ligands can self-assemble into reduced-symmetry Pd2L4 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 Pd2L4 cage isomers, ranking the likelihood for exclusively forming cis-Pd2L4 assemblies. From this narrowed search space, we successfully synthesised four new, low-symmetry, cis-Pd2L4 cages.
Tarzia A, Lewis J, Jelfs KE, 2021, High‐throughput computational evaluation of low symmetry Pd2L4 cages to aid in system design, Angewandte Chemie International Edition, Vol: 60, Pages: 20879-20887, ISSN: 1433-7851
The use of unsymmetrical components in metallo-supramolecular chemistry allows for low- symmetry architectures with anisotropic cavities toward guest-binding with high specificity and affinity. Unsymmetrical ditopic ligands mixed with Pd(II) have the potential to self-assemble into reduced symmetry Pd 2 L 4 metallo-architectures. Mixtures of isomers can form, however, resulting in potentially undesirable heterogeneity within a system. Therefore 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 a single isomer under constraints of geometrical mismatch. We successfully apply a collaborative computational and experimental workflow to mitigate costly trial-and-error synthetic approaches. Our low-cost computational workflow rapidly constructs new unsymmetrical ligands (and Pd 2 L 4 cage isomers) and ranks their likelihood for forming cis -Pd 2 L 4 assemblies. From this narrowed search space, we successfully synthesised four new low-symmetry, cis -Pd 2 L 4 cages, with cavities of different shapes and sizes.
Schmidt J, Weatherby J, Sugden I, et al., 2021, Computational screening of organic semiconductors: exploring side-group functionalisation and assembly to optimise charge transport in chiral molecules, Crystal Growth and Design, Vol: 21, Pages: 5036-5049, ISSN: 1528-7483
Molecular materials are challenging to design as their packing arrangement and hence properties are subject to subtle variations in the interplay of soft intermolecular interactions that are difficult to predict. The rational design of new molecular materials with tailored properties is currently hampered by the lack of knowledge of how a candidate molecule will pack in space and how we can control the polymorphs we can experimentally obtain. Here, we develop a simplified approach to aid the material design process, by the development of a screening process that is used to test 1344 helicene molecules that have potential as organic electronic materials. Our approach bridges the gap between single molecule design, molecular assembly, and the resulting charge-carrier mobilities. We find that fluorination significantly improves electron transport in the molecular material by up to 200%; the reference [6]helicene packing showed a mobility of 0.30 cm2 V-1 s-1, fluorination increased the mobility to up to 0.96 and 0.97 (13-fluoro[6]H and 4,13-difluoro[6]H), assuming an outer reorganisation energy of 0.30 eV. Side groups containing triple bonds largely lead to improved transfer integrals. We validate our screening approach through the use of crystal structure prediction to confirm the presence of favourable packing motifs to maximize charge mobility.
Reger D, Haines P, Amsharov KY, et al., 2021, A Family of Superhelicenes: Easily Tunable, Chiral Nanographenes by Merging Helicity with Planar π Systems, Angewandte Chemie, Vol: 133, Pages: 18221-18229, ISSN: 0044-8249
Jux N, Reger D, Haines P, et al., 2021, A family of superhelicenes - easily tunable, chiral nanographenes by merging helicity with planar π-systems, Angewandte Chemie International Edition, Vol: 60, Pages: 18073-18081, ISSN: 1433-7851
Incorporating helicity into large polycyclic aromatic hydrocarbons (PAHs) constitutes a new field of research at the interface between chemistry and material sciences. Lately, interest in the design of π-extended helicenes has surged. This new class of twisted, chiral nanographenes not only reveals unique characteristics but also finds its way into emerging applications such as spintronics. Insights into their structure-property relationships and on-demand tuning are scarce. To close these knowledge gaps, we designed a straightforward synthetic route towards a full-fledged family of π-extended helicenes: superhelicenes. Common are two hexa-peri-hexabenzocoronenes (HBCs) connected via a central 5-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.
Wolpert EH, Jelfs KE, 2021, Predicting the packing behaviour of porous organic cages, Publisher: INT UNION CRYSTALLOGRAPHY, Pages: C712-C712, ISSN: 2053-2733
Bennett S, Szczypiński F, Turcani L, et al., 2021, Materials Precursor Score: Modelling Chemists' Intuition for the Synthetic Accessibility of Porous Organic Cage Precursors
<jats:p><div>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 realisation. 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 realisation. We trained a machine learning model by first collecting data on 12,553 molecules categorised either as `easy-to-synthesise' or `difficult-to-synthesise' by expert chemists with years of experience in organic synthesis. We used an approach to address the class imbalance present in our dataset, producing a binary classifier able to categorise easy-to-synthesise molecules with few false positives. We then used our model during computational screening for porous organic molecules to bias towards precursors whose easier synthesis requirements would make them promising candidates for experimental realisation and material development. We found that even by limiting precursors to those that are easier-to-synthesise, we are still able to identify cages with favourable, and even some rare, properties. </div></jats:p>
Zou Y-Q, Zhang D, Ronson TK, et al., 2021, Sterics and Hydrogen Bonding Control Stereochemistry and Self-Sorting in BINOL-Based Assemblies, JOURNAL OF THE AMERICAN CHEMICAL SOCIETY, Vol: 143, Pages: 9009-9015, ISSN: 0002-7863
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- Citations: 15
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