A soft cable loop based gripper for robotic automation of chemistry

Robotic automation is proving itself indispensable in the modern Chemistry laboratory, but adoption is slowed down by the technical challenges of implementing such systems. This paper reports on a novel adaptive gripper mechanism that can easily and reliably grasp cylindrical and prismatic objects of various sizes with limited clearance required. The proposed design exploits the inherent compliance of a cable that is driven to fully envelope the target object. The cable is run through a rigid finger, allowing the loop to be placed around objects with minimal clearance required and to provide support for the object once the grip is complete. Thanks to the compliant nature of the mechanism, the gripper requires minimal control effort to complete a gasping task. A prototype of the gripper has been designed and built for chemistry automation tasks, where it showed very high grasp reliability with ≤ 1 % grasp failures.

Modular, multi-robot integration of laboratories: an autonomous workflow for solid-state chemistry

Automation can transform productivity in research activities that use liquid handling, such as organic synthesis, but it has made less impact in materials laboratories, which require sample preparation steps and a range of solid-state characterization techniques. For example, powder X-ray diffraction (PXRD) is a key method in materials and pharmaceutical chemistry, but its end-to-end automation is challenging because it involves solid powder handling and sample processing. Here we present a fully autonomous solid-state workflow for PXRD experiments that can match or even surpass manual data quality, encompassing crystal growth, sample preparation, and automated data capture. The workflow involves 12 steps performed by a team of three multipurpose robots, illustrating the power of flexible, modular automation to integrate complex, multitask laboratories.

Fine-tuning GPT-3 for machine learning electronic and functional properties of organic molecules

We evaluate the effectiveness of fine-tuning GPT-3 for the prediction of electronic and functional properties of organic molecules. Our findings show that fine-tuned GPT-3 can successfully identify and distinguish between chemically meaningful patterns, and discern subtle differences among them, exhibiting robust predictive performance for the prediction of molecular properties. We focus on assessing the fine-tuned models' resilience to information loss, resulting from the absence of atoms or chemical groups, and to noise that we introduce via random alterations in atomic identities. We discuss the challenges and limitations inherent to the use of GPT-3 in molecular machine-learning tasks and suggest potential directions for future research and improvements to address these issues.

Machine Learning Accelerated Exploration of Ternary Organic Heterojunction Photocatalysts for Sacrificial Hydrogen Evolution

Donor-acceptor heterojunctions in organic photocatalysts can provide enhanced exciton dissociation and charge separation, thereby improving the photocatalytic activity. However, the wide choice of possible donors and acceptors poses a challenge for the rational design of organic heterojunction photocatalysts, particularly for large ternary phase spaces. We accelerated the exploration of ternary organic heterojunction photocatalysts (TOHP) by using a combination of machine learning and high-throughput experimental screening. This involved 736 experiments in all, out of possible 4320 ternary combinations. The top ten most active TOHPs discovered using this strategy showed outstanding sacrificial hydrogen production rates of more than 500 mmol g-1 h-1, with the most active ternary material reaching a rate of 749.8 mmol g-1 h-1 under 1 sun illumination. These rates of photocatalytic hydrogen generation are among the highest reported for organic photocatalysts in the literature.

Continuous chiral distances for two-dimensional lattices

Chirality was traditionally considered a binary property of periodic lattices and crystals. However, the classes of two-dimensional lattices modulo rigid motion form a continuous space, which was recently parametrized by three geographic-style coordinates. The four non-oblique Bravais classes of two-dimensional lattices form low-dimensional singular subspaces in the full continuous space. Now, the deviations of a lattice from its higher symmetry neighbors can be continuously quantified by real-valued distances satisfying metric axioms. This article analyzes these and newer G-chiral distances for millions of two-dimensional lattices that are extracted from thousands of available two-dimensional materials and real crystal structures in the Cambridge Structural Database.

Controlling the Crystallisation and Hydration State of Crystalline Porous Organic Salts

Crystalline porous organic salts (CPOS) are a subclass of molecular crystals. The low solubility of CPOS and their building blocks limits the choice of crystallisation solvents to water or polar alcohols, hindering the isolation, scale-up, and scope of the porous material. In this work, high throughput screening was used to expand the solvent scope, resulting in the identification of a new porous salt, CPOS-7, formed from tetrakis(4-sulfophenyl)methane (TSPM) and tetrakis(4-aminophenyl)methane (TAPM). CPOS-7 does not form with standard solvents for CPOS, rather a hydrated phase (Hydrate2920) previously reported is isolated. Initial attempts to translate the crystallisation to batch led to challenges with loss of crystallinity and Hydrate2920 forming favorably in the presence of excess water. Using acetic acid as a dehydrating agent hindered formation of Hydrate2920 and furthermore allowed for direct conversion to CPOS-7. To allow for direct formation of CPOS-7 in high crystallinity flow chemistry was used for the first time to circumvent the issues found in batch. CPOS-7 and Hydrate2920 were shown to have promise for water and CO2 capture, with CPOS-7 having a CO2 uptake of 4.3 mmol/g at 195 K, making it one of the most porous CPOS reported to date.

Soft Hydrogen-Bonded Organic Frameworks Constructed Using a Flexible Organic Cage Hinge

Soft porous crystals combine flexibility and porosity, allowing them to respond structurally to external physical and chemical environments. However, striking the right balance between flexibility and sufficient rigidity for porosity is challenging, particularly for molecular crystals formed by using weak intermolecular interactions. Here, we report a flexible oxygen-bridged prismatic organic cage molecule, Cage-6-COOH, which has three pillars that exhibit "hinge-like" rotational motion in the solid state. Cage-6-COOH can form a range of hydrogen-bonded organic frameworks (HOFs) where the "hinge" can accommodate a remarkable 67° dihedral angle range between neighboring units. This stems both from flexibility in the noncovalent hydrogen-bonding motifs in the HOFs and the molecular flexibility in the oxygen-linked cage hinge itself. The range of structures for Cage-6-COOH includes two topologically complex interpenetrated HOFs, CageHOF-2α and CageHOF-2β. CageHOF-2α is nonporous, while CageHOF-2β has permanent porosity and a surface area of 458 m2 g-1. The flexibility of Cage-6-COOH allows this molecule to rapidly transform from a low-crystallinity solid into the two crystalline interpenetrated HOFs, CageHOF-2α and CageHOF-2β, under mild conditions simply by using acetonitrile or ethanol vapor, respectively. This self-healing behavior was selective, with the CageHOF-2β structure exhibiting structural memory behavior.

Making the connections: physical and electric interactions in biohybrid photosynthetic systems

Biohybrid photosynthesis systems, which combine biological and non-biological materials, have attracted recent interest in solar-to-chemical energy conversion. However, the solar efficiencies of such systems remain low, despite advances in both artificial photosynthesis and synthetic biology. Here we discuss the potential of conjugated organic materials as photosensitisers for biological hybrid systems compared to traditional inorganic semiconductors. Organic materials offer the ability to tune both photophysical properties and the specific physicochemical interactions between the photosensitiser and biological cells, thus improving stability and charge transfer. We highlight the state-of-the-art and opportunities for new approaches in designing new biohybrid systems. This perspective also summarises the current understanding of the underlying electron transport process and highlights the research areas that need to be pursued to underpin the development of hybrid photosynthesis systems.

Go with the flow: deep learning methods for autonomous viscosity estimations

Closed-loop experiments can accelerate material discovery by automating both experimental manipulations and decisions that have traditionally been made by researchers. Fast and non-invasive measurements are particularly attractive for closed-loop strategies. Viscosity is a physical property for fluids that is important in many applications. It is fundamental in application areas such as coatings; also, even if viscosity is not the key property of interest, it can impact our ability to do closed-loop experimentation. For example, unexpected increases in viscosity can cause liquid-handling robots to fail. Traditional viscosity measurements are manual, invasive, and slow. Here we use convolutional neural networks (CNNs) as an alternative to traditional viscometry by non-invasively extracting the spatiotemporal features of fluid motion under flow. To do this, we built a workflow using a dual-armed collaborative robot that collects video data of fluid motion autonomously. This dataset was then used to train a 3-dimensional convolutional neural network (3D-CNN) for viscosity estimation, either by classification or by regression. We also used these models to identify unknown laboratory solvents, again based on differences in fluid motion. The 3D-CNN model performance was compared with the performance of a panel of human participants for the same classification tasks. Our models strongly outperformed human classification in both cases. For example, even with training on fewer than 50 videos for each liquid, the 3D-CNN model gave an average accuracy of 88% for predicting the identity of five different laboratory solvents, compared to an average accuracy of 32% for human observation. For comparison, random category selection would give an average accuracy of 20%. Our method offers an alternative to traditional viscosity measurements for autonomous chemistry workflows that might be used both for process control (e.g., choosing not to pipette liquids that are too viscous) or for materials discovery (e.g., identifying new polymerization catalysts on the basis of viscosification).

Experimental Confirmation of a Predicted Porous Hydrogen-Bonded Organic Framework

Hydrogen-bonded organic frameworks (HOFs) with low densities and high porosities are rare and challenging to design because most molecules have a strong energetic preference for close packing. Crystal structure prediction (CSP) can rank the crystal packings available to an organic molecule based on their relative lattice energies. This has become a powerful tool for the a priori design of porous molecular crystals. Previously, we combined CSP with structure-property predictions to generate energy-structure-function (ESF) maps for a series of triptycene-based molecules with quinoxaline groups. From these ESF maps, triptycene trisquinoxalinedione (TH5) was predicted to form a previously unknown low-energy HOF (TH5-A) with a remarkably low density of 0.374 g cm-3 and three-dimensional (3D) pores. Here, we demonstrate the reliability of those ESF maps by discovering this TH5-A polymorph experimentally. This material has a high accessible surface area of 3,284 m2  g-1 , as measured by nitrogen adsorption, making it one of the most porous HOFs reported to date.

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Competitive aminal formation during the synthesis of a highly soluble, isopropyl-decorated imine porous organic cage

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.

Synthetic engineering of a new biocatalyst encapsulating [NiFe]-hydrogenases for enhanced hydrogen production

Hydrogenases are microbial metalloenzymes capable of catalyzing the reversible interconversion between molecular hydrogen and protons with high efficiency, and have great potential in the development of new electrocatalysts for renewable fuel production. Here, we engineered the intact proteinaceous shell of the carboxysome, a self-assembling protein organelle for CO₂ fixation in cyanobacteria and proteobacteria, and sequestered heterologously produced [NiFe]-hydrogenases into the carboxysome shell. The protein-based hybrid catalyst produced in E. coli shows substantially improved hydrogen production under both aerobic and anaerobic conditions and enhanced material and functional robustness, compared to unencapsulated [NiFe]-hydrogenases. The catalytically functional nanoreactor as well as the self-assembling and encapsulation strategies provide a framework for engineering new bioinspired electrocatalysts to improve the sustainable production of fuels and chemicals in biotechnological and chemical applications.

Packing-induced selectivity switching in molecular nanoparticle photocatalysts for hydrogen and hydrogen peroxide production

Molecular packing controls optoelectronic properties in organic molecular nanomaterials. Here we report a donor-acceptor organic molecule (2,6-bis(4-cyanophenyl)-4-(9-phenyl-9H-carbazol-3-yl)pyridine-3,5-dicarbonitrile) that exhibits two aggregate states in aqueous dispersions: amorphous nanospheres and ordered nanofibres with π-π molecular stacking. The nanofibres promote sacrificial photocatalytic H₂ production (31.85 mmol g^-1 h^-1) while the nanospheres produce hydrogen peroxide (H₂O₂) (3.20 mmol g^-1 h^-1 in the presence of O₂). This is the first example of an organic photocatalyst that can be directed to produce these two different solar fuels simply by changing the molecular packing. These different packings affect energy band levels, the extent of excited state delocalization, the excited state dynamics, charge transfer to O₂ and the light absorption profile. We use a combination of structural and photophysical measurements to understand how this influences photocatalytic selectivity. This illustrates the potential to achieve multiple photocatalytic functionalities with a single organic molecule by engineering nanomorphology and solid-state packing.

Investigating the factors that influence sacrificial hydrogen evolution activity for three structurally-related molecular photocatalysts: thermodynamic driving force, excited-state dynamics, and surface interaction with cocatalysts

The design of molecular organic photocatalysts for reactions such as water splitting requires consideration of factors that go beyond electronic band gap and thermodynamic driving forces. Here, we carried out a theoretical investigation of three molecular photocatalysts (1-3) that are structurally similar but that show different hydrogen evolution activities (25, 23 & 0 μmol h^-1 for 1-3, respectively). We used density functional theory (DFT) and time-dependent DFT calculations to evaluate the molecules' optoelectronic properties, such as ionization potential, electron affinity, and exciton potentials, as well as the interaction between the molecular photocatalysts and an idealized platinum cocatalyst surface. The 'static' picture thus obtained was augmented by probing the nonadiabatic dynamics of the molecules beyond the Born-Oppenheimer approximation, revealing a different picture of exciton recombination and relaxation for molecule 3. Our results suggest that slow exciton recombination, fast relaxation to the lowest-energy excited state, and a shorter charge transfer distance between the photocatalyst and the metal cocatalyst are important features that contribute to the photocatalytic hydrogen evolution activity of 1 and 2, and may partly rationalize the observed inactivity of 3, in addition to its lower light absorption profile.

Photoresponsive Type III Porous Liquids

Porous materials are the subject of extensive research because of potential applications in areas such as gas adsorption and molecular separations. Until recently, most porous materials were solids, but there is now an emerging class of materials known as porous liquids. The incorporation of intrinsic porosity or cavities in a liquid can result in free-flowing materials that are capable of gas uptakes that are significantly higher than conventional non-porous liquids. A handful of porous liquids have also been investigated for gas separations. Until now, the release of gas from porous liquids has relied on molecular displacement (e.g., by adding small solvent molecules), pressure or temperature swings, or sonication. Here, we explore a new method of gas release which involves photoisomerisable porous liquids comprising a photoresponsive MOF dispersed in an ionic liquid. This results in the selective uptake of CO₂ over CH₄ and allows gas release to be controlled by using UV light.

Geographic style maps for two-dimensional lattices

This paper develops geographic style maps containing two-dimensional lattices in all known periodic crystals parameterized by recent complete invariants. Motivated by rigid crystal structures, lattices are considered up to rigid motion and uniform scaling. The resulting space of two-dimensional lattices is a square with identified edges or a punctured sphere. The new continuous maps show all Bravais classes as low-dimensional subspaces, visualize hundreds of thousands of lattices of real crystal structures from the Cambridge Structural Database, and motivate the development of continuous and invariant-based crystallography.

Why Do Sulfone-Containing Polymer Photocatalysts Work So Well for Sacrificial Hydrogen Evolution from Water?

Many of the highest-performing polymer photocatalysts for sacrificial hydrogen evolution from water have contained dibenzo[b,d]thiophene sulfone units in their polymer backbones. However, the reasons behind the dominance of this building block are not well understood. We study films, dispersions, and solutions of a new set of solution-processable materials, where the sulfone content is systematically controlled, to understand how the sulfone unit affects the three key processes involved in photocatalytic hydrogen generation in this system: light absorption; transfer of the photogenerated hole to the hole scavenger triethylamine (TEA); and transfer of the photogenerated electron to the palladium metal co-catalyst that remains in the polymer from synthesis. Transient absorption spectroscopy and electrochemical measurements, combined with molecular dynamics and density functional theory simulations, show that the sulfone unit has two primary effects. On the picosecond timescale, it dictates the thermodynamics of hole transfer out of the polymer. The sulfone unit attracts water molecules such that the average permittivity experienced by the solvated polymer is increased. We show that TEA oxidation is only thermodynamically favorable above a certain permittivity threshold. On the microsecond timescale, we present experimental evidence that the sulfone unit acts as the electron transfer site out of the polymer, with the kinetics of electron extraction to palladium dictated by the ratio of photogenerated electrons to the number of sulfone units. For the highest-performing, sulfone-rich material, hydrogen evolution seems to be limited by the photogeneration rate of electrons rather than their extraction from the polymer.

Ultrathin Metal-Organic Framework Nanosheets Exhibiting Exceptional Catalytic Activity

Two-dimensional (2D) metal-organic framework nanosheets (MONs) or membranes are classes of periodic, crystalline polymeric materials that may show unprecedented physicochemical properties due to their modular structures, high surface areas, and high aspect ratios. Yet preparing 2D MONs from multiple components and two different types of polymerization reaction remains challenging and less explored. Here, we report the synthesis of MOF films via interfacial polymerization, which involves three active monomers for simultaneous polycondensation and polycoordination taking place in a confined interface. The well-defined lamellar structure of the MOF films allowed feasible and scalable exfoliation to produce free-standing 2D MONs with high aspect ratio up to 2000:1 and ultrathin thickness (∼1.7 nm). The pore structure was revealed by high-resolution TEM images with near-atomic precision. The imide-linkage of MONs provided superior thermal (up to 530 °C) and good chemical stability in the pH range from 3 to 12. More importantly, the MONs exhibited exceptional catalytic activity and superior reusability for the hydroboration reactions of alkynes, in which the turnover frequency (TOF) reached 41734 h^-1, which is 2-4 orders of magnitude greater than that reported for homogeneous and heterogeneous catalysts.

Hydrogen Isotope Separation Using a Metal–Organic Cage Built from Macrocycles

Porous materials that contain ultrafine pore apertures can separate hydrogen isotopes via kinetic quantum sieving (KQS). However, it is challenging to design materials with suitably narrow pores for KQS that also show good adsorption capacities and operate at practical temperatures. Here, we investigate a metal–organic cage (MOC) assembled from organic macrocycles and Zn^II ions that exhibits narrow windows (<3.0 Å). Two polymorphs, referred to as 2α and 2β, were observed. Both polymorphs exhibit D₂/H₂ selectivity in the temperature range 30–100 K. At higher temperature (77 K), the D₂ adsorption capacity of 2β increases to about 2.7 times that of 2α, along with a reasonable D₂/H₂ selectivity. Gas sorption analysis and thermal desorption spectroscopy suggest a gate‐opening effect of the MOCs pore aperture. This promotes KQS at temperatures above liquid nitrogen temperature, indicating that MOCs hold promise for hydrogen isotope separation in real industrial environments.

Photocatalytic Overall Water Splitting Under Visible Light Enabled by a Particulate Conjugated Polymer Loaded with Palladium and Iridium

Polymer photocatalysts have received growing attention in recent years for photocatalytic hydrogen production from water. Most studies report hydrogen production with sacrificial electron donors, which is unsuitable for large‐scale hydrogen energy production. Here we show that the palladium/iridium oxide‐loaded homopolymer of dibenzo[b,d]thiophene sulfone (P10) facilitates overall water splitting to produce stoichiometric amounts of H₂ and O₂ for an extended period (>60 hours) after the system stabilized. These results demonstrate that conjugated polymers can act as single component photocatalytic systems for overall water splitting when loaded with suitable co‐catalysts, albeit currently with low activities. Transient spectroscopy shows that the IrO₂ co‐catalyst plays an important role in the generation of the charge separated state required for water splitting, with evidence for fast hole transfer to the co‐catalyst.

Analogy Powered by Prediction and Structural Invariants: Computationally Led Discovery of a Mesoporous Hydrogen-Bonded Organic Cage Crystal

Mesoporous molecular crystals have potential applications in separation and catalysis, but they are rare and hard to design because many weak interactions compete during crystallization, and most molecules have an energetic preference for close packing. Here, we combine crystal structure prediction (CSP) with structural invariants to continuously qualify the similarity between predicted crystal structures for related molecules. This allows isomorphous substitution strategies, which can be unreliable for molecular crystals, to be augmented by a priori prediction, thus leveraging the power of both approaches. We used this combined approach to discover a rare example of a low-density (0.54 g cm^–3) mesoporous hydrogen-bonded framework (HOF), 3D-CageHOF-1. This structure comprises an organic cage (Cage-3-NH₂) that was predicted to form kinetically trapped, low-density polymorphs via CSP. Pointwise distance distribution structural invariants revealed five predicted forms of Cage-3-NH₂ that are analogous to experimentally realized porous crystals of a chemically different but geometrically similar molecule, T2. More broadly, this approach overcomes the difficulties in comparing predicted molecular crystals with varying lattice parameters, thus allowing for the systematic comparison of energy–structure landscapes for chemically dissimilar molecules.

A Pyrene-4,5,9,10-Tetraone-Based Covalent Organic Framework Delivers High Specific Capacity as a Li-Ion Positive Electrode

Electrochemically active covalent organic frameworks (COFs) are promising electrode materials for Li-ion batteries. However, improving the specific capacities of COF-based electrodes requires materials with increased conductivity and a higher concentration of redox-active groups. Here, we designed a series of pyrene-4,5,9,10-tetraone COF (PT-COF) and carbon nanotube (CNT) composites (denoted as PT-COFX, where X = 10, 30, and 50 wt % of CNT) to address these challenges. Among the composites, PT-COF50 achieved a capacity of up to 280 mAh g^-1 as normalized to the active COF material at a current density of 200 mA g^-1, which is the highest capacity reported for a COF-based composite cathode electrode to date. Furthermore, PT-COF50 exhibited excellent rate performance, delivering a capacity of 229 mAh g^-1 at 5000 mA g^-1 (18.5C). Using operando Raman microscopy the reversible transformation of the redox-active carbonyl groups of PT-COF was determined, which rationalizes an overall 4 e^-/4 Li⁺ redox process per pyrene-4,5,9,10-tetraone unit, accounting for its superior performance as a Li-ion battery electrode.

A smart and responsive crystalline porous organic cage membrane with switchable pore apertures for graded molecular sieving

Membranes with high selectivity offer an attractive route to molecular separations, where technologies such as distillation and chromatography are energy intensive. However, it remains challenging to fine tune the structure and porosity in membranes, particularly to separate molecules of similar size. Here, we report a process for producing composite membranes that comprise crystalline porous organic cage films fabricated by interfacial synthesis on a polyacrylonitrile support. These membranes exhibit ultrafast solvent permeance and high rejection of organic dyes with molecular weights over 600 g mol^-1. The crystalline cage film is dynamic, and its pore aperture can be switched in methanol to generate larger pores that provide increased methanol permeance and higher molecular weight cut-offs (1,400 g mol^-1). By varying the water/methanol ratio, the film can be switched between two phases that have different selectivities, such that a single, 'smart' crystalline membrane can perform graded molecular sieving. We exemplify this by separating three organic dyes in a single-stage, single-membrane process.

Linear Conjugated Polymers for Solar-Driven Hydrogen Peroxide Production: The Importance of Catalyst Stability

Hydrogen peroxide (H2O2) is one of the most important industrial oxidants. In principle, photocatalytic H2O2 synthesis from oxygen and H2O using sunlight could provide a cleaner alternative route to the current anthraquinone process. Recently, conjugated organic materials have been studied as photocatalysts for solar fuels synthesis because they offer synthetic tunability over a large chemical space. Here, we used high-throughput experiments to discover a linear conjugated polymer, poly(3-4-ethynylphenyl)ethynyl)pyridine (DE7), which exhibits efficient photocatalytic H2O2 production from H2O and O2 under visible light illumination for periods of up to 10 h or so. The apparent quantum yield was 8.7% at 420 nm. Mechanistic investigations showed that the H2O2 was produced via the photoinduced stepwise reduction of O2. At longer photolysis times, however, this catalyst decomposed, suggesting a need to focus the photostability of organic photocatalysts, as well as the initial catalytic production rates.

Scalable Synthesis of Ultrathin Polyimide Covalent Organic Framework Nanosheets for High-Performance Lithium-Sulfur Batteries

Development of new porous materials as hosts to suppress the dissolution and shuttle of lithium polysulfides is beneficial for constructing highly efficient lithium-sulfur batteries (LSBs). Although 2D covalent organic frameworks (COFs) as host materials exhibit promising potential for LSBs, their performance is still not satisfactory. Herein, we develop polyimide COFs (PI-COF) with a well-defined lamellar structure, which can be exfoliated into ultrathin (∼1.2 nm) 2D polyimide nanosheets (PI-CONs) with a large size (∼6 μm) and large quantity (40 mg/batch). Explored as new sulfur host materials for LSBs, PI-COF and PI-CONs deliver high capacities (1330 and 1205 mA h g^-1 at 0.1 C, respectively), excellent rate capabilities (620 and 503 mA h g^-1 at 4 C, respectively), and superior cycling stability (96% capacity retention at 0.2 C for PI-CONs) by virtue of the synergy of robust conjugated porous frameworks and strong oxygen-lithium interactions, surpassing the vast majority of organic/polymeric lithium-sulfur battery cathodes ever reported. Our finding demonstrates that ultrathin 2D COF nanosheets with carbonyl groups could be promising host materials for LSBs with excellent electrochemical performance.

Time-Resolved Raman Spectroscopy of Polaron Formation in a Polymer Photocatalyst

Polymer photocatalysts are a synthetically diverse class of materials that can be used for the production of solar fuels such as H₂, but the underlying mechanisms by which they operate are poorly understood. Time-resolved vibrational spectroscopy provides a powerful structure-specific probe of photogenerated species. Here we report the use of time-resolved resonance Raman (TR³) spectroscopy to study the formation of polaron pairs and electron polarons in one of the most active linear polymer photocatalysts for H₂ production, poly(dibenzo[b,d]thiophene sulfone), P10. We identify that polaron-pair formation prior to thermalization of the initially generated excited states is an important pathway for the generation of long-lived photoelectrons.

Polymeric Fiber Sorbents Embedded with Porous Organic Cages

The synthesis and functionalization of porous organic cages (POCs) for separation have attracted growing interest over the past decade. However, the potential of solid-phase POCs for practical, large-scale separations will require incorporation into appropriate gas-solid or liquid-solid contactors. Contactors with more effective mass transfer properties and lower pressure drops than pelletized systems are preferred. Here, we prepared and characterized fiber sorbents with POCs throughout a cellulose acetate (CA) polymer matrix, which were then deployed in model separations. The POC CC3 was shown to be stable after exposure to spinning solvents, as confirmed by NMR, powder X-ray diffraction, and gas sorption experiments. CC3-CA fibers were spun using the dry-jet wet-quench spinning method. Spun fibers retained the adsorptive properties of CC3 powders, as confirmed by CO₂ and N₂ physisorption and TGA, reaching upward of 60 wt % adsorbent loading, whereas the pelletized CC3 counterparts suffered significant losses in textural properties. The separation capabilities of the CC3-CA fibers are tested with both simulated postcombustion flue gas and with Xe/Kr mixtures. Fixed bed breakthrough experiments performed on fibers samples show that CC3 embedded in polymeric fibers can effectively perform these proof-of-concept gas separations. The development of fiber sorbents embedded with POCs provides an alternative to traditional pelletization for the incorporation of these materials into adsorptive separation systems.

A Cubic 3D Covalent Organic Framework with nbo Topology

The synthesis of three-dimensional (3D) covalent organic frameworks (COFs) requires high-connectivity polyhedral building blocks or the controlled alignment of building blocks. Here, we use the latter strategy to assemble square-planar cobalt(II) phthalocyanine (PcCo) units into the nbo topology by using tetrahedral spiroborate (SPB) linkages that were chosen to provide the necessary 90° dihedral angles between neighboring PcCo units. This yields a porous 3D COF, SPB-COF-DBA, with a noninterpenetrated nbo topology. SPB-COF-DBA shows high crystallinity and long-range order, with 11 resolved diffraction peaks in the experimental powder X-ray diffraction (PXRD) pattern. This well-ordered crystal lattice can also be imaged by using high-resolution transmission electron microscopy (HR-TEM). SPB-COF-DBA has cubic pores and exhibits permanent porosity with a Brunauer-Emmett-Teller (BET) surface area of 1726 m² g^-1.

The changing state of porous materials

Porous materials contain regions of empty space into which guest molecules can be selectively adsorbed and sometimes chemically transformed. This has made them useful in both industrial and domestic applications, ranging from gas separation, energy storage and ion exchange to heterogeneous catalysis and green chemistry. Porous materials are often ordered (crystalline) solids. Order-or uniformity-is frequently held to be advantageous, or even pivotal, to our ability to engineer useful properties in a rational way. Here we highlight the growing evidence that topological disorder can be useful in creating alternative properties in porous materials. In particular, we highlight here several concepts for the creation of novel porous liquids, rationalize routes to porous glasses and provide perspectives on applications for porous liquids and glasses.

Combining machine learning and high-throughput experimentation to discover photocatalytically active organic molecules

Light-absorbing organic molecules are useful components in photocatalysts, but it is difficult to formulate reliable structure–property design rules. More than 100 million unique chemical compounds are documented in the PubChem database, and a significant sub-set of these are π-conjugated, light-absorbing molecules that might in principle act as photocatalysts. Nature has used natural selection to evolve photosynthetic assemblies; by contrast, our ability to navigate the enormous potential search space of organic photocatalysts in the laboratory is limited. Here, we integrate experiment, computation, and machine learning to address this challenge. A library of 572 aromatic organic molecules was assembled with diverse compositions and structures, selected on the basis of availability in our laboratory, rather than more sophisticated criteria. This training library was then assessed experimentally for sacrificial photocatalytic hydrogen evolution using a high-throughput, automated method. Quantum chemical calculations and machine learning were used to visualise, interpret, and ultimately to predict the photocatalytic activities of these molecules, covering a much broader chemical space than for previous polymer photocatalyst libraries. By applying unsupervised learning to the molecular structures, we identified structural features that were common in molecules with high catalytic activity. Further analysis using calculated molecular descriptors within a suite of supervised classification algorithms revealed that light absorption, exciton electron affinity, electron affinity, exciton binding energy, and singlet–triplet energy gap had correlations with the photocatalytic performance. These trained predictive models can be used in future studies as filters to deprioritise or discard would-be low-activity candidate molecules from experiments, and to prioritize more favourable candidates. As a demonstration, we used virtual in silico experiments to show that it was possible to halve the experimental cost of finding 50% of the most active photocatalysts by using the machine learning model as an experimental advisor. We further showed that the ML advisor trained on the 572-molecule library could be used to make predictions for an unseen set of 96 molecules, achieving equivalent predictive accuracies to those in the initial training set. This marks a step toward the machine-learning assisted discovery of molecular organic photocatalysts and the approach might also be applied to problems beyond photocatalytic hydrogen evolution, such as CO₂ reduction and photoredox chemistry.

We developed models to predict the photoactivity of organic molecules for photocatalytic hydrogen evolution by integrating experiment, computation, and machine learning. This marks a step toward the data-driven discovery of molecular photocatalysts.

SO2 Capture Using Porous Organic Cages

We report the first experimental investigation of porous organic cages (POCs) for the demanding challenge of SO2 capture. Three structurally related N-containing cage molecular materials were studied. An imine-functionalized POC (CC3) showed modest and reversible SO2 capture, while a secondary-amine POC (RCC3) exhibited high but irreversible SO2 capture. A tertiary amine POC (6FT-RCC3) demonstrated very high SO2 capture (13.78 mmol g-1 ; 16.4 SO2 molecules per cage) combined with excellent reversibility for at least 50 adsorption-desorption cycles. The adsorption behavior was investigated by FTIR spectroscopy, 13 C CP-MAS NMR experiments, and computational calculations.

Accelerating computational discovery of porous solids through improved navigation of energy-structure-function maps

While energy-structure-function (ESF) maps are a powerful new tool for in silico materials design, the cost of acquiring an ESF map for many properties is too high for routine integration into high-throughput virtual screening workflows. Here, we propose the next evolution of the ESF map. This uses parallel Bayesian optimization to selectively acquire energy and property data, generating the same levels of insight at a fraction of the computational cost. We use this approach to obtain a two orders of magnitude speedup on an ESF study that focused on the discovery of molecular crystals for methane capture, saving more than 500,000 central processing unit hours from the original protocol. By accelerating the acquisition of insight from ESF maps, we pave the way for the use of these maps in automated ultrahigh-throughput screening pipelines by greatly reducing the opportunity risk associated with the choice of system to calculate.

Dynamics in Flexible Pillar[n]arenes Probed by Solid-State NMR

Pillar[n]arenes are supramolecular assemblies that can perform a range of technologically important molecular separations which are enabled by their molecular flexibility. Here, we probe dynamical behavior by performing a range of variable-temperature solid-state NMR experiments on microcrystalline perethylated pillar[n]arene (n = 5, 6) and the corresponding three pillar[6]arene xylene adducts in the 100-350 K range. This was achieved either by measuring site-selective motional averaged 13C 1H heteronuclear dipolar couplings and subsequently accessing order parameters or by determining 1H and 13C spin-lattice relaxation times and extracting correlation times based on dipolar and/or chemical shift anisotropy relaxation mechanisms. We demonstrate fast motional regimes at room temperature and highlight a significant difference in dynamics between the core of the pillar[n]arenes, the protruding flexible ethoxy groups, and the adsorbed xylene guest. Additionally, unexpected and sizable 13C 1H heteronuclear dipolar couplings for a quaternary carbon were observed for p-xylene adsorbed in pillar[6]arene only, indicating a strong host-guest interaction and establishing the p-xylene location inside the host, confirming structural refinements.

Creating porosity in a trianglimine macrocycle by heterochiral pairing

Macrocycles are usually non-porous or barely porous in the solid-state because of their small intrinsic cavity sizes and tendency to close-pack. Here, we use a heterochiral pairing strategy to introduce porosity in a trianglimine macrocycle, by co-crystallising two macrocycles with opposing chiralities. The stable racemic trianglimine crystal contains an interconnected pore network that has a Brunauer-Emmett-Teller (BET) surface area of 355 m2 g-1.

Inherent Ethyl Acetate Selectivity in a Trianglimine Molecular Solid

Ethyl acetate is an important chemical raw material and solvent. It is also a key volatile organic compound in the brewing industry and a marker for lung cancer. Materials that are highly selective toward ethyl acetate are needed for its separation and detection. Here, we report a trianglimine macrocycle (TAMC) that selectively adsorbs ethyl acetate by forming a solvate. Crystal structure prediction showed this to be the lowest energy solvate structure available. This solvate leaves a metastable, “templated” cavity after solvent removal. Adsorption and breakthrough experiments confirmed that TAMC has adequate adsorption kinetics to separate ethyl acetate from azeotropic mixtures with ethanol, which is a challenging and energy‐intensive industrial separation.

Crystallography companion agent for high-throughput materials discovery

The discovery of new structural and functional materials is driven by phase identification, often using X-ray diffraction (XRD). Automation has accelerated the rate of XRD measurements, greatly outpacing XRD analysis techniques that remain manual, time-consuming, error-prone and impossible to scale. With the advent of autonomous robotic scientists or self-driving laboratories, contemporary techniques prohibit the integration of XRD. Here, we describe a computer program for the autonomous characterization of XRD data, driven by artificial intelligence (AI), for the discovery of new materials. Starting from structural databases, we train an ensemble model using a physically accurate synthetic dataset, which outputs probabilistic classifications-rather than absolutes-to overcome the overconfidence in traditional neural networks. This AI agent behaves as a companion to the researcher, improving accuracy and offering substantial time savings. It is demonstrated on a diverse set of organic and inorganic materials characterization challenges. This method is directly applicable to inverse design approaches and robotic discovery systems, and can be immediately considered for other forms of characterization such as spectroscopy and the pair distribution function.

Probing Dynamics of Water Mass Transfer in Organic Porous Photocatalyst Water-Splitting Materials by Neutron Spectroscopy

The quest for efficient and economically accessible cleaner methods to develop sustainable carbon-free energy sources induced a keen interest in the production of hydrogen fuel. This can be achieved via the water-splitting process and by exploiting solar energy. However, the use of adequate photocatalysts is required to reach this goal. Covalent triazine-based frameworks (CTFs) are potential target photocatalysts for water splitting. Both electronic and structural characteristics of CTFs, particularly energy levels, optical band gaps, and porosities are directly relevant to water splitting and can be engineered through chemical design. Porosity can, in principle, be beneficial to water splitting by providing a larger surface area for the catalytic reactions to take place. However, porosity can also affect both charge transport within the photocatalyst and mass transfer of both reactants and products, thus impacting the overall kinetics of the reaction. Here, we focus on the link between chemical design and water (reactant) mass transfer, which plays a key role in the water uptake process and the subsequent hydrogen generation in practice. We use neutron spectroscopy to study the mass transfer of water in two porous CTFs, CTF-CN and CTF-2, that differ in the polarity of their struts. Quasi-elastic neutron scattering is used to quantify the amount of bound water and the translational diffusion of water. Inelastic neutron scattering measurements complement the quasi-elastic neutron scattering study and provide insights into the softness of the CTF structures and the changes in librational degrees of freedom of water in the porous CTFs. We show that two different types of interaction between water and CTFs take place in CTF-CN and CTF-2. CTF-CN exhibits a smaller surface area and lower water uptake due to its softer structure than CTF-2. However, the polar cyano group interacts locally with water leading to a large amount of bound water and a strong rearrangement of the water hydration monolayer, while water diffusion in CTF-2 is principally impacted by microporosity. The current study leads to new insights into the structure-dynamics-property relationship of CTF photocatalysts that pave the road for a better understanding of the guest-host interaction on the basis of water-splitting applications.

Digital navigation of energy-structure-function maps for hydrogen-bonded porous molecular crystals

Energy-structure-function (ESF) maps can aid the targeted discovery of porous molecular crystals by predicting the stable crystalline arrangements along with their functions of interest. Here, we compute ESF maps for a series of rigid molecules that comprise either a triptycene or a spiro-biphenyl core, functionalized with six different hydrogen-bonding moieties. We show that the positioning of the hydrogen-bonding sites, as well as their number, has a profound influence on the shape of the resulting ESF maps, revealing promising structure-function spaces for future experiments. We also demonstrate a simple and general approach to representing and inspecting the high-dimensional data of an ESF map, enabling an efficient navigation of the ESF data to identify 'landmark' structures that are energetically favourable or functionally interesting. This is a step toward the automated analysis of ESF maps, an important goal for closed-loop, autonomous searches for molecular crystals with useful functions.

Exploring cooperative porosity in organic cage crystals using in situ diffraction and molecular simulations

A porous organic cage crystal, α-CC2, shows unexpected adsorption of sulphur hexafluoride (SF₆) in its cage cavities: analysis of the static crystal structure indicates that SF₆ is occluded, as even the smallest diatomic gas, H₂, is larger than the window of the cage pore. Herein, we use in situ powder X-ray diffraction (PXRD) experiments to provide unequivocal evidence for the presence of SF₆ inside the 'occluded' cage voids, pointing to a mechanism of dynamic flexibility of the system. By combining PXRD results with molecular dynamics simulations, we build a molecular level picture of the cooperative porosity in α-CC2 that facilitates the passage of SF₆ into the cage voids.