Nanoscale covalent organic frameworks for enhanced photocatalytic hydrogen production.

Nanosizing confers unique functions in materials such as graphene and quantum dots. Here, we present two nanoscale-covalent organic frameworks (nano-COFs) that exhibit exceptionally high activity for photocatalytic hydrogen production that results from their size and morphology. Compared to bulk analogues, the downsizing of COFs crystals using surfactants provides greatly improved water dispersibility and light-harvesting properties. One of these nano-COFs shows a hydrogen evolution rate of 392.0 mmol g-1 h-1 (33.3 µmol h-1), which is one of the highest mass-normalized rates reported for a COF or any other organic photocatalysts. A reverse concentration-dependent photocatalytic phenomenon is observed, whereby a higher photocatalytic activity is found at a lower catalyst concentration. These materials also show a molecule-like excitonic nature, as studied by photoluminescence and transient absorption spectroscopy, which is again a function of their nanoscale dimensions. This charts a new path to highly efficient organic photocatalysts for solar fuel production.

High-speed 4-dimensional scanning transmission electron microscopy using compressive sensing techniques.

Here we show that compressive sensing allows 4-dimensional (4-D) STEM data to be obtained and accurately reconstructed with both high-speed and reduced electron fluence. The methodology needed to achieve these results compared to conventional 4-D approaches requires only that a random subset of probe locations is acquired from the typical regular scanning grid, which immediately generates both higher speed and the lower fluence experimentally. We also consider downsampling of the detector, showing that oversampling is inherent within convergent beam electron diffraction (CBED) patterns and that detector downsampling does not reduce precision but allows faster experimental data acquisition. Analysis of an experimental atomic resolution yttrium silicide dataset shows that it is possible to recover over 25 dB peak signal-to-noise ratio in the recovered phase using 0.3% of the total data. Lay abstract: Four-dimensional scanning transmission electron microscopy (4-D STEM) is a powerful technique for characterizing complex nanoscale structures. In this method, a convergent beam electron diffraction pattern (CBED) is acquired at each probe location during the scan of the sample. This means that a 2-dimensional signal is acquired at each 2-D probe location, equating to a 4-D dataset. Despite the recent development of fast direct electron detectors, some capable of 100kHz frame rates, the limiting factor for 4-D STEM is acquisition times in the majority of cases, where cameras will typically operate on the order of 2kHz. This means that a raster scan containing 256^2 probe locations can take on the order of 30s, approximately 100-1000 times longer than a conventional STEM imaging technique using monolithic radial detectors. As a result, 4-D STEM acquisitions can be subject to adverse effects such as drift, beam damage, and sample contamination. Recent advances in computational imaging techniques for STEM have allowed for faster acquisition speeds by way of acquiring only a random subset of probe locations from the field of view. By doing this, the acquisition time is significantly reduced, in some cases by a factor of 10-100 times. The acquired data is then processed to fill-in or inpaint the missing data, taking advantage of the inherently low-complex signals which can be linearly combined to recover the information. In this work, similar methods are demonstrated for the acquisition of 4-D STEM data, where only a random subset of CBED patterns are acquired over the raster scan. We simulate the compressive sensing acquisition method for 4-D STEM and present our findings for a variety of analysis techniques such as ptychography and differential phase contrast. Our results show that acquisition times can be significantly reduced on the order of 100-300 times, therefore improving existing frame rates, as well as further reducing the electron fluence beyond just using a faster camera.

2D to 3D Reconstruction of Boron-Linked Covalent-Organic Frameworks.

The transformation of two-dimensional (2D) covalent-organic frameworks (COFs) into three-dimensions (3D) is synthetically challenging, and it is typically addressed through interlayer cross-linking of alkene or alkyne bonds. Here, we report the first example of the chemical reconstruction of a 2D COF to a 3D COF with a complete lattice rearrangement facilitated by base-triggered boron hybridization. This chemical reconstruction involves the conversion of trigonal boronate ester linkages to tetrahedral anionic spiroborate linkages. This transformation reticulates the coplanar, closely stacked square cobalt(II) phthalocyanine (PcCo) units into a 3D perpendicular arrangement. As a result, the pore size of COFs expands from 2.45 nm for the initial 2D square lattice (sql) to 3.02 nm in the 3D noninterpenetrated network (nbo). Mechanistic studies reveal a base-catalyzed boronate ester protodeboronation pathway for the formation of the spiroborate structure.

Accessing Mg-Ion Storage in V2PS10 via Combined Cationic-Anionic Redox with Selective Bond Cleavage.

Magnesium batteries attract interest as alternative energy-storage devices because of elemental abundance and potential for high energy density. Development is limited by the absence of suitable cathodes, associated with poor diffusion kinetics resulting from strong interactions between Mg2+ and the host structure. V2PS10 is reported as a positive electrode material for rechargeable magnesium batteries. Cyclable capacity of 100 mAh g-1 is achieved with fast Mg2+ diffusion of 7.2 × ${\times }$ 10-11-4 × ${\times }$ 10-14 cm2 s-1. The fast insertion mechanism results from combined cationic redox on the V site and anionic redox on the (S2)2- site; enabled by reversible cleavage of S-S bonds, identified by X-ray photoelectron and X-ray absorption spectroscopy. Detailed structural characterisation with maximum entropy method analysis, supported by density functional theory and projected density of states analysis, reveals that the sulphur species involved in anion redox are not connected to the transition metal centres, spatially separating the two redox processes. This facilitates fast and reversible Mg insertion in which the nature of the redox process depends on the cation insertion site, creating a synergy between the occupancy of specific Mg sites and the location of the electrons transferred.

The Potential of Subsampling and Inpainting for Fast Low-Dose Cryo FIB-SEM Imaging.

Traditional image acquisition for cryo focused ion-beam scanning electron microscopy (FIB-SEM) tomography often sees thousands of images being captured over a period of many hours, with immense data sets being produced. When imaging beam sensitive materials, these images are often compromised by additional constraints related to beam damage and the devitrification of the material during imaging, which renders data acquisition both costly and unreliable. Subsampling and inpainting are proposed as solutions for both of these aspects, allowing fast and low-dose imaging to take place in the Focused ion-beam scanning electron microscopy FIB-SEM without an appreciable loss in image quality. In this work, experimental data are presented which validate subsampling and inpainting as a useful tool for convenient and reliable data acquisition in a FIB-SEM, with new methods of handling three-dimensional data being employed in the context of dictionary learning and inpainting algorithms using a newly developed microscope control software and data recovery algorithm.

Superionic lithium transport via multiple coordination environments defined by two-anion packing.

Fast cation transport in solids underpins energy storage. Materials design has focused on structures that can define transport pathways with minimal cation coordination change, restricting attention to a small part of chemical space. Motivated by the greater structural diversity of binary intermetallics than that of the metallic elements, we used two anions to build a pathway for three-dimensional superionic lithium ion conductivity that exploits multiple cation coordination environments. Li7Si2S7I is a pure lithium ion conductor created by an ordering of sulphide and iodide that combines elements of hexagonal and cubic close-packing analogously to the structure of NiZr. The resulting diverse network of lithium positions with distinct geometries and anion coordination chemistries affords low barriers to transport, opening a large structural space for high cation conductivity.

Towards real-time STEM simulations through targeted subsampling strategies.

Scanning transmission electron microscopy images can be complex to interpret on the atomic scale as the contrast is sensitive to multiple factors such as sample thickness, composition, defects and aberrations. Simulations are commonly used to validate or interpret real experimental images, but they come at a cost of either long computation times or specialist hardware such as graphics processing units. Recent works in compressive sensing for experimental STEM images have shown that it is possible to significantly reduce the amount of acquired signal and still recover the full image without significant loss of image quality, and therefore it is proposed here that similar methods can be applied to STEM simulations. In this paper, we demonstrate a method that can significantly increase the efficiency of STEM simulations through a targeted sampling strategy, along with a new approach to independently subsample each frozen phonon layer. We show the effectiveness of this method by simulating a SrTiO3 grain boundary and monolayer 2H-MoS2 containing a sulphur vacancy using the abTEM software. We also show how this method is not limited to only traditional multislice methods, but also increases the speed of the PRISM simulation method. Furthermore, we discuss the possibility for STEM simulations to seed the acquisition of real data, to potentially lead the way to self-driving (correcting) STEM.

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.

Selective bacterial separation of critical metals: towards a sustainable method for recycling lithium ion batteries.

The large scale recycling of lithium ion batteries (LIBs) is essential to satisfy global demands for the raw materials required to implement this technology as part of a clean energy strategy. However, despite what is rapidly becoming a critical need, an efficient and sustainable recycling process for LIBs has yet to be developed. Biological reactions occur with great selectivity under mild conditions, offering new avenues for the implementation of more environmentally sustainable processes. Here, we demonstrate a sequential process employing two bacterial species to recover Mn, Co and Ni, from vehicular LIBs through the biosynthesis of metallic nanoparticles, whilst Li remains within the leachate. Moreover the feasibility of Mn recovery from polymetallic solutions was demonstrated at semi-pilot scale in a 30 L bioreactor. Additionally, to provide insight into the biological process occurring, we investigated selectivity between Co and Ni using proteomics to identify the biological response and confirm the potential of a bio-based method to separate these two essential metals. Our approach determines the principles and first steps of a practical bio-separation and recovery system, underlining the relevance of harnessing biological specificity for recycling and up-cycling critical materials.

SIM-STEM Lab: Incorporating Compressed Sensing Theory for Fast STEM Simulation.

Recently it has been shown that precise dose control and an increase in the overall acquisition speed of atomic resolution scanning transmission electron microscope (STEM) images can be achieved by acquiring only a small fraction of the pixels in the image experimentally and then reconstructing the full image using an inpainting algorithm. In this paper, we apply the same inpainting approach (a form of compressed sensing) to simulated, sub-sampled atomic resolution STEM images. We find that it is possible to significantly sub-sample the area that is simulated, the number of g-vectors contributing the image, and the number of frozen phonon configurations contributing to the final image while still producing an acceptable fit to a fully sampled simulation. Here we discuss the parameters that we use and how the resulting simulations can be quantifiably compared to the full simulations. As with any Compressed Sensing methodology, care must be taken to ensure that isolated events are not excluded from the process, but the observed increase in simulation speed provides significant opportunities for real time simulations, image classification and analytics to be performed as a supplement to experiments on a microscope to be developed in the future.

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.

Accelerated Synthesis and Discovery of Covalent Organic Framework Photocatalysts for Hydrogen Peroxide Production.

A high-throughput sonochemical synthesis and testing strategy was developed to discover covalent organic frameworks (COFs) for photocatalysis. In total, 76 conjugated polymers were synthesized, including 60 crystalline COFs of which 18 were previously unreported. These COFs were then screened for photocatalytic hydrogen peroxide (H2O2) production using water and oxygen. One of these COFs, sonoCOF-F2, was found to be an excellent photocatalyst for photocatalytic H2O2 production even in the absence of sacrificial donors. However, after long-term photocatalytic tests (96 h), the imine sonoCOF-F2 transformed into an amide-linked COF with reduced crystallinity and loss of electronic conjugation, decreasing the photocatalytic activity. When benzyl alcohol was introduced to form a two-phase catalytic system, the photostability of sonoCOF-F2 was greatly enhanced, leading to stable H2O2 production for at least 1 week.

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.

Sub-Sampled Imaging for STEM: Maximising Image Speed, Resolution and Precision Through Reconstruction Parameter Refinement.

Sub-sampling during image acquisition in scanning transmission electron microscopy (STEM) has been shown to provide a means to increase the overall speed of acquisition while at the same time providing an efficient means to control the dose, dose rate and dose overlap delivered to the sample. In this paper, we discuss specifically the parameters used to reconstruct sub-sampled images and highlight their effect on inpainting using the beta-process factor analysis (BPFA) methodology. The selection of the main control parameters can have a significant effect on the resolution, precision and sensitivity of the final inpainted images, and here we demonstrate a method by which these parameters can be optimised for any image in STEM. As part of this work, we also provide a link to open source code and a tutorial on its use, whereby these parameters can be tested for any datasets. When coupled with the hardware necessary to rapidly sub-sample images in STEM, this approach can have significant implications for imaging beam sensitive materials and dynamic processes.

High temporal-resolution scanning transmission electron microscopy using sparse-serpentine scan pathways.

Scanning transmission electron microscopy (STEM) provides structural analysis with sub-angstrom resolution. But the pixel-by-pixel scanning process is a limiting factor in acquiring high-speed data. Different strategies have been implemented to increase scanning speeds while at the same time minimizing beam damage via optimizing the scanning strategy. Here, we achieve the highest possible scanning speed by eliminating the image acquisition dead time induced by the beam flyback time combined with reducing the amount of scanning pixels via sparse imaging. A calibration procedure was developed to compensate for the hysteresis of the magnetic scan coils. A combination of sparse and serpentine scanning routines was tested for a crystalline thin film, gold nanoparticles, and in an in-situ liquid phase STEM experiment. Frame rates of 92, 23 and 5.8 s-1 were achieved for images of a width of 128, 256, and 512 pixels, respectively. The methods described here can be applied to single-particle tracking and analysis of radiation sensitive materials.