Ultralow Catalytic Loading for Optimised Electrocatalytic Performance of AuPt Nanoparticles to Produce Hydrogen and Ammonia.

The hydrogen evolution and nitrite reduction reactions are key to producing green hydrogen and ammonia. Antenna-reactor nanoparticles hold promise to improve the performances of these transformations under visible-light excitation, by combining plasmonic and catalytic materials. However, current materials involve compromising either on the catalytic activity or the plasmonic enhancement and also lack control of reaction selectivity. Here, we demonstrate that ultralow loadings and non-uniform surface segregation of the catalytic component optimize catalytic activity and selectivity under visible-light irradiation. Taking Pt-Au as an example we find that fine-tuning the Pt content produces a 6-fold increase in the hydrogen evolution compared to commercial Pt/C as well as a 6.5-fold increase in the nitrite reduction and a 2.5-fold increase in the selectivity for producing ammonia under visible light excitation relative to dark conditions. Density functional theory suggests that the catalytic reactions are accelerated by the intimate contact between nanoscale Pt-rich and Au-rich regions at the surface, which facilitates the formation of electron-rich hot-carrier puddles associated with the Pt-based active sites. The results provide exciting opportunities to design new materials with improved photocatalytic performance for demanding sustainable energy applications.

Characterisation of the morphology of surface-assembled Au nanoclusters on amorphous carbon.

In this study, aberration-corrected scanning transmission electron microscopy is employed to investigate the morphology of Au clusters formed from the aggregation of single atoms sputtered onto an amorphous carbon surface. The morphologies of surface-assembled clusters of N > 100 atoms are referenced against the morphologies of size-selected clusters determined from previously published results. We observe that surface-assembled clusters (at the conditions employed here) are approximately spherical in shape. The structural isomers of the imaged clusters have also been identified, and the distribution of structural types is broadly in agreement with those from size-selected cluster deposition sources. For clusters of approximately 147 atoms, we find a preference for icosahedra over decahedra and truncated octahedra, but at this size there is a high proportion of unidentified/amorphous structures. At around 309 atoms, we find a preference for decahedra over icosahedra and truncated octahedra, but over half the structures remain unidentifiable/amorphous. For sizes above approximately 561 atoms we are able to identify most of the structures, and find decahedra are still the most favoured, although in competition with single-crystal fcc morphologies. The similarity in structure between surface-assembled and size-selected clusters from a cluster source provides evidence of the relevance of size-selected cluster studies to clusters synthesised by other, industrially relevant, methodologies.

In Situ Single Particle Reconstruction Reveals 3D Evolution of PtNi Nanocatalysts During Heating.

Tailoring nanoparticles' composition and morphology is of particular interest for improving their performance for catalysis. A challenge of this approach is that the nanoparticles' optimized initial structure often changes during use. Visualizing the three dimensional (3D) structural transformation in situ is therefore critical, but often prohibitively difficult experimentally. Although electron tomography provides opportunities for 3D imaging, restrictions in the tilt range of in situ holders together with electron dose considerations limit the possibilities for in situ electron tomography studies. Here, an in situ 3D imaging methodology is presented using single particle reconstruction (SPR) that allows 3D reconstruction of nanoparticles with controlled electron dose and without tilting the microscope stage. This in situ SPR methodology is employed to investigate the restructuring and elemental redistribution within a population of PtNi nanoparticles at elevated temperatures. The atomic structure of PtNi is further examined and a heat-induced transition is found from a disordered to an ordered phase. Changes in structure and elemental distribution are linked to a loss of catalytic activity in the oxygen reduction reaction. The in situ SPR methodology employed here can be extended to a wide range of in situ studies employing not only heating, but gaseous, aqueous, or electrochemical environments to reveal in-operando nanoparticle evolution in 3D.

Frame-by-frame observations of structure fluctuations in single mass-selected Au clusters using aberration-corrected electron microscopy.

The multi-dimensional potential energy surface (PES) of a nanoparticle, such as a bare cluster of metal atoms, controls both the structure and dynamic behaviour of the particle. These properties are the subject of numerous theoretical simulations. However, quantitative experimental measurements of critical PES parameters are needed to regulate the models employed in the theoretical work. Experimental measurements of parameters are currently few in number, while model parameters taken from bulk systems may not be suitable for nanosystems. Here we describe a new measurement methodology, in which the isomer structures of a single deposited nanocluster are obtained frame-by-frame in an aberration-corrected scanning transmission electron microscope (ac-STEM) in high angle annular dark field (HAADF) mode. Several gold clusters containing 309 ± 15 atoms were analysed individually after deposition from a mass-selected cluster source onto an amorphous carbon film. The main isomers identified are icosahedral (Ih), decahedral (Dh) and face-centred-cubic (fcc) (the bulk structure), alongside many amorphous (glassy) structures. The results, which are broadly consistent with static ac-STEM measurements of an ensemble of such clusters, open the way to dynamic measurements of many different nanoparticles of diverse sizes, shapes and compositions.

Bridging imaging users to imaging analysis - A community survey.

The 'Bridging Imaging Users to Imaging Analysis' survey was conducted in 2022 by the Center for Open Bioimage Analysis (COBA), BioImaging North America (BINA) and the Royal Microscopical Society Data Analysis in Imaging Section (RMS DAIM) to understand the needs of the imaging community. Through multichoice and open-ended questions, the survey inquired about demographics, image analysis experiences, future needs and suggestions on the role of tool developers and users. Participants of the survey were from diverse roles and domains of the life and physical sciences. To our knowledge, this is the first attempt to survey cross-community to bridge knowledge gaps between physical and life sciences imaging. Survey results indicate that respondents' overarching needs are documentation, detailed tutorials on the usage of image analysis tools, user-friendly intuitive software, and better solutions for segmentation, ideally in a format tailored to their specific use cases. The tool creators suggested the users familiarise themselves with the fundamentals of image analysis, provide constant feedback and report the issues faced during image analysis while the users would like more documentation and an emphasis on tool friendliness. Regardless of the computational experience, there is a strong preference for 'written tutorials' to acquire knowledge on image analysis. We also observed that the interest in having 'office hours' to get an expert opinion on their image analysis methods has increased over the years. The results also showed less-than-expected usage of online discussion forums in the imaging community for solving image analysis problems. Surprisingly, we also observed a decreased interest among the survey respondents in deep/machine learning despite the increasing adoption of artificial intelligence in biology. In addition, the community suggests the need for a common repository for the available image analysis tools and their applications. The opinions and suggestions of the community, released here in full, will help the image analysis tool creation and education communities to design and deliver the resources accordingly.

Chemical Kinetics of Metal Single Atom and Nanocluster Formation on Surfaces: An Example of Pt on Hexagonal Boron Nitride.

The production of atomically dispersed metal catalysts remains a significant challenge in the field of heterogeneous catalysis due to coexistence with continuously packed sites such as nanoclusters and nanoparticles. This work presents a comprehensive guidance on how to increase the degree of atomization through a selection of appropriate experimental conditions and supports. It is based on a rigorous macro-kinetic theory that captures relevant competing processes of nucleation and formation of single atoms stabilized by point defects. The effects of metal-support interactions and deposition parameters on the resulting single atom to nanocluster ratio as well as the role of metal centers formed on point defects in the kinetics of nucleation have been established, thus paving the way to guided synthesis of single atom catalysts. The predictions are supported by experimental results on sputter deposition of Pt on exfoliated hexagonal boron nitride, as imaged by aberration-corrected scanning transmission electron microscopy.

Bridging Imaging Users to Imaging Analysis - A community survey.

The "Bridging Imaging Users to Imaging Analysis" survey was conducted in 2022 by the Center for Open Bioimage Analysis (COBA), Bioimaging North America (BINA), and the Royal Microscopical Society Data Analysis in Imaging Section (RMS DAIM) to understand the needs of the imaging community. Through multi-choice and open-ended questions, the survey inquired about demographics, image analysis experiences, future needs, and suggestions on the role of tool developers and users. Participants of the survey were from diverse roles and domains of the life and physical sciences. To our knowledge, this is the first attempt to survey cross-community to bridge knowledge gaps between physical and life sciences imaging. Survey results indicate that respondents' overarching needs are documentation, detailed tutorials on the usage of image analysis tools, user-friendly intuitive software, and better solutions for segmentation, ideally in a format tailored to their specific use cases. The tool creators suggested the users familiarize themselves with the fundamentals of image analysis, provide constant feedback, and report the issues faced during image analysis while the users would like more documentation and an emphasis on tool friendliness. Regardless of the computational experience, there is a strong preference for 'written tutorials' to acquire knowledge on image analysis. We also observed that the interest in having 'office hours' to get an expert opinion on their image analysis methods has increased over the years. In addition, the community suggests the need for a common repository for the available image analysis tools and their applications. The opinions and suggestions of the community, released here in full, will help the image analysis tool creation and education communities to design and deliver the resources accordingly.

Subnanometer-Wide Indium Selenide Nanoribbons.

Indium selenides (InxSey) have been shown to retain several desirable properties, such as ferroelectricity, tunable photoluminescence through temperature-controlled phase changes, and high electron mobility when confined to two dimensions (2D). In this work we synthesize single-layer, ultrathin, subnanometer-wide InxSey by templated growth inside single-walled carbon nanotubes (SWCNTs). Despite the complex polymorphism of InxSey we show that the phase of the encapsulated material can be identified through comparison of experimental aberration-corrected transmission electron microscopy (AC-TEM) images and AC-TEM simulations of known structures of InxSey. We show that, by altering synthesis conditions, one of two different stoichiometries of sub-nm InxSey, namely InSe or ß-In2Se3, can be prepared. Additionally, in situ AC-TEM heating experiments reveal that encapsulated ß-In2Se3 undergoes a phase change to γ-In2Se3 above 400 °C. Further analysis of the encapsulated species is performed using X-ray photoelectron spectroscopy (XPS), thermogravimetric analysis (TGA), energy dispersive X-ray analysis (EDX), and Raman spectroscopy, corroborating the identities of the encapsulated species. These materials could provide a platform for ultrathin, subnanometer-wide phase-change nanoribbons with applications as nanoelectronic components.

Cd/Pt Precursor Solution for Solar H2 Production and in situ Photochemical Synthesis of Pt Single-atom Decorated CdS Nanoparticles.

Despite extensive efforts to develop high-performance H2 evolution catalysts, this remains a major challenge. Here, we demonstrate the use of Cd/Pt precursor solutions for significant photocatalytic H2 production (154.7 mmol g-1 h-1 ), removing the need for a pre-synthesized photocatalyst. In addition, we also report simultaneous in situ synthesis of Pt single-atoms anchored CdS nanoparticles (PtSA -CdSIS ) during photoirradiation. The highly dispersed in situ incorporation of extensive Pt single atoms on CdSIS enables the enhancement of active sites and suppresses charge recombination, which results in exceptionally high solar-to-hydrogen conversion efficiency of ≈1 % and an apparent quantum yield of over 91 % (365 nm) for H2 production. Our work not only provides a promising strategy for maximising H2 production efficiency but also provides a green process for H2 production and the synthesis of highly photoactive PtSA -CdSIS nanoparticles.

Methanol synthesis from CO2 and H2 using supported Pd alloy catalysts.

A number of Pd based materials have been synthesised and evaluated as catalysts for the conversion of carbon dioxide and hydrogen to methanol, a useful platform chemical and hydrogen storage molecule. Monometallic Pd catalysts show poor methanol selectivity, but this is improved through the formation of Pd alloys, with both PdZn and PdGa alloys showing greatly enhanced methanol productivity compared with monometallic Pd/Al2O3 and Pd/TiO2 catalysts. Catalyst characterisation shows that the 1 : 1 ß-PdZn alloy is present in all Zn containing post-reaction samples, including PdZn/Ga2O3, with the Pd2Ga alloy formed for the Pd/Ga2O3 sample. The heat of mixing was calculated for a variety of alloy compositions with high values determined for both PdZn and Pd2Ga alloys, at ca. -0.6 eV per atom and ca. -0.8 eV per atom, respectively. However, ZnO is more readily reduced than Ga2O3, providing a possible explanation for the preferential formation of the PdZn alloy, rather than PdGa, when in the presence of Ga2O3.

Enhanced H2O2 Production via Photocatalytic O2 Reduction over Structurally-Modified Poly(heptazine imide).

Solar H2O2 produced by O2 reduction provides a green, efficient, and ecological alternative to the industrial anthraquinone process and H2/O2 direct-synthesis. We report efficient photocatalytic H2O2 production at a rate of 73.4 mM h-1 in the presence of a sacrificial donor on a structurally engineered catalyst, alkali metal-halide modulated poly(heptazine imide) (MX → PHI). The reported H2O2 production is nearly 150 and >4250 times higher than triazine structured pristine carbon nitride under UV-visible and visible light (≥400 nm) irradiation, respectively. Furthermore, the solar H2O2 production rate on MX → PHI is higher than most of the previously reported carbon nitride (triazine, tri-s-triazine), metal oxides, metal sulfides, and other metal-organic photocatalysts. A record high AQY of 96% at 365 nm and 21% at 450 nm was observed. We find that structural modulation by alkali metal-halides results in a highly photoactive MX → PHI catalyst which has a broader light absorption range, enhanced light absorption ability, tailored bandgap, and a tunable band edge position. Moreover, this material has a different polymeric structure, high O2 trapping ability, interlayer intercalation, as well as surface decoration of alkali metals. The specific C≡N groups and surface defects, generated by intercalated MX, were also considered as potential contributors to the separation of photoinduced electron-hole pairs, leading to enhanced photocatalytic activity. A synergy of all these factors contributes to a higher H2O2 production rate. Spectroscopic data help us to rationalize the exceptional photochemical performance and structural characteristics of MX → PHI.

The Critical Role of ßPdZn Alloy in Pd/ZnO Catalysts for the Hydrogenation of Carbon Dioxide to Methanol.

The rise in atmospheric CO2 concentration and the concomitant rise in global surface temperature have prompted massive research effort in designing catalytic routes to utilize CO2 as a feedstock. Prime among these is the hydrogenation of CO2 to make methanol, which is a key commodity chemical intermediate, a hydrogen storage molecule, and a possible future fuel for transport sectors that cannot be electrified. Pd/ZnO has been identified as an effective candidate as a catalyst for this reaction, yet there has been no attempt to gain a fundamental understanding of how this catalyst works and more importantly to establish specific design criteria for CO2 hydrogenation catalysts. Here, we show that Pd/ZnO catalysts have the same metal particle composition, irrespective of the different synthesis procedures and types of ZnO used here. We demonstrate that all of these Pd/ZnO catalysts exhibit the same activity trend. In all cases, the ß-PdZn 1:1 alloy is produced and dictates the catalysis. This conclusion is further supported by the relationship between conversion and selectivity and their small variation with ZnO surface area in the range 6-80 m2g-1. Without alloying with Zn, Pd is a reverse water-gas shift catalyst and when supported on alumina and silica is much less active for CO2 conversion to methanol than on ZnO. Our approach is applicable to the discovery and design of improved catalysts for CO2 hydrogenation and will aid future catalyst discovery.

Trainable segmentation for transmission electron microscope images of inorganic nanoparticles.

We present a trainable segmentation method implemented within the python package ParticleSpy. The method takes user labelled pixels, which are used to train a classifier and segment images of inorganic nanoparticles from transmission electron microscope images. This implementation is based on the trainable Waikato Environment for Knowledge Analysis (WEKA) segmentation, but is written in python, allowing a large degree of flexibility and meaning it can be easily expanded using other python packages. We find that trainable segmentation offers better accuracy than global or local thresholding methods and requires as few as 100 user-labelled pixels to produce an accurate segmentation. Trainable segmentation presents a balance of accuracy and training time between global/local thresholding and neural networks, when used on transmission electron microscope images of nanoparticles. We also quantitatively investigate the effectiveness of the components of trainable segmentation, its filter kernels and classifiers, in order to demonstrate the use cases for the different filter kernels in ParticleSpy and the most accurate classifiers for different data types. A set of filter kernels is identified that are effective in distinguishing particles from background but that retain dissimilar features. In terms of classifiers, we find that different classifiers perform optimally for different image contrast; specifically, a random forest classifier performs best for high-contrast ADF images, but that QDA and Gaussian Naïve Bayes classifiers perform better for low-contrast TEM images.

Measurement of the size, shape and composition of nanoparticles is routinely performed using transmission electron microscopy and related techniques. Typically, distinguishing particles from the background in an image is performed using the intensity of each pixel, creating two sets of pixels to separate particles from background. However, this separation of intensity can be difficult if the contrast in an image is low, or if the intensity of the background varies significantly. In this study, an approach that takes into account additional image features (such as boundaries and texture) was investigated to study electron microscope images of metallic nanoparticles. In this 'trainable segmentation' approach, the user labels examples of particle and background pixels in order to train a machine learning algorithm to distinguish between particles and background. The performance of different machine learning algorithms was investigated, in addition to the effect of using different features to aid the segmentation. Overall, a trainable segmentation approach was found to perform better than use of an intensity threshold to distinguish between particles and background in electron microscope images.

Efficient energy transport in an organic semiconductor mediated by transient exciton delocalization.

Efficient energy transport is desirable in organic semiconductor (OSC) devices. However, photogenerated excitons in OSC films mostly occupy highly localized states, limiting exciton diffusion coefficients to below ~10-2 cm2/s and diffusion lengths below ~50 nm. We use ultrafast optical microscopy and nonadiabatic molecular dynamics simulations to study well-ordered poly(3-hexylthiophene) nanofiber films prepared using living crystallization-driven self-assembly, and reveal a highly efficient energy transport regime: transient exciton delocalization, where energy exchange with vibrational modes allows excitons to temporarily re-access spatially extended states under equilibrium conditions. We show that this enables exciton diffusion constants up to 1.1 ± 0.1 cm2/s and diffusion lengths of 300 ± 50 nm. Our results reveal the dynamic interplay between localized and delocalized exciton configurations at equilibrium conditions, calling for a re-evaluation of exciton dynamics and suggesting design rules to engineer efficient energy transport in OSC device architectures not based on restrictive bulk heterojunctions.

Oleylamine Aging of PtNi Nanoparticles Giving Enhanced Functionality for the Oxygen Reduction Reaction.

We report a rapid solution-phase strategy to synthesize alloyed PtNi nanoparticles which demonstrate outstanding functionality for the oxygen reduction reaction (ORR). This one-pot coreduction colloidal synthesis results in a monodisperse population of single-crystal nanoparticles of rhombic dodecahedral morphology with Pt-enriched edges and compositions close to Pt1Ni2. We use nanoscale 3D compositional analysis to reveal for the first time that oleylamine (OAm)-aging of the rhombic dodecahedral Pt1Ni2 particles results in Ni leaching from surface facets, producing aged particles with concave faceting, an exceptionally high surface area, and a composition of Pt2Ni1. We show that the modified atomic nanostructures catalytically outperform the original PtNi rhombic dodecahedral particles by more than two-fold and also yield improved cycling durability. Their functionality for the ORR far exceeds commercially available Pt/C nanoparticle electrocatalysts, both in terms of mass-specific activities (up to a 25-fold increase) and intrinsic area-specific activities (up to a 27-fold increase).

Automated Single-Particle Reconstruction of Heterogeneous Inorganic Nanoparticles.

Single-particle reconstruction can be used to perform three-dimensional (3D) imaging of homogeneous populations of nano-sized objects, in particular viruses and proteins. Here, it is demonstrated that it can also be used to obtain 3D reconstructions of heterogeneous populations of inorganic nanoparticles. An automated acquisition scheme in a scanning transmission electron microscope is used to collect images of thousands of nanoparticles. Particle images are subsequently semi-automatically clustered in terms of their properties and separate 3D reconstructions are performed from selected particle image clusters. The result is a 3D dataset that is representative of the full population. The study demonstrates a methodology that allows 3D imaging and analysis of inorganic nanoparticles in a fully automated manner that is truly representative of large particle populations.

Imaging Three-Dimensional Elemental Inhomogeneity in Pt-Ni Nanoparticles Using Spectroscopic Single Particle Reconstruction.

The properties of nanoparticles are known to critically depend on their local chemistry but characterizing three-dimensional (3D) elemental segregation at the nanometer scale is highly challenging. Scanning transmission electron microscope (STEM) tomographic imaging is one of the few techniques able to measure local chemistry for inorganic nanoparticles but conventional methodologies often fail due to the high electron dose imparted. Here, we demonstrate realization of a new spectroscopic single particle reconstruction approach built on a method developed by structural biologists. We apply this technique to the imaging of PtNi nanocatalysts and find new evidence of a complex inhomogeneous alloying with a Pt-rich core, a Ni-rich hollow octahedral intermediate shell and a Pt-rich rhombic dodecahedral skeleton framework with less Pt at ⟨100⟩ vertices. The ability to gain evidence of local surface enrichment that varies with the crystallographic orientation of facets and vertices is expected to provide significant insight toward the development of nanoparticles for sensing, medical imaging, and catalysis.

Micron-scale crack propagation in laser-irradiated enamel and dentine studied with nano-CT.

OBJECTIVES: The aim of this study was to see the effect of Er:YAG laser irradiation in dentine and compare this with its effect in enamel. The mechanism of crack propagation in dentine was emphasised and its clinical implications were discussed. MATERIALS AND METHODS: Coronal sections of sound enamel and dentine were machined to 50-µm thickness using a FEI-Helios Plasma (FIB). The specimen was irradiated for 30 s with 2.94-µm Er:YAG laser radiation in a moist environment, using a sapphire dental probe tip, with the tip positioned 2 mm away from the sample surface. One of the sections was analysed as a control and not irradiated. Samples were analysed using the Zeiss Xradia 810 Ultra, which allows high spatial resolution, nanoscale 3D imaging using X-ray computed tomography (CT). RESULTS: Dentine: In the peritubular dentine, micro-cracks ran parallel to the tubules whereas in the inter-tubular region, the cracks ran orthogonal to the dentinal tubules. These cracks extended to a mean depth of approximately 10 µm below the surface. On the dentine surface, there was preferential ablation of the less mineralised intertubular dentine, and this resulted in an irregular topography associated with tubules. Enamel: The irradiated enamel surface showed a characteristic 'rough' morphology suggesting some preferential ablation along certain microstructure directions. There appears to be very little subsurface damage, with the prismatic structure remaining intact. CONCLUSIONS: A possible mechanism is that laser radiation is transmitted down the dentinal tubules causing micro-cracks to form in the dentinal tubule walls that tend to be limited to this region. CLINICAL RELEVANCE: Crack might be a source of fracture as it represents a weak point and subsequently might lead to a failure in restorative dentistry.

Non-rigid registration and non-local principle component analysis to improve electron microscopy spectrum images.

Image registration and non-local Poisson principal component analysis (PCA) denoising improve the quality of characteristic x-ray (EDS) spectrum imaging of Ca-stabilized Nd2/3TiO3 acquired at atomic resolution in a scanning transmission electron microscope. Image registration based on the simultaneously acquired high angle annular dark field image significantly outperforms acquisition with a long pixel dwell time or drift correction using a reference image. Non-local Poisson PCA denoising reduces noise more strongly than conventional weighted PCA while preserving atomic structure more faithfully. The reliability of and optimal internal parameters for non-local Poisson PCA denoising of EDS spectrum images is assessed using tests on phantom data.

Energy Dispersive X-ray Tomography for 3D Elemental Mapping of Individual Nanoparticles.

Energy dispersive X-ray spectroscopy within the scanning transmission electron microscope (STEM) provides accurate elemental analysis with high spatial resolution, and is even capable of providing atomically resolved elemental maps. In this technique, a highly focused electron beam is incident upon a thin sample and the energy of emitted X-rays is measured in order to determine the atomic species of material within the beam path. This elementally sensitive spectroscopy technique can be extended to three dimensional tomographic imaging by acquiring multiple spectrum images with the sample tilted along an axis perpendicular to the electron beam direction. Elemental distributions within single nanoparticles are often important for determining their optical, catalytic and magnetic properties. Techniques such as X-ray tomography and slice and view energy dispersive X-ray mapping in the scanning electron microscope provide elementally sensitive three dimensional imaging but are typically limited to spatial resolutions of > 20 nm. Atom probe tomography provides near atomic resolution but preparing nanoparticle samples for atom probe analysis is often challenging. Thus, elementally sensitive techniques applied within the scanning transmission electron microscope are uniquely placed to study elemental distributions within nanoparticles of dimensions 10-100 nm. Here, energy dispersive X-ray (EDX) spectroscopy within the STEM is applied to investigate the distribution of elements in single AgAu nanoparticles. The surface segregation of both Ag and Au, at different nanoparticle compositions, has been observed.