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.

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.

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 sustainable energy applications.

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.

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.

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.

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.

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).

Suicidality in family caregivers of people with long-term illnesses and disabilities: A scoping review.

An emerging body of international research suggests family caregivers may be a high-risk group for suicide, but the evidence has not been synthesised. Forty-eight peer-reviewed journal articles were included in this review, spanning low-, middle-, and high-income countries and a variety of illnesses and disabilities. The proportion of caregivers experiencing suicidal ideation ranged from 2.7% to 71%, with evidence of suicide attempts, deaths by suicide, and deaths by homicide-suicide also reported. Risk and protective factors varied across studies and there was little consideration of differences by caregiving relationship, type of illness/disability, or country. There is sufficient evidence to warrant concern for caregivers around the world and prompt action in policy and practice, but more rigorous research is required to draw clear, nuanced conclusions about risk and inform evidence-based prevention and intervention.

Advanced care planning during the COVID-19 pandemic: ceiling of care decisions and their implications for observational data.

BACKGROUND: Observational studies investigating risk factors in coronavirus disease 2019 (COVID-19) have not considered the confounding effects of advanced care planning, such that a valid picture of risk for elderly, frail and multi-morbid patients is unknown. We aimed to report ceiling of care and cardiopulmonary resuscitation (CPR) decisions and their association with demographic and clinical characteristics as well as outcomes during the COVID-19 pandemic. METHODS: Retrospective, observational study conducted between 5th March and 7th May 2020 of all hospitalised patients with COVID-19. Ceiling of care and CPR decisions were documented using the Recommended Summary Plan for Emergency Care and Treatment (ReSPECT) process. Unadjusted and multivariable regression analyses were used to determine factors associated with ceiling of care decisions and death during hospitalisation. RESULTS: A total of 485 patients were included, of whom 409 (84·3%) had a documented ceiling of care; level one for 208 (50·9%), level two for 75 (18·3%) and level three for 126 (30·8%). CPR decisions were documented for 451 (93·0%) of whom 336 (74·5%) were 'not for resuscitation'. Advanced age, frailty, White-European ethnicity, a diagnosis of any co-morbidity and receipt of cardiovascular medications were associated with ceiling of care decisions. In a multivariable model only advanced age (odds 0·89, 0·86-0·93 p < 0·001), frailty (odds 0·48, 0·38-0·60, p < 0·001) and the cumulative number of co-morbidities (odds 0·72, 0·52-1·0, p = 0·048) were independently associated. Death during hospitalisation was independently associated with age, frailty and requirement for level two or three care. CONCLUSION: Ceiling of care decisions were made for the majority of patients during the COVID-19 pandemic, broadly in line with known predictors of poor outcomes in COVID-19, but with a focus on co-morbidities suggesting ICU admission might not be a reliable end-point for observational studies where advanced care planning is routine.

Implantable cardioverter-defibrillator therapy to reduce sudden cardiac death in adults with congenital heart disease: A registry study.

INTRODUCTION: The adult congenital heart disease (ACHD) population is rapidly expanding. However, a significant proportion of these patients suffer sudden cardiac death. Recommending implantable cardioverter-defibrillator (ICD) insertion requires balancing the need for appropriate therapy in malignant arrhythmia against the consequences of inappropriate therapy and procedural complications. Here we present long-term follow-up data for ICD insertion in patients with ACHD from a large Level 1 congenital cardiac center. METHODS AND RESULTS: All patients with ACHD undergoing ICD insertion over an 18-year period were identified. Data were extracted for baseline characteristics including demographics, initial diagnosis, ventricular function, relevant medication, and indication for ICD insertion. Details regarding device insertion were gathered along with follow-up data including appropriate and inappropriate therapy and complications. A total of 136 ICDs were implanted during this period: 79 for primary and 57 for secondary prevention. The most common congenital cardiac conditions in both groups were tetralogy of Fallot and transposition of the great arteries. Twenty-two individuals in the primary prevention group received appropriate antitachycardia pacing (ATP), 14 underwent appropriate cardioversion, 17 received inappropriate ATP, and 15 received inappropriate cardioversion. In the secondary prevention group, 18 individuals received appropriate ATP, 8 underwent appropriate cardioversion, 8 received inappropriate ATP, and 7 were inappropriately cardioverted. Our data demonstrate low complication rates, particularly with leads without advisories. CONCLUSION: ICD insertion in the ACHD population involves a careful balance of the risks and benefits. Our data show a significant proportion of patients receiving appropriate therapy indicating that ICDs were inserted appropriately.

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.

Trends in Antarctic Ice Sheet Elevation and Mass.

Fluctuations in Antarctic Ice Sheet elevation and mass occur over a variety of time scales, owing to changes in snowfall and ice flow. Here we disentangle these signals by combining 25 years of satellite radar altimeter observations and a regional climate model. From these measurements, patterns of change that are strongly associated with glaciological events emerge. While the majority of the ice sheet has remained stable, 24% of West Antarctica is now in a state of dynamical imbalance. Thinning of the Pine Island and Thwaites glacier basins reaches 122 m in places, and their rates of ice loss are now five times greater than at the start of our survey. By partitioning elevation changes into areas of snow and ice variability, we estimate that East and West Antarctica have contributed -1.1 ± 0.4 and +5.7 ± 0.8 mm to global sea level between 1992 and 2017.

Neutrophil Microparticles Deliver Active Myeloperoxidase to Injured Mucosa To Inhibit Epithelial Wound Healing.

Neutrophil (PMN) infiltration of the intestinal mucosa often leads to severe epithelial injury; however, how this process occurs is unclear. This article describes a novel mechanism whereby membrane-derived microparticles released by tissue infiltrating PMNs (PMN-MPs) serve as shuttles to protect and deliver active mediators to locally modulate cellular function during inflammation. Specifically, myeloperoxidase (MPO), which is abundantly expressed in PMN azurophilic granules and is used for microbial killing, was found to be mobilized to the PMN surface and subsequently released in association with PMN-MPs upon PMN activation and binding to intestinal epithelial cells (IECs). The enzymatic activity of PMN-MP-associated MPO was enhanced compared with soluble protein, leading to potent inhibition of wound closure following PMN-MP binding to IECs. Importantly, localized microinjection of PMN-MPs into wounded colonic mucosa was sufficient to impair epithelial wound healing in vivo. PMN-MP/MPO-dependent inhibition of IEC wound healing was due to impaired IEC migration and proliferation, resulting from impeded actin dynamics, cell spreading, and cell cycle arrest. Thus, our findings provide new insight into mechanisms governing PMN-induced tissue injury and implicate PMN-MPs and MPO as important regulators of cellular function.

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.

A Networked Sensor System for the Analysis of Plot-Scale Hydrology.

This study presents the latest updates to the Audubon Society of Western Pennsylvania (ASWP) testbed, a $50,000 USD, 104-node outdoor multi-hop wireless sensor network (WSN). The network collects environmental data from over 240 sensors, including the EC-5, MPS-1 and MPS-2 soil moisture and soil water potential sensors and self-made sap flow sensors, across a heterogeneous deployment comprised of MICAz, IRIS and TelosB wireless motes. A low-cost sensor board and software driver was developed for communicating with the analog and digital sensors. Innovative techniques (e.g., balanced energy efficient routing and heterogeneous over-the-air mote reprogramming) maintained high success rates (>96%) and enabled effective software updating, throughout the large-scale heterogeneous WSN. The edaphic properties monitored by the network showed strong agreement with data logger measurements and were fitted to pedotransfer functions for estimating local soil hydraulic properties. Furthermore, sap flow measurements, scaled to tree stand transpiration, were found to be at or below potential evapotranspiration estimates. While outdoor WSNs still present numerous challenges, the ASWP testbed proves to be an effective and (relatively) low-cost environmental monitoring solution and represents a step towards developing a platform for monitoring and quantifying statistically relevant environmental parameters from large-scale network deployments.

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.

X-Ray Absorption Correction for Quantitative Scanning Transmission Electron Microscopic Energy-Dispersive X-Ray Spectroscopy of Spherical Nanoparticles.

A new method to perform X-ray absorption correction for spherical particles in quantitative energy-dispersive X-ray spectroscopy in the scanning transmission electron microscope is presented. An absorption correction factor is derived and simulated data is presented encompassing a range of X-ray absorption conditions. Theoretical calculations are compared with experimental data of X-ray counts from Au nanoparticles to verify the derived methodology. The effect of detector elevation angle is considered and a comparison with thin-film absorption correction is included.