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.

Body mass index is an overlooked confounding factor in existing clustering studies of 3D facial scans of children with autism spectrum disorder.

Cluster analyzes of facial models of autistic patients aim to clarify whether it is possible to diagnose autism on the basis of facial features and further to stratify the autism spectrum disorder. We performed a cluster analysis of sets of 3D scans of ASD patients (116) and controls (157) using Euclidean and geodesic distances in order to recapitulate the published results on the Czech population. In the presented work, we show that the major factor determining the clustering structure and consequently also the correlation of resulting clusters with autism severity degree is body mass index corrected for age (BMIFA). After removing the BMIFA effect from the data in two independent ways, both the cluster structure and autism severity correlations disappeared. Despite the fact that the influence of body mass index (BMI) on facial dimensions was studied many times, this is the first time to our knowledge when BMI was incorporated into the faces clustering study and it thereby casts doubt on previous results. We also performed correlation analysis which showed that the only correction used in the existing clustering studies-dividing the facial distance by the average value within the face-is not eliminating correlation between facial distances and BMIFA within the facial cohort.

Stable mass-selected AuTiOx nanoparticles for CO oxidation.

Stability under reactive conditions poses a common challenge for cluster- and nanoparticle-based catalysts. Since the catalytic properties of <5 nm gold nanoparticles were first uncovered, optimizing their stability at elevated temperatures for CO oxidation has been a central theme. Here we report direct observations of improved stability of AuTiOx alloy nanoparticles for CO oxidation compared with pure Au nanoparticles on TiO2. The nanoparticles were synthesized using a magnetron sputtering, gas-phase aggregation cluster source, size-selected using a lateral time-of-flight mass filter and deposited onto TiO2-coated micro-reactors for thermocatalytic activity measurements of CO oxidation. The AuTiOx nanoparticles exhibited improved stability at elevated temperatures, which is attributed to a self-anchoring interaction with the TiO2 substrate. The structure of the AuTiOx nanoparticles was also investigated in detail using ion scattering spectroscopy, X-ray photoelectron spectroscopy, and transmission electron microscopy. The measurements showed that the alloyed nanoparticles exhibited a core-shell structure with an Au core surrounded by an AuTiOx shell. The structure of these alloy nanoparticles appeared stable even at temperatures up to 320 °C under reactive conditions, for more than 140 hours. The work presented confirms the possibility of tuning catalytic activity and stability via nanoparticle alloying and self-anchoring on TiO2 substrates, and highlights the importance of complementary characterization techniques to investigate and optimize nanoparticle catalyst designs of this nature.

Development of CuO/Cu4(OH)6SO4 Nanoparticle Mixtures to Optimize the H2S Adsorption.

In this paper, we report the H2S adsorption behavior of a sorbent composed of mixtures of tenorite (CuO) and brochantite [Cu4(OH)6SO4]. These materials are readily prepared through the addition of NaOH(aq) to CuSO4(aq). They can be loaded onto polymer foams to create effective filters that can remove malodorous H2S gas, as evidenced by breakthrough tests. X-ray diffraction shows that the ratio of the two compounds in the mixture can be finely tuned by varying the amount of NaOH(aq) that is added to the reaction mixture. X-ray photoelectron spectroscopy shows that brochantite, like tenorite, has the ability to chemically adsorb H2S. Correlation of the H2S breakthrough data with scanning transmission electron microscopy measurements shows that the most effective sorbents contain nanoscale needle-like particles. These are likely to be formed largely by the tenorite phase. The samples with the greatest H2S adsorption efficacy contained less than 20% tenorite in the mixture, where these particles had the greatest abundance. The application of this sorbent onto porous substrates to create effective filters, along with the synthetic ease of its production, could allow this methodology to find use in a number of areas where H2S poses a problem. This could include areas where protective clothing is required to adsorb the gas from environments where there is a high level of H2S, for example, in wastewater treatment plants, oil and gas wells, or in the medical sector, where it could be deployed as filter media.

Support-facet-dependent morphology of small Pt particles on ceria.

Direct atomic scale information on how the structure of supported nanoparticles is affected by the metal-support interaction is rare. Using scanning transmission electron microscopy, we provide direct evidence of a facet-dependent support interaction for Pt nanoparticles on CeO2, governing the dimensionality of small platinum particles. Our findings indicate that particles consisting of less than ∼130 atoms prefer a 3D shape on CeO2(111) facets, while 2D raft structures are favored on CeO2(100) facets. Measurements of stationary particles on both surface facets are supplemented by time resolved measurements following a single particle with atomic resolution as it migrates from CeO2(111) to CeO2(100), undergoing a dimensionality change from 3D to 2D. The intricate transformation mechanism reveals how the 3D particle disassembles and completely wets a neighboring CeO2(100) facet. Density functional theory calculations confirm the structure-trend and reveal the thermodynamic driving force for the migration of small particles. Knowledge of the presented metal-support interactions is crucial to establish structure-function relationships in a range of applications based on supported nanostructures.

Core atoms escape from the shell: reverse segregation of Pb-Al core-shell nanoclusters via nanoscale melting.

Melting is a phase transition that profoundly affects the fabrication and diverse applications of metal nanoclusters. Core-shell clusters offer distinctive properties and thus opportunities compared with other classes of nano-alloys. Molecular dynamics simulations have been employed to investigate the melting behaviour of Pb-Al core-shell clusters containing a fixed Pb147 core and varying shell thickness. Our results show that the core and shell melt separately. Surprisingly, core melting always drives the core Pb atoms to break out the shell and coat the nanoclusters in a reversed segregation process at the nanoscale. The melting point of the core increases with the shell thickness to exceed that of the bare core cluster, but the thinnest shell always supresses the core melting point. These results can be a reference for the future fabrication, manipulation, and exploitation of the core-shell nanoalloys chosen. The system chosen is ideally suited for experimental observations.

Periodontal examination and screening.

Periodontal screening is an important tool in dental practice, and the BPE system is recommended. Clinically, visual examination should identify inflammatory change, recession and enlargement. However, detailed periodontal charting is required in all patients with significant levels of disease. In addition, radiographic examination is important to verify loss of bone and to show root anatomy.

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.

Broadband and Spectrally Selective Photothermal Conversion through Nanocluster Assembly of Disordered Plasmonic Metasurfaces.

Plasmonic metasurfaces have been realized for efficient light absorption, thereby leading to photothermal conversion through nonradiative decay of plasmonic modes. However, current plasmonic metasurfaces suffer from inaccessible spectral ranges, costly and time-consuming nanolithographic top-down techniques for fabrication, and difficulty of scale-up. Here, we demonstrate a new type of disordered metasurface created by densely packing plasmonic nanoclusters of ultrasmall size on a planar optical cavity. The system either operates as a broadband absorber or offers a reconfigurable absorption band right across the visible region, resulting in continuous wavelength-tunable photothermal conversion. We further present a method to measure the temperature of plasmonic metasurfaces via surface-enhanced Raman spectroscopy (SERS), by incorporating single-walled carbon nanotubes (SWCNTs) as an SERS probe within the metasurfaces. Our disordered plasmonic system, generated by a bottom-up process, offers excellent performance and compatibility with efficient photothermal conversion. Moreover, it also provides a novel platform for various hot-electron and energy-harvesting functionalities.

3D facial analysis for rare disease diagnosis and treatment monitoring: Proof-Of-Concept plan for hereditary angioedema.

Rare diseases pose a diagnostic conundrum to even the most experienced clinicians around the world. The technology could play an assistive role in hastening the diagnosis process. Data-driven methodologies can identify distinctive disease features and create a definitive diagnostic spectrum. The healthcare professionals in developed and developing nations would benefit immensely from these approaches resulting in quicker diagnosis and enabling early care for the patients. Hereditary Angioedema is one such rare disease that requires a lengthy diagnostic cascade ensuing massive patient inconvenience and cost burden on the healthcare system. It is hypothesized that facial analysis with advanced imaging and algorithmic association can create an ideal diagnostic peer to the clinician while assimilating signs and symptoms in the hospital. 3D photogrammetry has been applied to diagnose rare diseases in various cohorts. The facial features are captured at a granular level in utmost finer detail. A validated and proven algorithm-powered software provides recommendations in real-time. Thus, paving the way for quick and early diagnosis to well-trained or less trained clinicians in different settings around the globe. The generated evidence indicates the strong applicability of 3 D photogrammetry in association with proprietary Cliniface software to Hereditary Angioedema for aiding in the diagnostic process. The approach, mechanism, and beneficial impact have been sketched out appropriately herein. This blueprint for hereditary angioedema may have far-reaching consequences beyond disease diagnosis to benefit all the stakeholders in the healthcare arena including research and new drug development.

Influence of air exposure on structural isomers of silver nanoparticles.

Up to date, the influence of ambient air exposure on the energetics and stability of silver clusters has rarely been investigated and compared to clusters in vacuum. Silver clusters up to 3000 atoms in size, on an amorphous carbon film, have been exposed to ambient air and investigated by atomic-resolution imaging in the aberration-corrected Scanning Transmission Electron Microscope. Ordered structures comprise more than half the population, the rest are amorphous. Here, we show that the most common ordered isomer structures is the icosahedron. These results contrast with the published behaviour of silver clusters protected from atmospheric exposure, where the predominant ordered isomer is face-centred cubic. We propose that the formation of surface oxide or sulphide species resulting from air exposure can account for this deviation in stable isomer. This interpretation is consistent with density functional theory calculations based on silver nanoclusters, in the size range 147-201 atoms, on which methanethiol molecules are adsorbed. An understanding of the effects of ambient exposure on the atomic structure and therefore functional properties of nanoparticles is highly relevant to their real-world performance and applications.

Metal Nanocluster-Metal Organic Framework-Polymer Hybrid Nanomaterials for Improved Hydrogen Detection.

The development of hydrogen sensors is of paramount importance for timely leak detection and remains a crucial unmet need. Palladium-based materials, well known as hydrogen sensors, still suffer from poisoning and deactivation. Here, a hybrid hydrogen sensor consisting of a Pd nanocluster (NC) film, a metal-organic framework (MOF), and a polymer, are proposed. The polymer coating, as a protection layer, endows the sensor with excellent H2 selectivity and CO-poisoning resistance. The MOF serves as an interface layer between the Pd NC film and the polymer layer, which alters the nature of the interaction with hydrogen and leads to significant sensing performance improvements, owing to the interfacial electronic coupling between Pd NCs and the MOF. The strategy overcomes the shortcomings of retarded response speed and degraded sensitivity induced by the polymer coating of a Pd NC film-polymer hybrid system. This is the first exhibition of a hydrogen-sensing enhancement mechanism achieved by engineering the electronic coupling between Pd and a MOF. The work establishes a deep understanding of the hydrogen-sensing enhancement mechanism at the nanoscale and provides a feasible strategy to engineer next-generation gas-sensing nanodevices with superior sensing figures of merit via hybrid material systems.

Molecular dynamics simulation of nanofilament breakage in neuromorphic nanoparticle networks.

Neuromorphic computing systems may be the future of computing and cluster-based networks are a promising architecture for the realization of these systems. The creation and dissolution of synapses between the clusters are of great importance for their function. In this work, we model the thermal breakage of a gold nanofilament located between two gold nanoparticles via molecular dynamics simulations to study on the mechanisms of neuromorphic nanoparticle-based devices. We employ simulations of Au nanowires of different lengths (20-80 Å), widths (4-8 Å) and shapes connecting two Au1415nanoparticles (NPs) and monitor the evolution of the system via a detailed structural identification analysis. We found that atoms of the nanofilament gradually aggregate towards the clusters, causing the middle of wire to gradually thin and then break. Most of the system remains crystalline during this process but the center is molten. The terminal NPs increase the melting point of the NWs by fixing the middle wire and act as recrystallization areas. We report a strong dependence on the width of the NWs, but also their length and structure. These results may serve as guidelines for the realization of cluster-based neuromorphic computing systems.

Interactions between multi-walled carbon nanotubes and plankton as detected by Raman spectroscopy.

Raman spectroscopy has been commonly used in materials science to detect chemicals. Based on inelastic scattering of light after incident photons interact with a molecule, it has high potential for non-destructive detection of specific contaminants in living biological specimens. The increasing use of carbon nanotubes (CNTs) increases its chance to enter the aquatic habitats through direct discharge, surface runoff and atmospheric deposition, but their potential environmental impacts remain poorly known. We tested the use of Raman spectroscopy to investigate the interactions between multi-walled CNTs (MWCNTs) and aquatic plankton in vivo. For phytoplankton cells (Scenedesmus obliquus) that were exposed to MWCNTs, Raman spectroscopy was able to distinguish between background biological material and MWCNTs that adhere to the cells (G-band peak at 1590 cm-1 and D-band peak at 1350 cm-1 in the Raman spectra that were unique to MWCNTs). Harmful effects of MWCNT exposure manifested as lower photosynthetic efficiency and/or lower specific growth rate in the phytoplankton. MWCNT particles also adhered to the body surface of zooplankton, especially the carapace. Both Ceriodaphnia sp. and Daphnia sp. ingested MWCNTs directly, which was verified by the signature G-band and D-band Raman peaks in the zooplankton gut region. MWCNTs remained in the gut overnight after the zooplankton had been returned to clean water, showing that the zooplankton retained MWCNTs inside their body for an extended time, thereby increasing the chance to disperse and transfer the contaminants throughout the aquatic food web. Our results demonstrate that Raman spectroscopy is a promising method for non-destructive investigation of the uptake and dynamic fate of CNTs and other contaminants in aquatic organisms.

A Fullerene-Platinum Complex for Direct Functional Patterning of Single Metal Atom-Embedded Carbon Nanostructures.

The development of patterning materials ("resists") at the nanoscale involves two distinct trends: one is toward high sensitivity and resolution for miniaturization, the other aims at functionalization of the resists to realize bottom-up construction of distinct nanoarchitectures. Patterning of carbon nanostructures, a seemingly ideal application for organic functional resists, has been highly reliant on complicated pattern transfer processes because of a lack of patternable precursors. Herein, we present a fullerene-metal coordination complex as a fabrication material for direct functional patterning of sub-10 nm metal-containing carbon structures. The attachment of one platinum atom per fullerene molecule not only leads to significant improvement of sensitivity and resolution but also enables stable atomic dispersion of the platinum ions within the carbon matrix, which may gain fundamentally new interest in functional patterning of hierarchical carbon nanostructures.

An ab initio study of size-selected Pd nanocluster catalysts for the hydrogenation of 1-pentyne.

The hydrogenation of alkynes is an important reaction in the synthesis of both fine and bulk chemicals. Palladium-based catalysts are widely used and therefore size-selected Pd nanoclusters may provide enhanced performance. An investigation of the adsorption and desorption of the molecules involved in the reaction can shed light on the activity and selectivity of the catalysts. We employ ab initio calculations to investigate the binding energies of all the molecules related to the hydrogenation of 1-pentyne (1-pentyne, 1-pentene, cis-2-pentene, trans-2-pentene and pentane) on a comprehensive set of possible binding sites of two Pd147 and Pd561 cuboctahedral nanoclusters. We extract the site and size dependence of these binding energies. We find that the adsorption of 1-pentyne occurs preferably on the (100) facets of the nanoclusters, followed by their (111) facets, their edges and their vertices. The molecule binds more strongly on the larger nanoclusters, which are therefore expected to display higher activity. The binding energies of the pentenes are found to be lower on the smaller nanoclusters. Therefore, these molecules are expected to desorb more easily and the small clusters should display better selectivity, i.e., partial hydrogenation to 1-pentene, compared with large clusters. Our results provide guidelines for the optimal design of Pd nanocatalysts.

Data-driven simulation and characterisation of gold nanoparticle melting.

The simulation and analysis of the thermal stability of nanoparticles, a stepping stone towards their application in technological devices, require fast and accurate force fields, in conjunction with effective characterisation methods. In this work, we develop efficient, transferable, and interpretable machine learning force fields for gold nanoparticles based on data gathered from Density Functional Theory calculations. We use them to investigate the thermodynamic stability of gold nanoparticles of different sizes (1 to 6 nm), containing up to 6266 atoms, concerning a solid-liquid phase change through molecular dynamics simulations. We predict nanoparticle melting temperatures in good agreement with available experimental data. Furthermore, we characterize the solid-liquid phase change mechanism employing an unsupervised learning scheme to categorize local atomic environments. We thus provide a data-driven definition of liquid atomic arrangements in the inner and surface regions of a nanoparticle and employ it to show that melting initiates at the outer layers.

Large-scale open-source three-dimensional growth curves for clinical facial assessment and objective description of facial dysmorphism.

Craniofacial dysmorphism is associated with thousands of genetic and environmental disorders. Delineation of salient facial characteristics can guide clinicians towards a correct clinical diagnosis and understanding the pathogenesis of the disorder. Abnormal facial shape might require craniofacial surgical intervention, with the restoration of normal shape an important surgical outcome. Facial anthropometric growth curves or standards of single inter-landmark measurements have traditionally supported assessments of normal and abnormal facial shape, for both clinical and research applications. However, these fail to capture the full complexity of facial shape. With the increasing availability of 3D photographs, methods of assessment that take advantage of the rich information contained in such images are needed. In this article we derive and present open-source three-dimensional (3D) growth curves of the human face. These are sequences of age and sex-specific expected 3D facial shapes and statistical models of the variation around the expected shape, derived from 5443 3D images. We demonstrate the use of these growth curves for assessing patients and show that they identify normal and abnormal facial morphology independent from age-specific facial features. 3D growth curves can facilitate use of state-of-the-art 3D facial shape assessment by the broader clinical and biomedical research community. This advance in phenotype description will support clinical diagnosis and the understanding of disease pathogenesis including genotype-phenotype relations.

Disorder-Induced Material-Insensitive Optical Response in Plasmonic Nanostructures: Vibrant Structural Colors from Noble Metals.

Materials show various responses to incident light, owing to their unique dielectric functions. A well-known example is the distinct colors displayed by metals, providing probably the simplest method to identify gold, silver, and bronze since ancient times. With the advancement of nanotechnology, optical structures with feature sizes smaller than the optical wavelength have been routinely achieved. In this regime, the optical response is also determined by the geometry of the nanostructures, inspiring flourishing progress in plasmonics, photonic crystals, and metamaterials. Nevertheless, the nature of the materials still plays a decisive role in light-matter interactions, and this material-dependent optical response is widely accepted as a norm in nanophotonics. Here, a counterintuitive system-plasmonic nanostructures composed of different materials but exhibiting almost identical reflection-is proposed and realized. The geometric disorder embedded in the system overwhelms the contribution of the material properties to the electrodynamics. Both numerical simulations and experimental results provide concrete evidence of the insensitivity of the optical response to different plasmonic materials. The same optical response is preserved with various materials, providing great flexibility of freedom in material selection. As a result, the proposed configuration may shed light on novel applications ranging from Raman spectroscopy, photocatalysis, to nonlinear optics.

Importance of Defective and Nonsymmetric Structures in Silver Nanoparticles.

Scanning transmission electron microscopy experiments indicate that face-centered cubic (FCC) is the predominant ordered structure for Ag309 ± 7 nanoclusters, synthesized in vacuum. Historically, experiments do not present a consensus on the morphology at these sizes, whereas theoretical studies find the icosahedral symmetry for Ag309 and the decahedral shape for nearby sizes. We employ density functional theory calculations to rationalize these observations, considering both regular and defective Ag nanoparticles (281-321 atoms). The change of stability induced by the presence of defects, symmetry loss, and change of number of atoms is evaluated by the nanoparticle surface energy, which was measured previously. FCC and decahedral symmetries are found to be more favorable than icosahedral, consistent with our measurements of clusters protected from extended atmospheric exposure. In addition, an energy-free descriptor, surface atomic density, is proposed and qualitatively reproduces the surface energy data. Nonsymmetric and defective structures may be preferred over perfectly regular ones within a given size range.