XEDS STEM tomography for 3D chemical characterization of nanoscale particles

Ultrastructure and Nanoporosity of Human Bone Shown with Correlative On-Axis Electron and Spectroscopic Tomographies

Mineralized collagen fibrils are the building block units of bone at the nanoscale. While it is known that collagen fibrils are mineralized both inside their gap zones (intra-fibrillar mineralization) and on their outer surfaces (extra-fibrillar mineralization), a clear visualization of this architecture in three dimensions (3D), combining structural and compositional information over large volumes, but without compromising the resolution, remains challenging. In this study, we demonstrate the use of on-axis Z-contrast electron tomography (ET) with correlative energy-dispersive X-ray spectroscopy (EDX) tomography to examine rod-shaped samples with diameters up to 700 nm prepared from individual osteonal lamellae in the human femur. Our work mainly focuses on two aspects: (i) low-contrast nanosized circular spaces ("holes") observed in sections of bone oriented perpendicular to the long axis of a long bone, and (ii) extra-fibrillar mineral, especially in terms of morphology and spatial relationship with respect to intra-fibrillar mineral and collagen fibrils. From our analyses, it emerges quite clearly that most "holes" are cross-sectional views of collagen fibrils. While this had been postulated before, our 3D reconstructions and reslicing along meaningful two-dimensional (2D) cross-sections provide a direct visual confirmation. Extra-fibrillar mineral appears to be composed of thin plates that are interconnected and span over several collagen fibrils, confirming that mineralization is cross-fibrillar, at least for the extra-fibrillar phase. EDX tomography shows mineral signatures (Ca and P) within the gap zones, but the signal appears weaker than that associated with the extra-fibrillar mineral, pointing toward the existence of dissimilarities between the two types of mineralization.

Three-dimensional reconstruction of Y-IrNi rhombic dodecahedron nanoframe by STEM/EDS tomography

The structural analysis of nanocrystals via transmission electron microscopy (TEM) is a valuable technique for the material science field. Recently, two-dimensional images by scanning TEM (STEM) and energy-dispersive X-ray spectroscopy (EDS) have successfully extended to three-dimensional (3D) imaging by tomography. However, despite improving TEM instruments and measurement techniques, detector shadowing, the missing-wedge problem, X-ray absorption effects, etc., significant challenges still remain; therefore, the various required corrections should be considered and applied when performing quantitative tomography. Nonetheless, this 3D reconstruction technique can facilitate active site analysis and the development of nanocatalyst systems, such as water electrolysis and fuel cell. Herein, we present a 3D reconstruction technique to obtain tomograms of IrNi rhombic dodecahedral nanoframes (IrNi-RFs) from STEM and EDS images by applying simultaneous iterative reconstruction technique and total variation minimization algorithms. From characterizing the morphology and spatial chemical composition of the Ir and Ni atoms in the nanoframes, we were able to infer the origin of the physical and catalytic durability of IrNi-RFs. Also, by calculating the surface area and volume of the 3D reconstructed model, we were able to quantify the Ir-to-Ni composition ratio and compare it to the EDS measurement result.

Chemical Electron Microscopy (CEM) for Heterogeneous Catalysis at Nano: Recent Progress and Challenges

Chemical electron microscopy (CEM), a toolbox that comprises imaging and spectroscopy techniques, provides dynamic morphological, structural, chemical, and electronic information about an object in chemical environment under conditions of observable performance. CEM has experienced a revolutionary improvement in the past years and is becoming an effective characterization method for revealing the mechanism of chemical reactions, such as catalysis. Here, we mainly address the concept of CEM for heterogeneous catalysis in the gas phase and what CEM could uniquely contribute to catalysis, and illustrate what we can know better with CEM and the challenges and future development of CEM.

Element Specific Atom Counting at the Atomic Scale by Combining High Angle Annular Dark Field Scanning Transmission Electron Microscopy and Energy Dispersive X-ray Spectroscopy

A new methodology is presented to count the number of atoms in multimetallic nanocrystals by combining energy dispersive X-ray spectroscopy (EDX) and high angle annular dark field scanning transmission electron microscopy (HAADF STEM). For this purpose, the existence of a linear relationship between the incoherent HAADF STEM and EDX images is exploited. Next to the number of atoms for each element in the atomic columns, the method also allows quantification of the error in the obtained number of atoms, which is of importance given the noisy nature of the acquired EDX signals. Using experimental images of an Au@Ag core-shell nanorod, it is demonstrated that 3D structural information can be extracted at the atomic scale. Furthermore, simulated data of an Au@Pt core-shell nanorod show the prospect to characterize heterogeneous nanostructures with adjacent atomic numbers.

Compositional analysis of oxide-embedded III-V nanostructures

Nanowire growth enables creation of embedded heterostructures, where one material is completely surrounded by another. Through materials-selective post-growth oxidation it is also possible to combine amorphous oxides and crystalline, e.g. III-V materials. Such oxide-embedded structures pose a challenge for compositional characterization through transmission electron microscopy since the materials will overlap in projection. Furthermore, materials electrically isolated by an embedding oxide are more sensitive to electron beam-induced alterations. Methods that can directly isolate the embedded material, preferably at reduced electron doses, will be required in this situation. Here, we analyse the performance of two such techniques-local lattice parameter measurements from high resolution micrographs and bulk plasmon energy measurements from electron energy loss spectra-by applying them to analyse InP-AlInP segments embedded in amorphous aluminium oxide. We demonstrate the complementarity of the two methods, which show an overall excellent agreement. However, in regions with residual strain, which we analyse through molecular dynamics simulations, the two techniques diverge from the true value in opposite directions.

Deep learning-based denoising for improved dose efficiency in EDX tomography of nanoparticles

The combination of energy-dispersive X-ray spectroscopy (EDX) and electron tomography is a powerful approach to retrieve the 3D elemental distribution in nanomaterials, providing an unprecedented level of information for complex, multi-component systems, such as semiconductor devices, as well as catalytic and plasmonic nanoparticles. Unfortunately, the applicability of EDX tomography is severely limited because of extremely long acquisition times and high electron irradiation doses required to obtain 3D EDX reconstructions with an adequate signal-to-noise ratio. One possibility to address this limitation is intelligent denoising of experimental data using prior expectations about the objects of interest. Herein, this approach is followed using the deep learning methodology, which currently demonstrates state-of-the-art performance for an increasing number of data processing problems. Design choices for the denoising approach and training data are discussed with a focus on nanoparticle-like objects and extremely noisy signals typical for EDX experiments. Quantitative analysis of the proposed method demonstrates its significantly enhanced performance in comparison to classical denoising approaches. This allows for improving the tradeoff between the reconstruction quality, acquisition time and radiation dose for EDX tomography. The proposed method is therefore especially beneficial for the 3D EDX investigation of electron beam-sensitive materials and studies of nanoparticle transformations.

Reducing Time to Discovery: Materials and Molecular Modeling, Imaging, Informatics, and Integration

Multiscale and multimodal imaging of material structures and properties provides solid ground on which materials theory and design can flourish. Recently, KAIST announced 10 flagship research fields, which include KAIST Materials Revolution: Materials and Molecular Modeling, Imaging, Informatics and Integration (M3I3). The M3I3 initiative aims to reduce the time for the discovery, design and development of materials based on elucidating multiscale processing-structure-property relationship and materials hierarchy, which are to be quantified and understood through a combination of machine learning and scientific insights. In this review, we begin by introducing recent progress on related initiatives around the globe, such as the Materials Genome Initiative (U.S.), Materials Informatics (U.S.), the Materials Project (U.S.), the Open Quantum Materials Database (U.S.), Materials Research by Information Integration Initiative (Japan), Novel Materials Discovery (E.U.), the NOMAD repository (E.U.), Materials Scientific Data Sharing Network (China), Vom Materials Zur Innovation (Germany), and Creative Materials Discovery (Korea), and discuss the role of multiscale materials and molecular imaging combined with machine learning in realizing the vision of M3I3. Specifically, microscopies using photons, electrons, and physical probes will be revisited with a focus on the multiscale structural hierarchy, as well as structure-property relationships. Additionally, data mining from the literature combined with machine learning will be shown to be more efficient in finding the future direction of materials structures with improved properties than the classical approach. Examples of materials for applications in energy and information will be reviewed and discussed. A case study on the development of a Ni-Co-Mn cathode materials illustrates M3I3's approach to creating libraries of multiscale structure-property-processing relationships. We end with a future outlook toward recent developments in the field of M3I3.

Electron tomography imaging methods with diffraction contrast for materials research

Transmission electron microscopy (TEM) and scanning transmission electron microscopy (STEM) enable the visualization of three-dimensional (3D) microstructures ranging from atomic to micrometer scales using 3D reconstruction techniques based on computed tomography algorithms. This 3D microscopy method is called electron tomography (ET) and has been utilized in the fields of materials science and engineering for more than two decades. Although atomic resolution is one of the current topics in ET research, the development and deployment of intermediate-resolution (non-atomic-resolution) ET imaging methods have garnered considerable attention from researchers. This research trend is probably not irrelevant due to the fact that the spatial resolution and functionality of 3D imaging methods of scanning electron microscopy (SEM) and X-ray microscopy have come to overlap with those of ET. In other words, there may be multiple ways to carry out 3D visualization using different microscopy methods for nanometer-scale objects in materials. From the above standpoint, this review paper aims to (i) describe the current status and issues of intermediate-resolution ET with regard to enhancing the effectiveness of TEM/STEM imaging and (ii) discuss promising applications of state-of-the-art intermediate-resolution ET for materials research with a particular focus on diffraction contrast ET for crystalline microstructures (superlattice domains and dislocations) including a demonstration of in situ dislocation tomography.

A Multichannel Cross-Modal Fusion Framework for Electron Tomography

In this paper, we present a multichannel cross-modal fusion algorithm to combine two complementary modalities in electron tomography: X-ray spectroscopy and scanning transmission electron microscopy (STEM). The former reveals compositions with high elemental specificity but low signal-to-noise ratio (SNR), while the latter characterizes the structure with high SNR but little chemical information. We use a multivariate regression to build a cross-modal fusion framework for these two modalities to simultaneously achieve high elemental specificity and high SNR for a target element chosen from the sample under study. Specifically, we first compute three-dimensional tomograms from tilt-series datasets of X-ray and STEM using different reconstruction algorithms. Then, we generate many feature images from each tomogram. Finally, we adopt partial least squares regression to assess the connection between these feature images and the reconstruction of the target element. Based on the simulated and experimental datasets of semiconductor devices, we demonstrate that our algorithm can not only produce continuous edges, homogeneous foreground, and clean background in its element-specific reconstructions but also can more accurately preserve fine structures than state-of-the-art tomography techniques. Moreover, we show that it can deliver results with high fidelity even for X-ray datasets with limited tilts or low counts. This property is highly desired in the semiconductor industry where acquisition time and sample damage are essential.

Total generalized variation regularization for multi-modal electron tomography

In multi-modal electron tomography, tilt series of several signals such as X-ray spectra, electron energy-loss spectra, annular dark-field, or bright-field data are acquired at the same time in a transmission electron microscope and subsequently reconstructed in three dimensions. However, the acquired data are often incomplete and suffer from noise, and generally each signal is reconstructed independently of all other signals, not taking advantage of correlation between different datasets. This severely limits both the resolution and validity of the reconstructed images. In this paper, we show how image quality in multi-modal electron tomography can be greatly improved by employing variational modeling and multi-channel regularization techniques. To achieve this aim, we employ a coupled Total Generalized Variation (TGV) regularization that exploits correlation between different channels. In contrast to other regularization methods, coupled TGV regularization allows to reconstruct both hard transitions and gradual changes inside each sample, and links different channels at the level of first and higher order derivatives. This favors similar interface positions for all reconstructions, thereby improving the image quality for all data, in particular, for 3D elemental maps. We demonstrate the joint multi-channel TGV reconstruction on tomographic energy-dispersive X-ray spectroscopy (EDXS) and high-angle annular dark field (HAADF) data, but the reconstruction method is generally applicable to all types of signals used in electron tomography, as well as all other types of projection-based tomographies.

Electron Tomography Reveals the Droplet Covered Surface Structure of Nanowires Grown by Aerotaxy

For the purpose of functionalizing III-V semiconductor nanowires using n-doping, Sn-doped GaAs zincblende nanowires are produced, using the growth method of Aerotaxy. The growth conditions used are such that Ga droplets, formed on the nanowire surface, increase in number and concentrations when the Sn-precursor concentration is increased. Droplet-covered wires grown with varying Sn concentrations are analyzed by transmission electron microscopy and electron tomography, which together establish the positioning of the droplets to be preferentially on {-111}B facets. These facets have the same polarity as the main wire growth direction, [-1-1-1]B. This means that the generated Ga particles can form nucleation sites for possible nanowire branch growth. The concept of azimuthal mapping is introduced as a useful tool for nanowire surface visualization and evaluation. It is demonstrated here that electron tomography is useful in revealing both the surface and internal morphologies of the nanowires, opening up for applications in the analysis of more structurally complicated systems like radially asymmetrical nanowires. The analysis also gives a further understanding of the limits of the dopants which can be used for Aerotaxy nanowires.

Visualizing Arsenate Reactions and Encapsulation in a Single Zero-Valent Iron Nanoparticle

A nanostructure-based mechanism is presented on the enrichment, separation, and immobilization of arsenic with nanoscale zero-valent iron (nZVI). The As-Fe reactions are studied with spherical aberration corrected scanning transmission electron microscopy (Cs-STEM). Near-atomic resolution (<1 nm³) electron tomography discovers a thin continuous layer (23 ± 3 Å) of elemental arsenic sandwiched between the iron oxide shell and the zerovalent iron core. This points to a unique mechanism of nanoencapsulation and proves that the outer layer, especially the Fe(0)-oxide interface, is the edge of the As-Fe reactions. Atomic-resolution imaging on the grain boundary provides strong evidence that arsenic atoms diffuse preferably along the nonequilibrium, high-energy, and defective polycrystalline grain boundary of iron oxides. Results also offer direct evidence on the surface sorption or surface complex formation of arsenate on ferric hydroxide (FeOOH). The core-shell structure and unique properties of nZVI clearly underline rapid separation, large capacity, and stability for the treatment of toxic heavy metals such as cadmium, chromium, arsenic, and uranium.

Linear chemically sensitive electron tomography using DualEELS and dictionary-based compressed sensing

We have investigated the use of DualEELS in elementally sensitive tilt series tomography in the scanning transmission electron microscope. A procedure is implemented using deconvolution to remove the effects of multiple scattering, followed by normalisation by the zero loss peak intensity. This is performed to produce a signal that is linearly dependent on the projected density of the element in each pixel. This method is compared with one that does not include deconvolution (although normalisation by the zero loss peak intensity is still performed). Additionally, we compare the 3D reconstruction using a new compressed sensing algorithm, DLET, with the well-established SIRT algorithm. VC precipitates, which are extracted from a steel on a carbon replica, are used in this study. It is found that the use of this linear signal results in a very even density throughout the precipitates. However, when deconvolution is omitted, a slight density reduction is observed in the cores of the precipitates (a so-called cupping artefact). Additionally, it is clearly demonstrated that the 3D morphology is much better reproduced using the DLET algorithm, with very little elongation in the missing wedge direction. It is therefore concluded that reliable elementally sensitive tilt tomography using EELS requires the appropriate use of DualEELS together with a suitable reconstruction algorithm, such as the compressed sensing based reconstruction algorithm used here, to make the best use of the limited data volume and signal to noise inherent in core-loss EELS.

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.

Quantitative Energy-Dispersive X-Ray Analysis of Catalyst Nanoparticles Using a Partial Cross Section Approach

The new generation of energy-dispersive X-ray (EDX) detectors with higher count rates than ever before, paves the way for a new approach to quantitative elemental analysis in the scanning transmission electron microscope. Here we demonstrate a method of calculating partial cross sections for use in quantifying EDX data, beneficial especially because of the simplicity of its implementation. Applying this approach to acid-leached PtCo catalyst nanoparticles leads to quantitative determination of the Pt surface enrichment.

Quantitative 3D analysis of huge nanoparticle assemblies

Nanoparticle assemblies can be investigated in 3 dimensions using electron tomography. However, it is not straightforward to obtain quantitative information such as the number of particles or their relative position. This becomes particularly difficult when the number of particles increases. We propose a novel approach in which prior information on the shape of the individual particles is exploited. It improves the quality of the reconstruction of these complex assemblies significantly. Moreover, this quantitative Sparse Sphere Reconstruction approach yields directly the number of particles and their position as an output of the reconstruction technique, enabling a detailed 3D analysis of assemblies with as many as 10,000 particles. The approach can also be used to reconstruct objects based on a very limited number of projections, which opens up possibilities to investigate beam sensitive assemblies where previous reconstructions with the available electron tomography techniques failed.

Unravelling structural ambiguities in lithium- and manganese-rich transition metal oxides

Although Li- and Mn-rich transition metal oxides have been extensively studied as high-capacity cathode materials for Li-ion batteries, the crystal structure of these materials in their pristine state is not yet fully understood. Here we apply complementary electron microscopy and spectroscopy techniques at multi-length scale on well-formed Li1.2(Ni0.13Mn0.54Co0.13)O2 crystals with two different morphologies as well as two commercially available materials with similar compositions, and unambiguously describe the structural make-up of these samples. Systematically observing the entire primary particles along multiple zone axes reveals that they are consistently made up of a single phase, save for rare localized defects and a thin surface layer on certain crystallographic facets. More specifically, we show the bulk of the oxides can be described as an aperiodic crystal consisting of randomly stacked domains that correspond to three variants of monoclinic structure, while the surface is composed of a Co- and/or Ni-rich spinel with antisite defects.

Electron Tomography: A Three-Dimensional Analytic Tool for Hard and Soft Materials Research

Three-dimensional (3D) structural analysis is essential to understand the relationship between the structure and function of an object. Many analytical techniques, such as X-ray diffraction, neutron spectroscopy, and electron microscopy imaging, are used to provide structural information. Transmission electron microscopy (TEM), one of the most popular analytic tools, has been widely used for structural analysis in both physical and biological sciences for many decades, in which 3D objects are projected into two-dimensional (2D) images. In many cases, 2D-projection images are insufficient to understand the relationship between the 3D structure and the function of nanoscale objects. Electron tomography (ET) is a technique that retrieves 3D structural information from a tilt series of 2D projections, and is gradually becoming a mature technology with sub-nanometer resolution. Distinct methods to overcome sample-based limitations have been separately developed in both physical and biological science, although they share some basic concepts of ET. This review discusses the common basis for 3D characterization, and specifies difficulties and solutions regarding both hard and soft materials research. It is hoped that novel solutions based on current state-of-the-art techniques for advanced applications in hybrid matter systems can be motivated.

Visualizing nanoscale 3D compositional fluctuation of lithium in advanced lithium-ion battery cathodes

The distribution of cations in Li-ion battery cathodes as a function of cycling is a pivotal characteristic of battery performance. The transition metal cation distribution has been shown to affect cathode performance; however, Li is notoriously challenging to characterize with typical imaging techniques. Here laser-assisted atom probe tomography (APT) is used to map the three-dimensional distribution of Li at a sub-nanometre spatial resolution and correlate it with the distribution of the transition metal cations (M) and the oxygen. As-fabricated layered Li_1.2Ni_0.2Mn_0.6O₂ is shown to have Li-rich Li₂MO₃ phase regions and Li-depleted Li(Ni_0.5Mn_0.5)O₂ regions. Cycled material has an overall loss of Li in addition to Ni-, Mn- and Li-rich regions. Spinel LiNi_0.5Mn_1.5O₄ is shown to have a uniform distribution of all cations. APT results were compared to energy dispersive spectroscopy mapping with a scanning transmission electron microscope to confirm the transition metal cation distribution.

It is challenging to quantitatively diagnose the lithium-ion distribution in batteries. Here, the authors use laser-assisted atom probe tomography to probe the nanoscale compositional fluctuations of lithium ions in two popular lithium-ion battery cathodes before and after electrochemical cycling.

The Dark Side of EDX Tomography: Modeling Detector Shadowing to Aid 3D Elemental Signal Analysis

A simple model is proposed to account for the loss of collected X-ray signal by the shadowing of X-ray detectors in the scanning transmission electron microscope. The model is intended to aid the analysis of three-dimensional elemental data sets acquired using energy-dispersive X-ray tomography methods where shadow-free specimen holders are unsuitable or unavailable. The model also provides a useful measure of the detection system geometry.

Segregation in bimetallic nanoparticles

Theoretical models and experimental results for segregation in bimetallic nanoparticles are discussed and compared in this perspective.

Nanoscale voxel spectroscopy by simultaneous EELS and EDS tomography

Extending the capabilities of electron tomography with advanced imaging techniques and novel data processing methods, can augment the information content in three-dimensional (3D) reconstructions from projections taken in the transmission electron microscope (TEM). In this work we present the application of simultaneous electron energy-loss spectroscopy (EELS) and energy-dispersive X-ray spectroscopy (EDS) to scanning TEM tomography. Various tools, including refined tilt alignment procedures, multivariate statistical analysis and total-variation minimization enable the 3D reconstruction of analytical tomograms, providing 3D analytical metrics of materials science samples at the nanometer scale. This includes volumetric elemental maps, and reconstructions of EDS, low-loss and core-loss EELS spectra as four-dimensional spectrum volumes containing 3D local voxel spectra. From these spectra, compositional, 3D localized elemental analysis becomes possible opening the pathway to 3D nanoscale elemental quantification.

Three-dimensional valency mapping in ceria nanocrystals

Using electron tomography combined with electron energy loss spectroscopy (EELS), we are able to map the valency of the Ce ions in CeO2-x nanocrystals in three dimensions. Our results show a clear facet-dependent reduction shell at the surface of ceria nanoparticles; {111} surface facets show a low surface reduction, whereas at {001} surface facets, the cerium ions are more likely to be reduced over a larger surface shell. Our generic tomographic technique allows a full 3D data cube to be reconstructed, containing an EELS spectrum in each voxel. This possibility enables a three-dimensional investigation of a plethora of material-specific physical properties such as valency, chemical composition, oxygen coordination, or bond lengths, triggering the synthesis of nanomaterials with improved properties.

Monitoring galvanic replacement through three-dimensional morphological and chemical mapping

Galvanic replacement reactions on metal nanoparticles are often used for the preparation of hollow nanostructures with tunable porosity and chemical composition, leading to tailored optical and catalytic properties. However, the precise interplay between the three-dimensional (3D) morphology and chemical composition of nanostructures during galvanic replacement is not always well understood as the 3D chemical imaging of nanoscale materials is still challenging. It is especially far from straightforward to obtain detailed information from the inside of hollow nanostructures using electron microscopy techniques such as SEM or TEM. We demonstrate here that a combination of state-of-the-art EDX mapping with electron tomography results in the unambiguous determination of both morphology transformation and elemental composition of nanostructures in 3D, during galvanic replacement of Ag nanocubes. This work provides direct and unambiguous experimental evidence toward understanding the galvanic replacement reaction. In addition, the powerful approach presented here can be applied to a wide range of nanoscale transformation processes, which will undoubtedly guide the development of novel nanostructures.

Correlating catalytic activity of Ag-Au nanoparticles with 3D compositional variations

Significant elemental segregation is shown to exist within individual hollow silver-gold (Ag-Au) bimetallic nanoparticles obtained from the galvanic reaction between Ag particles and AuCl4(-). Three-dimensional compositional mapping using energy dispersive X-ray (EDX) tomography within the scanning transmission electron microscope (STEM) reveals that nanoparticle surface segregation inverts from Au-rich to Ag-rich as Au content increases. Maximum Au surface coverage was observed for nanoparticles with approximately 25 atom % Au, which correlates to the optimal catalytic performance in a three-component coupling reaction among cyclohexane carboxyaldehyde, piperidine, and phenylacetylene.

In-situ TEM visualization of vacancy injection and chemical partition during oxidation of Ni-Cr nanoparticles

Oxidation of alloy often involves chemical partition and injection of vacancies. Chemical partition is the consequence of selective oxidation, while injection of vacancies is associated with the differences of diffusivity of cations and anions. It is far from clear as how the injected vacancies behave during oxidation of metal. Using in-situ transmission electron microscopy, we captured unprecedented details on the collective behavior of injected vacancies during oxidation of metal, featuring an initial multi-site oxide nucleation, vacancy supersaturation, nucleation of a single cavity, sinking of vacancies into the cavity and accelerated oxidation of the particle. High sensitive energy dispersive x-ray spectroscopy mapping reveals that Cr is preferentially oxidized even at the initial oxidation, leading to a structure that Cr oxide is sandwiched near the inner wall of the hollow particle. The work provides a general guidance on tailoring of nanostructured materials involving multi-ion exchange such as core-shell structured composite nanoparticles.