Atomic Columns Research Articles

Atomic-resolution STEM image denoising by total variation regularization.

Atomic-resolution electron microscopy imaging of solid-state material is a powerful method for structural analysis. Scanning transmission electron microscopy (STEM) is one of the actively used techniques to directly observe atoms in materials. However, some materials are easily damaged by the electron beam irradiation, and only noisy images are available when we decrease the electron dose to avoid beam damages. Therefore, a denoising process is necessary for precise structural analysis in low-dose STEM. In this study, we propose total variation (TV) denoising algorithm to remove quantum noise in an STEM image. We defined an entropy of STEM image that corresponds to the image contrast to determine a hyperparameter and we found that there is a hyperparameter that maximizes the entropy. We acquired atomic-resolution STEM image of CaF2 viewed along the [001] direction and executed TV denoising. The atomic columns of Ca and F are clearly visualized by the TV denoising, and atomic positions of Ca and F are determined with the error of ±1 pm and ±4 pm, respectively.

Direct Visualisation of the Surface Atomic Active Sites of Carbon-Supported Co3 O4 Nanocrystals via High-Resolution Phase Restoration.

The atomic arrangement of the terminating facets on spinel Co3O4 nanocrystals is strongly linked to their catalytic performance. However, the spinel crystal structure offers multiple possible surface terminations depending on the synthesis. Thus, understanding the terminating surface atomic structure is essential in developing high‐performance Co3O4 nanocrystals. In this work, we present direct atomic‐scale observation of the surface terminations of Co3O4 nanoparticles supported on hollow carbon spheres (HCSs) using exit wavefunction reconstruction from aberration‐corrected transmission electron microscopy focal‐series. The restored high‐resolution phases show distinct resolved oxygen and cobalt atomic columns. The data show that the structure of {100}, {110}, and {111} facets of spinel Co3O4 exhibit characteristic active sites for carbon monoxide (CO) adsorption, in agreement with density functional theory calculations. Of these facets, the {100} and {110} surface terminations are better suited for CO adsorption than the {111}. However, the presence of oxygen on the {111} surface termination indicates this facet also plays an essential role in CO adsorption. Our results demonstrate direct evidence of the surface termination atomic structure beyond the assumed stoichiometry of the surface.

DMPFIT: A Tool for Atomic-Scale Metrology via Nonlinear Least-Squares Fitting of Peaks in Atomic-Resolution TEM Images

Despite the wide availability and usage of Gatan’s DigitalMicrograph software in the electron microscopy community for image recording and analysis, nonlinear least-squares fitting in DigitalMicrograph is less straightforward. This work presents a ready-to-use tool, the DMPFIT software package, written in DigitalMicrograph script and C++ language, for nonlinear least-squares fitting of the intensity distribution of atomic columns in atomic-resolution transmission electron microscopy (TEM) images with a general two-dimensional (2D) Gaussian model. Applications of the DMPFIT software are demonstrated both in atomic-resolution conventional coherent TEM (CTEM) images recorded by the negative spherical aberration imaging technique and in high angle annular dark field (HAADF) scanning TEM (STEM) images. The implemented peak-finding algorithm based on the periodicity of 2D lattices enables reliable and convenient atomic-scale metrology as well as intuitive presentation of the resolved atomic structures.

High-precision atomic-scale strain mapping of nanoparticles from STEM images

Strain is a crucial factor that influences the physicochemical properties of nanoparticles. Being able to precisely measure strain is important in understanding the intrinsic mechanism of the enhanced performance of nanoparticles. Techniques that have been developed for strain analysis using scanning transmission electron microscopy (STEM) images can be categorized into diffraction-based method and imaging-based method. Here, using image simulation techniques, it is found that the measured two-dimensional (2D) displacements from annular dark field (ADF) STEM images of a nanoparticle are a good approximation to a projection of the actual three-dimensional (3D) displacements. A methodology for deformation analysis is presented which is based on the detection of atomic columns from atomic-resolution STEM images in real space. Elastic deformation parameters such as strain are usually defined on the basis of a continuum of deformation. The appropriateness of various deformation parameters for atomic-scale investigation on STEM images is explored and a method for determining these is presented. We found that the local lattice parameter and principal strain components are the most physically meaningful parameters to express the materials distortion behaviour. Apart from the local lattice parameter, the other deformation parameters such as normal strains, shear strains and displacements, heavily rely on the choice of reference lattice. It is also found that different reference grids add a series of uniform offsets to these strain variations. Finally, this approach is applied to a PtCo3 bimetallic nanoparticle to quantify its deformation behaviour.

Spatial resolution in secondary-electron microscopy.

We first review the significance of resolution and contrast in electron microscopy and the effect of the electron optics on these two quantities. We then outline the physics of the generation of secondary electrons (SEs) and their transport and emission from the surface of a specimen. Contrast and resolution are discussed for different kinds of SE imaging in scanning electron microscope (SEM) and scanning-transmission microscope instruments, with some emphasis on the observation of individual atoms and atomic columns in a thin specimen. The possibility of achieving atomic resolution from a bulk specimen at SEM energies is also considered.

Direct imaging of the disconnection climb mediated point defects absorption by a grain boundary

Grain boundaries (GBs) are considered as the effective sinks for point defects, which improve the radiation resistance of materials. However, the fundamental mechanisms of how the GBs absorb and annihilate point defects under irradiation are still not well understood at atomic scale. With the aid of the atomic resolution scanning transmission electron microscope, we experimentally investigate the atomistic mechanism of point defects absorption by a ∑31 GB in α-Al2O3 under high energy electron beam irradiation. It is shown that a disconnection pair is formed, during which all the Al atomic columns are tracked. We demonstrate that the formation of the disconnection pair is proceeded with disappearing of atomic columns in the GB core, which suggests that the GB absorbs vacancies. Such point defect absorption is attributed to the nucleation and climb motion of disconnections. These experimental results provide an atomistic understanding of how GBs improve the radiation resistance of materials.

Atomic and electronic band structures of Y-doped Al<sub>2</sub>O<sub>3</sub> grain boundaries

An Y-doped Σ7{4510}[0001] Al2O3 grain boundary was fabricated by the bicrystal method. The grain boundary segregation structure was studied using atomic-resolution scanning transmission electron microscopy and energy dispersive X-ray spectroscopy. It was found that the atomic structure of the Y-doped grain boundary differs from that of the non-doped grain boundary, indicating that Y doping induced the structural transformation from asymmetrical shape to symmetrical shape in the grain boundary core. Apart from Y, impurities of Ca were also segregated at the grain boundary. Both Y3+ and Ca2+ are segregated at the same atomic columns in the grain boundary, mainly due to their larger ionic size compared with Al3+. In addition, valence electron energy loss spectroscopy measurements indicate that the bandgap energy of the doped grain boundary is about 0.5 eV smaller than that of the pristine grain boundary.

A method for a column-by-column EELS quantification of barium lanthanum ferrate

High-resolution STEM-EELS provides information about the composition of crystalline materials at the atomic scale, though a reliable quantitative chemical analysis is often hampered by zone axis conditions, where neighbouring atomic column intensities contribute to the signal at the probe position. In this work, we present a procedure to determine the concentration of two elements within equivalent atomic columns from EELS elemental maps – in our case barium and lanthanum within the A-sites of Ba1.1La1.9Fe2O7, a second order Ruddlesden-Popper phase. We took advantage of the large changes in the elemental distribution from column to column and introduced a technique, which substitutes inelastic scattering cross sections during the quantification step by using parameters obtained from the actual experiment. We considered channelling / de-channelling effects via inelastic multislice simulations and were thereby able to count occupancies in each atomic column. The EELS quantification results were then used as prior information during the Rietveld refinement in XRD measurements in order to differentiate between barium and lanthanum.

Dynamical effects of the radiative stellar feedback on the H I-to-H2 transition

Context. The atomic-to-molecular hydrogen (H/H2) transition has been extensively studied as it controls the fraction of gas in a molecular state in an interstellar cloud. This fraction is linked to star-formation by the Schmidt–Kennicutt law. While theoretical estimates of the column density of the H I layer have been proposed for static photodissociation regions (PDRs), Herschel and well-resolved Atacama Large Millimeter Array observations have revealed dynamical effects in star forming regions, caused by the process of photoevaporation. Aims. We extend the analytic study of the H/H2 transition to include the effects of the propagation of the ionization front, in particular in the presence of photoevaporation at the walls of blister H II regions, and we find its consequences on the total atomic hydrogen column density at the surface of clouds in the presence of an ultraviolet field, and on the properties of the H/H2 transition. Methods. We solved semi-analytically the differential equation giving the H2 column density profile by taking into account H2 formation on grains, H2 photodissociation, and the ionization front propagation dynamics modeled as advection of the gas through the ionization front. Results. Taking this advection into account reduces the width of the atomic region compared to static models. The atomic region may disappear if the ionization front velocity exceeds a certain value, leading the H/H2 transition and the ionization front to merge. For both dissociated and merged configurations, we provide analytical expressions to determine the total H I column density. Our results take the metallicity into account. Finally, we compared our results to observations of PDRs illuminated by O-stars, for which we conclude that the dynamical effects are strong, especially for low-excitation PDRs.

Atomic-scale evidence of chemical short-range order in CrCoNi medium-entropy alloy

High (or medium)-entropy alloys (H/MEAs) are complex concentrated solid solutions that may develop chemical short-range order (CSRO). In this regard, CrCoNi, the prototypical face-centered-cubic MEA, has recently kindled a debate in the H/MEA community, as it is uncertain if CSRO can possibly form in such a multi-principal-element solution, where no equilibrium or metastable intermetallic compounds have ever been seen or predicted. To answer this challenging question, here we present firm experimental evidence for the CSRO from electron diffraction as well as atomic-resolution chemical mapping, under an appropriate zone axis. We also develop a methodology to reliably determine the locations of atomic columns from the line scan profiles in the chemical maps, as well as a quantitative covariance-based correlation analysis of the column chemical compositions to reveal the spatial correlations between various atomic pairs. The detailed chemical information affirms the tendency for like-pair avoidance and unlike-pair preference, specifies the preferred atomic packing and plane stacking by the three constituent species, and suggests a proposed atomic configuration that constitutes the CSRO motif. The fraction of CSRO regions is moderately lowered after either plastic deformation or high-temperature heating. A comparison is also made with previous attempts to identify CSROs in H/MEAs.

Detecting Framework Distortions Predicted by Hybrid-DFT: An Opportunity to Improve the M1 Catalyst.

Scanning transmission electron microscopy imaging of the MoVNbTe-oxide used as a catalyst for oxidative dehydrogenation and partial oxidation establishes anisotropic scattering projections of atom columns composed of Mo and V atoms which image the catalytically active S2 site and were predicted to be distorted by hybrid density functional theory calculations. These distortions of the S2 sites toward empty hexagonal channels created by the removal of [TeO]2+ entities experimentally corroborate that controlled partial occupancy of (TeO)n chains in the hexagonal channels of the MoVNbO-framework provides a means to introduce polarons and thereby increase the catalytic reactivity and selectivity of this catalyst.

Mapping the Evolution of Surface Strain in PtCo Core-Shell Catalysts By 4D-STEM

With the recent shift in attention from light-duty to heavy-duty vehicles for fuel cell research, the efficiency and durability requirements for catalyst materials have significantly increased [1]. As a result, it is more important than ever to understand the effects of degradation on catalyst nanoparticle surface structure and properties. Surface strain, for example, plays an important role in dictating the activity of catalyst nanoparticles [2], and understanding its evolution over the lifetime of a cell is therefore important. State-of-the-art PtCo core-shell catalyst nanoparticles contain complex strain gradients since, in addition to the surface strain that can occur for even single-metal nanoparticles [3], the lattice constant of the ordered PtCo core is smaller than that of the Pt shell [4]. These strain gradients may evolve over the lifetime of the cell due to cycling-induced metal dissolution, leading to compositional and shell thickness changes. Since these particles are generally <10 nm in diameter and have Pt shells only a few monolayers thick, a technique that can directly reveal their surface strain with high spatial resolution is needed to enable a better understanding of the relationship between surface strain and the performance and durability of heavy-duty fuel cells.High-resolution strain mapping can be performed by conventional high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) techniques, for example through geometric phase analysis [5] or direct tracking of atomic column positions [6,7]. These methods require the material to be tilted to a low-order zone axis for data acquisition, a very time-consuming process for randomly oriented nanoparticles that significantly limits the number of particles, and hence the statistically relevant information, that can be included in a given study [6-8]. Four-dimensional (4D)-STEM provides an alternative approach for mapping strain at high resolution by tracking diffraction disk shifts in patterns recorded in a two-dimensional STEM scan [9]. Recently, 4D-STEM was shown to offer advantages over more conventional methods for nanoparticle strain mapping, such as reduced noise and/or artifacts [10]. While initial demonstrations of off-axis 4D-STEM strain measurements have been shown [11], strain analysis based on 4D-STEM typically still requires particles to be oriented on a zone axis, which again limits the number of particles measurable for a given study. A strain mapping technique that incorporates the strengths of 4D-STEM while allowing off-axis measurements to be made would therefore significantly increase the throughput of the technique, enabling statistically relevant information about particle surface strain as a function of size, composition, or cycling history to be obtained.In this talk, we will demonstrate advancements in 4D-STEM strain mapping that allow strain to be mapped in off-axis particles, therefore enabling hundreds of catalyst nanoparticles to be measured with unit-cell spatial resolution in a single instrument session. This allows mean strain profiles to be generated for the particles as a function of distance from the surface and correlate this with particle size, composition, and cycling history. By significantly increasing the throughput of high-resolution strain mapping, this technique paves the way to a better understanding of the role strain plays in catalyst performance and degradation, accelerating development of advanced heavy-duty fuel cell catalyst materials [12].

Deep learning for mapping element distribution of high-entropy alloys in scanning transmission electron microscopy images

The latest developments of machine learning (ML) and deep learning (DL) algorithms have paved the way to effectively analyze the atomic structure of chemically-complex materials. In this work, we present a DL model built upon a fully convolutional neural network (FCN) to resolve the random elements distribution of complex PtNiPdCoFe high-entropy alloys (HEAs) represented in the scanning transmission electron microscopy (STEM) images at atomic resolution. The objective of the proposed neural network is to learn through semantic segmentation the non-linear correlations between the pixels’ intensities of STEM images and the number of atoms of different constituent elements in the atomic columns (i.e., column heights) in the HEA’s structure. We demonstrate that our DL model is capable of correctly estimating the column heights or with an error up to 1 atom for the majority of the columns in the HEA structures represented in the simulated STEM images used to train and test the network. This establishes a sufficiently high level of confidence in the estimation of the element distribution in experimental images. The predicted distributions in different STEM images of nanoparticles reveal inhomogeneous fluctuations with local aggregations in the elemental atomic fractions within the columns. The most pronounced aggregation is displayed by Pt, which is the largest and most electronegative element in the synthesized HEA material. The proposed DL method is beneficial for an in-depth characterization of the structural properties of HEAs and multielement 3D materials in general.

Modelling ADF STEM images using elliptical Gaussian peaks and its effects on the quantification of structure parameters in the presence of sample tilt

A small sample tilt away from a main zone axis orientation results in an elongation of the atomic columns in ADF STEM images. An often posed research question is therefore whether the ADF STEM image intensities of tilted nanomaterials should be quantified using a parametric imaging model consisting of elliptical rather than the currently used symmetrical peaks. To this purpose, simulated ADF STEM images corresponding to different amounts of sample tilt are studied using a parametric imaging model that consists of superimposed 2D elliptical Gaussian peaks on the one hand and symmetrical Gaussian peaks on the other hand. We investigate the quantification of structural parameters such as atomic column positions and scattering cross sections using both parametric imaging models. In this manner, we quantitatively study what can be gained from this elliptical model for quantitative ADF STEM, despite the increased parameter space and computational effort. Although a qualitative improvement can be achieved, no significant quantitative improvement in the estimated structure parameters is achieved by the elliptical model as compared to the symmetrical model. The decrease in scattering cross sections with increasing sample tilt is even identical for both types of parametric imaging models. This impedes direct comparison with zone axis image simulations. Nonetheless, we demonstrate how reliable atom-counting can still be achieved in the presence of small sample tilt.

Deep learning ferroelectric polarization distributions from STEM data via with and without atom finding

Over the last decade, scanning transmission electron microscopy (STEM) has emerged as a powerful tool for probing atomic structures of complex materials with picometer precision, opening the pathway toward exploring ferroelectric, ferroelastic, and chemical phenomena on the atomic scale. Analyses to date extracting a polarization signal from lattice coupled distortions in STEM imaging rely on discovery of atomic positions from intensity maxima/minima and subsequent calculation of polarization and other order parameter fields from the atomic displacements. Here, we explore the feasibility of polarization mapping directly from the analysis of STEM images using deep convolutional neural networks (DCNNs). In this approach, the DCNN is trained on the labeled part of the image (i.e., for human labelling), and the trained network is subsequently applied to other images. We explore the effects of the choice of the descriptors (centered on atomic columns and grid-based), the effects of observational bias, and whether the network trained on one composition can be applied to a different one. This analysis demonstrates the tremendous potential of the DCNN for the analysis of high-resolution STEM imaging and spectral data and highlights the associated limitations.

Nano-patterning on multilayer MoS2 via block copolymer lithography for highly sensitive and responsive phototransistors

Indirect bandgap of multilayer molybdenum disulfide has been recognized as a major hindrance to high responsivity of MoS2 phototransistors. Here, to overcome this fundamental limitation, we propose a structural engineering of MoS2 via nano-patterning using block copolymer lithography. The fabricated nanoporous MoS2, consisting of periodic hexagonal arrays of hexagon nanoholes, includes abundant edges having a zigzag configuration of atomic columns with molybdenum and sulfur atoms. These exposed zigzag edges are responsible for multiple trap states in the bandgap region, as confirmed by photo-excited charge-collection spectroscopy measurements on multilayer nanoporous MoS2 phototransistors, showing that in-gap states only near the valence band can result in a photogating effect. The effect of nano-patterning is therefore to significantly enhance the responsivity of multilayer nanoporous MoS2 phototransistors, exhibiting an ultra-high photoresponsivity of 622.2 A W−1. Our nano-patterning of MoS2 for photosensing application paves a route to structural engineering of two-dimensional materials for highly sensitive and responsive optoelectronic devices.

Chemical short-range order in Fe50Mn30Co10Cr10 high-entropy alloy

Chemical short-range order (CSRO) is generally possible in concentrated solid solutions and currently of considerable interest for multi-principal element alloys. However, a convincing demonstration of CSRO has been challenging and achieved thus far only for ternary medium-entropy alloys such as VCoNi. Here, we report definitive proof of CSRO in a quaternary face-centered-cubic Fe50Mn30Co10Cr10 high-entropy alloy, acquired from systematic electron microscopy experiments. The evidence includes extra diffuse disks in nano-beam electron diffraction patterns, images in state-of-the-art aberration-corrected scanning transmission electron microscope, as well as compositional profiles across neighboring atomic planes/columns in atomic-resolution chemical maps. The CSRO regions are found to occupy an areal fraction of 20% and have dimensions on a sub-nanometer scale. This length scale, as well as the diffraction features of the CSRO, are different from those of intermetallic compound precipitates; as such, the CSRO is not a growing stage of a nucleated second phase, the precipitation of which has been dealt with previously in classical alloys. We further conducted a spatial correlation analysis of the concentrations in atomic columns in the chemical map, enabling us to uncover a general tendency toward nearest-neighbor chemical ordering, specifically, preference for unlike species (such as Fe–Mn) and avoidance for like-species (such as Fe–Fe). The persistence of this trend, the same as that found in VCoNi MEA, recently, is somewhat intriguing for a high-entropy alloy in which all the constituent elements are similar in atomic size and have rather a small enthalpy of mixing.

Confined Ir single sites with triggered lattice oxygen redox: Toward boosted and sustained water oxidation catalysis

Confined Ir single sites with triggered lattice oxygen redox: Toward boosted and sustained water oxidation catalysis

Structural atomic study in platinum heterogeneous catalyst by aberration-corrected STEM

The atomic and structural analysis of platinum nanoparticles (PtNPs) heterogeneous catalysts was carried out using the scanning transmission electron microscopy with spherical aberration-corrected (Cs-STEM) technique. The corrected spherical aberration coefficients in the convergent electron beam under focus and over focus made it possible to obtain subangstrom resolution to perfectly identify positions and atomic columns in PtNPs supported on magnetite (Fe3O4). The images formed in high-angle annular dark field (HAADF), allowed to observe PtNPs < 2 nm, crystalline defects, steps, twin boundaries and disorder in the atomic columns, as well as an estimate of the number of atoms contains in a cluster of PtNPs according to our 3D simulation. Hence, the perspective of this work is to study high resolution HAADF images to extract as much information as possible according to the challenges and opportunities involved the use and development of new systems used in nano-catalysis.

Crystal structure characterization of martensite of Cu–Zn–Al ternary alloy by spherical aberration corrected scanning transmission electron microscopy

The crystal structure of martensite in Cu-27at.%Zn-9.0 at.%Al alloy has been studied by using spherical-aberration-corrected high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) and geometrical phase analysis (GPA) to examine possible changes in atomic rearrangements during martensitic transformation of this ternary system. Observation along [100]M zone axis is suitable for examining a chemical order of the martensite, and showed that, despite the non-stoichiometry of the alloy, atomic columns containing Al atoms are imaged and distinguished from the others. On the other hand, observation along [010]M zone axis directly revealed that the parent and martensitic phases possess L21 and 18R (21‾) structures, respectively. These observations suggested that the martensite retained the local chemical order of the parent phase without shuffling before and after the transformation. GPA revealed that the interface between the two phases was coherent with tilting of the basal plane approximately 6° across the boundary, which makes otherwise large inclination small during the martensitic transformation.