Four-dimensional Scanning Transmission Electron Microscopy Research Articles

In situ observation of medium range ordering and crystallization of amorphous TiO2 ultrathin films grown by atomic layer deposition

The evolution of medium range ordering (MRO) and crystallization behavior of amorphous TiO2 films grown by atomic layer deposition (ALD) were studied using in situ four-dimensional scanning transmission electron microscopy. The films remain fully amorphous when grown at 120 °C or below, but they start showing crystallization of anatase phases when grown at 140 °C or above. The degree of MRO increases as a function of temperature and maximizes at 140 °C when crystallization starts to occur, which suggests that crystallization prerequires the development of nanoscale MRO that serves as the site of nucleation. In situ annealing of amorphous TiO2 films grown at 80 °C shows enhancement of MRO but limited number of nucleation, which suggests that post-annealing develops only a small portion of MRO into crystal nuclei. The MRO regions that do not develop into crystals undergo structural relaxation instead, which provides insights into the critical size and degree of ordering and the stability of certain MRO types at different temperatures. In addition, crystallographic defects were observed within crystal phases, which likely negate corrosion resistance of the film. Our result highlights the importance of understanding and controlling MRO for optimizing ALD-grown amorphous films for next-generation functional devices and renewable energy applications.

The Effect of Dynamical Scattering on Single-plane Phase Retrieval in Electron Ptychography

Abstract Segmented and pixelated detectors on scanning transmission electron microscopes enable the complex specimen transmission function to be reconstructed. Imaging the transmission function is key to interpreting the electric and magnetic properties of the specimen, and as such four-dimensional scanning transmission electron microscopy (4D-STEM) imaging techniques are crucial for our understanding of functional materials. Many of the algorithms used in the reconstruction of the transmission function rely on the multiplicative approximation and the (weak) phase object approximation, which are not valid for many materials, particularly at high resolution. Herein, we study the breakdown of simple phase imaging in thicker samples. We demonstrate the behavior of integrated center of mass imaging, single-side band ptychography, and Wigner distribution deconvolution over a thickness series of simulated GaN 4D-STEM datasets. We further give guidance as to the optimal focal conditions for obtaining a more interpretable dataset using these algorithms.

Analysis of Interpretable Data Representations for 4D-STEM Using Unsupervised Learning.

Understanding the structure of materials is crucial for engineering devices and materials with enhanced performance. Four-dimensional scanning transmission electron microscopy (4D-STEM) is capable of mapping nanometer-scale local crystallographic structure over micron-scale field of views. However, 4D-STEM datasets can contain tens of thousands of images from a wide variety of material structures, making it difficult to automate detection and classification of structures. Traditional automated analysis pipelines for 4D-STEM focus on supervised approaches, which require prior knowledge of the material structure and cannot describe anomalous or deviant structures. In this article, a pipeline for engineering 4D-STEM feature representations for unsupervised clustering using non-negative matrix factorization (NMF) is introduced. Each feature is evaluated using NMF and results are presented for both simulated and experimental data. It is shown that some data representations more reliably identify overlapping grains. Additionally, real space refinement is applied to identify spatially distinct sample regions, allowing for size and shape analysis to be performed. This work lays the foundation for improved analysis of nanoscale structural features in materials that deviate from expected crystallographic arrangement using 4D-STEM.

Assessment of Active Dopants and p-n Junction Abruptness Using In Situ Biased 4D-STEM.

A key issue in the development of high-performance semiconductor devices is the ability to properly measure active dopants at the nanometer scale. In a p-n junction, the abruptness of the dopant profile around the metallurgical junction directly influences the electric field. Here, a contacted nominally symmetric and highly doped (NA = ND = 9 × 1018 cm-3) silicon p-n specimen is studied through in situ biased four-dimensional scanning transmission electron microscopy (4D-STEM). Measurements of electric field, built-in voltage, depletion region width, and charge density are combined with analytical equations and finite-element simulations in order to evaluate the quality of the junction interface. It is shown that all the junction parameters measured are compatible with a linearly graded junction. This hypothesis is also consistent with the evolution of the electric field with bias as well as off-axis electron holography data. These results demonstrate that in situ biased 4D-STEM can allow a better understanding of the electrostatics of semiconductor p-n junctions with nm-scale resolution.

4D-STEM Ptychography for Electron-Beam-Sensitive Materials.

Recent advances in high-speed pixelated electron detectors have substantially facilitated the implementation of four-dimensional scanning transmission electron microscopy (4D-STEM). A critical application of 4D-STEM is electron ptychography, which reveals the atomic structure of a specimen by reconstructing its transmission function from redundant convergent-beam electron diffraction patterns. Although 4D-STEM ptychography offers many advantages over conventional imaging modes, this emerging technique has not been fully applied to materials highly sensitive to electron beams. In this Outlook, we introduce the fundamentals of 4D-STEM ptychography, focusing on data collection and processing methods, and present the current applications of 4D-STEM ptychography in various materials. Next, we discuss the potential advantages of imaging electron-beam-sensitive materials using 4D-STEM ptychography and explore its feasibility by performing simulations and experiments on a zeolite material. The preliminary results demonstrate that, at the low electron dose required to preserve the zeolite structure, 4D-STEM ptychography can reliably provide higher resolution and greater tolerance to the specimen thickness and probe defocus as compared to existing imaging techniques. In the final section, we discuss the challenges and possible strategies to further reduce the electron dose for 4D-STEM ptychography. If successful, it will be a game-changer for imaging extremely sensitive materials, such as metal-organic frameworks, hybrid halide perovskites, and supramolecular crystals.

Formation and impact of nanoscopic oriented phase domains in electrochemical crystalline electrodes.

Electrochemical phase transformation in ion-insertion crystalline electrodes is accompanied by compositional and structural changes, including the microstructural development of oriented phase domains. Previous studies have identified prevailingly transformation heterogeneities associated with diffusion- or reaction-limited mechanisms. In comparison, transformation-induced domains and their microstructure resulting from the loss of symmetry elements remain unexplored, despite their general importance in alloys and ceramics. Here, we map the formation of oriented phase domains and the development of strain gradient quantitatively during the electrochemical ion-insertion process. A collocated four-dimensional scanning transmission electron microscopy and electron energy loss spectroscopy approach, coupled with data mining, enables the study. Results show that in our model system of cubic spinel MnO2 nanoparticles their phase transformation upon Mg2+ insertion leads to the formation of domains of similar chemical identity but different orientations at nanometre length scale, following the nucleation, growth and coalescence process. Electrolytes have a substantial impact on the transformation microstructure ('island' versus 'archipelago'). Further, large strain gradients build up from the development of phase domains across their boundaries with high impact on the chemical diffusion coefficient by a factor of ten or more. Our findings thus provide critical insights into the microstructure formation mechanism and its impact on the ion-insertion process, suggesting new rules of transformation structure control for energy storage materials.

A Three-Dimensional Reconstruction Algorithm for Scanning Transmission Electron Microscopy Data from a Single Sample Orientation

Abstract Increasing interest in three-dimensional nanostructures adds impetus to electron microscopy techniques capable of imaging at or below the nanoscale in three dimensions. We present a reconstruction algorithm that takes as input a focal series of four-dimensional scanning transmission electron microscopy (4D-STEM) data. We apply the approach to a lead iridate, PbIrO, and yttrium-stabilized zirconia, YZrO, heterostructure from data acquired with the specimen in a single plan-view orientation, with the epitaxial layers stacked along the beam direction. We demonstrate that Pb–Ir atomic columns are visible in the uppermost layers of the reconstructed volume. We compare this approach to the alternative techniques of depth sectioning using differential phase contrast scanning transmission electron microscopy (DPC-STEM) and multislice ptychographic reconstruction.

Large Area, High Resolution Mapping of Approximate Rotational Symmetries in a Pd77.5Cu6Si16.5 Metallic Glass Thin Film

Densely spaced four-dimensional scanning transmission electron microscopy (4D STEM) analyzed using correlation symmetry coefficients enables large area mapping of approximate rotational symmetries in amorphous materials. Here, we report the effects of Poisson noise, limited electron counts, probe coherence, reciprocal space sampling, and the probe-sample interaction volume on 4D STEM symmetry mapping experiments. These results lead to an experiment parameter envelope for high quality, high confidence 4D STEM symmetry mapping. We also establish a direct link between the symmetry coefficients and approximate rotational symmetries of nearest-neighbor atomic clusters using electron diffraction simulations from atomic models of a metallic glass. Experiments on a Pd77.5Cu6Si16.5 metallic glass thin film demonstrate the ability to image the types, sizes, volume fractions, and spatial correlations amongst local rotationally symmetry regions in the glass.

Correlative study between the local atomic and electronic structures of amorphous carbon materials via 4D-STEM and STEM-EELS

Amorphous materials have been used in a range of electronic and photonic applications, and the need for quantitative analytical techniques on their local structural information is growing. We present a comprehensive analysis of the atomic and electronic structures of an amorphous material, amorphous carbon (a-C), with scanning transmission electron microscopy (STEM)-derived techniques, four-dimensional STEM (4D-STEM), and STEM-electron energy loss spectroscopy (STEM-EELS). Each diffraction pattern of an a-C layer stack acquired via 4D-STEM is transformed into a reduced density function (RDF) and a radial variance profile (RVP) to retrieve the information on the atomic structures. Importantly, a machine-learning approach (preferably cluster analysis) separates distinct features in the EELS and RDF datasets; it also describes the spatial distributions of these features in the scanned regions. Consequently, we showed that the differences in the sp2/sp3 ratio and the involvement of additional elements led to changes in the bond length. Furthermore, we identified the dominant types of medium-range ordering structures (diamond-like or graphite-like nano-crystals) by correlations among the EELS, RDF, and RVP data. The information obtained via STEM-EELS and 4D-STEM can be strongly correlated, leading to the comprehensive characterization of the a-C layer stack for a nanometer-scale area. This process can be used to investigate any amorphous material, thereby yielding comprehensive information regarding the origins of notable properties.

Investigation of Graphite Electrode Degradation in Lithium-Ion Cells Using 4D-STEM

The development of longer lasting and faster charging lithium-ion batteries (LIBs) remains a critical engineering priority for the U.S. Department of Energy. To enable the next-generation technology, it is essential to understand the nature and extent of materials failure during battery operation. Under fast-charging conditions, it has been shown that graphite particles, which comprise the active material of the LIB anode, suffer irreversible material degradation that limits ultimate battery performance. This damage to the graphite manifests as turbostratic lattice disorder, severe morphological roughening, and anode swelling [1]. While these findings are essential to understand the nature of damage to the anode under fast-charge conditions, it remains to be seen whether such damage occurs at slower rates or is instead accelerated by extreme rate conditions and aging. In this regard, the recent advances in high-resolution electron microscopy (HREM) and four-dimensional scanning transmission electron microscopy (4D-STEM) methods provide the essential tools to enable nanoscopic quantification of battery degradation [2], [3].In this work, we use advanced analytical electron microscopy and diffraction strategies to analyze nanoscopic degradation of graphite anode material under different cycling rate and aging conditions. The results of this work will demonstrate novel strategies for identifying nanoscale structural disorder that arise in battery materials as well as provide key understanding of graphite material failure to aid in the development of high-performance anode materials. We study (in post-mortem) the graphite particle cross-sections harvested from LIBs at different aging conditions for both C/2 (i.e., 2 hours to full charge) and 6C (i.e., 10 minutes to full charge) rate. At the nano- to atomic-scale, we rely primarily on aberration-corrected STEM for imaging and diffraction acquisition for each sample (see Figure 1 for the results). High resolution imaging reveals the extent of lattice disorder and amorphous character localized at graphite pore edges. The 4D-STEM data helps to further quantify the extent and distribution of nanoscale structural disorder (including permanent strain and turbostratic disorder). The experimental methods employed to acquire the datasets and the strategies employed to interpret the data to understand the nature of the resulting damage, including recent progress into Cepstral STEM, will be discussed. Additional supporting evidences of graphite disorder from Raman spectroscopy studies and rate-dependent anode swelling from scanning electron microscopy will also be presented. References : [1] S. Pidaparthy, M.-T. F. Rodrigues, J.-M. Zuo, and D. P. Abraham, “Increased Disorder at Graphite Particle Edges Revealed by Multi-length Scale Characterization of Anodes from Fast-Charged Lithium-Ion Cells,” J. Electrochem. Soc., vol. 168, no. 10, p. 100509, 2021.[2] J.-M. Zuo et al., “Data-Driven Electron Microscopy: Electron Diffraction Imaging of Materials Structural Properties,” arXiv Prepr. arXiv2110.02070, 2021.[3] E. Padgett et al., “The exit-wave power-cepstrum transform for scanning nanobeam electron diffraction: robust strain mapping at subnanometer resolution and subpicometer precision,” Ultramicroscopy, vol. 214, p. 112994, 2020. Acknowledgements: SP acknowledges support from the U. S. Department of Energy Graduate Student Research (SCGSR) program. The SCGSR program is administered by the Oak Ridge Institute for Science and Education for the U. S. Department of Energy under contract number DE‐SC0014664. This work was carried out in part in the Materials Research Laboratory Central Research Facilities, University of Illinois. DA and MTFR acknowledge support from DOE’s Vehicle Technologies Office. This document has been created by UChicago Argonne, LLC, Operator of Argonne National Laboratory (“Argonne”). Argonne, a U.S. Department of Energy Office of Science laboratory, is operated under Contract No. DE-AC02-06CH11357. Figure 1

Uncovering material deformations via machine learning combined with four-dimensional scanning transmission electron microscopy

Understanding lattice deformations is crucial in determining the properties of nanomaterials, which can become more prominent in future applications ranging from energy harvesting to electronic devices. However, it remains challenging to reveal unexpected deformations that crucially affect material properties across a large sample area. Here, we demonstrate a rapid and semi-automated unsupervised machine learning approach to uncover lattice deformations in materials. Our method utilizes divisive hierarchical clustering to automatically unveil multi-scale deformations in the entire sample flake from the diffraction data using four-dimensional scanning transmission electron microscopy (4D-STEM). Our approach overcomes the current barriers of large 4D data analysis without a priori knowledge of the sample. Using this purely data-driven analysis, we have uncovered different types of material deformations, such as strain, lattice distortion, bending contour, etc., which can significantly impact the band structure and subsequent performance of nanomaterials-based devices. We envision that this data-driven procedure will provide insight into materials’ intrinsic structures and accelerate the discovery of materials.

Direct observation of elemental fluctuation and oxygen octahedral distortion-dependent charge distribution in high entropy oxides

The enhanced compositional flexibility to incorporate multiple-principal cations in high entropy oxides (HEOs) offers the opportunity to expand boundaries for accessible compositions and unconventional properties in oxides. Attractive functionalities have been reported in some bulk HEOs, which are attributed to the long-range compositional homogeneity, lattice distortion, and local chemical bonding characteristics in materials. However, the intricate details of local composition fluctuation, metal-oxygen bond distortion and covalency are difficult to visualize experimentally, especially on the atomic scale. Here, we study the atomic structure-chemical bonding-property correlations in a series of perovskite-HEOs utilizing the recently developed four-dimensional scanning transmission electron microscopy techniques which enables to determine the structure, chemical bonding, electric field, and charge density on the atomic scale. The existence of compositional fluctuations along with significant composition-dependent distortion of metal-oxygen bonds is observed. Consequently, distinct variations of metal-oxygen bonding covalency are shown by the real-space charge-density distribution maps with sub-ångström resolution. The observed atomic features not only provide a realistic picture of the local physico-chemistry of chemically complex HEOs but can also be directly correlated to their distinctive magneto-electronic properties.

Free, flexible and fast: Orientation mapping using the multi-core and GPU-accelerated template matching capabilities in the Python-based open source 4D-STEM analysis toolbox Pyxem

This work presents the new template matching capabilities implemented in Pyxem, an open source Python library for analyzing four-dimensional scanning transmission electron microscopy (4D-STEM) data. Template matching is a brute force approach for deriving local crystal orientations. It works by comparing a library of simulated diffraction patterns to experimental patterns collected with nano-beam and precession electron diffraction (NBED and PED). This is a computationally demanding task, therefore the implementation combines efficiency and scalability by utilizing multiple CPU cores or a graphical processing unit (GPU). The code is built on top of the scientific Python ecosystem, and is designed to support custom and reproducible workflows that combine the image processing, template library generation, indexation and visualization all in one environment. The tools are agnostic to file size and format, which is significant in light of the increased adoption of pixelated detectors from different manufacturers. This paper details the implementation and validation of the method. The method is illustrated by calculating orientation maps of nanocrystalline materials and precipitates embedded in a crystalline matrix. The combination of speed and flexibility opens the door for automated parameter studies and real-time on-line orientation mapping inside the TEM.

Mapping 1D Confined Electromagnetic Edge States in 2D Monolayer Semiconducting MoS2 Using 4D-STEM.

Four-dimensional (4D) scanning transmission electron microscopy is used to study the electric fields at the edges of 2D semiconducting monolayer MoS2. Sub-nanometer 1D features in the 2D electric field maps are observed at the outermost region along zigzag edges and also along nanowire MoS-terminated MoS2 edges. Atomic-scale oscillations are detected in the magnitude of the 1D electromagnetic edge state, with spatial variations that depend on the specific periodic edge reconstructions. Electric field reconstructions, along with integrated differential phase contrast reconstructions, reveal the presence of low Z number atoms terminating many of the uniform edges, which are difficult to detect by annular dark field scanning transmission electron microscopy due to its limited dynamic range. Density functional theory calculations support the formation of periodic 1D edge states and also show that enhancement of the electric field magnitude can occur for some edge terminations. The experimentally observed electric fields at the edges are attributed to the absence of an opposing electric field from a nearest neighbor atom when the electron beam propagates through the 2D monolayer and interacts. These results show the potential of 4D-STEM to map the atomic scale structure and fluctuations of electric fields around edge atoms with different bonding states than bulk atoms in 2D materials, beyond conventional imaging.

Investigation of wurtzite formation in MOVPE-grown zincblende GaN epilayers on AlxGa1−xN nucleation layers

The influence of AlGaN nucleation layers on zincblende GaN epilayers was studied to investigate the formation of wurtzite phase inclusions in the epilayer. GaN epilayers grown on AlGaN nucleation layers with varying aluminum contents suffer from the increasing presence of wurtzite inclusions as the aluminum content of the nucleation layer increases. High-resolution transmission electron microscopy along with four-dimensional scanning transmission electron microscopy is used to investigate the origin of the wurtzite inclusions in the nucleation layer and at the GaN/AlGaN interface. It was observed that a GaN nucleation layer and an Al0.95Ga0.05N nucleation layer grew in the zincblende and wurtzite phase, respectively. These phases were then adopted by the overgrown GaN epilayers. For a GaN epilayer on an Al0.29Ga0.71N nucleation layer, wurtzite inclusions tend to form at the GaN/ Al0.29Ga0.71N interface due to strong {111}-type faceting observed in the zincblende nucleation layer. This strong faceting is correlated with an enrichment of aluminum in the upper part of the nucleation layer, as observed in energy dispersive x-ray spectroscopy, which may influence the kinetics or thermodynamics controlling the surface morphology.

AutoDisk: Automated diffraction processing and strain mapping in 4D-STEM

Development in lattice strain mapping using four-dimensional scanning transmission electron microscopy (4D-STEM) method now offers improved precision and feasibility. However, automatic and accurate diffraction analysis is still challenging due to noise and the complexity of intensity in diffraction patterns. In this work, we demonstrate an approach, employing the blob detection on cross-correlated diffraction patterns followed by a lattice fitting algorithm, to automate the processing of four-dimensional data, including identifying and locating disks, and extracting local lattice parameters without prior knowledge about the material. The approach is both tested using simulated diffraction patterns and applied on experimental data acquired from a Pd@Pt core-shell nanoparticle. Our method shows robustness against various sample thicknesses and high noise, capability to handle complex patterns, and picometer-scale accuracy in strain measurement, making it a promising tool for high-throughput 4D-STEM data processing.

Accurate and Robust Calibration of the Uniform Affine Transformation Between Scan-Camera Coordinates for Atom-Resolved In-Focus 4D-STEM Datasets.

Accurate geometrical calibration between the scan coordinates and the camera coordinates is critical in four-dimensional scanning transmission electron microscopy (4D-STEM) for both quantitative imaging and ptychographic reconstructions. For atomic-resolved, in-focus 4D-STEM datasets, we propose a hybrid method incorporating two sub-routines, namely a J-matrix method and a Fourier method, which can calibrate the uniform affine transformation between the scan-camera coordinates using raw data, without a priori knowledge of the crystal structure of the specimen. The hybrid method is found robust against scan distortions and residual probe aberrations. It is also effective even when defects are present in the specimen, or the specimen becomes relatively thick. We will demonstrate that a successful geometrical calibration with the hybrid method will lead to a more reliable recovery of both the specimen and the electron probe in a ptychographic reconstruction. We will also show that, although the elimination of local scan position errors still requires an iterative approach, the rate of convergence can be improved, and the residual errors can be further reduced if the hybrid method can be firstly applied for initial calibration. The code is made available as a simple-to-use tool to correct affine transformations of the scan-camera coordinates in 4D-STEM experiments.

Microstructural dependence of defect formation in iron-oxide thin films

Passivating iron-oxide films are grown atop iron films simulating the corrosion process in a nuclear reactor environment. Two oxide films grown via physical vapor deposition at 600 °C and room temperature exhibited dense-epitactic and columnar-polycrystalline, microstructures respectively. A third oxide film grown in open air at 600 °C exhibited an eqiuaxed, porous morphology. Cubic maghemite and magnetite phases in each oxide film were identified via grazing incidence X-ray diffraction. Positron annihilation spectroscopy was used to characterize point defects and measure their depth and size distributions in each oxide layer and showed a range of average positron lifetimes from 0.23 ns in the high temperature, vapor deposited film, 0.35 ns in the room temperature-grown film, and 0.31 ns in the thermally grown oxide. These data indicate that the film morphology, which varies greatly in these films, leads to very different defect content. Finally, four-dimensional scanning transmission electron microscopy was used to measure the internal stress of each film and was correlated to the strain state presented in the X-ray diffraction spectra. The defect formation in each film is reasoned through using a thin film growth model.

Correlative image learning of chemo-mechanics in phase-transforming solids.

Constitutive laws underlie most physical processes in nature. However, learning such equations in heterogeneous solids (for example, due to phase separation) is challenging. One such relationship is between composition and eigenstrain, which governs the chemo-mechanical expansion in solids. Here we developed a generalizable, physically constrained image-learning framework to algorithmically learn the chemo-mechanical constitutive law at the nanoscale from correlative four-dimensional scanning transmission electron microscopy and X-ray spectro-ptychography images. We demonstrated this approach on LiXFePO4, a technologically relevant battery positive electrode material. We uncovered the functional form of the composition-eigenstrain relation in this two-phase binary solid across the entire composition range (0 ≤ X ≤ 1), including inside the thermodynamically unstable miscibility gap. The learned relation directly validates Vegard's law of linear response at the nanoscale. Our physics-constrained data-driven approach directly visualizes the residual strain field (by removing the compositional and coherency strain), which is otherwise impossible to quantify. Heterogeneities in the residual strain arise from misfit dislocations and were independently verified by X-ray diffraction line profile analysis. Our work provides the means to simultaneously quantify chemical expansion, coherency strain and dislocations in battery electrodes, which has implications on rate capabilities and lifetime. Broadly, this work also highlights the potential of integrating correlative microscopy and image learning for extracting material properties and physics.

Visualizing Grain Statistics in MOCVD WSe2 through Four-Dimensional Scanning Transmission Electron Microscopy.

Using four-dimensional scanning transmission electron microscopy, we demonstrate a method to visualize grains and grain boundaries in WSe2 grown by metal organic chemical vapor deposition (MOCVD) directly onto silicon dioxide. Despite the chemical purity and uniform thickness and texture of the MOCVD-grown WSe2, we observe a high density of small grains that corresponds with the overall selenium deficiency we measure through ion beam analysis. Moreover, reconstruction of grain information permits the creation of orientation maps that demonstrate the nucleation mechanism for new layers-triangular domains with the same orientation as the layer underneath induces a tensile strain increasing the lattice parameter at these sites.