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Amorphous thin films grown by magnetron co-sputtering exhibit changes in atomic structure with varying growth and annealing temperatures. Structural variations influence the bulk properties of the films. Scanning nanodiffraction performed in a transmission electron microscope (TEM) is applied to amorphous Tb17Co83 (a-Tb-Co) films deposited over a range of temperatures to measure relative changes in medium-range ordering (MRO). These measurements reveal an increase in MRO with higher growth temperatures and a decrease in MRO with higher annealing temperatures. The trend in MRO indicates a relationship between the growth conditions and local atomic ordering. By tilting select films, the TEM measures variations in the local atomic structure as a function of orientation within the films. The findings support claims that preferential ordering along the growth direction results from temperature-mediated adatom configurations during deposition, and that oriented MRO correlates with increased structural anisotropy, explaining the strong growth-induced perpendicular magnetic anisotropy found in rare earth-transition metal films. Beyond magnetic films, we propose the tilted FEM workflow as a method of extracting anisotropic structural information in a variety of amorphous materials with directionally dependent bulk properties, such as films with inherent bonding asymmetry grown by physical vapor deposition.

Data management is a critical component of modern experimental workflows. As data generation rates increase, transferring data from acquisition servers to processing servers via conventional file-based methods is becoming increasingly impractical. The 4D Camera at the National Center for Electron Microscopy generates data at a nominal rate of 480 Gbit s-1 (87,000 frames s-1), producing a 700 GB dataset in 15 s. To address the challenges associated with storing and processing such quantities of data, we developed a streaming workflow that utilizes a high-speed network to connect the 4D Camera's data acquisition system to supercomputing nodes at the National Energy Research Scientific Computing Center, bypassing intermediate file storage entirely. In this work, we demonstrate the effectiveness of our streaming pipeline in a production setting through an hour-long experiment that generated over 10 TB of raw data, yielding high-quality datasets suitable for advanced analyses. Additionally, we compare the efficacy of this streaming workflow against the conventional file-transfer workflow by conducting a postmortem analysis on historical data from experiments performed by real users. Our findings show that the streaming workflow significantly improves data turnaround time, enables real-time decision-making, and minimizes the potential for human error by eliminating manual user interactions.

We describe the development, operation, and application of the 4D Camera-a 576 by 576 pixel active pixel sensor for scanning/transmission electron microscopy which operates at 87,000 Hz. The detector generates data at ∼480 Gbit/s which is captured by dedicated receiver computers with a parallelized software infrastructure that has been implemented to process the resulting 10-700 Gigabyte-sized raw datasets. The back illuminated detector provides the ability to detect single electron events at accelerating voltages from 30 to 300 kV. Through electron counting, the resulting sparse data sets are reduced in size by 10--300× compared to the raw data, and open-source sparsity-based processing algorithms offer rapid data analysis. The high frame rate allows for large and complex scanning diffraction experiments to be accomplished with typical scanning transmission electron microscopy scanning parameters.

Current reports of thermal expansion coefficients (TEC) of two-dimensional (2D) materials show large discrepancies that span orders of magnitude. Determining the TEC of any 2D material remains difficult due to approaches involving indirect measurement of samples that are atomically thin and optically transparent. We demonstrate a methodology to address this discrepancy and directly measure TEC of nominally monolayer epitaxial WSe2 using four-dimensional scanning transmission electron microscopy (4D-STEM). Experimentally, WSe2 from metal-organic chemical vapor deposition (MOCVD) was heated through a temperature range of 18-564 °C using a barrel-style heating sample holder to observe temperature-induced structural changes without additional alterations or destruction of the sample. By combining 4D-STEM measurements with quantitative structural analysis, the thermal expansion coefficient of nominally monolayer polycrystalline epitaxial 2D WSe2 was determined to be (3.5 ± 0.9) × 10-6 K-1 and (5.7 ± 2) × 10-5 K-1 for the in- and out-of-plane TEC, respectively, and (3.6 ± 0.2) × 10-5 K-1 for the unit cell volume TEC, in good agreement with historically determined values for bulk crystals.

We employ analytical transmission electron microscopy (TEM) to correlate the structural and chemical environment variations within a stacked epitaxial thin film of the high entropy oxide (HEO) Mg0.2Co0.2Ni0.2Cu0.2Zn0.2O (J14), with two layers grown at different substrate temperatures (500 and 200 °C) using pulsed laser deposition (PLD). Electron diffraction and atomically resolved STEM imaging reveal the difference in out-of-plane lattice parameters in the stacked thin film, which is further quantified on a larger scale using four-dimensional STEM (4D-STEM). In the layer deposited at a lower temperature, electron energy loss spectroscopy (EELS) mapping indicates drastic changes in the oxidation states and bonding environment for Co ions, and energy-dispersive X-ray spectroscopy (EDX) mapping detects more significant cation deficiency. Ab initio density functional theory (DFT) calculations validate that vacancies on the cation sublattice of J14 result in significant electronic and structural changes. The experimental and computational analyses indicate that low temperatures during film growth result in cation deficiency, an altered chemical environment, and reduced lattice parameters while maintaining a single phase. Our results demonstrate that the complex correlation of configurational entropy, kinetics, and thermodynamics can be utilized for accessing a range of metastable configurations in HEO materials without altering cation proportions, enabling further engineering of functional properties of HEO materials.

Y2TiO5 belongs to the Ln2TiO5 (Ln = lanthanide or Y) family of ceramic materials and exhibits a range of desirable material properties such as radiation tolerance, frustrated magnetism, and large dielectric constant. However, understanding the complex crystal structure of Y2TiO5 remains elusive, given that Y2TiO5 can adopt multiple polymorphs such as cubic, orthorhombic, and hexagonal phases within the lattice. In this work, we report a detailed structural analysis of Y2TiO5 using four‐dimensional scanning transmission electron microscopy coupled with unsupervised machine learning. The pyrochlore nanodomains, characterized by the ordered arrangement of yttrium cations on the A site of their A2BO5 structure, are present within the matrix of a predominantly fluorite‐structured Y2TiO5 along with a third polymorph, the hexagonal phase. The pyrochlore phase is found to form 2 nm boundary regions around hexagonal phase stacking faults, highlighting the potential influence of the hexagonal phase on the occurrence and distribution of the pyrochlore phase. Lastly, we identify a unique pyrochlore phase with asymmetric arrangement of cation ordering along a single planar direction. Our findings provide invaluable insights into the possible mechanisms stabilizing pyrochlore nanodomains within the fluorite lattice of Y2TiO5. [ABSTRACT FROM AUTHOR]

Ferroelectric hafnium zirconium oxide (HZO) holds promise for nextgeneration memory and transistors due to its superior scalability and seamless integration with complementary metal‐oxide‐semiconductor processing. A major challenge in developing this emerging ferroelectric material is the metastable nature of the non‐centrosymmetric polar phase responsible for ferroelectricity, resulting in a coexistence of both polar and non‐polar phases with uneven grain sizes and random orientations. Due to the structural similarity between the multiple phases and the nanoscale dimensions of the thin film devices, accurate measurement of phase‐specific information remains challenging. Here, the application of 4D scanning transmission electron microscopy is demonstrated with automated electron diffraction pattern indexing to analyze multiphase polycrystalline HZO thin films, enabling the characterization of crystallographic phase and orientation across large working areas on the order of hundreds of nanometers. This approach offers a powerful characterization framework to produce a quantitative and statistically robust analysis of the intricate structure of HZO films by uncovering phase composition, polarization axis alignment, and unique phase distribution within the HZO film. This study introduces a novel approach for analyzing ferroelectric HZO, facilitating reliable characterization of process‐structure‐property relationships imperative to accelerating the growth optimization, performance, and successful implementation of ferroelectric HZO in devices. [ABSTRACT FROM AUTHOR]

Scanning transmission electron microscopy is a common tool used to study the atomic structure of materials. It is an inherently multimodal tool allowing for the simultaneous acquisition of multiple information channels. Despite its versatility, however, experimental workflows currently rely heavily on experienced human operators and can only acquire data from small regions of a sample at a time. Here, we demonstrate a flexible pipeline-based system for high-throughput acquisition of atomic-resolution structural data using an all-piezo sample stage applied to large-scale imaging of nanoparticles and multimodal data acquisition. The system is available as part of the user program of the Molecular Foundry at Lawrence Berkeley National Laboratory.

In a scanning transmission electron microscope (STEM), producing a high-resolution image generally requires an electron beam focused to the smallest point possible. However, the magnetic lenses used to focus the beam are unavoidably imperfect, introducing aberrations that limit resolution. Modern STEMs overcome this by using hardware aberration correctors comprised of many multipole elements, but these devices are complex, expensive, and can be difficult to tune. We demonstrate a design for an electrostatic phase plate that can act as an aberration corrector. The corrector is comprised of annular segments, each of which is an independent two-terminal device that can apply a constant or ramped phase shift to a portion of the electron beam. We show the improvement in image resolution using an electrostatic corrector. Engineering criteria impose that much of the beam within the probe-forming aperture be blocked by support bars, leading to large probe tails for the corrected probe that sample the specimen beyond the central lobe. We also show how this device can be used to create other STEM beam profiles such as vortex beams and probes with a high degree of phase diversity, which improve information transfer in ptychographic reconstructions.

The results of a combined grazing incidence wide‐angle X‐ray scattering (GIWAXS) and 4D scanning transmission microscopy (4D‐STEM) analysis of the effects of thermal processing on poly(3[2‐(2‐methoxyethoxy)ethoxy]‐methylthiophene‐2,5‐diyl) are reported, a conjugated semiconducting polymer used as the active layer in organic electrochemical transistor devices. GIWAXS provides a measure of overall crystallinity in the film, while 4D‐STEM produces real‐space maps of the morphology and orientation of individual crystallites along with their spatial extent and distribution. The sensitivity of the 4D‐STEM detector allows for collection of electron diffraction patterns at each position in an image scan while limiting the imparted electron dose to below the damage threshold. The effects of heat treatment on the distribution and type of crystallites present in the films is determined. [ABSTRACT FROM AUTHOR]

Interfaces in energy materials and devices often involve beam‐sensitive materials such as fast ionic, soft, or liquid phases. 4D scanning transmission electron microscopy (4D‐STEM) offers insights into local lattice, strain charge, and field distributions, but faces challenges in analyzing beam‐sensitive interfaces at high spatial resolutions. Here, a 4D‐STEM compressive sensing algorithm is introduced that significantly reduces data acquisition time and electron dose. This method autonomously allocates probe positions on interfaces and reconstructs missing information from datasets acquired via dynamic sampling. This algorithm allows for the integration of various scanning schemes and electron probe conditions to optimize data integrity. Its data reconstruction employs a neural network and an autoencoder to correlate diffraction pattern features with measured properties, significantly reducing training costs. The accuracy of the reconstructed 4D‐STEM datasets is verified using a combination of explicitly and implicitly trained parameters from atomic resolution datasets. This method is broadly applicable for 4D‐STEM imaging of any local features of interest and will be available on GitHub upon publication. [ABSTRACT FROM AUTHOR]

We study the coupled charge density wave (CDW) and insulator-to-metal transitions in the 2D quantum material 1T-TaS2. By applying in situ cryogenic 4D scanning transmission electron microscopy with in situ electrical resistance measurements, we directly visualize the CDW transition and establish that the transition is mediated by basal dislocations (stacking solitons). We find that dislocations can both nucleate and pin the transition and locally alter the transition temperature Tc by nearly ~75 K. This finding was enabled by the application of unsupervised machine learning to cluster five-dimensional, terabyte scale datasets, which demonstrate a one-to-one correlation between resistance--a global property--and local CDW domain-dislocation dynamics, thereby linking the material microstructure to device properties. This work represents a major step toward defect-engineering of quantum materials, which will become increasingly important as we aim to utilize such materials in real devices. [ABSTRACT FROM AUTHOR]

Nanobeam electron diffraction can probe local structural properties of complex crystalline materials including phase, orientation, tilt, strain, and polarization. Ideally, each diffraction pattern from a projected area of a few unit cells would produce a clear Bragg diffraction pattern, where the reciprocal lattice vectors can be measured from the spacing of the diffracted spots, and the spot intensities are equal to the square of the structure factor amplitudes. However, many samples are too thick for this simple interpretation of their diffraction patterns, as multiple scattering of the electron beam can produce a highly nonlinear relationship between the spot intensities and the underlying structure. Here, we develop a stacked Bloch wave method to model the diffracted intensities from thick samples with structure that varies along the electron beam. Our method reduces the large parameter space of electron scattering to just a few structural variables per probe position, making it fast enough to apply to very large fields of view. We apply our method to SrTiO3/PbTiO3/SrTiO3 multilayer samples, and successfully disentangle specimen tilt from the mean polarization of the PbTiO3 layers. We elucidate the structure of complex vortex topologies in the PbTiO3 layers, demonstrating the promise of our method to extract material properties from thick samples.

One approach to three-dimensional structure determination using the wealth of scattering data in four-dimensional (4D) scanning transmission electron microscopy (STEM) is the parallax method proposed by Ophus et al. (2019. Advanced phase reconstruction methods enabled by 4D scanning transmission electron microscopy, Microsc Microanal25, 10-11), which determines the scattering matrix and uses it to synthesize a virtual depth-sectioning reconstruction of the sample structure. Drawing on an equivalence with a hypothetical confocal imaging mode, we derive contrast transfer and point spread functions for this parallax method applied to weakly scattering objects, showing them identical to earlier depth-sectioning STEM modes when only bright field signal is used, but that improved depth resolution is possible if dark field signal can be used. Through a simulation-based study of doped Si, we show that this depth resolution is preserved for thicker samples, explore the impact of shot noise on the parallax reconstructions, discuss challenges to making use of dark field signal, and identify cases where the interpretation of the parallax reconstruction breaks down.

A Twinning Induced Plasticity (TWIP) steel with a nominal composition of Fe-16.4Mn-0.9C-0.5Si-0.05Nb-0.05V was deformed to an engineering strain of 6%. The strain around the deformation twins were mapped using the 4D-STEM technique. Strain mapping showed a large average elastic strain of approximately 6% in the directions parallel and perpendicular to the twinning direction. However, the large average strain comprised of several hot spots of even larger strains of up to 12%. These hot spots could be attributed to a high density of sessile Frank dislocations on the twin boundary and correspond to shear stresses of 1–1.5 GPa. The strain and therefore stress fields are significantly larger than other materials known to twin and are speculated to be responsible for the early thickness saturation of TWIP steel nanotwins. The ability to keep twins extremely thin helps improve grain fragmentation, i.e. the dynamic Hall–Petch effect, and underpins the large elongations and strain hardening rates in TWIP steels.

The design and synthesis of nanocatalysts with well-defined sizes, compositions, and structures have revolutionized our accessibility to tunable catalyst activity and selectivity for a variety of energy-related electrochemical reactions. Nonetheless, establishing structure-(re)activity correlations requires the understanding of the dynamic evolution of pristine nanocatalysts and the identification of their active states under operating conditions. We previously communicated the operando observation of Cu nanocatalysts evolving into active metallic Cu nanograins for CO2 electroreduction (Yang et al. Nature 2023, 614, 262−269 ). Here, we expand our discussion to the technical capabilities and further research applications of operando electrochemical liquid-cell scanning transmission electron microscopy (EC-STEM), which enables quantitative electrochemistry while tracking dynamic structural evolution of sub-10 nm Cu nanocatalysts. The coexistent H2 bubbles, often disruptive to operando spectroscopy, are an effective approach to create a thin-liquid layer that significantly improves spatial resolution while remaining electrochemically accessible to Cu nanocatalysts. Operando four-dimensional (4D) STEM in liquids provides insights into the complex structure of active polycrystalline metallic Cu nanograins. With continuous technical developments, we anticipate that operando EC-STEM will evolve into a powerful electroanalytical method to advance our understanding of a variety of nanoscale electrocatalysts at solid/liquid interfaces.

Cellulose, being a renewable and abundant biopolymer, has garnered significant attention for its unique properties and potential applications in hybrid materials. Understanding the hierarchical arrangement of cellulose nanofibers is crucial for developing cellulose‐based materials with enhanced mechanical properties. In this study, the use of Scanning Electron Diffraction (SED) is presented to map the nanoscale orientation of cellulose fibers in a bio‐composite material with a preserved wood cell structure. The SED data provides detailed insights into the ordering of cellulose with an extraordinary resolution of ≈15 nm. It enables a quantitative analysis of the fiber orientation over regions as large as entire cells. A highly organized arrangement of cellulose fibers within the secondary cell wall is observed, with a gradient of orientations toward the outer part of the wall. The in‐plane fiber rotation is quantified, revealing a uniform orientation close to the middle lamella. Transversely sectioned material exhibits similar trends, suggesting a layered cell wall structure. Based on the SED data, a 3D model depicting the complex helical alignment of fibers throughout the cell wall is constructed. This study demonstrates the unique opportunities SED provides for characterizing the nanoscale hierarchical arrangement of cellulose nanofibers, empowering further research on a range of hybrid materials. [ABSTRACT FROM AUTHOR]

This study reveals the influence of crystal orientation on formation of growth twins in magnetron-sputtered coatings. A comparison between materials with low and high stacking fault energy (SFE) was made: CoCrFeMnNi (25 mJ/m2) and Ni (125 mJ/m2). The coatings were grown on a polycrystalline 316L stainless-steel substrate with near-random crystal texture, providing a comprehensive selection of samples on a single substrate. Electron backscatter diffraction was used to identify the film orientation, followed by transmission electron microscopy of selected regions.The presence and density of twins depended on both the material and the growth orientation. For Ni, nanotwins were observed on

Phase contrast imaging is well-suited for studying weakly scattering samples. Its strength lies in its ability to measure how the phase of the electron beam is affected by the sample, even when other imaging techniques yield low contrast. In this study, we explore via simulations two phase contrast techniques: integrated center of mass (iCOM) and ptychography, specifically using the extended ptychographical iterative engine (ePIE). We simulate the four-dimensional scanning transmission electron microscopy (4D-STEM) datasets for specific parameters corresponding to a scanning electron microscope (SEM) with an immersive objective and a given pixelated detector. The performance of these phase contrast techniques is analyzed using a contrast transfer function. Simulated datasets from a sample consisting of graphene sheets and carbon nanotubes are used for iCOM and ePIE reconstructions for two aperture sizes and two electron doses. We highlight the influence of aperture size, showing that for a smaller aperture, the radiation dose is spent mostly on larger sample features, which may aid in imaging sensitive samples while minimizing radiation damage.

Recent advancements in electron detectors and computing power have revolutionized the rapid recording of millions of 2D diffraction patterns across a grid of probe positions, known as four-dimensional scanning transmission electron microscopy (4D-STEM). These datasets serve as the foundation for innovative STEM imaging techniques like integrated center of mass (iCOM) and symmetry STEM (S-STEM). This paper delves into the application of 4D-STEM datasets for diffraction analysis. We therefore use the term scanning electron diffraction (SED) instead of 4D-STEM in this review. We comprehensively explore groundbreaking diffraction methods based on SED, structured into two main segments: (i) utilizing an atomic-scale electron probe and (ii) employing a nanoscale electron probe. Achieving an atomic-scale electron probe necessitates a significant convergence angle (α > 30 mrad), leading to interference between direct and diffracted beams, distinguishing it from its nanoscale counterpart. Additionally, integrating machine learning approaches with SED experiments holds promise in various directions, as discussed in this review. Our aim is to equip materials scientists with valuable insights for characterizing atomic structures using cutting-edge SED techniques. [ABSTRACT FROM AUTHOR]

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.

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.

Lithium iron phosphate (LixFePO4), a cathode material used in rechargeable Li-ion batteries, phase separates upon de/lithiation under equilibrium. The interfacial structure and chemistry within these cathode materials affects Li-ion transport, and therefore battery performance. Correlative imaging of LixFePO4 was performed using four-dimensional scanning transmission electron microscopy (4D-STEM), scanning transmission X-ray microscopy (STXM), and X-ray ptychography in order to analyze the local structure and chemistry of the same particle set. Over 50,000 diffraction patterns from 10 particles provided measurements of both structure and chemistry at a nanoscale spatial resolution (16.6–49.5 nm) over wide (several micron) fields-of-view with statistical robustness. LixFePO4 particles at varying stages of delithiation were measured to examine the evolution of structure and chemistry as a function of delithiation. In lithiated and delithiated particles, local variations were observed in the degree of lithiation even while local lattice structures remained comparatively constant, and calculation of linear coefficients of chemical expansion suggest pinning of the lattice structures in these populations. Partially delithiated particles displayed broadly core–shell-like structures, however, with highly variable behavior both locally and per individual particle that exhibited distinctive intermediate regions at the interface between phases, and pockets within the lithiated core that correspond to FePO4 in structure and chemistry. The results provide insight into the LixFePO4 system, subtleties in the scope and applicability of Vegard's law (linear lattice parameter-composition behavior) under local versus global measurements, and demonstrate a powerful new combination of experimental and analytical modalities for bridging the crucial gap between local and statistical characterization.

Herein, the crystallization behavior of a Li2O–Al2O3–SiO2 (LAS) glass system with the addition of ZrO2 and SnO2 as nucleating agents was investigated using X‐ray diffraction, differential scanning calorimetry, four‐dimensional scanning transmission electron microscopy, and X‐ray absorption fine‐structure measurements. At lower heat‐treatment temperatures, the addition of ZrO2 and SnO2 afforded a ZrSnO4 solid solution (SS), whereas at higher heat‐treatment temperatures, the ZrSnO4 SS decomposed, affording tetragonal ZrO2 and tetragonal SnO2. LAS‐based crystalline phases, such as β‐quartz and β‐spodumene phases SS, were formed after the formation of the ZrSnO4 SS. ZrSnO4 SS particles a few nanometers in size were present in contact with the β‐quartz SS particles a few dozen nanometers in size. This suggests that the ZrSnO4 SS served as a crystal nucleus for the β‐quartz SS, promoting its growth. [ABSTRACT FROM AUTHOR]

4D scanning transmission electron microscopy (4D‐STEM) is a powerful method for characterizing electron‐transparent samples with down to sub‐Ångstrom spatial resolution. 4D‐STEM can reveal local crystallinity, orientation, grain size, strain, and many more sample properties by rastering a convergent electron beam over a sample area and acquiring a transmission diffraction pattern (DP) at each scan position. These patterns are rich in information about the atomic structure of the probed volume, making this technique a potent tool to characterize even inhomogeneous samples. 4D‐STEM can also be used in scanning electron microscopes (SEMs) by placing an electron‐sensitive camera below the sample. 4D‐STEM‐in‐SEMs is ideally suited to characterize 2D materials and 2D‐like van der Waals heterostructures (vdWH) due to their inherent thickness of a few nanometers. The lower accelerating voltage of SEMs leads to strong scattering even from monolayers. The large field of view and down to sub‐nm spatial resolution of SEMs are ideal to map properties of the different constituents of 2D‐like vdWH by probing their combined sample volume. A unique 4D‐STEM‐in‐SEM system is applied to reveal the single crystallinity of MoS2 exfoliated with gold‐mediation as well as the crystal orientation and coverage of both components of a C60/MoS2 vdWH are determined. [ABSTRACT FROM AUTHOR]

High-throughput grain mapping with sub-nanometer spatial resolution is demonstrated using scanning nanobeam electron diffraction (also known as 4D scanning transmission electron microscopy, or 4D-STEM) combined with high-speed direct-electron detection. An electron probe size down to 0.5 nm in diameter is used and the sample investigated is a gold–palladium nanoparticle catalyst. Computational analysis of the 4D-STEM data sets is performed using a disk registration algorithm to identify the diffraction peaks followed by feature learning to map the individual grains. Two unsupervised feature learning techniques are compared: principal component analysis (PCA) and non-negative matrix factorization (NNMF). The characteristics of the PCA versus NNMF output are compared and the potential of the 4D-STEM approach for statistical analysis of grain orientations at high spatial resolution is discussed.

Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a full two-dimensional (2D) image of the diffracted electron beam at each probe position, typically a 2D grid of probe positions. These 4D-STEM datasets are rich in information, including signatures of the local structure, orientation, deformation, electromagnetic fields, and other sample-dependent properties. However, extracting this information requires complex analysis pipelines that include data wrangling, calibration, analysis, and visualization, all while maintaining robustness against imaging distortions and artifacts. In this paper, we present py4DSTEM, an analysis toolkit for measuring material properties from 4D-STEM datasets, written in the Python language and released with an open-source license. We describe the algorithmic steps for dataset calibration and various 4D-STEM property measurements in detail and present results from several experimental datasets. We also implement a simple and universal file format appropriate for electron microscopy data in py4DSTEM, which uses the open-source HDF5 standard. We hope this tool will benefit the research community and help improve the standards for data and computational methods in electron microscopy, and we invite the community to contribute to this ongoing project.

A quantitative four‐dimensional scanning transmission electron microscopy (4D‐STEM) imaging technique (q4STEM) for local thickness estimation across amorphous specimen such as obtained by focused ion beam (FIB)‐milling of lamellae for (cryo‐)TEM analysis is presented. This study is based on measuring spatially resolved diffraction patterns to obtain the angular distribution of electron scattering, or the ratio of integrated virtual dark and bright field STEM signals, and their quantitative evaluation using Monte Carlo simulations. The method is independent of signal intensity calibrations and only requires knowledge of the detector geometry, which is invariant for a given instrument. This study demonstrates that the method yields robust thickness estimates for sub‐micrometer amorphous specimen using both direct detection and light conversion 2D‐STEM detectors in a coincident FIB‐SEM and a conventional SEM. Due to its facile implementation and minimal dose reauirements, it is anticipated that this method will find applications for in situ thickness monitoring during lamella fabrication of beam‐sensitive materials. [ABSTRACT FROM AUTHOR]

The operating conditions of functional materials usually involve varying stress fields, resulting in structural changes, whether intentional or undesirable. Complex multiscale microstructures including defects, domains, and new phases, can be induced by mechanical loading in functional materials, providing fundamental insight into the deformation process of the involved materials. On the other hand, these microstructures, if induced in a controllable fashion, can be used to tune the functional properties or to enhance certain performance. In situ nanomechanical tests conducted in scanning/transmission electron microscopes (STEM/TEM) provide a critical tool for understanding the microstructural evolution in functional materials. Here, select results on a variety of functional material systems in the field are presented, with a brief introduction into some newly developed multichannel experimental capabilities to demonstrate the impact of these techniques.

Nanoscale strain mapping by four-dimensional scanning transmission electron microscopy (4D-STEM) relies on determining the precise locations of Bragg-scattered electrons in a sequence of diffraction patterns, a task which is complicated by dynamical scattering, inelastic scattering, and shot noise. These features hinder accurate automated computational detection and position measurement of the diffracted disks, limiting the precision of measurements of local deformation. Here, we investigate the use of patterned probes to improve the precision of strain mapping. We imprint a "bullseye" pattern onto the probe, by using a binary mask in the probe-forming aperture, to improve the robustness of the peak finding algorithm to intensity modulations inside the diffracted disks. We show that this imprinting leads to substantially improved strain-mapping precision at the expense of a slight decrease in spatial resolution. In experiments on an unstrained silicon reference sample, we observe an improvement in strain measurement precision from 2.7% of the reciprocal lattice vectors with standard probes to 0.3% using bullseye probes for a thin sample, and an improvement from 4.7% to 0.8% for a thick sample. We also use multislice simulations to explore how sample thickness and electron dose limit the attainable accuracy and precision for 4D-STEM strain measurements.

Recent advancements in electron detectors and computing power have revolutionized the rapid recording of millions of 2D diffraction patterns across a grid of probe positions, known as four-dimensional scanning transmission electron microscopy (4D-STEM). These datasets serve as the foundation for innovative STEM imaging techniques like integrated center of mass (iCOM) and symmetry STEM (S-STEM). This paper delves into the application of 4D-STEM datasets for diffraction analysis. We therefore use the term scanning electron diffraction (SED) instead of 4D-STEM in this review. We comprehensively explore groundbreaking diffraction methods based on SED, structured into two main segments: (i) utilizing an atomic-scale electron probe and (ii) employing a nanoscale electron probe. Achieving an atomic-scale electron probe necessitates a significant convergence angle (α > 30 mrad), leading to interference between direct and diffracted beams, distinguishing it from its nanoscale counterpart. Additionally, integrating machine learning approaches with SED experiments holds promise in various directions, as discussed in this review. Our aim is to equip materials scientists with valuable insights for characterizing atomic structures using cutting-edge SED techniques.

Large superelastic deformation in ferroelastic-ferroelectrics (FMs) is a complex phenomenon involving multiple mechanisms operating simultaneously. Understanding how these mechanisms contribute corporately is critical to apply this useful property to the intrinsically brittle FMs, which can therefore display both excellent functional and mechanical performance. Here, we have directly observed and quantitatively analyzed in situ in a transmission electron microscope the three main mechanisms of twinning domain, phase transformation and mobile point defect contributing to extremely large superelastic deformation in single-crystal BaTiO3 (5.0% strain) and Pb(Mg1/3Nb2/3)O3-PbTiO3 (10.1% strain). Our results reveal the hierarchical origin of large recoverable strain in “brittle” FMs.

Large superelastic deformation in ferroelastic-ferroelectrics (FMs) is a complex phenomenon involving multiple mechanisms operating simultaneously. Understanding how these mechanisms contribute corporately is critical to apply this useful property to the intrinsically brittle FMs, which can therefore display both excellent functional and mechanical performance. Here, we have directly observed and quantitatively analyzed in situ in a transmission electron microscope the three main mechanisms of twinning domain, phase transformation and mobile point defect contributing to extremely large superelastic deformation in single-crystal BaTiO3 (5.0% strain) and Pb(Mg1/3Nb2/3)O3-PbTiO3 (10.1% strain). Our results reveal the hierarchical origin of large recoverable strain in “brittle” FMs.

A 4-dimensional modality of a scanning transmission electron microscope (4D-STEM) acquires diffraction images formed by a coherent and focused electron beam scanning the specimen. Newly developed ultrafast detectors offer a possibility to acquire high throughput diffraction patterns at each pixel of the scan, enabling rapid tilt series acquisition for 4D-STEM tomography. Here we present a solution to the problem of synchronizing the electron probe scan with the diffraction image acquisition, and demonstrate on a fast hybrid-pixel detector camera (ARINA, DECTRIS). Image-guided tracking and autofocus corrections are handled by the freely-available microscope-control software SerialEM, in conjunction with a high angle annular dark field (HAADF) image acquired simultaneously. The open source SavvyScan system offers a versatile set of scanning patterns, operated by commercially available multi-channel acquisition and signal generator computer cards (Spectrum Instrumentation GmbH). Images are recorded only within a sub-region of the total field, so as to avoid spurious data collection during flyback and/or acceleration periods in the scan. Hence, the trigger of the fast camera follows selected pulses from the scan generator clock gated according to the chosen scan pattern. Software and protocol are provided for gating the trigger pulses via a microcontroller (ST Microelectronics ARM Cortex). We demonstrate the system on a standard replica grating and by diffraction imaging of a ferritin specimen.

For the study of magnetic materials at the nanoscale, differential phase contrast (DPC) imaging is a potent tool. With the advancements in direct detector technology, and consequent popularity gain for four-dimensional scanning transmission electron microscopy (4D-STEM), there has been an ongoing development of new and enhanced ways for STEM-DPC big data processing. Conventional algorithms are experimentally tailored, and so in this article we explore how supervised learning with convolutional neural networks (CNN) can be utilized for automated and consistent processing of STEM-DPC data. Two different approaches are investigated, one with direct tracking of the beam with regression analysis, and one where a modified U-net is used for direct beam segmentation as a pre-processing step. The CNNs are trained on experimentally obtained 4D-STEM data, enabling them to effectively handle data collected under similar instrument acquisition parameters. The model outputs are compared to conventional algorithms, particularly in how they process data in the presence of strong diffraction contrast, and how they affect domain wall profiles and width measurement. • Convolutional neural network (CNN) models presented for automated STEM-DPC processing. • CNNs trained on experimentally acquired 4D-STEM datasets. • Algorithm performance assessed on diffraction data from magnetic domain walls, and in the presence of strong diffraction contrast. • Consistent performance across data recorded from different samples given similar instrument acquisition parameters. [ABSTRACT FROM AUTHOR]