Influence of distortions of recorded diffraction patterns on strain analysis by nano-beam electron diffraction

In Situ Transmission Electron Microscopy Methods for Lithium-Ion Batteries

In situ Transmission Electron Microscopy (TEM) stands as an invaluable instrument for the real-time examination of the structural changes in materials. It features ultrahigh spatial resolution and powerful analytical capability, making it significantly versatile across diverse fields. Particularly in the realm of Lithium-Ion Batteries (LIBs), in situ TEM is extensively utilized for real-time analysis of phase transitions, degradation mechanisms, and the lithiation process during charging and discharging. This review aims to provide an overview of the latest advancements in in situ TEM applications for LIBs. Additionally, it compares the suitability and effectiveness of two techniques: the open cell technique and the liquid cell technique. The technical aspects of both the open cell and liquid cell techniques are introduced, followed by a comparison of their applications in cathodes, anodes, solid electrolyte interphase (SEI) formation, and lithium dendrite growth in LIBs. Lastly, the review concludes by stimulating discussions on possible future research trajectories that hold potential to expedite the progression of battery technology.

Acquisition and evaluation procedure to improve the accuracy of SAED

The achievement of this work is that fine tuning of experimental and evaluation parameters can improve the absolute accuracy and reproducibility of selected area electron diffraction (SAED) to 0.1% without using internal standard. Due to the proposed procedure it was possible to reach a reproducibility better than 0.03% for camera length between sessions by careful control of specimen height and illumination conditions by monitoring lens currents. We applied a calibration specimen composed of nanocrystalline grains free of texture and providing narrow diffraction rings. Refinements of the centre of the diffraction pattern and corrections for elliptic ring distortions allowed for determining the ring diameters with an accuracy of 0.1%. We analyze the effect of different error sources and reason the achieved absolute accuracy of the measurement. Application of the proposed evaluation procedure is inevitable in case of multicomponent nanocomposites or textured materials and/or having close diffraction rings where application of automated procedures is limited. The achieved accuracy of 0.1% without internal standard is approaching that of routine laboratory XRD, and reduction of instrumental broadening due to the elaborated evaluation procedure allows for separation of close reflections, provides more reliable ring width and thus improved input parameters for further nanostructure analysis as demonstrated on dental enamel bioapatite.

Accurate lattice parameters from 3D electron diffraction data. I. Optical distortions

Determination of lattice parameters from 3D electron diffraction (3D ED) data measured in a transmission electron microscope is hampered by a number of effects that seriously limit the achievable accuracy. The distortion of the diffraction patterns by the optical elements of the microscope is often the most severe problem. A thorough analysis of a number of experimental datasets shows that, in addition to the well known distortions, namely barrel-pincushion, spiral and elliptical, an additional distortion, dubbed parabolic, may be observed in the data. In precession electron diffraction data, the parabolic distortion leads to excitation-error-dependent shift and splitting of reflections. All distortions except for the elliptical distortion can be determined together with lattice parameters from a single 3D ED data set. However, the parameters of the elliptical distortion cannot be determined uniquely due to correlations with the lattice parameters. They can be determined and corrected either by making use of the known Laue class of the crystal or by combining data from two or more crystals. The 3D ED data can yield lattice parameter ratios with an accuracy of about 0.1% and angles with an accuracy better than 0.03°.

py4DSTEM: A Software Package for Four-Dimensional Scanning Transmission Electron Microscopy Data Analysis

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.

Unravelling stacking order in epitaxial bilayer MX2 using 4D-STEM with unsupervised learning

Following an extensive investigation of various monolayer transition metal dichalcogenides (MX₂), research interest has expanded to include multilayer systems. In bilayer MX₂, the stacking order strongly impacts the local band structure as it dictates the local confinement and symmetry. Determination of stacking order in multilayer MX₂ domains usually relies on prior knowledge of in-plane orientations of constituent layers. This is only feasible in case of growth resulting in well-defined triangular domains and not useful in-case of closed layers with hexagonal or irregularly shaped islands. Stacking order can be discerned in the reciprocal space by measuring changes in diffraction peak intensities. Advances in detector technology allow fast acquisition of high-quality four-dimensional datasets which can later be processed to extract useful information such as thickness, orientation, twist and strain. Here, we use 4D scanning transmission electron microscopy combined with multislice diffraction simulations to unravel stacking order in epitaxially grown bilayer MoS₂. Machine learning based data segmentation is employed to obtain useful statistics on grain orientation of monolayer and stacking in bilayer MoS₂.

Expanding the Dimensions of a Small, Two-Dimensional Diffraction Detector

We report an approach to expand the effective number of pixels available to small, two-dimensional electron detectors. To do so, we acquire subsections of a diffraction pattern that are then accurately stitched together in post-processing. Using an electron microscopy pixel array detector (EMPAD) that has only 128 × 128 pixels, we show that the field of view can be expanded while achieving high reciprocal-space sampling. Further, we highlight the need to properly account for the detector position (rotation) and the non-orthonormal diffraction shift axes to achieve an accurate reconstruction. Applying the method, we provide examples of spot and convergent beam diffraction patterns acquired with a pixelated detector.

Fast Pixelated Detectors in Scanning Transmission Electron Microscopy. Part II: Post-Acquisition Data Processing, Visualization, and Structural Characterization

Fast pixelated detectors incorporating direct electron detection (DED) technology are increasingly being regarded as universal detectors for scanning transmission electron microscopy (STEM), capable of imaging under multiple modes of operation. However, several issues remain around the post-acquisition processing and visualization of the often very large multidimensional STEM datasets produced by them. We discuss these issues and present open source software libraries to enable efficient processing and visualization of such datasets. Throughout, we provide examples of the analysis methodologies presented, utilizing data from a 256 × 256 pixel Medipix3 hybrid DED detector, with a particular focus on the STEM characterization of the structural properties of materials. These include the techniques of virtual detector imaging; higher-order Laue zone analysis; nanobeam electron diffraction; and scanning precession electron diffraction. In the latter, we demonstrate a nanoscale lattice parameter mapping with a fractional precision ≤6 × 10−4 (0.06%).

Fast Pixelated Detectors in Scanning Transmission Electron Microscopy. Part I: Data Acquisition, Live Processing, and Storage

The use of fast pixelated detectors and direct electron detection technology is revolutionizing many aspects of scanning transmission electron microscopy (STEM). The widespread adoption of these new technologies is impeded by the technical challenges associated with them. These include issues related to hardware control, and the acquisition, real-time processing and visualization, and storage of data from such detectors. We discuss these problems and present software solutions for them, with a view to making the benefits of new detectors in the context of STEM more accessible. Throughout, we provide examples of the application of the technologies presented, using data from a Medipix3 direct electron detector. Most of our software are available under an open source licence, permitting transparency of the implemented algorithms, and allowing the community to freely use and further improve upon them.

Recent Progress of In Situ Transmission Electron Microscopy for Energy Materials

In situ transmission electron microscopy (TEM) is one of the most powerful approaches for revealing physical and chemical process dynamics at atomic resolutions. The most recent developments for in situ TEM techniques are summarized; in particular, how they enable visualization of various events, measure properties, and solve problems in the field of energy by revealing detailed mechanisms at the nanoscale. Related applications include rechargeable batteries such as Li-ion, Na-ion, Li-O₂ , Na-O₂ , Li-S, etc., fuel cells, thermoelectrics, photovoltaics, and photocatalysis. To promote various applications, the methods of introducing the in situ stimuli of heating, cooling, electrical biasing, light illumination, and liquid and gas environments are discussed. The progress of recent in situ TEM in energy applications should inspire future research on new energy materials in diverse energy-related areas.

Four-Dimensional Scanning Transmission Electron Microscopy (4D-STEM): From Scanning Nanodiffraction to Ptychography and Beyond

Scanning transmission electron microscopy (STEM) is widely used for imaging, diffraction, and spectroscopy of materials down to atomic resolution. Recent advances in detector technology and computational methods have enabled many experiments that record a full image of the STEM probe for many probe positions, either in diffraction space or real space. In this paper, we review the use of these four-dimensional STEM experiments for virtual diffraction imaging, phase, orientation and strain mapping, measurements of medium-range order, thickness and tilt of samples, and phase contrast imaging methods, including differential phase contrast, ptychography, and others.