Improved ACOM pattern matching in 4D-STEM through adaptive sub-pixel peak detection and image reconstruction.

The technique known as 4D-STEM has recently emerged as a powerful tool for the local characterization of crystalline structures in materials, such as cathode materials for Li-ion batteries or perovskite materials for photovoltaics. However, the use of new detectors optimized for electron diffraction patterns and other advanced techniques requires constant adaptation of methodologies to address the challenges associated with crystalline materials. In this study, we present a novel image-processing method to improve pattern matching in the determination of crystalline orientations and phases. Our approach uses sub-pixel adaptive image processing to register and reconstruct electron diffraction signals in large 4D-STEM datasets. By using adaptive prominence and linear filters, we can improve the quality of the diffraction pattern registration. The resulting data compression rate of 103 is well-suited for the era of big data and provides a significant enhancement in the performance of the entire ACOM data processing method. Our approach is evaluated using dedicated metrics, which demonstrate a high improvement in phase recognition. Several features are extracted from the registered data to map properties such as the spot count, and various virtual dark fields, which are used to enhance the handling of the results maps. Our results demonstrate that this data preparation method not only enhances the quality of the resulting image but also boosts the confidence level in the analysis of the outcomes related to determining crystal orientation and phase. Additionally, it mitigates the impact of user bias that may occur during the application of the method through the manipulation of parameters.

Reconstructing dual-phase nanometer scale grains within a pearlitic steel tip in 3D through 4D-scanning precession electron diffraction tomography and automated crystal orientation mapping.

The properties of polycrystalline materials are related to their microstructures and hence a complete description, including size, shape, and orientation of the grains, is necessary to understand the behavior of materials. Here, we use Scanning Precession Electron Diffraction (SPED) in the Transmission Electron Microscope (TEM) combined with a tilt series to reconstruct individual grains in 3D within a polycrystalline dual-phase cold wire-drawn pearlitic steel sample. Nanoscale ferrite grains and intragranular cementite particles were indexed using an Automated Crystallographic Orientation Mapping (ACOM) tool for each tilt dataset. The grain orientations were tracked through the tilt datasets and projections of the individual grains were reconstructed from the diffraction data using an orientation-specific Virtual Dark Field (VDF) approach for tomographic reconstruction. The algorithms used to process and reconstruct such datasets are presented. These algorithms represent an extension to the ACOM approach that may be straightforwardly applied to other multi-phase polycrystalline materials to enable 3D spatial and orientation reconstructions.

Novel TEM Microscopy and Electron Diffraction Techniques to Characterize Cultural Heritage Materials: From Ancient Greek Artefacts to Maya Mural Paintings.

To understand in-depth material properties, manufacturing, and conservation in cultural heritage artefacts, there is a strong need for advanced characterization tools that enable analysis down to the nanometric scale. Transmission electron microscopy (TEM) and electron diffraction (ED) techniques, like 3D precession electron diffraction tomography and ASTAR phase/orientation mapping, are proposed to study cultural heritage materials at nanoscale. In this work, we show how electron crystallography in TEM helps to determine precise structural information and phase/orientation distribution of various pigments in cultural heritage materials from various historical periods like Greek amphorisks, Roman glass tesserae, and pre-Hispanic Maya mural paintings. Such TEM-based methods can be an alternative to synchrotron techniques and can allow distinguishing accurately different crystalline phases even in cases of identical or very close chemical compositions at the nanometric scale.

Identifying and mapping the polytypes and orientation relationships in ZnO/CdSe core-shell nanowire arrays.

Identifying and mapping the crystalline phases and orientation relationships on the local scale in core-shell ZnO nanowire heterostructures are of primary importance to improve the interface quality, which governs the performances of the nanoscale devices. However, this represents a major difficulty, especially when the expected polytypes exhibit very similar properties as in the case of CdSe. In the present work, we address that issue in ZnO nanowire heterostructures involving a uniform and highly conformal CdSe shell grown by molecular beam epitaxy. It is shown by x-ray diffraction and Raman spectroscopy through the occurrence of the (101̄0) and (101̄1) diffraction peaks and of the [Formula: see text] mode at 34 cm-1, respectively, that the CdSe shell is mostly crystallized into the wurtzite phase. By using automated crystal phase and orientation mapping with precession (ASTAR) in a transmission electron microscope and thus by benefiting from highly precise electron diffraction patterns, the CdSe shell is found to crystallize also into the minority zinc blende phase. The wurtzite CdSe shell is epitaxially grown on the top of ZnO nanowires, and some specific orientation relationships are mapped and revealed when grown on their vertical sidewalls. Zinc blende CdSe domains are also formed exclusively in the center of wurtzite CdSe grains located on the vertical sidewalls; both wurtzite and zinc blende CdSe crystalline phases have a strong orientation relationship. These findings reveal that ASTAR is a powerful technique to elucidate the structural properties on the local scale and to gain a deeper insight into their crystalline phases and orientation relationships, which is highly promising for many types of semiconducting nanowire heterostructures.

Highlighting material structure with transmission electron diffraction correlation coefficient maps.

Correlation coefficient maps are constructed by computing the differences between neighboring diffraction patterns collected in a transmission electron microscope in scanning mode. The maps are shown to highlight material structural features like grain boundaries, second phase particles or dislocations. The inclination of the inner crystal interfaces are directly deduced from the resulting contrast.

A Tool for Local Thickness Determination and Grain Boundary Characterization by CTEM and HRTEM Techniques.

A new approach for measurement of local thickness and characterization of grain boundaries is presented. The method is embodied in a software tool that helps to find and set sample orientations useful for high-resolution transmission electron microscopic (HRTEM) examination of grain boundaries in polycrystalline thin films. The novelty is the simultaneous treatment of the two neighboring grains and orienting both grains and the boundary plane simultaneously. The same metric matrix-based formalism is used for all crystal systems. Input into the software tool includes orientation data for the grains in question, which is determined automatically for a large number of grains by the commercial ASTAR program. Grain boundaries suitable for HRTEM examination are automatically identified by our software tool. Individual boundaries are selected manually for detailed HRTEM examination from the automatically identified set. Goniometer settings needed to observe the selected boundary in HRTEM are advised by the software. Operation is demonstrated on examples from cubic and hexagonal crystal systems.