Real-time 3D analysis during electron tomography using tomviz

Unraveling Impurity-Dependent Morphological and Chemical Evolution of Ni-20Cr Alloy in Eutectic LiCl-KCl Molten Salt

Understanding the interfacial evolution of alloys in molten salt with different amounts of water (H2O) and oxygen (O2) impurities is significant for applications in many fields, including concentrated solar power, molten salt reactors, and applications in pyrochemical reprocessing and electrorefining. Additionally, the impurity-driven corrosion mechanisms that lead to various morphological and chemical evolution characteristics at the interfaces of structural alloys and molten salts are not fully understood. In the present work, the three-dimensional (3D) morphological evolution of Ni-20Cr microwires in LiCl-KCl was studied at 500 °C under different moisture and oxygen conditions using in situ synchrotron transmission X-ray microscopy (TXM) and scanning transmission electron microscopy (STEM) techniques. No significant morphological changes were observed in Ni-20Cr microwires under vacuum conditions. However, the wires exhibited distinct morphological evolutions when exposed to molten salt containing H2O alone, as well as when both H2O and O2 were present. Furthermore, Cr2O3 precipitates were observed in the molten salt during corrosion with only H2O present, while Cr6+ species were identified in the salt when O2 was added. These findings are crucial for understanding the corrosion mechanisms of molten salt with different amounts of H2O and O2 contamination, providing insights for developing corrosion mitigation methods and improving the stability of containment alloys in molten salt applications.

Correlating Grain Boundary Character and Composition in 3-Dimensions Using 4D-Scanning Precession Electron Diffraction and Atom Probe Tomography

Grain boundaries (GBs) are dominant imperfections in nanocrystalline materials that form a complex 3D network. Solute segregation to GBs is strongly coupled to the GB character, which governs the stability and macroscopic properties of nanostructured materials. Here, a 3D transmission electron microscopy and atom probe tomography (APT) correlation framework are developed to retrieve the GB character and composition at the highest spatial resolution and chemical sensitivity by correlating 4D scanning precession electron diffraction tomography (4D-SPEDT) and APT on the same sample. The 3D GB habit plane network and explore the preferential segregation of Cu and Si in a nanocrystalline Ni-W alloy is obtained. The correlation of structural and compositional information reveals that Cu segregates predominantly along high-angle GBs and incoherent twin boundaries, whereas Si segregation to low-angle and incommensurate GBs is observed. The novel full 3D correlative approach employed in this work opens up new possibilities to explore the 3D crystallographic and compositional nature of nanomaterials. This lays the foundation for both probing the true 3D structure-chemistry at the sub-nanometer scale and, consequentially, tailoring the macroscopic properties of advanced nanomaterials.

Quantifying elemental colocation in nanostructured materials using energy-dispersive X-ray spectroscopy

Multicomponent nanostructured materials are key amongst others for energy and catalysis applications. The nanoscale proximity of different metals critically determines the performance of these functional materials. However, it is difficult to study the spatial distribution of different elements at the nanoscale, especially achieving a statistically relevant assessment. Additionally, common support materials like metal oxides are sensitive to electron beam damage when using high resolution local techniques, such as transmission electron microscopy. We present a robust strategy to quantitatively assess elemental distributions in 3D nanostructured beam-sensitive samples. Key elements are resin embedding, and elemental co-localisation building on a combination of electron tomography and energy-dispersive X-ray spectroscopy. We showcase the methodology with ∼ 3 nm Pd-Ni nanoparticles supported on mesoporous silica. Epoxy resin-embedding ensured sufficient sample stability under the electron beam for tomography-based quantification of different mano- and mesoscale elemental distributions in these samples. Reliable co-location results were obtained and practical guidelines are provided for acquisition and post-processing, relevant for elemental overlap analysis in multi-metallic samples.

Native state structural and chemical characterisation of Pickering emulsions: A cryo-electron microscopy study

Transmission electron microscopy can be used for the characterisation of a wide range of thin specimens, but soft matter and aqueous samples such as gels, nanoparticle dispersions, and emulsions will dry out and collapse under the microscope vacuum, therefore losing information on their native state and ultimately limiting the understanding of the sample. This study examines commonly used techniques in transmission electron microscopy when applied to the characterisation of cryogenically frozen Pickering emulsion samples. Oil-in-water Pickering emulsions stabilised by 3 to 5 nm platinum nanoparticles were cryogenically frozen by plunge-freezing into liquid ethane to retain the native structure of the system without inducing crystallisation of the droplet oil cores. A comparison between the droplet morphology following different sample preparation methods has confirmed the effectiveness of using plunge-freezing to prepare these samples. Scanning transmission electron microscopy imaging showed that dry droplets collapse under the microscope vacuum, changing their shape and size (average apparent diameter: ∼342 nm) compared to frozen samples (average diameter: ∼183 nm). Cryogenic electron tomography was used to collect additional information of the 3D shape and size of the emulsion droplets, and the position of the stabilising nanoparticles relative to the droplet surface. Cryogenic energy dispersive X-ray and electron energy loss spectroscopy were used to successfully obtain elemental data and generate elemental maps to identify the stabilising nanoparticles and the oil phase. Elemental maps generated from spectral data were used in conjunction with electron tomography to obtain 3D information of the oil phase in the emulsion droplets. Beam-induced damage to the ice was the largest limiting factor to the sample characterisation, limiting the effective imaging resolution and signal-to-noise ratio, though careful consideration of the imaging parameters used allowed for the characterisation of the samples presented in this study. Ultimately this study shows that cryo-methods are effective for the representative characterisation of Pickering emulsions.

Scalable fabrication of Chip-integrated 3D-nanostructured electronic devices via DNA-programmable assembly

DNA-based self-assembly methods have demonstrated powerful and unique capabilities to encode nanomaterial structures through the prescribed placement of inorganic and biological nanocomponents. However, the challenge of selectively growing DNA superlattices on specific locations of surfaces and their integration with conventional nanofabrication has hindered the fabrication of three-dimensional (3D) DNA-assembled functional devices. Here, we present a scalable nanofabrication technique that combines bottom-up and top-down approaches for selective growth of 3D DNA superlattices on gold microarrays. This approach allows for the fabrication of self-assembled 3D-nanostructured electronic devices. DNA strands are bound onto the gold arrays, which anchor DNA origami frames and promote ordered framework growth on the specific areas of the surface, enabling control of the lateral placement and orientation of superlattices. DNA frameworks selectively grown on the pads are subsequently templated to nanoscale silica and tin oxide (SnOx) that follow the architecture, as confirmed by structural and chemical characterizations. The fabricated SnOx superlattices are integrated into devices that demonstrate photocurrent response.

ETSpy: A HyperSpy extension package for electron tomography data processing and reconstruction

Electron tomography is a powerful tool for the three-dimensional characterization of materials at the nano- and atomic-scales. A typical workflow for tomography involves several pre-processing steps that may include spatial binning, image registration, and tilt-axis alignment depending upon the nature of the acquired data. Here we describe the capabilities of a new, open-source software package named ETSpy that builds upon the widely used HyperSpy package. The basic usage of the software and some specific applications are presented.

Characterization of a mock up nuclear waste package using energy resolved MeV neutron analysis

Reliable radiographic methods for characterizing nuclear waste packages non-destructively (without the need to open containers) have the potential to significantly contribute to safe handling and future disposal options, particularly for legacy waste of unknown content. Due to required shielding of waste containers and the need to characterize materials consisting of light elements, X-ray methods are not suitable. Here, energy-resolved MeV neutron radiography is demonstrated as a first-of-its-kind application for non-destructive and remote examination of mock up nuclear waste packages from a safe position using time-of-flight techniques enabled by a novel event-mode imaging detector system. Energy-resolved neutron transmission spectra were measured spatially, permitting the detection of analogue materials to actual nuclear waste such as water, melamine, and ion exchange resin within a 2.54 cm wall thickness steel pipe. The results demonstrate the capability to locate the materials through this wall thickness by radiography and tomographic reconstruction, revealing detailed 3D distributions and structural anomalies. The method effectively detects residual water in ion exchange resin, highlighting its sensitivity to moisture content, a crucial parameter for nuclear waste characterization. Monte Carlo simulations are in agreement with the experimental findings, providing a pathway to simulate waste forms more difficult to tackle experimentally. This work paves the way to apply sub-nanosecond intense MeV neutron sources, such as laser-driven neutron sources under development, to nuclear waste characterization.

532- and 52-symmetric Au helicoids synthesized through controlled seed twinning and aspect ratio

Chiral plasmonic crystals with 5-fold symmetries were synthesized from Au icosahedra, decahedra, and pentatwinned nanorods, unraveling the effects of seed twinning and aspect ratio on chiral overgrowth directed by L-glutathione. The influence of seed size on the overgrowth from pentatwinned nanorods was also studied, giving insight into the role volumetric strain plays in chiral crystal formation. Single particle reconstructions were obtained using electron tomography, and optical simulations on the measured structures verify their optical chirality.

TomoPyUI: a user-friendly tool for rapid tomography alignment and reconstruction

The management and processing of synchrotron and neutron computed tomography data can be a complex, labor-intensive and unstructured process. Users devote substantial time to both manually processing their data (i.e. organizing data/metadata, applying image filters etc.) and waiting for the computation of iterative alignment and reconstruction algorithms to finish. In this work, we present a solution to these problems: TomoPyUI, a user interface for the well known tomography data processing package TomoPy. This highly visual Python software package guides the user through the tomography processing pipeline from data import, preprocessing, alignment and finally to 3D volume reconstruction. The TomoPyUI systematic intermediate data and metadata storage system improves organization, and the inspection and manipulation tools (built within the application) help to avoid interrupted workflows. Notably, TomoPyUI operates entirely within a Jupyter environment. Herein, we provide a summary of these key features of TomoPyUI, along with an overview of the tomography processing pipeline, a discussion of the landscape of existing tomography processing software and the purpose of TomoPyUI, and a demonstration of its capabilities for real tomography data collected at SSRL beamline 6-2c.

Microscopic insights into metal diffusion and ohmic contact formation in delta-doped GaAs/(Al,Ga)As core/shell nanowires

Semiconductor nanowires (NWs) are promising candidates for use in electronic and optoelectronic applications, offering numerous advantages over their thin film counterparts. Their performance relies heavily on the quality of the contacts to the NW, which should exhibit ohmic behavior with low resistance and should be formed in a reproducible manner. In the case of heterostructure NWs for high-mobility applications that host a two-dimensional electron gas, ohmic contacts are particularly challenging to implement since the NW core constituting the conduction channel is away from the NW surface. We investigated contact formation to modulation-doped GaAs/(Al,Ga)As core/shell NWs using scanning transmission electron microscopy, energy dispersive x-ray spectroscopy and electron tomography to correlate microstructure, diffusion profile and chemical composition of the NW contact region with the current-voltage (I-V) characteristics of the contacted NWs. Our results illustrate how diffusion, alloying and phase formation processes essential to the effective formation of ohmic contacts are more intricate than in planar layers, leading to reproducibility challenges even when the processing conditions are the same. We demonstrate that the NW geometry plays a crucial role in the creation of good contacts. Both ohmic and rectifying contacts were obtained under nominally identical processing conditions. Furthermore, the presence of Ge in the NW core, in the absence of Au and Ni, was found as the key factor leading to ohmic contacts. The analysis contributes to the current understanding of ohmic contact formation to heterostructure core/shell NWs offering pathways to enhance the reproducibility and further optimization of such NW contacts.

Imaging 3D chemistry at 1 nm resolution with fused multi-modal electron tomography

Measuring the three-dimensional (3D) distribution of chemistry in nanoscale matter is a longstanding challenge for metrological science. The inelastic scattering events required for 3D chemical imaging are too rare, requiring high beam exposure that destroys the specimen before an experiment is completed. Even larger doses are required to achieve high resolution. Thus, chemical mapping in 3D has been unachievable except at lower resolution with the most radiation-hard materials. Here, high-resolution 3D chemical imaging is achieved near or below one-nanometer resolution in an Au-Fe3O4 metamaterial within an organic ligand matrix, Co3O4-Mn3O4 core-shell nanocrystals, and ZnS-Cu0.64S0.36 nanomaterial using fused multi-modal electron tomography. Multi-modal data fusion enables high-resolution chemical tomography often with 99% less dose by linking information encoded within both elastic (HAADF) and inelastic (EDX/EELS) signals. We thus demonstrate that sub-nanometer 3D resolution of chemistry is measurable for a broad class of geometrically and compositionally complex materials.

Blik is an extensible 3D visualisation tool for the annotation and analysis of cryo-electron tomography data

Powerful, workflow-agnostic and interactive visualisation is essential for the ad hoc, human-in-the-loop workflows typical of cryo-electron tomography (cryo-ET). While several tools exist for visualisation and annotation of cryo-ET data, they are often integrated as part of monolithic processing pipelines, or focused on a specific task and offering limited reusability and extensibility. With each software suite presenting its own pros and cons and tools tailored to address specific challenges, seamless integration between available pipelines is often a difficult task. As part of the effort to enable such flexibility and move the software ecosystem towards a more collaborative and modular approach, we developed blik, an open-source napari plugin for visualisation and annotation of cryo-ET data (source code: https://github.com/brisvag/blik). blik offers fast, interactive, and user-friendly 3D visualisation thanks to napari, and is built with extensibility and modularity at the core. Data is handled and exposed through well-established scientific Python libraries such as numpy arrays and pandas dataframes. Reusable components (such as data structures, file read/write, and annotation tools) are developed as independent Python libraries to encourage reuse and community contribution. By easily integrating with established image analysis tools-even outside of the cryo-ET world-blik provides a versatile platform for interacting with cryo-ET data. On top of core visualisation features-interactive and simultaneous visualisation of tomograms, particle picks, and segmentations-blik provides an interface for interactive tools such as manual, surface-based and filament-based particle picking, and image segmentation, as well as simple filtering tools. Additional self-contained napari plugins developed as part of this work also implement interactive plotting and selection based on particle features, and label interpolation for easier segmentation. Finally, we highlight the differences with existing software and showcase blik's applicability in biological research.

Understanding the Effect of Curvature on the Magnetization Reversal of Three-Dimensional Nanohelices

Comprehending the interaction between geometry and magnetism in three-dimensional (3D) nanostructures is important to understand the fundamental physics of domain wall (DW) formation and pinning. Here, we use focused-electron-beam-induced deposition to fabricate magnetic nanohelices with increasing helical curvature with height. Using electron tomography and Lorentz transmission electron microscopy, we reconstruct the 3D structure and magnetization of the nanohelices. The surface curvature, helical curvature, and torsion of the nanohelices are then quantified from the tomographic reconstructions. Furthermore, by using the experimental 3D reconstructions as inputs for micromagnetic simulations, we can reveal the influence of surface and helical curvature on the magnetic reversal mechanism. Hence, we can directly correlate the magnetic behavior of a 3D nanohelix to its experimental structure. These results demonstrate how the control of geometry in nanohelices can be utilized in the stabilization of DWs and control of the response of the nanostructure to applied magnetic fields.

Statistical 3D morphology characterization of vaterite microspheres produced by engineered Escherichia coli

Hollow vaterite microspheres are important materials for biomedical applications such as drug delivery and regenerative medicine owing to their biocompatibility, high specific surface area, and ability to encapsulate a large number of bioactive molecules and compounds. We demonstrated that hollow vaterite microspheres are produced by an Escherichia coli strain engineered with a urease gene cluster from the ureolytic bacteria Sporosarcina pasteurii in the presence of bovine serum albumin. We characterized the 3D nanoscale morphology of five biogenic hollow vaterite microspheres using 3D high-angle annular dark field scanning transmission electron microscopy (HAADF-STEM) tomography. Using automated high-throughput HAADF-STEM imaging across several sample tilt orientations, we show that the microspheres evolved from a smaller more ellipsoidal shape to a larger more spherical shape while the internal hollow core increased in size and remained relatively spherical, indicating that the microspheres produced by this engineered strain likely do not contain the bacteria. The statistical 3D morphology information demonstrates the potential for using biogenic calcium carbonate mineralization to produce hollow vaterite microspheres with controlled morphologies. STATEMENT OF SIGNIFICANCE: The nanoscale 3D structures of biomaterials determine their physical, chemical, and biological properties, however significant efforts are required to obtain a statistical understanding of the internal 3D morphology of materials without damaging the structures. In this study, we developed a non-destructive, automated technique that allows us to understand the nanoscale 3D morphology of many unique hollow vaterite microspheres beyond the spectroscopy methods that lack local information and microscopy methods that cannot interrogate the full 3D structure. The method allowed us to quantitatively correlate the external diameters and aspect ratios of vaterite microspheres with their hollow internal structures at the nanoscale. This work demonstrates the opportunity to use automated transmission electron microscopy to characterize nanoscale 3D morphologies of many biomaterials and validate the chemical and biological functionality of these materials.

Revealing the 3D Structure of Block Copolymers with Electron Microscopy: Current Status and Future Directions

Block copolymers (BCPs) are considered model systems for understanding and utilizing self-assembly in soft matter. Their tunable nanometric structure and composition enable comprehensive studies of self-assembly processes as well as make them relevant materials in diverse applications. A key step in developing and controlling BCP nanostructures is a full understanding of their three-dimensional (3D) structure and how this structure is affected by the BCP chemistry, confinement, boundary conditions, and the self-assembly evolution and dynamics. Electron microscopy (EM) is a leading method in BCP 3D characterization owing to its high resolution in imaging nanosized structures. Here we discuss the two main 3D EM methods: namely, transmission EM tomography and slice and view scanning EM tomography. We present each method's principles, examine their strengths and weaknesses, and discuss ways researchers have devised to overcome some of the challenges in BCP 3D characterization with EM- from specimen preparation to imaging radiation-sensitive materials. Importantly, we review current and new cutting-edge EM methods such as direct electron detectors, energy dispersive X-ray spectroscopy of soft matter, high temporal rate imaging, and single-particle analysis that have great potential for expanding the BCP understanding through EM in the future.

Reducing radiation dose for NN-based COVID-19 detection in helical chest CT using real-time monitored reconstruction

Computed tomography is a powerful tool for medical examination, which plays a particularly important role in the investigation of acute diseases, such as COVID-19. A growing concern in relation to CT scans is the radiation to which the patients are exposed, and a lot of research is dedicated to methods and approaches to how to reduce the radiation dose in X-ray CT studies. In this paper, we propose a novel scanning protocol based on real-time monitored reconstruction for a helical chest CT using a pre-trained neural network model for COVID-19 detection as an expert. In a simulated study, for the first time, we proposed using per-slice stopping rules based on the COVID-19 detection neural network output to reduce the frequency of projection acquisition for portions of the scanning process. The proposed method allows reducing the total number of X-ray projections necessary for COVID-19 detection, and thus reducing the radiation dose, without a significant decrease in the prediction accuracy. The proposed protocol was evaluated on 163 patients from the COVID-CTset dataset, providing a mean dose reduction of 15.1% while the mean decrease in prediction accuracy amounted to only 1.9% achieving a Pareto improvement over a fixed protocol.

A general image misalignment correction method for tomography experiments

Tomography experiments generate three-dimensional (3D) reconstructed slices from a series of two-dimensional (2D) projection images. However, the mechanical system generates joint offsets that result in unaligned 2D projections. This misalignment affects the reconstructed images and reduces their actual spatial resolution. In this study, we present a novel method called outer contour-based misalignment correction (OCMC) for correcting image misalignments in tomography. We use the sample's outer contour structure as auxiliary information to estimate the extent of misalignment in each image. This method is generic and can be used with various tomography imaging techniques. We validated our method with five datasets collected from different samples and across various tomography techniques. The OCMC method demonstrated significant advantages in terms alignment accuracy and time efficiency. As an end-to-end correction method, OCMC can be easily integrated into an online tomography data processing pipeline and facilitate feedback control in future synchrotron tomography experiments.

Autonomous Electron Tomography Reconstruction with Machine Learning

Modern electron tomography has progressed to higher resolution at lower doses by leveraging compressed sensing (CS) methods that minimize total variation (TV). However, these sparsity-emphasized reconstruction algorithms introduce tunable parameters that greatly influence the reconstruction quality. Here, Pareto front analysis shows that high-quality tomograms are reproducibly achieved when TV minimization is heavily weighted. However, in excess, CS tomography creates overly smoothed three-dimensional (3D) reconstructions. Adding momentum to the gradient descent during reconstruction reduces the risk of over-smoothing and better ensures that CS is well behaved. For simulated data, the tedious process of tomography parameter selection is efficiently solved using Bayesian optimization with Gaussian processes. In combination, Bayesian optimization with momentum-based CS greatly reduces the required compute time-an 80% reduction was observed for the 3D reconstruction of SrTiO3 nanocubes. Automated parameter selection is necessary for large-scale tomographic simulations that enable the 3D characterization of a wider range of inorganic and biological materials.

Three-dimensional reconstruction of Y-IrNi rhombic dodecahedron nanoframe by STEM/EDS tomography

The structural analysis of nanocrystals via transmission electron microscopy (TEM) is a valuable technique for the material science field. Recently, two-dimensional images by scanning TEM (STEM) and energy-dispersive X-ray spectroscopy (EDS) have successfully extended to three-dimensional (3D) imaging by tomography. However, despite improving TEM instruments and measurement techniques, detector shadowing, the missing-wedge problem, X-ray absorption effects, etc., significant challenges still remain; therefore, the various required corrections should be considered and applied when performing quantitative tomography. Nonetheless, this 3D reconstruction technique can facilitate active site analysis and the development of nanocatalyst systems, such as water electrolysis and fuel cell. Herein, we present a 3D reconstruction technique to obtain tomograms of IrNi rhombic dodecahedral nanoframes (IrNi-RFs) from STEM and EDS images by applying simultaneous iterative reconstruction technique and total variation minimization algorithms. From characterizing the morphology and spatial chemical composition of the Ir and Ni atoms in the nanoframes, we were able to infer the origin of the physical and catalytic durability of IrNi-RFs. Also, by calculating the surface area and volume of the 3D reconstructed model, we were able to quantify the Ir-to-Ni composition ratio and compare it to the EDS measurement result.

Unique identification of gold and banknotes through the use of antipode elements: Material selection, laboratory verification steps, and industrial software-hardware implementation

The falsification problems associated with golden coins, banknotes, and legal documents could be solved through "antipode elements," microfiber materials selected to have the exact opposite (antipode) properties when incorporated into gold, paper, or any other tangible manufactured object. Any discrepancies in gold or banknotes could be found using various non-destructive testing machinery. This research focus was given to help a student or junior lab technician replicate all steps and conclude that a fully functional product is ready for the alpha test. It requires minimal interdisciplinary knowledge in statistics, programming, and metrology, along with chemical, material, and digital electronics engineering. The research methodology can be categorized into four tracks: material selection and method validation. The two validation steps were kept short and low level, that is, minimal and only to guide reproducibility, due to limitations in presentation, procedural specification, pricing, consumable options, and software modules. A last-minute development occurred by describing the procedures in the current submission, not initially granted in the invention patents. This technique is an innovative design to capture raw sensor data straight from the photodiode pad. These Big-Data are manipulated using the presented and future data analytics methodologies.

Towards routine 3D characterization of intact mesoscale samples by multi-scale and multimodal scanning X-ray tomography

Non-invasive multi-scale and multimodal 3D characterization of heterogeneous or hierarchically structured intact mesoscale samples is of paramount importance in tackling challenging scientific problems. Scanning hard X-ray tomography techniques providing simultaneous complementary 3D information are ideally suited to such studies. However, the implementation of a robust on-site workflow remains the bottleneck for the widespread application of these powerful multimodal tomography methods. In this paper, we describe the development and implementation of such a robust, holistic workflow, including semi-automatic data reconstruction. Due to its flexibility, our approach is especially well suited for on-the-fly tuning of the experiments to study features of interest progressively at different length scales. To demonstrate the performance of the method, we studied, across multiple length scales, the elemental abundances and morphology of two complex biological systems, Arabidopsis plant seeds and mouse renal papilla samples. The proposed approach opens the way towards routine multimodal 3D characterization of intact samples by providing relevant information from pertinent sample regions in a wide range of scientific fields such as biology, geology, and material sciences.