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At least 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Semantic segmentation with a sparse convolutional neural network for event reconstruction in MicroBooNE

We present the performance of a semantic segmentation network, SparseSSNet, that provides pixel-level classification of MicroBooNE data. The MicroBooNE experiment employs a liquid argon time projection chamber for the study of neutrino properties and interactions. SparseSSNet is a submanifold sparse convolutional neural network, which provides the initial machine learning based algorithm utilized in one of MicroBooNE's ν e -appearance oscillation analyses. The network is trained to categorize pixels into five classes, which are re-classified into two classes more relevant to the current analysis. The output of SparseSSNet is a key input in further analysis steps. This technique, used for the first time in liquid argon time projection chambers data and is an improvement compared to a previously used convolutional neural network, both in accuracy and computing resource utilization. Here, the accuracy achieved on the test sample is ≥ 99%. For full neutrino interaction simulations, the time for processing one image is ≈ 0.5 sec, the memory usage is at 1 GB level, which allows utilization of most typical CPU worker machine.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Errors in reconstruction of dichroic X-ray orientation tomography due to polarization rotation of the incident beam

Dichroic X-ray tomography is a technique in which the crystal orientation or magnetization of a sample is resolved in three dimensions. The best-known uses of this technique are for observation of magnetic moments via circular dichroism, using left- and right-handed circularly polarized X-ray beams. Another variant uses linear dichroism to resolve the crystal orientation. In both these techniques, it is assumed that the absorption of X-rays along a path inside a material can be computed as a line integral of a local absorption coefficient along the ray path. For linear dichroism, this assumption is inaccurate because the polarization of the beam changes along the propagation direction when the optic axis of the material is not aligned along the polarization. In this work, a finite-element Maxwell solver is used to simulate tomography and reconstructions. The propagation effect can lead to significant errors in the reconstructed orientations. These errors may be mitigated by taking data at additional angles or by operating at energies at which the dichroism is weak. An iterative approach is proposed which may allow accurate reconstruction with fewer data than would otherwise be required.

X-ray linear dichroism↗
DOE OSTI2025

PvaPy streaming framework for real-time data processing

User facility upgrades, new measurement techniques, advances in data analysis algorithms as well as advances in detector capabilities result in an increasing amount of data collected at X-ray beamlines. Some of these data must be analyzed and reconstructed on demand to help execute experiments dynamically and modify them in real time. In turn, this requires a computing framework for real-time processing capable of moving data quickly from the detector to local or remote computing resources, processing data, and returning results to users. In this paper, we discuss the streaming framework built on top of PvaPy, a Python API for the EPICS pvAccess protocol. We describe the framework architecture and capabilities, and discuss scientific use cases and applications that benefit from streaming workflows implemented on top of this framework. We also illustrate the framework's performance in terms of achievable data-processing rates for various detector image sizes.

EPICS pvAccess↗
DOE OSTI2021

Improved Gamma-Ray Point Source Quantification in Three Dimensions by Modeling Attenuation in the Scene

We discuss using a series of detector measurements taken at different locations to localize a source of radiation as a well-studied problem. The source of radiation is sometimes constrained to a single point-like source, in which case the location of the point source can be found using techniques such as maximum likelihood. Recent advancements have shown the ability to locate point sources in 2D and even 3D, but few have studied the effect of intervening material on the problem. In this work we examine gamma-ray data taken from a freely moving system and develop voxelized 3-D models of the scene using data from the onboard LiDAR. Ray casting is used to compute the distance each gamma ray travels through the scene material, which is then used to calculate attenuation assuming a single attenuation coefficient for solids within the geometry. Parameter estimation using maximum likelihood is performed to simultaneously find the attenuation coefficient, source activity, and source position that best match the data. Using a simulation, we validate the ability of this method to reconstruct the true location and activity of a source, along with the true attenuation coefficient of the structure it is inside, and then we apply the method to measured data with sources and find good agreement.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Time series methods for the analysis of soundscapes and other cyclical ecological data

Biodiversity monitoring has entered an era of ‘big data’, exemplified by a near-continuous collection of sounds, images, chemical and other signals from organisms in diverse ecosystems. Such data streams have the potential to help identify new threats, assess the effectiveness of conservation interventions, as well as generate new ecological insights. However, appropriate analytical methods are often still missing, particularly with respect to characterizing cyclical temporal patterns. Here, we present a framework for characterizing and analysing ecological responses that represent nonstationary, complex temporal patterns and demonstrate the value of using Fourier transforms to decorrelate continuous data points. In our example, we use a framework based on three approaches (spectral analysis, magnitude squared coherence, and principal component analysis) to characterize differences in tropical forest soundscapes within and across sites and seasons in Gabon. By reconstructing the underlying, cyclic behaviour of the soundscape for each site, we show how one can identify circadian patterns in acoustic activity. Soundscapes in the dry season had a complex diel cycle, requiring multiple harmonics to represent daily variation, while in the wet season there was less variance attributable to the daily cyclic patterns. Our framework can be applied to most continuous, or near-continuous ecological data collected at a fine temporal resolution, allowing ecologists to explore patterns of temporal autocorrelation at multiple levels for biologically meaningful trends. Such methods will become indispensable as biological big data are used to understand the impact of anthropogenic pressures on biodiversity and to inform efforts to mitigate them.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Scalable method for micro-CT analysis enables large scale quantitative characterization of brain lesions and implants

Anatomic evaluation is an important aspect of many studies in neuroscience; however, it often lacks information about the three-dimensional structure of the brain. Micro-CT imaging provides an excellent, nondestructive, method for the evaluation of brain structure, but current applications to neurophysiological or lesion studies require removal of the skull as well as hazardous chemicals, dehydration, or embedding, limiting their scalability and utility. Here we present a protocol using eosin in combination with bone decalcification to enhance contrast in the tissue and then employ monochromatic and propagation phase-contrast micro-CT imaging to enable the imaging of brain structure with the preservation of the surrounding skull. Instead of relying on descriptive, time-consuming, or subjective methods, we develop simple quantitative analyses to map the locations of recording electrodes and to characterize the presence and extent of hippocampal brain lesions.

3-D reconstruction↗
DOE OSTI2020

Role of fast-ion transport manipulating safety factor profile in KSTAR early diverting discharges

Magnetohydrodynamics (MHD) activity is analyzed for a particular KSTAR discharge category, the main features of which are a high-$q_\mathrm{min}$ and a broad q profile. An interesting finding in this scenario is that a steady-state high-$q_\mathrm{min}$ and broad q profile has been constructed even without a strong off-axis current drive scheme. Time traces of magnetics spectrograms and electron cyclotron emission imaging (ECEI) clearly show that Alfvénic type MHD activity appears as a high-$q_\mathrm{min}$ and broad q profile is formed. Conversely, this activity disappears as the current profiles evolve toward a low-$q_\mathrm{min}$ profile. In this study, the effect of MHD modes and accompanying fast-particle transport on the formation of various current profiles is explored. The frequency patterns of the magnetics spectrograms and ECEI coherence are compared using a NOVA analysis to determine which series of Alfvénic modes are active. Then, the kick-model is applied to potential modes, and used to estimate how much fast-ions are transported and beam driven current profiles are varied. Here, by comparing the reconstructed total current profile from the kinetic EFIT with the beam-driven current profile estimated from the kick model, it is determined how energetic particle transport is responsible for maintaining the safety factor profile and which q profile can provide high β N operation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Investigation of Nanoparticle Degradation in Hydrogen Fuel Cell Systems through Automated Electron Microscopy

Proton exchange membrane fuel cells (PEMFC) are promising devices for the deployment of hydrogen-powered heavy-duty vehicles, providing a higher efficiency for similar driving range and fueling time than the existing ones. However, PEMFCs still encounter durability challenges mainly due to catalyst degradation in the cathode. Mitigating these performance losses requires a better understanding of the degradation mechanisms under heavy-duty accelerated stress tests (ASTs) [1]. Scanning transmission electron microscopy (STEM) combined with energy dispersive X-ray spectroscopy (EDS) are key tools for the analysis of Pt and PtCo nanoparticle size, spatial distribution and composition [2]. Electron tomography is also used to determine the rate and type of degradation of catalyst nanoparticles as a function of their position on the carbon support. In this work, automated data acquisition software, paired with a custom Python code, have been used to study the effect of different accelerated stress tests (ASTs) on nanoparticle coarsening [2]. Figure 1 shows high-angle annular dark-field (HAADF)-STEM images and EDS maps comparing the cathodes of membrane electrode assemblies (MEAs) following an electrocatalyst AST performed under H2/N2 with that of the heavy-duty AST performed under H2/air. We will discuss how AST conditions affect considerably the spatial distribution of the nanoparticles across the electrode between the membrane and microporous layer. Although the median particle size increased more in the MEA aged under the heavy-duty AST, as determined using a high-throughput image analysis, the quantitative EDS measurements demonstrate that the electrocatalyst AST resulted in more Pt and Co dissolution from the cathode, which is another important indicator of electrocatalyst degradation. We will further present the impact of the relative humidity (% RH) on the degradation mechanisms demonstrated using the same approach. Electron tomography has been used to distinguish the Pt nanoparticles residing on the carbon support surface (exterior) from those within the pore structure (interior) in order to determine the relative stability of interior and exterior nanoparticles. As shown in Figure 2, we will compare the Pt catalyst particle size at the beginning of test (BOT) and end of test (EOT), and discuss the importance of automating the electron tomography workflow, i.e. acquisition, reconstruction, and visualization, to increase sampling and determine the standard deviation of these measurement. The outlook for utilizing low-dose cryo-tomography for limiting damage to the catalyst, support, and especially proton-conducting ionomer will also be discussed [3].

Amichi, Lynda↗
DOE OSTI2022

A kinematic excess in the annular gap and gas-depleted cavity in the disc around HD 169142

ABSTRACT We present ALMA band 6 images of the 12CO, 13CO, and C18O J = 2-1 line emissions for the circumstellar disc around HD 169142, at ∼8 au spatial resolution. We resolve a central gas-depleted cavity, along with two independent near-symmetric ring-like structures in line emission: a well-defined inner gas ring [∼25 au] and a second relatively fainter and diffuse outer gas ring [∼65 au]. We identify a localized super-Keplerian feature or vertical flow with a magnitude of ∼75 ms−1 in the 12CO map. This feature has the shape of an arc that spans azimuthally across a position angle range of −60° to 45° and radially in between the B1[26au] and B2[59au] dust rings. Through reconstruction of the gas surface density profile, we find that the magnitude of the background perturbations by the pressure support and self-gravity terms are not significant enough to account for the kinematic excess. If of planetary origin, the relative depletion in the gas-density profile would suggest a 1 MJ planet. In contrast, the central cavity displays relatively smooth kinematics, suggesting either a low-mass companion and/or a binary orbit with a minimal vertical velocity component.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Surface elevation, snow depth, vegetation height, and color imagery from multiple UAV surveys from 2018 to 2023 across a watershed near Teller road mile marker 27, Seward Peninsula, Alaska

Multiple photogrammetric surveys using an unoccupied aerial system (UAS) were performed across a watershed along Teller road on the Seward Peninsula (Alaska) to investigate terrain, vegetation and snowpack properties. This work was led by the environmental geophysics team from Lawrence Berkeley National Laboratory as part of the Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic). The multiple photogrammetric surveys used mostly a DJI Matrice 210 UAS with a DJI X5S camera, Ground Control Points (GCPs) surveyed with a Real Time Kinematic (RTK)-GPS, and a structure from motion (SfM) technique for photogrammetric reconstruction. Digital Surface elevation Models (DSMs) were inferred at various times of year, including near peak in plant and leaf density (July 19 2017), close to peak in snow depth (April 1 2019 and April 11 2022), and at low plant and leaf density of tall after the first bare-ground date (June 9 2019). Snow and canopy height were obtained by subtracting DSMs from a Digital Terrain Model (DTM) proxy inferred from the June 9 2019 survey. The derived products include ortho-mosaiced RGB map, DSMs, a DTM proxy, snow depth (April 2019 and 2022) and canopy height (July 2017). Unprocessed and processed data products are included in this package (processing levels 0-2). Data and metadata are provided as text (*.csv), image (*.jpg), and GeoTiff (*.tif) formats. This metadata document contains a description of the survey and processing steps and the inferred products.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Accurate real space iterative reconstruction (RESIRE) algorithm for tomography

Tomography has made a revolutionary impact on the physical, biological and medical sciences. The mathematical foundation of tomography is to reconstruct a three-dimensional (3D) object from a set of two-dimensional (2D) projections. As the number of projections that can be measured from a sample is usually limited by the tolerable radiation dose and/or the geometric constraint on the tilt range, a main challenge in tomography is to achieve the best possible 3D reconstruction from a limited number of projections with noise. Over the years, a number of tomographic reconstruction methods have been developed including direct inversion, real-space, and Fourier-based iterative algorithms. Here, we report the development of a real-space iterative reconstruction (RESIRE) algorithm for accurate tomographic reconstruction. RESIRE iterates between the update of a reconstructed 3D object and the measured projections using a forward and back projection step. The forward projection step is implemented by the Fourier slice theorem or the Radon transform, and the back projection step by a linear transformation. Our numerical and experimental results demonstrate that RESIRE performs more accurate 3D reconstructions than other existing tomographic algorithms, when there are a limited number of projections with noise. Furthermore, RESIRE can be used to reconstruct the 3D structure of extended objects as demonstrated by the determination of the 3D atomic structure of an amorphous Ta thin film. We expect that RESIRE can be widely employed in the tomography applications in different fields. Finally, to make the method accessible to the general user community, the MATLAB source code of RESIRE and all the simulated and experimental data are available at https://zenodo.org/record/7273314.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Resolving the fast ion distribution from imaging neutral particle analyzer measurements

A recently developed imaging neutral particle analyzer (INPA) on the DIII-D tokamak (Du 2018 Nucl. Fusion 58 082006) enables fast ion velocity-space tomography of high fidelity at the interrogated phase space. To accomplish this, the spatial and energy depending fast ( E < 80 keV) neutral flux towards the INPA stripping foils is calculated with FIDASIM and a newly developed code INPASIM simulates the INPA instrumental response to this neutral flux. Included in INPASIM is the neutral-foil interaction, the Larmor orbit tracing between the foil and the phosphor, the phosphor response to the incident ion flux as well as camera focusing. Benefiting from heavy, localized velocity-space weights and excellent signal to noise, computed tomography using the Ridge regression method is able to successfully reconstruct fine-scale velocity-space structures produced by multiple neutral beams separated by as small as ~3 keV in tests. Applying the inversion method to a sawtooth crash event reveals a significant profile flattening of confined passing particles across q = 1 flux surface, as well as a redistribution of fast ions into the trapped orbits at the plasma edge close to the last closed flux surface.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

In situ high-temperature X-ray diffraction study of Sc-doped titanium oxide nanocrystallites

Titanium dioxide is an inexpensive wide-gap highly ionic semiconductor with striking photocatalytic capabilities in several heterogeneous photoredox reactions. A small crystal size is desirable to maximize the surface area, since photocatalytic reactions occur at the surface of a photocatalyst. Presented in this work are the synthesis and microstructural characterization of 4 at.% Sc-doped TiO 2 (4SDT) prepared by water-based co-precipitation. The crystal structure of 4SDT was examined via in situ high-temperature powder X-ray diffraction experiments from 25 to 1200°C. Rietveld analysis revealed single-phase anatase up to 875°C, while at 900°C the anatase-to-rutile phase transformation occurred and at higher temperatures additional reflections of Sc-rich phases (Sc 2 TiO 5 from 975°C and Ti 3 Sc 4 O 12 or Sc 2 O 3 at 1200°C) were observed. Debye function analysis (DFA) was applied to model the total scattering pattern directly in reciprocal space, allowing the reconstruction of Ti vacancies. Both Rietveld and DFA methods were applied to estimate the nanocrystallite size and shape with consistent growth in crystallite size with temperature: an ellipsoid shape with equatorial ~4.7 nm / axial (001) ~6.9 nm at 25°C to equatorial ~27.9 nm / axial (001) ~39.6 nm at 900°C refined by Rietveld analysis, versus a cylinder shape with D a , b = 4.3 nm and size dispersion σ ab = 1.5 nm, L c = 4.9 nm and σ c = 2.3 nm at 25°C to D a , b = 21.4 nm, σ ab = 8.3 nm, L c = 23.9 and σ c = 10.9 nm at 900°C estimated by DFA. The microstructural changes obtained by Rietveld and DFA methods were supported by high-resolution transmission electron microscopy image analysis, as well as by the less direct nitrogen sorption techniques that provide information on the size of non-agglomerated and dense particles. The Ti site-occupancy factor showed a linear increase from 0.6–0.8 at 25°C to unity at 900°C for anatase, and from ~0.7 at 900°C to unity at 1200°C for rutile, via Rietveld analysis and DFA.

36 MATERIALS SCIENCE↗
DOE OSTI2022

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

Here, 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 MoS 2 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.

2D materials↗
DOE OSTI2020

Open Source Visualization and Analysis Platform for 3D Reconstructions of Materials by Transmission Electron Microscopy

Three-dimensional characterization of materials at the nano- and meso-scale has become possible with transmission and scanning transmission electron microscopes (S/TEM). Its importance has extended to a wide class of nanomaterials such as hydrogen fuel cells, solar cells, industrial catalysts, new battery materials and semiconductor devices, as well as spanning high-tech industry, universities, and national labs. While capable instrumentation is abundant, this rapidly expanding demand for high-resolution tomography is bottlenecked by software that is instead tailored for lower-dose, biological applications and not optimized for higher-resolution materials applications. Existing tomography fails to utilize the chemical information provided by S/TEM spectrometers. To address this problem, this project delivered a scalable, fully functional, freely-distributable, open Source materials tomography package with a modern user interface that enables automated acquisition, alignment, and real-time reconstruction of raw tomography data, and provides advanced segmentation, three-dimensional chemical visualization and analysis optimized for materials applications. It has established an extendable framework capable of automation for high-throughput for the tomography of materials from data acquisition to visualization. Phase I and II delivered a full-featured, cross-platform, clean and integrated application for S/TEM materials tomography. It can read projection data from the microscope, with graphical tools for alignment of data, tomographic reconstruction, segmentation, and visualization of the reconstructed 3D volume. The entire pipeline can be saved to an XML state file, enabling fully reproducible data processing and analysis with a full Python environment for the development of custom algorithms, processing, and analysis requirements. Phase IIB extended the application to provide real-time tomographic reconstruction, "live updates" as data is processed, analysis of big data, and multi-channel tomography. Here, quantitative assessment of nanomaterials can occur as data is being recorded on a 3D visualization platform that accommodates additional information from multiple channels. We provide unmatched high-throughput tomography, where the complete tomographic pipeline from measurement to 3D visualization can occur rapidly. The project was extended to offer capabilities for micro-CT, X-ray, neutron, focused ion beam, atomic electron tomography and atom probe tomography. With over 600 transmission electron microscopes worldwide and approximately 50 coming online each year, the demand and impact of an open-source tomography tool is large. Significant opportunities exist in high-tech industry, universities, and national labs to enable or enhance three-dimensional imaging at the nanoscale and bring automated high-throughput approaches that will accelerate progress in materials characterization and metrology. The project supports a service based business model by enabling lab-specific acquisition and processing customization and integration-support and development that will be provided into Phase III and beyond.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Machine learning for imaging Cherenkov detectors

Imaging Cherenkov detectors are largely used in modern nuclear and particle physics experiments where cutting-edge solutions are needed to face always more growing computing demands. This is a fertile ground for AI-based approaches and at present we are witnessing the onset of new highly efficient and fast applications. This paper presents novel directions with applications to Cherenkov detectors. In particular, recent advances on detector design and calibration, as well as particle identification are presented.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

The picasso map-making code: application to a simulation of the QUIJOTE northern sky survey

ABSTRACT Map-making is an important step for the data analysis of cosmic microwave background (CMB) experiments. It consists of converting the data, which are typically a long, complex, and noisy collection of measurements, into a map, which is an image of the observed sky. We present in this paper a new map-making code named picasso (Polarization and Intensity CArtographer for Scanned Sky Observations), which was implemented to construct intensity and polarization maps from the Multi Frequency Instrument (MFI) of the QUIJOTE (Q-U-I Joint TEnerife) CMB polarization experiment. picasso is based on the destriping algorithm, and is suited to address specific issues of ground-based microwave observations, with a technique that allows the fit of a template function in the time domain, during the map-making step. This paper describes the picasso code, validating it with simulations and assessing its performance. For this purpose, we produced realistic simulations of the QUIJOTE-MFI survey of the northern sky (approximately ∼20 000 deg2), and analysed the reconstructed maps with picasso, using real and harmonic space statistics. We show that, for this sky area, picasso is able to reconstruct, with high fidelity, the injected signal, recovering all the scales with ℓ > 10 in TT, EE, and BB. The signal error is better than 0.001 per cent at 20 < ℓ < 200. Finally, we validated some of the methods that will be applied to the real wide-survey data, like the detection of the CMB anisotropies via cross-correlation analyses. Despite that the implementation of picasso is specific for QUIJOTE-MFI data, it could be adapted to other experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Multibeam Electron Diffraction

One of the primary uses for transmission electron microscopy (TEM) is to measure diffraction pattern images in order to determine a crystal structure and orientation. In nanobeam electron diffraction (NBED), we scan a moderately converged electron probe over the sample to acquire thousands or even millions of sequential diffraction images, a technique that is especially appropriate for polycrystalline samples. However, due to the large Ewald sphere of TEM, excitation of Bragg peaks can be extremely sensitive to sample tilt, varying strongly for even a few degrees of sample tilt for crystalline samples. In this paper, we present multibeam electron diffraction (MBED), where multiple probe-forming apertures are used to create multiple scanning transmission electron microscopy (STEM) probes, all of which interact with the sample simultaneously. We detail designs for MBED experiments, and a method for using a focused ion beam to produce MBED apertures. We show the efficacy of the MBED technique for crystalline orientation mapping using both simulations and proof-of-principle experiments. We also show how the angular information in MBED can be used to perform 3D tomographic reconstruction of samples without needing to tilt or scan the sample multiple times. Finally, we also discuss future opportunities for the MBED method.

47 OTHER INSTRUMENTATION↗