Nanoscale Optical Imaging of 2D Semiconductor Stacking Orders by Exciton-Enhanced Second Harmonic Generation
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Materials Science↗
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Propagation of Noise Uncertainty Through Virtual Strain Gauge Formulations for 2D Digital Image Correlation
The effect of displacement uncertainty is examined on 2-dimensional strain, calculated using linear surfaces fitted to the displacement field. A classical engineering error propagation method is used to calculate uncertainty in Green-Lagrangian strain calculations. The derived uncertainty is compared to a Monte Carlo simulation and discrepancies under 2% are seen between these two methods. The effect of virtual strain gauge size, displacement uncertainty, and boundaries on the region of interest on the strain uncertainty are considered. Here, an exponential decay relationship is observed between strain uncertainty and virtual strain gauge size, while a linear relationship is seen between strain and displacement uncertainty. For boundaries in the region of interest, strain uncertainty is affected by the reduced number of points available to perform the regression.
42 ENGINEERING↗
Extracting a mixing parameter from 2D radiographic imaging of variable-density turbulent flow
We extract a suitably averaged fluctuating density from the two-dimensional radiographic image of a flow. The X-ray attenuation is given by the Beer–Lambert law which exponentially damps the incident beam intensity by a factor proportional to the density, opacity and thickness of the target. By making reasonable assumptions for the mean density, opacity and effective thickness of the target flow, we estimate the density fluctuation contribution to the attenuation. The extracted density fluctuations averaged across the thickness of the flow in the direction of the beam may be used to form the density–specific-volume correlation $b$. In a statistical description of variable-density turbulence, $b$ quantifies the degree of mixedness. The ability to extract a measure of mixedness from experimental data would be a powerful tool that could be used in the validation of mix models. The scheme proposed is tested for DNS data computed for variable density buoyancy-driven mixing. We quantify the deficits in the extracted value of $b$ due to target thickness, Atwood number and modeled signal noise. This analysis justifies using the proposed scheme to infer the mix parameter from thin targets at moderate to low Atwood numbers. Furthermore, to illustrate how the scheme might be used in a practical problem, we demonstrate its application to a radiographic image of counter-shear flow obtained from experiments at the National Ignition Facility.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Direct Optoelectronic Imaging of 2D Semiconductor–3D Metal Buried Interfaces
The semiconductor-metal junction is one of the most critical factors for high performance electronic devices. In two-dimensional (2D) semiconductor devices, minimizing voltage drop at this junction is of particularly challenging and important. Despite numerous studies on contact resistance in 2D semiconductors, the exact nature of the buried interface under a 3D metal remains elusive and unclear. Herein, we report the direct observation of 2D semiconductor-metal buried interface using recently developed metal-assisted transfer technique to expose the buried interface which is then directly investigated using scanning probe techniques. We characterize the spatially varying electronic and optical properties of this buried interface with < 20 nm resolution. To be specific, potential, conductance and photoluminescence at the buried metal/MoS 2 interface are correlated under variety of metal deposition conditions as well as type of metal contacts. We observe that direct evaporation of Au on MoS 2 induces large strain of ~5% in the MoS 2 which coupled with charge transfer leads to degenerate doping of the MoS 2 underneath the contact. These factors lead to improvement of contact resistance to record values of 138 kΩ μm measured using local conductance probes. This approach was adopted to investigate MoS 2 -In/Au alloy interface, which records lowest contact resistance of 63 kΩ μm. Overall, our results highlight that the MoS 2 /Metal interface is very sensitive to method of contact making and provides a universal strategy to characterize buried contact interfaces involving 2D semiconductors.
77 NANOSCIENCE AND NANOTECHNOLOGY↗
Aberration-corrected STEM imaging of 2D materials: Artifacts and practical applications of threefold astigmatism
High-resolution scanning transmission electron microscopy (HR-STEM) with spherical aberration correction enables researchers to peer into two-dimensional (2D) materials and correlate the material properties with those of single atoms. The maximum intensity of corrected electron beam is confined in the area having sub-angstrom size. Meanwhile, the residual threefold astigmatism of the electron probe implies a triangular shape distribution of the intensity, whereas its tails overlap and thus interact with several atomic species simultaneously. The result is the resonant modulation of contrast that interferes the determination of phase transition of 2D materials. Here, we theoretically reveal and experimentally determine the origin of resonant modulation of contrast and its unintended impact on violating the power-law dependence of contrast on coordination modes between transition metal and chalcogenide atoms. The finding illuminates the correlation between atomic contrast, spatially inequivalent chalcogenide orientation, and residual threefold astigmatism on determining the atomic structure of emerging 2D materials.
36 MATERIALS SCIENCE↗
3D Optical Coherence Tomography image processing in BISCAP: characterization of biofilm structure and properties
Abstract Motivation BISCAP is a state-of-the-art tool for automatically characterizing biofilm images obtained from Optical Coherence Tomography. Limited availability of other software tools is reported in the field. BISCAP’s first version processes 2D images only. Processing 3D images is a problem of greater scientific relevance since it deals with the entire structure of biofilms instead of their 2D slices. Results Building on the image-processing principles and algorithms proposed earlier for 2D images, these were adapted to the 3D case, and a more general implementation of BISCAP was developed. The primary goal concerns the extension of the initial methodology to incorporate the depth axis in 3D images; multiple improvements were also made to boost computational performance. The calculation of structural properties and visual outputs was extended to offer new insights into the 3D structure of biofilms. BISCAP was tested using 3D images of biofilms with different morphologies, consistently delivering accurate characterizations of 3D structures in a few minutes using standard laptop machines. Low user dependency is required for image analysis. Availability and implementation BISCAP is available from https://github.com/diogonarciso/BISCAP. All images used in the tutorials and the validation examples are available from https://web.fe.up.pt/∼fgm/biscap3d.
Narciso, Diogo A. C. (ORCID:0000000227767477)↗
Upgrades to the gamma ray imager on DIII-D enabling access to high flux hard x-ray measurements during the runaway electron plateau phase (invited)
The Gamma Ray Imager (GRI) is a pinhole camera providing 2D imaging of MeV hard x-ray (HXR) bremsstrahlung emission from runaway electrons (REs) over the poloidal cross section of the DIII-D tokamak. We report a series of upgrades to the GRI expanding the access to RE scenarios from the diagnosis of a trace amount of REs to high flux HXR measurements during the RE plateau phase. We present the implementation of novel gamma ray detectors based on LYSO and YAP crystals coupled to multi-pixel photon counters, enabling a count rate in excess of 1 MHz. Finally, we highlight new insights into the RE physics discovered during the current quench and RE plateau phase experiments as the result of these upgrades.
Lvovskiy, A. (ORCID:0000000236491169)↗
3D Source Reconstruction Using Coded Aperture Gamma-Ray Imaging
Recent measurements with coded-aperture imagers demonstrate material mass determination in a holdup setting to an accuracy within a few percent. This capability is of particular interest to the Surplus Plutonium Disposition (SPD) project, which aims to dilute and dispose of surplus plutonium oxide. Gamma-ray imagers can be used to determine holdup without interrupting normal operations. In this work, we examine techniques for 3D source localization and mass determination using gamma-ray imagers. Coded-aperture imagers provide excellent source localization within the 2D image plane; however, multiple imagers operating in tandem are necessary to identify source location in 3D space. A Maximum Likelihood Expectation-Maximization (MLEM) method for fitting detector mappings is a powerful tool for accomplishing this task. MLEM allows 3D source localization to be simultaneously constrained using multiple gamma-ray imagers by constructing the basis for the MLEM fit using detector mappings from different detector locations stitched together. Each of these basis points represents a singular response from a source in 3D space and is generated using Monte Carlo simulations of sources placed individually at different locations throughout the imager’s field of view. Additionally, implementing knowledge of the physical equipment in the simulations of the glovebox used for the SPD project incorporates attenuation effects that are needed to calculate material holdup.
Laminack, Alex↗
Characterization of a Low-Temperature Plasma (LTP) Ambient Ionization Source Using Temporally Resolved Monochromatic Imaging Spectrometry
The low-temperature plasma (LTP) probe is a common plasma-based source used for ambient desorption–ionization mass spectrometry (MS). While the LTP probe has been characterized in detail with MS, relatively few studies have used optical spectroscopy. In this paper, two-dimensional (2D) imaging at selected wavelengths is used to visualize important species in the LTP plasma jet. First, 2D steady-state images of the LTP plume for N 2 + (391.2 nm), He I (706.5 nm), and N 2 (337.1 nm) emissions were recorded under selected plasma conditions. Second, time-resolved 2D emission maps of radiative species in the LTP plasma jet were recorded through the use of a 200 ns detection gate and varying gate delays with respect to the LTP trigger pulse. Emission from He I, N 2 + , and N 2 in the plasma jet region was found to show a transient behavior (often referred to as plasma bullets) lasting only a few microseconds. The N 2 + and He I maps were highly correlated in spatial and temporal structure. Further, emission from N 2 showed two maxima in time, one before and one after the maximum emission for N 2 + and He I, due to an initial electronic excitation wave and ion–electron recombination, respectively. Third, the interaction of the LTP probe with a sample substrate and an electrically grounded metallic needle was studied. Emission from a fluorophore on the sample substrate showed an initial photon-induced excitation from plasma-generated photons followed by electronic excitation by other plasma species. The presence of a grounded needle near the plasma jet significantly extended the plasma jet lifetime and also generated a long-lived corona discharge on the needle. The effect of LTP operating parameters on emission spectra was correlated with mass-spectral results including reagent-ion signals. Lastly, five movies provide a side-by-side comparison of the temporal behavior of emitting species and insights into the interactions of the emission clouds with a sample surface as well as an external needle. Temporally and spatially resolved imaging provided insights into important processes in the LTP plasma jet, which will help improve analyte ion sampling in LTP–MS.
Chan, George C. -Y.↗
A VR-based volumetric medical image segmentation and visualization system with natural human interaction
Volume rendering produces informative two-dimensional (2D) images from a 3-dimensional (3D) volume. It highlights the region of interest and facilitates a good comprehension of the entire data set. However, volume rendering faces a few challenges. First, a high-dimensional transfer function is usually required to differentiate the target from its neighboring objects with subtle variance. Unfortunately, designing such a transfer function is a strenuously trial-and-error process. Second, manipulating/visualizing a 3D volume with a traditional 2D input/output device suffers dimensional limitations. To address all the challenges, we design NUI-VR 2 , a natural user interface-enabled volume rendering system in the virtual reality space. NUI-VR 2 marries volume rendering and interactive image segmentation. It transforms the original volume into a probability map with image segmentation. A simple linear transfer function will highlight the target well in the probability map. More importantly, we set the entire image segmentation and volume rendering pipeline in an immersive virtual reality environment with a natural user interface. NUI-VR 2 eliminates the dimensional limitations in manipulating and perceiving 3D volumes and dramatically improves the user experience.
42 ENGINEERING↗
Biases associated with a particular image volume metric
Image analysis area and volume metrics A 80 and V 80 , used by others, are studied as a function of image morphology, a 3D feature, and Monte Carlo noise in simulated images. The A 80 area metric is found to be stable, with consistent results (and meaning) obtainable without a detailed understanding of 3D features and/or simulation noise levels. However, the V 80 volume metric varies significantly with image morphology, 3D features, and simulation noise. If an experimental image set gives A 80 area inferences that are consistent with 2D image simulations, but V 80 volume inferences that are significantly larger than those corresponding to simulated images, then issues related to 3D features and simulation noise should be explored before conclusions are drawn related to a possible mismatch in the real physical size of experimental and simulated source volumes.
47 OTHER INSTRUMENTATION↗
Bayesian inference in band excitation scanning probe microscopy for optimal dynamic model selection in imaging
The universal tendency in scanning probe microscopy (SPM) over the last two decades is to transition from simple 2D imaging to complex detection and spectroscopic imaging modes. The emergence of complex SPM engines brings forth the challenge of reliable data interpretation, i.e., conversion from detected signals to descriptors specific to tip–surface interactions and subsequently to material’s properties. In this work, we implemented a Bayesian inference approach for the analysis of the image formation mechanisms in band excitation SPM. Compared to the point estimates in classical functional fit approaches, Bayesian inference allows for the incorporation of extant knowledge of materials and probe behavior in the form of corresponding prior distribution and return the information on the material functionality in the form of readily interpretable posterior distributions. We explore the nonlinear mechanical behaviors spatially in a classical ferroelectric material, PbTiO 3 . We observe the non-trivial evolution of the Duffing stiffness term and the nonlinearity of the sample surface, determine spatial clustering of the nonlinear response, and perform a Landau analysis on predicting the nonlinear coefficient, which indicates that ferroelectric behavior can be a cause of the observed results. These observations suggest that the spectrum of anomalous behaviors at the ferroelectric domain walls may be broader than previously believed and can extend to non-conventional mechanical properties in addition to static and microwave conductance.
36 MATERIALS SCIENCE↗
Creating ground truth for nanocrystal morphology: a fully automated pipeline for unbiased transmission electron microscopy analysis
Control over colloidal nanocrystal morphology (size, size distribution, and shape) is important for tailoring the functionality of individual nanocrystals and their ensemble behavior. Despite this, traditional methods to quantify nanocrystal morphology are laborious. New developments in automated morphology classification will accelerate these analyses but the assessment of machine learning models is limited by human accuracy for ground truth, causing even unsupervised machine learning models to have inherent bias. Herein, we introduce synthetic image rendering to solve the ground truth problem of nanocrystal morphology classification. By simulating 2D images of nanocrystal shapes via a function of high-dimensional parameter space, we trained a convolutional neural network to link unique morphologies to their simulated parameters, defining nanocrystal morphology quantitatively rather than qualitatively. An automated pipeline then processes, quantitatively defines, and classifies nanocrystal morphology from experimental transmission electron microscopy (TEM) images. Using improved computer vision techniques, 42,650 nanocrystals were identified, assessed, and labeled with quantitative parameters, offering a 600-fold improvement in efficiency over best-practice manual measurements. Further, a classification algorithm was trained with a prediction accuracy of 99.5%, which can successfully analyze a range of concave, convex, and irregular nanocrystal shapes. The resulting pipeline was applied to differentiating two syntheses of nominally cuboidal CsPbBr 3 nanocrystals and uniquely classifying binary nickel sulfide nanocrystal phase based on morphology. This pipeline provides a simple, efficient, and unbiased method to quantify nanocrystal morphology and represents a practical route to construct large datasets with an absolute ground truth for training unbiased morphology-based machine learning algorithms.
77 NANOSCIENCE AND NANOTECHNOLOGY↗
DeepPatent2: A Large-Scale Benchmarking Corpus for Technical Drawing Understanding
Abstract Recent advances in computer vision (CV) and natural language processing have been driven by exploiting big data on practical applications. However, these research fields are still limited by the sheer volume, versatility, and diversity of the available datasets. CV tasks, such as image captioning, which has primarily been carried out on natural images, still struggle to produce accurate and meaningful captions on sketched images often included in scientific and technical documents. The advancement of other tasks such as 3D reconstruction from 2D images requires larger datasets with multiple viewpoints. We introduce DeepPatent2, a large-scale dataset, providing more than 2.7 million technical drawings with 132,890 object names and 22,394 viewpoints extracted from 14 years of US design patent documents. We demonstrate the usefulness of DeepPatent2 with conceptual captioning. We further provide the potential usefulness of our dataset to facilitate other research areas such as 3D image reconstruction and image retrieval.
97 MATHEMATICS AND COMPUTING↗
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.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Wavelength domain spatial frequency modulation imaging: enabling fiber optic delivery and detection
Spatial frequency modulation imaging (SPIFI) provides a simple architecture for modulating an extended illumination source that is compatible with single pixel imaging. We demonstrate wavelength domain SPIFI (WD-SPIFI) by encoding time-varying spatial frequencies in the spectral domain that can produce enhanced resolution images, like its spatial domain counterpart, spatial domain (SD) SPIFI. However, contrary to SD-SPIFI, WD-SPIFI enables remote delivery by single mode fiber, which can be attractive for applications where free-space imaging is not practical. Finally, we demonstrate a cascaded system incorporating WD-SPIFI in-line with SD-SPIFI enabling single pixel 2D imaging without any beam or sample scanning.
47 OTHER INSTRUMENTATION↗
Molecular imaging of plant-microbe interactions on the Brachypodium seed surface
Plant growth-promoting rhizobacteria (PGPR) play a crucial role in biological control and pathogenic defense on and with-in plant tissues, however the mechanism(s) by which plants associate with PGPR to elicit such beneficial effects needs further study. Here, we present high mass resolution time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging of Brachypodium distachyon (Brachypodium) seeds with and without exposure to two model PGPR, i.e., Gram-negative Pseudomonas fluorescens SBW25::GFP (P.) and Gram-positive Arthrobacter chlorophenolicus A6::GFP (A.). Delayed image extraction was used to image PGPB-treated seed sections to reveal morphological changes. ToF-SIMS spectral compari-son, principal component analysis (PCA), and two-dimensional (2D) imaging show that the selected PGPR have different effects on the host seed surface, resulting in changes in chemical composition and morphology. Metabolite prod-ucts and biomarkers, such as flavonoids, phenolic com-pounds, fatty acids, and indole-3-acetic acid (IAA), were ob-served on the PGPR-treated seed surfaces. These compounds had different distributions on the Brachypodium seed surface for the two PGPR, indicating that the different bacteria elicited distinct responses from the host. Our results illustrate that ToF-SIMS is an effective tool to study plant-microbe interac-tions and to provide insightful information with submicrome-ter lateral resolution of the chemical distributions associated with morphological features, potentially offering a new way to study the mechanisms underlying beneficial roles of PGPR.
PGPR, Brachypodium distachyon, ToF-SIMS, metabolit↗