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SNIa Cosmology Analysis Results from Simulated LSST Images: From Difference Imaging to Constraints on Dark Energy

Abstract The Vera Rubin Observatory Legacy Survey of Space and Time (LSST) is expected to process ∼10 6 transient detections per night. For precision measurements of cosmological parameters and rates, it is critical to understand the detection efficiency, magnitude limits, artifact contamination levels, and biases in the selection and photometry. Here we rigorously test the LSST Difference Image Analysis (DIA) pipeline using simulated images from the Rubin Observatory LSST Dark Energy Science Collaboration Data Challenge (DC2) simulation for the Wide-Fast-Deep survey area. DC2 is the first large-scale (300 deg 2 ) image simulation of a transient survey that includes realistic cadence, variable observing conditions, and CCD image artifacts. We analyze ∼15 deg 2 of DC2 over a 5 yr time span in which artificial point sources from Type Ia supernova (SNIa) light curves have been overlaid onto the images. The magnitude limits per filter are u = 23.66 mag, g = 24.69 mag, r = 24.06 mag, i = 23.45 mag, z = 22.54 mag, and y = 21.62 mag. The artifact contamination levels are ∼90% of all detections, corresponding to ∼1000 artifacts deg –2 in g band, and falling to 300 deg –2 in y band. The photometry has biases <1% for magnitudes 19.5 < m < 23. Our DIA performance on simulated images is similar to that of the Dark Energy Survey difference-imaging pipeline on real images. We also characterize DC2 image properties to produce catalog-level simulations needed for distance bias corrections. We find good agreement between DC2 data and simulations for distributions of signal-to-noise ratio, redshift, and fitted light-curve properties. Applying a realistic SNIa cosmology analysis for redshifts z < 1, we recover the input cosmology parameters to within statistical uncertainties.

79 ASTRONOMY AND ASTROPHYSICS↗

Conversion of mammographic images to appear with the noise and sharpness characteristics of a different detector and x-ray system

Purpose: Undertaking observer studies to compare imaging technology using clinical radiological images is challenging due to patient variability. To achieve a significant result, a large number of patients would be required to compare cancer detection rates for different image detectors and systems. The aim of this work was to create a methodology where only one set of images is collected on one particular imaging system. These images are then converted to appear as if they had been acquired on a different detector and x-ray system. Therefore, the effect of a wide range of digital detectors on cancer detection or diagnosis can be examined without the need for multiple patient exposures. Methods: Three detectors and x-ray systems [Hologic Selenia (ASE), GE Essential (CSI), Carestream CR (CR)] were characterized in terms of signal transfer properties, noise power spectra (NPS), modulation transfer function, and grid properties. The contributions of the three noise sources (electronic, quantum, and structure noise) to the NPS were calculated by fitting a quadratic polynomial at each spatial frequency of the NPS against air kerma. A methodology was developed to degrade the images to have the characteristics of a different (target) imaging system. The simulated images were created by first linearizing the original images such that the pixel values were equivalent to the air kerma incident at the detector. The linearized image was then blurred to match the sharpness characteristics of the target detector. Noise was then added to the blurred image to correct for differences between the detectors and any required change in dose. The electronic, quantum, and structure noise were added appropriate to the air kerma selected for the simulated image and thus ensuring that the noise in the simulated image had the same magnitude and correlation as the target image. A correction was also made for differences in primary grid transmission, scatter, and veiling glare. The method was validated by acquiring images of a CDMAM contrast detail test object (Artinis, The Netherlands) at five different doses for the three systems. The ASE CDMAM images were then converted to appear with the imaging characteristics of target CR and CSI detectors. Results: The measured threshold gold thicknesses of the simulated and target CDMAM images were closely matched at normal dose level and the average differences across the range of detail diameters were -4% and 0% for the CR and CSI systems, respectively. The conversion was successful for images acquired over a wide dose range. The average difference between simulated and target images for a given dose was a maximum of 11%. Conclusions: The validation shows that the image quality of a digital mammography image obtained with a particular system can be degraded, in terms of noise magnitude and color, sharpness, and contrast to account for differences in the detector and antiscatter grid. Potentially, this is a powerful tool for observer studies, as a range of image qualities can be examined by modifying an image set obtained at a single (better) image quality thus removing the patient variability when comparing systems.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Image Collection Simulation Using High-Resolution Atmospheric Modeling

A new method is described for simulating the passive remote sensing image collection of ground targets that includes effects from atmospheric physics and dynamics at fine spatial and temporal scales. The innovation in this research is the process of combining a high-resolution weather model with image collection simulation to attempt to account for heterogeneous and high-resolution atmospheric effects on image products. The atmosphere was modeled on a 3D voxel grid by a Large-Eddy Simulation (LES) driven by forcing data constrained by local ground-based and air-based observations. The spatial scale of the atmospheric model (10–100 m) came closer than conventional weather forecast scales (10–100 km) to approaching the scale of typical commercial multispectral imagery (2 m). This approach was demonstrated through a ground truth experiment conducted at the Department of Energy Atmospheric Radiation Measurement Southern Great Plains site. In this experiment, calibrated targets (colored spectral tarps) were placed on the ground, and the scene was imaged with WorldView-3 multispectral imagery at a resolution enabling the tarps to be visible in at least 9–12 image pixels. The image collection was simulated with Digital Imaging and Remote Sensing Image Generation (DIRSIG) software, using the 3D atmosphere from the LES model to generate a high-resolution cloud mask. The high-resolution atmospheric model-predicted cloud coverage was usually within 23% of the measured cloud cover. The simulated image products were comparable to the WorldView-3 satellite imagery in terms of the variations of cloud distributions and spectral properties of the ground targets in clear-sky regions, suggesting the potential utility of the proposed modeling framework in improving simulation capabilities, as well as testing and improving the operation of image collection processes.

54 ENVIRONMENTAL SCIENCES↗

Simulating realistic imaging conditions for in situ liquid microscopy

In situ transmission electron microscopy enables the imaging of biological cells, macromolecular protein complexes, nanoparticles, and other systems in a near-native environment. In order to improve interpretation of image contrast features and also predict ideal imaging conditions ahead of time, new virtual electron microscopic techniques are needed. A technique for virtual fluid-stage high-angle annular dark-field scanning transmission electron microscopy with the multislice method is presented that enables the virtual imaging of model fluid-stage systems composed of millions of atoms. The virtual technique is exemplified by simulating images of PbS nanoparticles under different imaging conditions and the results agree with previous experimental findings. General insight is obtained on the influence of the effects of fluid path length, membrane thickness, nanoparticle position, defocus and other microscope parameters on attainable image quality.

Atomistic model↗

Discriminating Accretion States via Rotational Symmetry in Simulated Polarimetric Images of M87

In 2017 April, the Event Horizon Telescope observed the shadow of the supermassive black hole at the core of the elliptical galaxy Messier 87. While the original image was constructed from measurements of the total intensity, full polarimetric data were also collected, and linear polarimetric images are expected in the near future. We propose a modal image decomposition of the linear polarization field into basis functions with varying azimuthal dependence of the electric vector position angle. We apply this decomposition to images of ray traced general relativistic magnetohydrodynamics simulations of the Messier 87 accretion disk. Furthermore, for simulated images that are physically consistent with previous observations, the magnitude of the coefficient associated with rotational symmetry, β2, is a useful discriminator between accretion states. We find that at 20 μas resolution, $| {\beta }_{2}| $ is greater than 0.2 only for models of disks with horizon-scale magnetic pressures large enough to disrupt steady accretion. We also find that images with a more radially directed electric vector position angle correspond to models with higher black hole spin. Our analysis demonstrates the utility of the proposed decomposition as a diagnostic framework to improve constraints on theoretical models.

79 ASTRONOMY AND ASTROPHYSICS↗

SU-E-J-30: Benchmark Image-Based TCP Calculation for Evaluation of PTV Margins for Lung SBRT Patients

Purpose: Tumor control probability (TCP) calculated with accumulated radiation doses may help design appropriate treatment margins. Image registration errors, however, may compromise the calculated TCP. The purpose of this study is to develop benchmark CT images to quantify registration-induced errors in the accumulated doses and their corresponding TCP. Methods: 4DCT images were registered from end-inhale (EI) to end-exhale (EE) using a “demons” algorithm. The demons DVFs were corrected by an FEM model to get realistic deformation fields. The FEM DVFs were used to warp the EI images to create the FEM-simulated images. The two images combined with the FEM DVF formed a benchmark model. Maximum intensity projection (MIP) images, created from the EI and simulated images, were used to develop IMRT plans. Two plans with 3 and 5 mm margins were developed for each patient. With these plans, radiation doses were recalculated on the simulated images and warped back to the EI images using the FEM DVFs to get the accumulated doses. The Elastix software was used to register the FEM-simulated images to the EI images. TCPs calculated with the Elastix-accumulated doses were compared with those generated by the FEM to get the TCP error of the Elastix registrations. Results: For six lung patients, the mean Elastix registration error ranged from 0.93 to 1.98 mm. Their relative dose errors in PTV were between 0.28% and 6.8% for 3mm margin plans, and between 0.29% and 6.3% for 5mm-margin plans. As the PTV margin reduced from 5 to 3 mm, the mean TCP error of the Elastix-reconstructed doses increased from 2.0% to 2.9%, and the mean NTCP errors decreased from 1.2% to 1.1%. Conclusion: Patient-specific benchmark images can be used to evaluate the impact of registration errors on the computed TCPs, and may help select appropriate PTV margins for lung SBRT patients.

60 APPLIED LIFE SCIENCES↗

Beam Characterization at the Neutron Radiography Facility

The quality of a neutron imaging beam directly impacts the quality of radiographic images produced using that beam. Fully characterizing a neutron beam, including determination of the beam’s effective length-to-diameter ratio, neutron flux profile, energy spectrum, image quality, and beam divergence, is vital for producing quality radiographic images. This project characterized the east neutron imaging beamline at the Idaho National Laboratory Neutron Radiography Reactor (NRAD). The experiments which measured the beam’s effective length-to-diameter ratio and image quality are based on American Society for Testing and Materials (ASTM) standards. An analysis of the image produced by a calibrated phantom measured the beam divergence. The energy spectrum measurements consist of a series of foil irradiations using a selection of activation foils, compared to the results produced by a Monte Carlo n-Particle (MCNP) model of the beamline. Improvement of the existing NRAD MCNP beamline model includes validation of the model’s energy spectrum and the development of enhanced image simulation methods. The image simulation methods predict the radiographic image of an object based on the foil reaction rate data obtained by placing a model of the object in front of the image plane in an MCNP beamline model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Realistic simulation of reduced-dose CT with noise modeling and sinogram synthesis using DICOM CT images

Purpose: Reducing the patient dose while maintaining the diagnostic image quality during CT exams is the subject of a growing number of studies, in which simulations of reduced-dose CT with patient data have been used as an effective technique when exploring the potential of various dose reduction techniques. Difficulties in accessing raw sinogram data, however, have restricted the use of this technique to a limited number of institutions. Here, we present a novel reduced-dose CT simulation technique which provides realistic low-dose images without the requirement of raw sinogram data. Methods: Two key characteristics of CT systems, the noise equivalent quanta (NEQ) and the algorithmic modulation transfer function (MTF), were measured for various combinations of object attenuation and tube currents by analyzing the noise power spectrum (NPS) of CT images obtained with a set of phantoms. Those measurements were used to develop a comprehensive CT noise model covering the reduced x-ray photon flux, object attenuation, system noise, and bow-tie filter, which was then employed to generate a simulated noise sinogram for the reduced-dose condition with the use of a synthetic sinogram generated from a reference CT image. The simulated noise sinogram was filtered with the algorithmic MTF and back-projected to create a noise CT image, which was then added to the reference CT image, finally providing a simulated reduced-dose CT image. The simulation performance was evaluated in terms of the degree of NPS similarity, the noise magnitude, the bow-tie filter effect, and the streak noise pattern at photon starvation sites with the set of phantom images. Results: The simulation results showed good agreement with actual low-dose CT images in terms of their visual appearance and in a quantitative evaluation test. The magnitude and shape of the NPS curves of the simulated low-dose images agreed well with those of real low-dose images, showing discrepancies of less than +/−3.2% in terms of the noise power at the peak height and +/−1.2% in terms of the spatial frequency at the peak height. The magnitudes of the noise measured for 12 different combinations the phantom size, tube current, and reconstruction kernel for the simulated and real low-dose images were very similar, with differences of 0.1 to 4.7%. Thep value for a statistical testing of the difference in the noise magnitude ranged from 0.99 to 0.11, showing that there was no difference statistically between the noise magnitudes of the real and simulated low-dose images using our method. The strength and pattern of the streak noise in an anthropomorphic phantom was also consistent with expectations. Conclusions: A novel reduced-dose CT simulation technique was developed which uses only CT images while not requiring raw sinogram data. Our method can provide realistic simulation results under reduced-dose conditions both in terms of the noise magnitude and the textual appearance. This technique has the potential to promote clinical research for patient dose reductions.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

The Blending ToolKit: A simulation framework for evaluation of galaxy detection and deblending

We present an open source Python library for simulating overlapping (i.e., blended) images of galaxies and performing self-consistent comparisons of detection and deblending algorithms based on a suite of metrics. The package, named Blending Toolkit (BTK), serves as a modular, flexible, easy-to-install, and simple-to-use interface for exploring and analyzing systematic effects related to blended galaxies in cosmological surveys such as the Vera Rubin Observatory Legacy Survey of Space and Time (LSST). BTK has three main components: (1) a set of modules that perform fast image simulations of blended galaxies, using the open source image simulation package GalSim; (2) a module that standardizes the inputs and outputs of existing deblending algorithms; (3) a library of deblending metrics commonly defined in the galaxy deblending literature. In combination, these modules allow researchers to explore the impacts of galaxy blending in cosmological surveys. Additionally, BTK provides researchers who are developing a new deblending algorithm a framework to evaluate algorithm performance and make principled comparisons with existing deblenders. BTK includes a suite of tutorials and comprehensive documentation. The source code is publicly available on GitHub at https://github.com/LSSTDESC/BlendingToolKit.

79 ASTRONOMY AND ASTROPHYSICS↗

Evaluation of an improved algorithm for producing realistic 3D breast software phantoms: Application for mammography

Purpose: This work presents an improved algorithm for the generation of 3D breast software phantoms and its evaluation for mammography. Methods: The improved methodology has evolved from a previously presented 3D noncompressed breast modeling method used for the creation of breast models of different size, shape, and composition. The breast phantom is composed of breast surface, duct system and terminal ductal lobular units, Cooper's ligaments, lymphatic and blood vessel systems, pectoral muscle, skin, 3D mammographic background texture, and breast abnormalities. The key improvement is the development of a new algorithm for 3D mammographic texture generation. Simulated images of the enhanced 3D breast model without lesions were produced by simulating mammographic image acquisition and were evaluated subjectively and quantitatively. For evaluation purposes, a database with regions of interest taken from simulated and real mammograms was created. Four experienced radiologists participated in a visual subjective evaluation trial, as they judged the quality of the simulated mammograms, using the new algorithm compared to mammograms, obtained with the old modeling approach. In addition, extensive quantitative evaluation included power spectral analysis and calculation of fractal dimension, skewness, and kurtosis of simulated and real mammograms from the database. Results: The results from the subjective evaluation strongly suggest that the new methodology for mammographic breast texture creates improved breast models compared to the old approach. Calculated parameters on simulated images such as {beta} exponent deducted from the power law spectral analysis and fractal dimension are similar to those calculated on real mammograms. The results for the kurtosis and skewness are also in good coincidence with those calculated from clinical images. Comparison with similar calculations published in the literature showed good agreement in the majority of cases. Conclusions: The improved methodology generated breast models with increased realism compared to the older model as shown in evaluations of simulated images by experienced radiologists. It is anticipated that the realism will be further improved using an advanced image simulator so that simulated images may be used in feasibility studies in mammography.

60 APPLIED LIFE SCIENCES↗

Automated registration of diagnostic to prediagnostic x-ray mammograms: Evaluation and comparison to radiologists' accuracy

Purpose: To compare and evaluate intensity-based registration methods for computation of serial x-ray mammogram correspondence. Methods: X-ray mammograms were simulated from MRIs of 20 women using finite element methods for modeling breast compressions and employing a MRI/x-ray appearance change model. The parameter configurations of three registration methods, affine, fluid, and free-form deformation (FFD), were optimized for registering x-ray mammograms on these simulated images. Five mammography film readers independently identified landmarks (tumor, nipple, and usually two other normal features) on pairs of diagnostic and corresponding prediagnostic digitized images from 52 breast cancer cases. Landmarks were independently reidentified by each reader. Target registration errors were calculated to compare the three registration methods using the reader landmarks as a gold standard. Data were analyzed using multilevel methods. Results: Between-reader variability varied with landmark (p<0.01) and screen (p=0.03), with between-reader mean distance (mm) in point location on the diagnostic/prediagnostic images of 2.50 (95% CI 1.95, 3.15)/2.84 (2.24, 3.55) for nipples and 4.26 (3.43, 5.24)/4.76 (3.85, 5.84) for tumors. Registration accuracy was sensitive to the type of landmark and the amount of breast density. For dense breasts ({>=}40%), the affine and fluid methods outperformed FFD. For breasts with lower density, the affine registration surpassed both fluid and FFD. Mean accuracy (mm) of the affine registration varied between 3.16 (95% CI 2.56, 3.90) for nipple points in breasts with density 20%-39% and 5.73 (4.80, 6.84) for tumor points in breasts with density <20%. Conclusions: Affine registration accuracy was comparable to that between independent film readers. More advanced two-dimensional nonrigid registration algorithms were incapable of increasing the accuracy of image alignment when compared to affine registration.

60 APPLIED LIFE SCIENCES↗

A semiempirical linear model of indirect, flat-panel x-ray detectors

Purpose: It is important to understand signal and noise transfer in the indirect, flat-panel x-ray detector when developing and optimizing imaging systems. For optimization where simulating images is necessary, this study introduces a semiempirical model to simulate projection images with user-defined x-ray fluence interaction. Methods: The signal and noise transfer in the indirect, flat-panel x-ray detectors is characterized by statistics consistent with energy-integration of x-ray photons. For an incident x-ray spectrum, x-ray photons are attenuated and absorbed in the x-ray scintillator to produce light photons, which are coupled to photodiodes for signal readout. The signal mean and variance are linearly related to the energy-integrated x-ray spectrum by empirically determined factors. With the known first- and second-order statistics, images can be simulated by incorporating multipixel signal statistics and the modulation transfer function of the imaging system. To estimate the semiempirical input to this model, 500 projection images (using an indirect, flat-panel x-ray detector in the breast CT system) were acquired with 50-100 kilovolt (kV) x-ray spectra filtered with 0.1-mm tin (Sn), 0.2-mm copper (Cu), 1.5-mm aluminum (Al), or 0.05-mm silver (Ag). The signal mean and variance of each detector element and the noise power spectra (NPS) were calculated and incorporated into this model for accuracy. Additionally, the modulation transfer function of the detector system was physically measured and incorporated in the image simulation steps. For validation purposes, simulated and measured projection images of air scans were compared using 40 kV/0.1-mm Sn, 65 kV/0.2-mm Cu, 85 kV/1.5-mm Al, and 95 kV/0.05-mm Ag. Results: The linear relationship between the measured signal statistics and the energy-integrated x-ray spectrum was confirmed and incorporated into the model. The signal mean and variance factors were linearly related to kV for each filter material (r{sup 2} of signal mean to kV: 0.91, 0.93, 0.86, and 0.99 for 0.1-mm Sn, 0.2-mm Cu, 1.5-mm Al, and 0.05-mm Ag, respectively; r{sup 2} of signal variance to kV: 0.99 for all four filters). The comparison of the signal and noise (mean, variance, and NPS) between the simulated and measured air scan images suggested that this model was reasonable in predicting accurate signal statistics of air scan images using absolute percent error. Overall, the model was found to be accurate in estimating signal statistics and spatial correlation between the detector elements of the images acquired with indirect, flat-panel x-ray detectors. Conclusions: The semiempirical linear model of the indirect, flat-panel x-ray detectors was described and validated with images of air scans. The model was found to be a useful tool in understanding the signal and noise transfer within indirect, flat-panel x-ray detector systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Monitoring of chlorin-based photosensitiser localisation with dual-wavelength fluorescence imaging: numerical simulations

An approach to the estimation of chlorin-based photosensitiser localisation with dual-wavelength fluorescence imaging after topical application or intravenous injection is developed based on numerical simulations. Fluorescence imaging, which is commonly used for the monitoring of photosensitiser distribution within tissue, does not allow for its depth-resolved imaging. Chlorin-based photosensitisers feature two peaks in their absorption spectra corresponding to 402 and 662 nm, which allows for fluorescence excitation at two wavelengths with significantly different light penetration depths into biotissues. The ratio of fluorescence signals detected upon irradiation at different excitation wavelengths is shown to provide the information about photosensitiser localisation. The cases of exponential in-depth decay of the photosensitiser concentration and uniform photosensitiser distribution within the layer at a certain depth within the medium are analysed. These cases simulate topical application of photosensitiser and its intravenous injection and further accumulation in tumour, respectively. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Frequency and Clinical Significance of Previously Undetected Incidental Findings Detected on Computed Tomography Simulation Scans for Breast Cancer Patients

Purpose: To determine the frequency and clinical significance of previously undetected incidental findings found on computed tomography (CT) simulation images for breast cancer patients. Methods and Materials: All CT simulation images were first interpreted prospectively by radiation oncologists and then double-checked by diagnostic radiologists. The official reports of CT simulation images for 881 consecutive postoperative breast cancer patients from 2009 to 2010 were retrospectively reviewed. Potentially important incidental findings (PIIFs) were defined as any previously undetected benign or malignancy-related findings requiring further medical follow-up or investigation. For all patients in whom a PIIF was detected, we reviewed the clinical records to determine the clinical significance of the PIIF. If the findings from the additional studies prompted by a PIIF required a change in management, the PIIF was also recorded as a clinically important incidental finding (CIIF). Results: There were a total of 57 (6%) PIIFs. The 57 patients in whom a PIIF was detected were followed for a median of 17 months (range, 3-26). Six cases of CIIFs (0.7% of total) were detected. Of the six CIIFs, three (50%) cases had not been noted by the radiation oncologist until the diagnostic radiologist detected the finding. On multivariate analysis, previous CT examination was an independent predictor for PIIF (p = 0.04). Patients who had not previously received chest CT examinations within 1 year had a statistically significantly higher risk of PIIF than those who had received CT examinations within 6 months (odds ratio, 3.54; 95% confidence interval, 1.32-9.50; p = 0.01). Conclusions: The rate of incidental findings prompting a change in management was low. However, radiation oncologists appear to have some difficulty in detecting incidental findings that require a change in management. Considering cost, it may be reasonable that routine interpretations are given to those who have not received previous chest CT examinations within 1 year.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

High-pressure phase transition in 3-D printed nanolamellar high-entropy alloy by imaging and simulation insights

Abstract We report on the high-resolution imaging and molecular dynamics simulations of a 3D-printed eutectic high-entropy alloy (EHEA) Ni 40 Co 20 Fe 10 Cr 10 Al 18 W 2 consisting of nanolamellar BCC and FCC phases. The direct lattice imaging of 3D-printed samples shows the Kurdjumov–Sachs (K–S) orientation relation {111} FCC parallel to {110} BCC planes in the dual-phase lamellae. Unlike traditional iron and steels, this alloy shows an irreversible BCC-to-FCC phase transformation under high pressures. The nanolamellar morphology is maintained after pressure cycling to 30 GPa, and nano-diffraction studies show both layers to be in the FCC phase. The chemical compositions of the dual-phase lamellae after pressure recovery remain unchanged, suggesting a diffusion-less BCC–FCC transformation in this EHEA. The lattice imaging of the pressure-recovered sample does not show any specific orientation relation between the two resulting FCC phases, indicating that many grain orientations are produced during the BCC–FCC phase transformation. Molecular dynamics simulations on phase transformation in a nanolamellar BCC/FCC in K–S orientation show that phase transformation from BCC to FCC is completed under high pressures, and the FCC phase is retained on decompression aided by the stable interfaces. Our work elucidates the irreversible phase transformation under static compression, providing an understanding of the orientation relationships in 3-D printed EHEA under high pressures.

3-D Printing↗

Quantitative Analysis of HAADF–STEM Images of MoVTeTaO M1 Phase Catalyst for Propane Ammoxidation to Acrylonitrile

Abstract High‐angle annular dark‐field scanning transmission electron microscopy (HAADF–STEM) image simulations were performed to determine accurate metal distributions in the MoVTeTaO M1 phase catalyst for propane ammoxidation. QSTEM simulation, based on a multislice method with the frozen phonon approximation, was chosen because of the excellent agreement between experimental and simulated HAADF–STEM images. This simulation method successfully provided accurate metal distributions in the MoVTeTaO M1 phase and indicated significantly lower V occupancies of the linking sites 1, 2, 3, 4, and 7, and higher Ta occupancy in site 9 than the previously reported metal occupancies. This novel methodology for accurate HAADF–STEM image analysis is a valuable tool for accurate analysis of local chemical compositions in a wide range of ordered catalytic materials.

Woo, Jungwon↗

Simulated NMIS Imaging Data for an Unknown Object

This report presents simulated Nuclear Materials Identification System (NMIS) imaging data for an unclassified object, whose characteristics are initially unknown to the reader. This data will be used to test various analysis capabilities and was created with a simple deterministic ray-tracing algorithm. NMIS is a time-dependent coincidence counting system that is used to characterize both fissile and non-fissile materials undergoing nondestructive assay. NMIS characterizes materials by interrogating them with neutrons, either from an associated-particle deuterium-tritium (DT) neutron generator, which produces a time and directionally tagged monoenergetic beam of 14.1 MeV neutrons, or a time-tagged spontaneous fission source in an ionization chamber.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗