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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Enhanced spatial resolution of Eljen-204 plastic scintillators for use in rep-rated proton diagnostics

A pixelated scintillator has been designed, fabricated, and tested using a laser-accelerated proton source for use in proton diagnostics at rep-rated laser facilities. The work presented here demonstrates the enhanced spatial resolution of thin, organic scintillators through a novel pixelation technique. Furthermore, experimental measurements using laser-generated protons incident onto 130 μm-thick scintillators indicate a >20% reduction in the scintillator point spread function (PSF) for the detectors tested. The best performing pixelated detector reduced the ~200 μm PSF of the stock material to ~150 μm. The fabrication technique may be tailored to reduce the pixel size and achieve higher spatial resolutions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Design of the high-yield time-gated x-ray hot-spot imager for OMEGA

Time-resolved x-ray self-emission imaging of hot spots in inertial confinement fusion experiments along several lines of sight provides critical information on the pressure and the transient morphology of the hot spot on the University of Rochester’s OMEGA Laser System. At least three quasi-orthogonal lines of sight are required to infer the tomographic information of the hot spots of deuterium–tritium cryogenic layered implosions. OMEGA currently has two time-gated x-ray hot-spot imagers: the time-resolved Kirkpatrick–Baez x-ray microscope and the single-line-of-sight, time-resolved x-ray imager (SLOS-TRXI). The time-gated x-ray hot-spot imager (XRHSI) is being developed for use on OMEGA as the third line of sight for the high-yield operation of up to 4 × 10 14 neutrons. XRHSI follows the SLOS-TRXI concept; however, it will have improved spatial and temporal resolutions of 5 μm and 20 ps, respectively. The simultaneous operation of the three instruments will provide 3-D reconstructions of the assembled hot-spot fuel at various times through peak thermonuclear output. The technical approach consists of a pinhole array imager and demagnifying time-dilation drift tube that are coupled to two side-by-side hybrid complementary metal–oxide semiconductor (hCMOS) image sensors. To minimize the background and to harden the diagnostics, an angled drift-tube assembly shifting the hCMOS sensors out of the direct line of sight and neutron shielding will be applied. As a result, the technical design space for the instrument will be discussed and the conceptual design will be presented.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Sparse regression for plasma physics

Many scientific problems can be formulated as sparse regression, i.e., regression onto a set of parameters when there is a desire or expectation that some of the parameters are exactly zero or do not substantially contribute. This includes many problems in signal and image processing, system identification, optimization, and parameter estimation methods such as Gaussian process regression. Sparsity facilitates exploring high-dimensional spaces while finding parsimonious and interpretable solutions. In the present work, we illustrate some of the important ways in which sparse regression appears in plasma physics and point out recent contributions and remaining challenges to solving these problems in this field. Further, a brief review is provided for the optimization problem and the state-of-the-art solvers, especially for constrained and high-dimensional sparse regression.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Genetic algorithm-based geometry calibration for dynamic compression x-ray diffraction experiments

An important component of dynamic compression x-ray diffraction (XRD) experiment analysis is geometry calibration: proper data interpretation requires knowledge of the precise detector position and orientation and, if the experiment involves a single-crystal sample, knowledge of the lattice orientation. The determination of these parameters in the arbitrary three-dimensional (3D) scattering geometries often present in dynamic compression facilities is challenging, as the associated optimization problem can be highly nonlinear, nonsmooth, and discontinuous. We present a genetic algorithm-based approach for performing dynamic compression XRD calibrations that overcomes these obstacles. We provide details regarding the image processing, algorithm implementation, and open-source software deployment and demonstrate the capability of the approach to calibrate the detector and crystal parameters in 3D geometries. Notably, we demonstrate the solver’s capacity to find the crystal orientation without a priori rotation constraints.

Brown, Nathan P. [Sandia National Laboratories (SN↗
DOE OSTI2020

Subdomain cryo-EM structure of nodaviral replication protein A crown complex provides mechanistic insights into RNA genome replication

For positive-strand RNA [(+)RNA] viruses, the major target for antiviral therapies is genomic RNA replication, which occurs at poorly understood membrane-bound viral RNA replication complexes. Recent cryoelectron microscopy (cryo-EM) of nodavirus RNA replication complexes revealed that the viral double-stranded RNA replication template is coiled inside a 30- to 90-nm invagination of the outer mitochondrial membrane, whose necked aperture to the cytoplasm is gated by a 12-fold symmetric, 35-nm diameter “crown” complex that contains multifunctional viral RNA replication protein A. Here we report optimizing cryo-EM tomography and image processing to improve crown resolution from 33 to 8.5 Å. This resolves the crown into 12 distinct vertical segments, each with 3 major subdomains: A membrane-connected basal lobe and an apical lobe that together comprise the ~19-nm-diameter central turret, and a leg emerging from the basal lobe that connects to the membrane at ~35-nm diameter. Despite widely varying replication vesicle diameters, the resulting two rings of membrane interaction sites constrain the vesicle neck to a highly uniform shape. Labeling protein A with a His-tag that binds 5-nm Ni-nanogold allowed cryo-EM tomography mapping of the C terminus of protein A to the apical lobe, which correlates well with the predicted structure of the C-proximal polymerase domain of protein A. These and other results indicate that the crown contains 12 copies of protein A arranged basally to apically in an N-to-C orientation. Moreover, the apical polymerase localization has significant mechanistic implications for template RNA recruitment and (-) and (+)RNA synthesis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Cryo-EM structure determination of small proteins by nanobody-binding scaffolds (Legobodies)

We describe a general method that allows structure determination of small proteins by single-particle cryo-electron microscopy (cryo-EM). The method is based on the availability of a target-binding nanobody, which is then rigidly attached to two scaffolds: 1) a Fab fragment of an antibody directed against the nanobody and 2) a nanobody-binding protein A fragment fused to maltose binding protein and Fab-binding domains. The overall ensemble of ~120 kDa, called Legobody, does not perturb the nanobody–target interaction, is easily recognizable in EM images due to its unique shape, and facilitates particle alignment in cryo-EM image processing. The utility of the method is demonstrated for the KDEL receptor, a 23-kDa membrane protein, resulting in a map at 3.2-Å overall resolution with density sufficient for de novo model building, and for the 22-kDa receptor-binding domain (RBD) of SARS-CoV-2 spike protein, resulting in a map at 3.6-Å resolution that allows analysis of the binding interface to the nanobody. The Legobody approach thus overcomes the current size limitations of cryo-EM analysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Fringing Analysis and Simulation for the Vera C. Rubin Observatory’s Legacy Survey of Space and Time

Abstract The presence of fringing in astronomical Charge-Coupled Device (CCD) images will have an impact on photometric quality and measurements. Yet its impact on the Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) has not been fully studied. We present a detailed study on fringing for CCDs already implemented on the Rubin Observatory LSST Camera’s focal plane. After making physical measurements and knowing the compositions, we developed a model for the e2v CCDs. We present a method to fit for the internal height variation of the epoxy layer within the sensors based on fringing measurements in a laboratory setting. This method is generic enough that it can be easily modified to work for other CCDs. Using the derived fringing model, we successfully reproduce comparable fringing amplitudes that match the observed levels in images taken by existing telescopes with different optical designs. This model is then used to forecast the expected level of fringing in a single LSST y -band sky background exposure with Rubin telescope optics in the presence of a realistic time-varying sky spectrum. The predicted fringing amplitude in LSST images ranges from 0.04% to 0.2% depending on the location of a CCD on the focal plane. We find that the predicted variation in surface brightness caused by fringing in LSST y -band sky background images is about 0.6 μ Jy arcsec − 2 , which is 40 times larger than the current measurement error. We conclude that it is necessary to include fringing correction in the Rubin’s LSST image processing pipeline.

Astronomy & Astrophysics↗
DOE OSTI2024

Mitigation of the Brighter-fatter Effect in the LSST Camera

Abstract Thick, fully depleted charge-coupled devices are known to exhibit nonlinear behavior at high signal levels due to the dynamic behavior of charges collecting in the potential wells of pixels, called the brighter-fatter effect (BFE). The effect results in distorted images of bright calibration stars, creating a flux-dependent point-spread function that if left unmitigated, could make up a large fraction of the error budget in Stage IV weak-lensing (WL) surveys such as the Legacy Survey of Space and Time (LSST). In this paper, we analyze image measurements of flat fields and artificial stars taken at different illumination levels with the LSST Camera (LSSTCam) at SLAC National Accelerator Laboratory in order to quantify this effect in the LSSTCam before and after a previously introduced correction technique. We observe that the BFE evolves anisotropically as a function of flux due to higher-order BFEs, which violates the fundamental assumption of this correction method. We then introduce a new method based on a physically motivated model to account for these higher-order terms in the correction, and then we test the modified correction on both data sets. We find that the new method corrects the effect in flat fields better than it corrects the effect in artificial stars, which we suggest is the result of sub-pixel physics not included in this correction model. We use these results to define a new metric for the full-well capacity of our sensors and advise image processing strategies to further limit the impact of the effect on LSST WL science pathways.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Third data release of the Hyper Suprime-Cam Subaru Strategic Program

This work presents the third data release of the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP), a wide-field multi-band imaging survey with the Subaru 8.2 m telescope. HSC-SSP has three survey layers (Wide, Deep, and UltraDeep) with different area coverages and depths, designed to address a wide array of astrophysical questions. This third release from HSC-SSP includes data from 278 nights of observing time and covers about 670 deg 2 in all five broad-band filters (grizy) at the full depth (~26 mag at 5σ depending on filter) in the Wide layer. If we include partially observed areas, the release covers 1470 deg 2 . The Deep and UltraDeep layers have ~80% of the originally planned integration times, and are considered done, as we have slightly changed the observing strategy in order to compensate for various time losses. There are a number of updates in the image processing pipeline. Of particular importance is the change in the sky subtraction algorithm; we subtract the sky on small scales before the detection and measurement stages, which has significantly reduced the number of false detections. Thanks to this and other updates, the overall quality of the processed data has improved since the previous release. However, there are limitations in the data (for example, the pipeline is not optimized for crowded fields), and we encourage the user to check the quality assurance plots as well as a list of known issues before exploiting the data. The data release website is https://hsc-release.mtk.nao.ac.jp.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Synthesizing pseudo-Kossel lines from neutron transmission data. I. An analytical approach for recovering single-crystal orientation

The energy-dispersive neutron spectra transmitted through single crystals are characterized by sharp Bragg dips at specific wavelengths, where Bragg's law is being fulfilled for certain crystallographic planes. This phenomenon allows for developing methods for crystal-orientation determination techniques similar to electron backscatter diffraction and X-ray diffraction microscopy. This work presents a new procedure to recover the orientation matrix for single crystals using transmission spectra recorded during rotation of a crystal about an axis perpendicular to a polychromatic neutron beam. The proposed method consists of an initial transformation of the as-collected wavelength–rotation maps to a wavevector $\textit{K}$ space, resulting in linear pseudo-Kossel lines that are suitable for analysis and indexing using image-processing procedures. Further, simulated neutron transmission spectra through a copper crystal with known orientations were used to set and prove the numerical approach. This technique may be expanded for cases where the neutron beam intersects multiple single-crystal grains with different orientations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Assessing an aqueous flow cell designed for in situ crystal growth under X-ray nanotomography and effects of radiolysis products

Nucleation and growth of minerals has broad implications in the geological, environmental and materials sciences. Recent developments in fast X-ray nanotomography have enabled imaging of crystal growth in solutions in situ with a resolution of tens of nanometres, far surpassing optical microscopy. Here, a low-cost, custom-designed aqueous flow cell dedicated to the study of heterogeneous nucleation and growth of minerals in aqueous environments is shown. To gauge the effects of radiation damage from the imaging process on growth reactions, radiation-induced morphological changes of barite crystals (hundreds of nanometres to ∼1 µm) that were pre-deposited on the wall of the flow cell were investigated. Under flowing solution, minor to major crystal dissolution was observed when the tomography scan frequency was increased from every 30 min to every 5 min (with a 1 min scan duration). The production of reactive radicals from X-ray induced water radiolysis and decrease of pH close to the surface of barite are likely responsible for the observed dissolution. The flow cell shown here can possibly be adopted to study a wide range of other chemical reactions in solutions beyond crystal nucleation and growth where the combination of fast flow and fast scan can be used to mitigate the radiation effects.

36 MATERIALS SCIENCE↗
DOE OSTI2024

VitroJet: new features and case studies

Single-particle cryo-electron microscopy has become a widely adopted method in structural biology due to many recent technological advances in microscopes, detectors and image processing. Before being able to inspect a biological sample in an electron microscope, it needs to be deposited in a thin layer on a grid and rapidly frozen. The VitroJet was designed with this aim, as well as avoiding the delicate manual handling and transfer steps that occur during the conventional grid-preparation process. Since its creation, numerous technical developments have resulted in a device that is now widely utilized in multiple laboratories worldwide. It features plasma treatment, low-volume sample deposition through pin printing, optical ice-thickness measurement and cryofixation of pre-clipped Autogrids through jet vitrification. This paper presents recent technical improvements to the VitroJet and the benefits that it brings to the cryo-EM workflow. A wide variety of applications are shown: membrane proteins, nucleosomes, fatty-acid synthase, Tobacco mosaic virus, lipid nanoparticles, tick-borne encephalitis viruses and bacteriophages. These case studies illustrate the advancement of the VitroJet into an instrument that enables accurate control and reproducibility, demonstrating its suitability for time-efficient cryo-EM structure determination.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

A Two-Tier Convolutional Neural Network for Combined Detection and Segmentation in Biological Imagery

Deep learning techniques have been useful for modern microscopy imaging techniques to further study and analyze biological structures and organs. Convolutional neural networks (CNN) have improved 2D object detection, localization, and segmentation. For imagery containing biological structures with depth, it is especially desirable to perform these tasks in 3D. Traditionally, performing these tasks simultaneously in 3D has proven to be computationally expensive. Currently available methodologies thus largely work to segment 3D objects from 2D images (without context from captured 3D volumes). In this work, we present a novel approach to perform fast and accurate localization, detection, and segmentation of volumes containing cells. Specifically, in our method, we modify and tune two state-of-the-art CNNs, namely 2D YOLOv2 and 3D U-Net, and combine them with a new fusion and image processing algorithms. Annotated volumes in this space are limited, and we have created synthetic data that mimics actual structures for training and testing our proposed approach. Promising results on this test data demonstrate the value of the technique and offers a methodology for 3D cell analysis in real microscopy imagery.

Ziabari, Amir↗
DOE OSTI2025

Random Walks With Tweedie: A Unified View of Score-Based Diffusion Models [In the Spotlight]

We present a concise derivation for several influential score-based diffusion models that relies on only a few textbook results. Diffusion models have recently emerged as powerful tools for generating realistic, synthetic signals—particularly natural images—and often play a role in state-of-the-art algorithms for inverse problems in image processing. While these algorithms are often surprisingly simple, the theory behind them is not, and multiple complex theoretical justifications exist in the literature. Here, in this study, we provide a simple and largely self-contained theoretical justification for score-based diffusion models that is targeted towards the signal processing community. This approach leads to generic algorithmic templates for training and generating samples with diffusion models. We show that several influential diffusion models correspond to particular choices within these templates and demonstrate that alternative, more straightforward algorithmic choices can provide comparable results. This approach has the added benefit of enabling conditional sampling without any likelihood approximation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Robust and Simple ADMM Penalty Parameter Selection

We present a new method for online selection of the penalty parameter for the alternating direction method of multipliers (ADMM) algorithm. ADMM is a widely used method for solving a range of optimization problems, including those that arise in signal and image processing. In its standard form, ADMM includes a scalar hyperparameter, known as the penalty parameter, which usually has to be tuned to achieve satisfactory empirical convergence. In this work, we develop a framework for analyzing the ADMM algorithm applied to a quadratic problem as an affine fixed point iteration. Using this framework, we develop a new method for automatically tuning the penalty parameter by detecting when it has become too large or small. We analyze this and several other methods with respect to their theoretical properties, i.e., robustness to problem transformations, and empirical performance on several optimization problems. Our proposed algorithm is based on a theoretical framework with clear, explicit assumptions and approximations, is theoretically covariant/invariant to problem transformations, is simple to implement, and exhibits competitive empirical performance.

42 ENGINEERING↗
DOE OSTI2026

An Adaptive Multiparameter Penalty Selection Method for Multiconstraint and Multiblock ADMM

This work presents a new method for online selection of multiple penalty parameters for the alternating direction method of multipliers (ADMM) algorithm applied to optimization problems with multiple constraints or functions with block matrix components. ADMM is widely used for solving constrained optimization problems in a variety of fields, including signal and image processing. Implementations of ADMM often utilize a single hyperparameter, referred to as the penalty parameter, which needs to be tuned to control the rate of convergence. However, in problems with multiple constraints, ADMM may demonstrate slow convergence regardless of penalty parameter selection due to scale differences between constraints. Accounting for scale differences between constraints to improve convergence in these cases requires introducing a penalty parameter for each constraint. The proposed method is able to adaptively account for differences in scale between constraints, providing robustness with respect to problem transformations and initial selection of penalty parameters. It is also simple to understand and implement. Our numerical experiments demonstrate that the proposed method performs favorably compared to a variety of existing penalty parameter selection methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Event-to-Video Conversion for Overhead Object Detection

Collecting overhead imagery using an event camera is desirable due to the energy efficiency of the image sensor compared to standard cameras. However, event cameras complicate downstream image processing, especially for complex tasks such as object detection. In this paper, we investigate the viability of event streams for overhead object detection. We demonstrate that across a number of standard modeling approaches, there is a significant gap in performance between dense event representations and corresponding RGB frames. We establish that this gap is, in part, due to a lack of overlap between the event representations and the pre-training data that the object detectors were initially trained on through a number of experiments. Then, apply an off-the-shelf event-to-video conversion tool that converts event streams into gray-scale video to close this gap. We demonstrate that this approach results in a large performance increase, outperforming even event-specific object detection techniques on our overhead target task. These results suggest that better aligning event representations with existing large pre-trained models may result in greater short-term performance gains compared to end-to-end event-specific architectural improvements.

machine learning (ML), computer vision, Neuromorph↗
DOE OSTI2021

Quantitative order-parameter measurement in lattice-mismatched AlInP using precession electron diffraction

Precession electron diffraction (PED) was used to measure the long-range order parameter in lattice-mismatched AlInP epitaxial films under investigation for solid-state-lighting applications. Both double- and single-variant films grown at 620, 650, and 680°C were analyzed in TEM cross-section. PED patterns were acquired in selected-area-diffraction mode through external microscope control using serial acquisition, which allows inline image processing. The integrated peak intensities from experimental patterns were fit using dynamical simulations of diffraction from the ordered domain structures. Included in the structure-factor calculations were mean atomic displacements of the anions (P) due to ordering, which were found by valence-force-field calculations to have a nearly linear dependence on order parameter. A maximum order parameter of S = 0.36 was measured for a double-variant specimen grown at 650°C.

77 NANOSCIENCE AND NANOTECHNOLOGY↗