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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Scattered-light uniformity imager for diagnosing laser absorption asymmetries on OMEGA

Light scattered from a target is the most-direct measurement for diagnosing laser absorption in a direct-drive implosion. Observations from OMEGA implosions show much larger scattered-light asymmetries than predictions. A new instrument has been developed to absolutely measure the scattered-light intensity and nonuniformity for the purpose of diagnosing the asymmetry. The scattered-light uniformity imager (SLUI) diagnostic records the variation in scattered-light intensity over a transmission diffuser using a charge-coupled device (CCD)/lens assembly. At the standard operating position, an 11.3° (f/2.5) cone of light is collected. A stray light baffle, debris shield, and antireflection absorbing filter are also incorporated into the diagnostic payload inserted into the target chamber. The imaging parts of the diagnostic (light baffle, vacuum window, filters, lens, and CCD camera) are located outside the target chamber. Five SLUIs have been built and deployed in OMEGA’s ten-inch manipulator diagnostic ports, covering almost 5% of the emission surface, enabling an absolute scattered-light measurement should be within a few percent of the global average. Each SLUI system is calibrated offline, providing absolute scattered-light intensity measurements. Based on the measured point spread function, each diffuser plate image contains over 20 000 independent scattered-light absolute-intensity measurements of the variation over the collection cone. SLUI provides a platform to study scattered light and absorption asymmetries, and their possible sources.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Pedestal fluctuation measurements with charge exchange imaging at the DIII-D tokamak

A new high radial resolution 2D multichannel Charge eXchange Imaging (CXI) diagnostic is under development for deployment at DIII-D. Here, the diagnostic system will measure low-to-intermediate radial wavenumber carbon density fluctuations by observing the n = 8 – 7 (λ = 529.06 nm) C-VI emission line, resulting from charge exchange collisions between heating neutral beam atoms and the intrinsic carbon ion density. The new CXI diagnostic will provide measurements with ΔR ~ 0.4 cm to access higher k r instabilities (k r < 8 cm –1 ) predicted to arise in the steep-gradient region of the H-mode pedestal. The CXI system will feature 60 fiber bundles in a 12 × 5 arrangement, with each bundle consisting of four 1 mm fibers. A custom optical system has been designed to filter and image incoming signals onto an 8 × 8 avalanche photodiode array. Additionally, a novel electronics suite has been designed and commissioned to amplify and digitize the relatively low-intensity carbon signal at a 2 MHz bandwidth. Forward modeling results of the active C-VI emission suggest sufficient signal to noise ratios to resolve turbulent fluctuations. Prototype measurements demonstrate the ability to perform high frequency pedestal measurements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Two-dimensional spin systems in PECVD-grown diamond with tunable density and long coherence for enhanced quantum sensing and simulation

Systems of spins engineered with tunable density and reduced dimensionality enable a number of advancements in quantum sensing and simulation. Defects in diamond, such as nitrogen-vacancy (NV) centers and substitutional nitrogen (P1 centers), are particularly promising solid-state platforms to explore. However, the ability to controllably create coherent, two-dimensional spin systems and characterize their properties, such as density, depth confinement, and coherence, is an outstanding materials challenge. We present a refined approach to engineer dense (≳1 ppm ∙ nm), 2D nitrogen, and NV layers in diamond using delta-doping during plasma-enhanced chemical vapor deposition epitaxial growth. We employ both traditional materials techniques, e.g., secondary ion mass spectrometry, alongside NV spin decoherence-based measurements to characterize the density and dimensionality of the P1 and NV layers. We find P1 densities of 5–10 ppm ∙ nm, NV densities between 1 and 3.5 ppm ∙ nm tuned via electron irradiation dosage, and depth confinement of the spin layer down to 1.6 nm. We also observe high (up to 0.74) ratios of NV to P1 centers and reproducibly long NV coherence times, dominated by dipolar interactions with the engineered P1 and NV spin baths.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Flatfielding of hybrid pixel detectors in tender x-ray scattering

The ability of the soft matter interfaces beamline at National Synchrotron Light Source II to access x-ray energy in the tender x-ray regime, i.e., from 2.1 to 5 keV, enables new resonant x-ray scattering studies at the sulfur K-edge and others. We present a new approach to correct data acquired in the tender x-ray regime with a Pilatus3 detector in order to improve the data quality and to correct the various artifacts inherent to hybrid pixel detectors, such as variations in modules’ efficiency or noisy detector module junctions. Further, this new flatfielding significantly enhances the data quality and enables detection of weak scattering signals.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Electrical design of the flexible imaging diffraction diagnostic for laser experiments (FIDDLE) at the National Ignition Facility (NIF)—Requirements, design, and performance

The Flexible Imaging Diffraction Diagnostic for Laser Experiments (FIDDLE) is a newly developed diagnostic for imaging time resolved diffraction in experiments at the National Ignition Facility (NIF). It builds on the successes of its predecessor, the Gated Diffraction Development Diagnostic (G3D). The FIDDLE was designed to support eight Daedalus version 2 sensors (six more hCMOS sensors than any other hCMOS-based diagnostic in NIF to date) and an integrated streak camera. We will review the electrical requirements, design, and performance of the electrical subsystems that were created to support this large number of cameras in the FIDDLE. The analysis of the data that the FIDDLE is intended to collect relies heavily on the accurate and well-understood timing of each sensor. We report camera-to-camera timing jitter of less than 100 ps rms and sensor integration times of 2.2 ns FWHM in 2-2 timing mode. Additionally, diffraction experiments on the NIF produce electric fields (EMI) on the order of 1 kV/m, which have been observed to negatively impact the performance of some electrical components of the FIDDLE. We report on the results of testing hCMOS camera electronics in a similar EMI environment generated in an offline lab. In addition, we also summarize the use of a novel approach to using a vector network analyzer as an EMI leak detector to understand and reduce the negative impacts of EMI on the FIDDLE.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Voltage-induced magnetic domain evolution in a phase-change material

Applying voltage to metal–insulator transition (MIT) materials allows electrical actuation of the local electronic phase state. In MIT systems that have the electronic order coupled with the magnetic order, voltage switching of the electronic phase state can also enable the electrical manipulation of magnetic properties. In this work, we utilized x-ray magnetic circular dichroism photoemission electron microscopy (XMCD-PEEM) to investigate the control of magnetic domain configurations in ferromagnetic MIT electrical switches. For applied voltages above a threshold value, the XMCD-PEEM images show that the magnetic domains separate into two distinct regions: one with a high contrast (white/black), indicating well-defined micrometer-scale magnetic domains with a component of their magnetization aligned parallel/antiparallel to the x-ray helicity, and the other with different shades of intermediate contrast (gray). Significant changes in magnetic domain configurations upon voltage biasing were only observed in these gray regions. Furthermore, the voltage-induced magnetic domain separation was found to be bias polarity-dependent, with the gray regions expanding from the opposite sample edge when the applied voltage polarity was reversed. This polarity-dependent electrical control of magnetic domain configurations during the MIT switching opens alternative opportunities in memory applications for magnetic MIT switching materials.

42 ENGINEERING↗
DOE OSTI2025

Distortions in charged-particle images of laser direct-drive inertial confinement fusion implosions

Energetic charged particles generated by inertial confinement fusion (ICF) implosions encode information about the spatial morphology of the hotspot and dense fuel during the time of peak fusion reactions. The knock-on deuteron imager (KoDI) was developed at the Omega Laser Facility to image these particles in order to diagnose low-mode asymmetries in the hotspot and dense fuel layer of cryogenic deuterium–tritium ICF implosions. However, the images collected are distorted in several ways that prevent reconstruction of the deuteron source. In this paper, we describe these distortions and a series of attempts to mitigate or compensate for them. We present several potential mechanisms for the distortions, including a new model for scattering of charged particles in filamentary electric or magnetic fields surrounding the implosion. Particle-tracing is used to create synthetic KoDI data based on the filamentary field model that reproduces the main experimentally observed image distortions. We conclude that the filamentary scattering model best matches the observed image distortions. Finally, we discuss potential impacts of filamentary fields on other charged-particle diagnostics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Mind the gap: Bridging the divide between AI aspirations and the reality of autonomous microscopy

What does materials science look like in the “Age of Artificial Intelligence?” Each material’s domain—synthesis, characterization, and modeling—has a different answer to this question, motivated by unique challenges and constraints. This work focuses on the tremendous potential of autonomous characterization within electron microscopy. We present our recent advancements in developing domain-aware, multimodal models for microscopy analysis capable of describing complex atomic systems. We then address the critical gap between the theoretical promise of autonomous microscopy and its current practical limitations, showcasing recent successes while highlighting the necessary developments to achieve robust, real-world autonomy.

2D materials↗
DOE OSTI2025

Calibration and characterization of the line-VISAR diagnostic at the HED-HIBEF instrument at the European XFEL

In dynamic-compression experiments, the line-imaging Velocity Interferometer System for Any Reflector (VISAR) is a well-established diagnostic used to probe the velocity history, including wave profiles derived from dynamically compressed interfaces and wavefronts, depending on material optical properties. Knowledge of the velocity history allows for the determination of the pressure achieved during compression. Such a VISAR analysis is often based on Fourier transform techniques and assumes that the recorded interferograms are free from image distortions. In this paper, we describe the VISAR diagnostic installed at the HED-HIBEF instrument located at the European XFEL along with its calibration and characterization. It comprises a two-color (532, 1064 nm), three-arm (with three velocity sensitivities) line imaging system. We provide a procedure to correct VISAR images for geometric distortions and evaluate the performance of the system using Fourier analysis. We finally discuss the spatial and temporal calibrations of the diagnostic. As an example, we compare the pressure extracted from the VISAR analysis of shock-compressed polyimide and silicon.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Spatiotemporal evolution of runaway electrons from synchrotron images in Alcator C-Mod

We report in the Alcator C-Mod tokamak, relativistic runaway electron (RE) generation can occur during the flattop current phase of low density, diverted plasma discharges. Due to the high toroidal magnetic field (B 0 = 5.4 T), RE synchrotron radiation is measured by a wide-view camera in the visible wavelength range (λ ≈ 400–900 nm). In this paper, a statistical analysis of over one thousand camera images is performed to investigate the plasma conditions under which synchrotron emission is observed in C-Mod. In addition, the spatiotemporal evolution of REs during one particular discharge is explored in detail via a thorough analysis of the distortion-corrected synchrotron images. To accurately predict RE energies, the kinetic solver CODE is used to evolve the electron momentum-space distribution at six locations throughout the plasma: the magnetic axis and flux surfaces q = 1, 4/3, 3/2, 2, and 3. These results, along with the experimentally-measured magnetic topology and camera geometry, are input into the synthetic diagnostic SOFT to simulate synchrotron emission and detection. Interesting spatial structure near the surface q = 2 is found to coincide with the onset of a locked mode and increased MHD activity. Furthermore, the RE density profile evolution is fit by comparing experimental to synthetic images, providing important insight into RE spatiotemporal dynamics.

synthetic diagnostic↗
DOE OSTI2025

Interior soft x-ray tomography with sparse global sampling

To investigate the feasibility of interior imaging reconstruction in soft X-ray tomography for higher-resolution cellular imaging, including whole-cell imaging, we develop an alignment and reconstruction algorithm that combines a small number of sparse whole-cell images with a high-resolution local interior scan. Based on numerical simulations, we demonstrate that combined reconstructions mitigate the depth-of-field limitation in high-resolution scans, enable radiation dose optimization, and yield quantitative X-ray absorption values with sparse sampling. We further validate our numerical approach using experimental data from two different cell types and show that the combined reconstruction reliably provides high spatial resolution within an interior region of interest of a whole cell. The resulting sparse reconstruction framework offers robust, faithful visualization of cellular organelles in soft X-ray tomography. This mesoscale imaging strategy allows one to ‘scout’ and zoom into selected subcellular volumes of interest, enabling increased spatial resolution without sacrificing larger-volume imaging and providing information on the relative positions of all organelles within a cell.

3D imaging↗
DOE OSTI2017

SkyFACT: high-dimensional modeling of gamma-ray emission with adaptive templates and penalized likelihoods

We present SkyFACT (Sky Factorization with Adaptive Constrained Templates), a new approach for studying, modeling and decomposing diffuse gamma-ray emission. Like most previous analyses, the approach relies on predictions from cosmic-ray propagation codes like GALPROP and DRAGON. However, in contrast to previous approaches, we account for the fact that models are not perfect and allow for a very large number (∼> 10{sup 5}) of nuisance parameters to parameterize these imperfections. We combine methods of image reconstruction and adaptive spatio-spectral template regression in one coherent hybrid approach. To this end, we use penalized Poisson likelihood regression, with regularization functions that are motivated by the maximum entropy method. We introduce methods to efficiently handle the high dimensionality of the convex optimization problem as well as the associated semi-sparse covariance matrix, using the L-BFGS-B algorithm and Cholesky factorization. We test the method both on synthetic data as well as on gamma-ray emission from the inner Galaxy, |ℓ|<90{sup o} and | b |<20{sup o}, as observed by the Fermi Large Area Telescope. We finally define a simple reference model that removes most of the residual emission from the inner Galaxy, based on conventional diffuse emission components as well as components for the Fermi bubbles, the Fermi Galactic center excess, and extended sources along the Galactic disk. Variants of this reference model can serve as basis for future studies of diffuse emission in and outside the Galactic disk.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Is flat fielding safe for precision CCD astronomy?

The ambitious goals of precision cosmology with wide-field optical surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope (LSST) demand precision CCD astronomy as their foundation. This in turn requires an understanding of previously uncharacterized sources of systematic error in CCD sensors, many of which manifest themselves as static effective variations in pixel area. Such variation renders a critical assumption behind the traditional procedure of flat fielding—that a sensor's pixels comprise a uniform grid—invalid. In this work, we present a method to infer a curl-free model of a sensor's underlying pixel grid from flat-field images, incorporating the superposition of all electrostatic sensor effects—both known and unknown—present in flat-field data. We use these pixel grid models to estimate the overall impact of sensor systematics on photometry, astrometry, and PSF shape measurements in a representative sensor from the Dark Energy Camera (DECam) and a prototype LSST sensor. Applying the method to DECam data recovers known significant sensor effects for which corrections are currently being developed within DES. For an LSST prototype CCD with pixel-response non-uniformity (PRNU) of 0.4%, we find the impact of "improper" flat fielding on these observables is negligible in nominal .7'' seeing conditions. Furthermore, these errors scale linearly with the PRNU, so for future LSST production sensors, which may have larger PRNU, our method provides a way to assess whether pixel-level calibration beyond flat fielding will be required.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

On determination of charge transfer efficiency of thick, fully depleted CCDs with 55 Fe x-rays

Charge transfer efficiency (CTE) is one of the most important CCD characteristics. Our paper examines ways to optimize the algorithms used to analyze 55 Fe x-ray data on the CCDs, as well as explores new types of observables for CTE determination that can be used for testing LSST CCDs. Furthermore, the observables are modeled employing simple Monte Carlo simulations to determine how the charge diffusion in thick, fully depleted silicon affects the measurement. The data is compared to the simulations for one of the observables, integral flux of the x-ray hit.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Spot-based measurement of the brighter-fatter effect on a Roman Space Telescope H4RG detector and comparison with flat-field data

Here, we present the measurement and characterization of the brighter-fatter effect (BFE) on a NASA Roman Space Telescope development Teledyne H4RG-10 near-infrared detector using laboratory measurements with projected point sources. After correcting for other interpixel non-linearity effects such as classical non-linearity and inter-pixel capacitance, we quantify the magnitude of the BFE by calculating the fractional area change per electron of charge contrast. We also introduce a mathematical framework to compare our results with the BFE measured on similar devices using autocorrelations from flat-field images. We find an agreement of 18 ± 5% between the two methods. We identify potential sources of discrepancy and discuss future investigations to characterize and address them.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Neutron imaging analysis using jupyter Python notebook

Abstract Independently of the image modality (x-rays, neutrons, etc), image data analysis requires normalization, a preprocessing step. While the normalization can sometimes easily be generalized, the analysis is, in most cases, specific to an experiment and a sample. Although many tools (MATLAB, ImageJ, VG Studio…) offer a large collection of pre-programmed image analysis tools, they usually require a learning step that can be lengthy depending on the skills of the end user. We have implemented Jupyter Python notebooks to allow easy and straightforward data analysis, along with live interaction with the data. Jupyter notebooks require little programming knowledge and the steep learning curve is bypassed. Most importantly, each notebook can be tailored to a specific experiment and sample with minimized effort. Here, we present the pros and cons of the main methods to analyse data and show the reason why we have found that Jupyter Python notebooks are well suited for imaging data processing, visualization and analysis.

Bilheux, Jean-Christophe (ORCID:0000000321726487)↗
DOE OSTI2020

A semblance measure for model comparison

Algorithmic and computational advances have made it possible that geophysical survey and earth model design can be aided by many systematic trial inverse-modelling runs with synthetic data. Such may, for example, come up in machine-learning approaches. Automated image appraisal pertaining to such applications will involve common statistical tests for goodness-of-data fit as a primary evaluation method. However, solution non-uniqueness may render multiple images equivalent in terms of their data fit, requiring secondary categorizers. A logical choice for classifying synthetic-imaging results quantifies the goodness of model fit where a known reference model replaces the observational input. The task of model intercomparison in terms of measuring the resemblance to the reference model poses challenges to common distance-based metrics like root mean square error and mean absolute error. First, distance-based metrics can introduce spurious contributions when smooth models with fuzzy target contours are to be compared against a sharp reference. Second, large differences due to parameter-estimation overshoots can dominate distance metrics. Here, we propose a remedy that is referred to as semblance and is based on the idea of logistic functions, where a binary-dependent variable adds non-zero or zero accumulation terms for the, respectively, passing or failing of preset target thresholds. This classifying approach is amenable to an objective where model feature recognition is primary. Numerical comparisons to distance-based metrics provide evidence for the advantages of the semblance in view of this objective. Geophysical imaging in conjunction with machine-learning is seen as a benefitting upcoming application area.

58 GEOSCIENCES↗