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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Proton deflectometry with in situ x-ray reference for absolute measurement of electromagnetic fields in high-energy-density plasmas

In this work, we report a technique of proton deflectometry that uses a grid and an in situ reference x-ray grid image for precise measurements of magnetic fields in high-energy-density plasmas. A D 3 He fusion implosion provides a bright point source of both protons and x-rays, which is split into beamlets by a grid. The protons undergo deflections as they propagate through the plasma region of interest, whereas the x-rays travel along straight lines. The x-ray image, therefore, provides a zero-deflection reference image. The line-integrated magnetic fields are inferred from the shifts of beamlets between the deflected (proton) and reference (x-ray) images. We developed a system for analysis of these data, including automatic algorithms to find beamlet locations and to calculate their deflections from the reference image. The technique is verified in an experiment performed at OMEGA to measure a nonuniform magnetic field in vacuum and then applied to observe the interaction of an expanding plasma plume with the magnetic field.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Development of an operando characterization stage for multi-modal synchrotron x-ray experiments

It is widely accepted that micro- and nanoscale inhomogeneities govern the performance of many thin-film solar cell absorbers. These inhomogeneities yield material properties (e.g., composition, structure, and charge collection) that are challenging to correlate across length scales and measurement modalities. The challenge is compounded if a correlation is sought during device operation or in conditions that mimic aging under particular stressors (e.g., heat and electrical bias). Correlative approaches, particularly those based on synchrotron x-ray sources, are powerful since they can access several material properties in different modes (e.g., fluorescence, diffraction, and absorption) with minimal sample preparation. Small-scale laboratory x-ray instruments have begun to offer multi-modality but are typically limited by low x-ray photon flux, low spatial resolution, or specific sample sizes. To overcome these limitations, a characterization stage was developed to enable multi-scale, multi-modal operando measurements of industrially relevant photovoltaic devices. The stage offers compatibility across synchrotron x-ray facilities, enabling correlation between nanoscale x-ray fluorescence microscopy, microscale x-ray diffraction microscopy, and x-ray beam induced current microscopy, among others. Furthermore, the stage can accommodate device sizes up to 25 × 25 mm 2 , offering access to multiple regions of interest and increasing the statistical significance of correlated properties. The stage materials can sustain humid and non-oxidizing atmospheres, and temperature ranges encountered by photovoltaic devices in operational environments (e.g., from 25 to 100 °C). As a case study, we discuss the functionality of the stage by studying Se-alloyed CdTe photovoltaic devices aged in the stage between 25 and 100 °C.

14 SOLAR ENERGY↗
DOE OSTI2023

Measurement of ion temperature and toroidal flow during magnetic reconnection with a large guide field

Here, ion temperature and toroidal flow along the guide field direction are measured using a new ion tomographic diagnostic on the Magnetic Reconnection eXperiment (MRX) during magnetic reconnection with a guide field strength of about 1.4 and 2.1 times the strength of the reconnecting component. Strong toroidal flows, beyond what has been measured in anti-parallel and lower guide field conditions on MRX, are observed. Sustained ion heating with no discernible structure within the measurement region is also observed. Probe measurements including Langmuir and Mach probe measurements are made to support the tomographic inversion of line-integrated measurements, as well as to provide local measurements of plasma parameters. Measurements of toroidal velocity and ion temperature are supported with time series data. Energy flow into and out of the X-line region is estimated using a guiding center framework and presented in the Appendix of this manuscript, suggesting an outsized role played by parallel electric field in energizing ions. The guiding center approximation is not well satisfied in the region of interest; however, the estimates provide a springboard for future, further experimentation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Development and application of hybrid AIMD/cDFT simulations for atomic-to-mesoscale chemistry

Many important chemical processes involve reactivity and dynamics in complex solutions. Gaining a fundamental understanding of these reaction mechanisms is a challenging goal that requires advanced computational and experimental approaches. However, important techniques such as molecular simulation have limitations in terms of scales of time, length, and system complexity. Furthermore, among the currently available solvation models, there are very few designed to describe the interaction between the molecular scale and the mesoscale. To help address this challenge, here, we establish a novel hybrid approach that couples first-principles plane-wave density functional theory with classical density functional theory (cDFT). In this approach, a region of interest described by ab initio molecular dynamics (AIMD) interacts with the surrounding medium described using cDFT to arrive at a self-consistent ground state. cDFT is a robust but efficient mesoscopic approach to accurate thermodynamics of bulk electrolyte solutions over a wide concentration range (up to 2M concentrations). Benchmarking against commonly used continuum models of solvation, such as SMD, as well as experiments, demonstrates that our hybrid AIMD–cDFT method is able to produce reasonable solvation energies for a variety of molecules and ions. With this model, we also examined the solvent effects on a prototype S N 2 reaction of the nucleophilic attack of a chloride ion on methyl chloride in the solution. The resulting reaction pathway profile and the solution phase barrier agree well with experiment, showing that our AIMD/cDFT hybrid approach can provide insight into the specific role of the solvent on the reaction coordinate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A multifidelity Bayesian optimization method for inertial confinement fusion design

Due to their cost, experiments for inertial confinement fusion (ICF) heavily rely on numerical simulations to guide design. As simulation technology progresses, so too can the fidelity of models used to plan for new experiments. However, these high-fidelity models are by themselves insufficient for optimal experimental design, because their computational cost remains too high to efficiently and effectively explore the numerous parameters required to describe a typical experiment. Therefore, traditionally, ICF design has relied on low-fidelity modeling to initially identify potentially interesting design regions, which are then subsequently explored via selected high-fidelity modeling. In this paper, we demonstrate that this two-step approach can be insufficient: even for simple design problems, a two-step optimization strategy can lead high-fidelity searching toward incorrect regions and consequently waste computational resources on parameter regimes far away from the true optimal solution. We reveal that a primary cause of this behavior in ICF design problems is the presence of low-fidelity optima in different regions of the parameter space far away from high-fidelity optima. To address this issue, we propose an iterative multifidelity Bayesian optimization method based on Gaussian Process Regression that leverages both low- and high-fidelity models simultaneously. We demonstrate, using both two- and eight-dimensional ICF test problems, that our algorithm can effectively utilize both low-fidelity and high-fidelity models to refine the designs. This approach proves to be more efficient than relying solely on high-fidelity modeling for optimization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Radius measurement via super-resolution microscopy enables the development of a variable radii proximity labeling platform

The elucidation of protein interaction networks is critical to understanding fundamental biology as well as developing new therapeutics. Proximity labeling platforms (PLPs) are state-of-the-art technologies that enable the discovery and delineation of biomolecular networks through the identification of protein-protein interactions. These platforms work via catalytic generation of reactive probes at a biological region of interest; these probes then diffuse through solution and covalently “tag” proximal biomolecules. The physical distance that the probes diffuse determines the effective labeling radius of the PLP and is a critical parameter that influences the scale and resolution of interactome mapping. As such, by expanding the degrees of labeling resolution offered by PLPs, it is possible to better capture the various size scales of interactomes. At present, however, there is little quantitative understanding of the labeling radii of different PLPs. Here, we report the development of a superresolution microscopy-based assay for the direct quantification of PLP labeling radii. Using this assay, we provide direct extracellular measurements of the labeling radii of state-of-the-art antibody-targeted PLPs, including the peroxidase-based phenoxy radical platform (269 ± 41 nm) and the high-resolution iridium-catalyzed µMap technology (54 ± 12 nm). Last, we apply these insights to the development of a molecular diffusion-based approach to tuning PLP resolution and introduce a new aryl-azide-based µMap platform with an intermediate labeling radius (80 ± 28 nm).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Reuniting crystallography with real space: Ab initio structure elucidation with 4D-STEM

Structure elucidation via single-crystal methods has historically lacked experimental access to real-space information, instead relying exclusively on diffraction-space measurements of Bragg reflections. Here we exploit the dual-space imaging power of 4D scanning transmission electron microscopy to meaningfully integrate real-space information into the crystallographic workflow. We show that virtual apertures assembled by segmentation of high-angle annular dark-field images enable i) pixel-by-pixel separation of coherent Bragg signal from clusters of closely spaced nanocrystals and ii) selective extraction of integrated intensities from thinner subregions of individual specimens, facilitating retroactive tuning of multiple scattering artifacts. This strategy empowers us to simply pick and choose whichever nanoscale regions of interest generate the highest-quality diffraction patterns, allowing us to solve several independent structures of the metal-organic framework UiO-66 from specimens whose agglomerated morphology proved intractable for conventional microcrystal electron diffraction. Our method is compatible with both rotational and serial approaches to data processing, ultimately divulging the first scanning nanobeam electron diffraction structures determined by direct methods at subangstrom resolution.

Saha, Ambarneil↗
DOE OSTI2023

Automated piezoresponse force microscopy domain tracking during fast thermally stimulated phase transition in CuInP 2 S 6

Real-time tracking of dynamic nanoscale processes such as phase transitions by scanning probe microscopy is a challenging task, typically requiring extensive and laborious human supervision. Smart strategies to track specific regions of interest (ROI) in the system during such transformations in a fast and automated manner are necessary to study the evolution of the microscopic changes in such dynamic systems. In this work, we realize automated ROI tracking in piezoresponse force microscopy during a fast (≈0.8 °C s –1 ) thermally stimulated ferroelectric-to-paraelectric phase transition in CuInP 2 S 6 . We use a combination of fast (1 frame per second) sparse scanning with compressed sensing image reconstruction and real-time offset correction via phase cross correlation. The applied methodology enables in situ fast and automated functional nanoscale characterization of a certain ROI during external stimulation that generates sample drift and changes local functionality.

36 MATERIALS SCIENCE↗
DOE OSTI2024

In situ tumor model for longitudinal in silico imaging trials

Abstract Objective.In this article, we introduce a computational model for simulating the growth of breast cancer lesions accounting for the stiffness of surrounding anatomical structures.Approach.In our model, ligaments are classified as the most rigid structures while the softer parts of the breast are occupied by fat and glandular tissues As a result of these variations in tissue elasticity, the rapidly proliferating tumor cells are met with differential resistance. It is found that these cells are likely to circumvent stiffer terrains such as ligaments, instead electing to proliferate preferentially within the more yielding confines of the breast’s soft topography. By manipulating the interstitial tumor pressure in direct proportion to the elastic constants of the tissues surrounding the tumor, this model thus creates the potential for realizing a database of unique lesion morphology sculpted by the distinctive topography of each local anatomical infrastructure. We modeled the growth of simulated lesions within volumes extracted from fatty breast models, developed by Graffet alwith a resolution of 50μm generated with the open-source and readily available Virtual Imaging Clinical Trials for Regulatory Evaluation (VICTRE) imaging pipeline. To visualize and validate the realism of the lesion models, we leveraged the imaging component of the VICTRE pipeline, which replicates the siemens mammomat inspiration mammography system in a digital format. This system was instrumental in generating digital mammogram (DM) images for each breast model containing the simulated lesions.Results.By utilizing the DM images, we were able to effectively illustrate the imaging characteristics of the lesions as they integrated with the anatomical backgrounds. Our research also involved a reader study that compared 25 simulated DM regions of interest (ROIs) with inserted lesions from our models with DM ROIs from the DDSM dataset containing real manifestations of breast cancer. In general the simulation time for the lesions was approximately 2.5 hours, but it varied depending on the lesion’s local environment.Significance.The lesion growth model will facilitate and enhance longitudinal in silico trials investigating the progression of breast cancer.

Engineering↗
DOE OSTI2020

Large enhancement of the in-field critical current density of YBCO coated conductors due to composite pinning landscape

YBa 2 Cu 3 O 7 -based coated conductors (CCs) achieve the highest critical current densities (J c ) of any known superconductor and are a key technology for applications such as rotatory machines, high-field magnets and power transmission. Incorporation of nano-sized non-superconducting second phases as additional vortex pinning centers has been considered the most amenable route to further enhance J c at an industrial scale, and has been successfully used in commercial CCs. The resulting pinning landscape is quite complex, with both synergistic and competing interactions among the various types of defects. Particle irradiation, on the other hand, allows for a controlled post-processing incorporation of a well-defined defect morphology. We have previously shown that irradiation with protons and other light ions can further enhance the in-field J c in commercial state-of-the-art CCs. Here we develop a combined irradiation process that increases J c above values previously achieved by irradiating with only one species. Our new approach involves sequentially irradiating with 250 MeV Au ions and 4 MeV protons. For example, at T ~ 27 K (liquid neon) and μ 0 H ~ 4 T, a region of interest for rotatory machines applications, we obtain J c ~ 5 MA cm -2 , which is about 40% higher than the values produced by the individual irradiations. Finally, we conclude that this is due to the synergistic pinning effects of the introduced splayed, non-uniform columnar defects and small clusters.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
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 OSTI2020

Search for magnetically-induced signatures in the arrival directions of ultra-high-energy cosmic rays measured at the Pierre Auger Observatory

We search for signals of magnetically-induced effects in the arrival directions of ultra-high-energy cosmic rays detected at the Pierre Auger Observatory. We apply two different methods. One is a search for sets of events that show a correlation between their arrival direction and the inverse of their energy, which would be expected if they come from the same point-like source, they have the same electric charge and their deflection is relatively small and coherent. We refer to these sets of events as “multiplets”. The second method, called “thrust”, is a principal axis analysis aimed to detect the elongated patterns in a region of interest. We study the sensitivity of both methods using a benchmark simulation and we apply them to data in two different searches. The first search is done assuming as source candidates a list of nearby active galactic nuclei and starburst galaxies. The second is an all-sky blind search. We report the results and we find no statistically significant features. We discuss the compatibility of these results with the indications on the mass composition inferred from data of the Pierre Auger Observatory.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Scaling the training of particle classification on simulated MicroBooNE events to multiple GPUs

Measurements in Liquid Argon Time Projection Chamber (LArTPC) neutrino detectors, such as the MicroBooNE detector at Fermilab, feature large, high fidelity event images. Deep learning techniques have been extremely successful in classification tasks of photographs, but their application to LArTPC event images is challenging, due to the large size of the events. Events in these detectors are typically two orders of magnitude larger than images found in classical challenges, like recognition of handwritten digits contained in the MNIST database or object recognition in the ImageNet database. Ideally, training would occur on many instances of the entire event data, instead of many instances of cropped regions of interest from the event data. However, such efforts lead to extremely long training cycles, which slow down the exploration of new network architectures and hyperparameter scans to improve the classification performance. We present studies of scaling a LArTPC classification problem on multiple architectures, spanning multiple nodes. The studies are carried out on simulated events in the MicroBooNE detector. We emphasize that it is beyond the scope of this study to optimize networks or extract the physics from any results here. Institutional computing at Pacific Northwest National Laboratory and the SummitDev machine at Oak Ridge National Laboratory’s Leadership Computing Facility have been used. To our knowledge, this is the first use of state-of-the-art Convolutional Neural Networks for particle physics and their attendant compute techniques onto the DOE Leadership Class Facilities. We expect benefits to accrue particularly to the Deep Underground Neutrino Experiment (DUNE) LArTPC program, the flagship US High Energy Physics (HEP) program for the coming decades.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Augmented signal processing in Liquid Argon Time Projection Chambers with a deep neural network

The Liquid Argon Time Projection Chamber (LArTPC) is an advanced neutrino detector technology widely used in recent and upcoming accelerator neutrino experiments. It features a low energy threshold and high spatial resolution that allow for comprehensive reconstruction of event topologies. In current-generation LArTPCs, the recorded data consist of digitized waveforms on wires produced by induced signal on wires of drifting ionization electrons, which can also be viewed as two-dimensional (2D) (time versus wire) projection images of charged-particle trajectories. For such an imaging detector, one critical step is the signal processing that reconstructs the original charge projections from the recorded 2D images. For the first time, we introduce a deep neural network in LArTPC signal processing to improve the signal region of interest detection. By combining domain knowledge (e.g., matching information from multiple wire planes) and deep learning, this method shows significant improvements over traditional methods. This work details the method, software tools, and performance evaluated with realistic detector simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Performance study of charcoal-based radon reduction systems for ultraclean rare event detectors

The continuous emanation of radon due to trace amounts of uranium and thorium in detector materials introduces radon to the active detection volume of low-background rare event search detectors. 222 Rn produces a particularly problematic background in the physics region of interest by the "naked" beta decay of its 214 Pb daughter nucleus. While charcoal-based adsorption traps are expected to be effective for radon reduction in auxiliary circulation loops that service the warm components of current ton-scale detectors at slow flow rates (0.5-2 SLPM), radon reduction in the entire circulation loop at high flow rates $\mathcal{O}$(100s SLPM) is necessary to reach high sensitivity in future generation experiments. In this article we explore radon dynamics with a charcoal-based radon reduction system in the main circulation loop of time projection chamber detectors. Here, we find that even for perfect radon traps, circulation speeds of 2,000 SLPM are needed to reduce radon concentration in a 10 ton detector by 90%. This is faster by a factor of four than the highest circulation speeds currently achieved in dark matter detectors. We further find that the effectiveness of vacuum swing adsorption systems, which have been employed very successfully at reducing atmospheric radon levels in clean-rooms, is limited by the intrinsic radon activity of the charcoal adsorbent in ultra-low radon environments. Adsorbents with significantly lower intrinsic radon activity than in currently available activated charcoals would be necessary to build effective vacuum swing adsorption systems operated at room temperature for rare event search experiments. If such VSA systems are cooled to about 190 K, this requirement relaxes drastically.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

The nylon balloon for xenon loaded liquid scintillator in KamLAND-Zen 800 neutrinoless double-beta decay search experiment

The KamLAND-Zen 800 experiment is searching for the neutrinoless double-beta decay of 136 Xe by using 136 Xe-loaded liquid scintillator. The liquid scintillator is enclosed inside a balloon made of thin, transparent, low-radioactivity film that we call Inner Balloon (IB). The IB, apart from guaranteeing the liquid containment, also allows to minimize the background from cosmogenic muon-spallation products and 8B solar neutrinos. Indeed these events could contribute to the total counts in the region of interest around the Q-value of the double-beta decay of 136 Xe. In this paper, we present an overview of the IB and describe the various steps of its commissioning minimizing the radioactive contaminations, from the material selection, to the fabrication of the balloon and its installation inside the KamLAND detector. Finally, we show the impact of the IB on the KamLAND background as measured by the KamLAND detector itself.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

GRAPH — an readout ASIC for large MCP based detectors

We present a programmable 16 channel, mixed signal, low power readout ASIC, having the project historically named Gigasample Recorder of Analog waveforms from a PHotodetector (GRAPH). It is designed to read large aperture single photon imaging detectors using micro channel plates for charge multiplication, and measuring the detector's response on crossed strips anodes to extrapolate the incoming photon position. Each channel consists of a fast, low power and low noise charge sensitive amplifier, which provides a myriad of coarse and fine programmable options for gain and shaping settings. Further, the amplified signal is recorded using, to our knowledge novel, the Hybrid Universal sampLing Architecture (HULA) ADC. A kind of mixed signal double buffer memory, that enables concurrent waveform recording, and selected event digitized data extraction. The sampling frequency is freely adjustable between few kHz up to 125 MHz, while the chip's internal digital memory holds a history 2048 samples for each channel, with a digital headroom of 12 bits. An optimized region of interest sample-read algorithm allows to extract the information just around the event pulse peak, while selecting the next event, thus substantially reducing the operational dead time. The chip is designed in 130 nm TSMC CMOS technology, and its power consumption is around 47 mW per channel.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

K-means-driven Gaussian Process data collection for angle-resolved photoemission spectroscopy

Abstract We propose the combination of k-means clustering with Gaussian Process (GP) regression in the analysis and exploration of 4D angle-resolved photoemission spectroscopy (ARPES) data. Using cluster labels as the driving metric on which the GP is trained, this method allows us to reconstruct the experimental phase diagram from as low as 12% of the original dataset size. In addition to the phase diagram, the GP is able to reconstruct spectra in energy-momentum space from this minimal set of data points. These findings suggest that this methodology can be used to improve the efficiency of ARPES data collection strategies for unknown samples. The practical feasibility of implementing this technology at a synchrotron beamline and the overall efficiency implications of this method are discussed with a view on enabling the collection of more samples or rapid identification of regions of interest.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗