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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

As-Built Simulation of the High Flux Isotope Reactor

The Oak Ridge National Laboratory High Flux Isotope Reactor (HFIR) is an 85 MWt flux trap-type research reactor that supports key research missions, including isotope production, materials irradiation, and neutron scattering. The core consists of an inner and an outer fuel element containing 171 and 369 involute-shaped plates, respectively. The thin fuel plates consist of a U 3 O 8 -Al dispersion fuel (highly enriched), an aluminum-based filler, and aluminum cladding. The fuel meat thickness is varied across the width of the involute plate to reduce thermal flux peaks at the radial edges of the fuel elements. Some deviation from the designed fuel meat shaping is allowed during manufacturing. A homogeneity scan of each fuel plate checks for potential anomalies in the fuel distribution by scanning the surface of the plate and comparing the attenuation of the beam to calibration standards. While typical HFIR simulations use homogenized fuel regions, explicit models of the plates were developed under the Low-Enriched Uranium Conversion Program. These explicit models typically include one inner and one outer fuel plate with nominal fuel distributions, and then the plates are duplicated to fill the space of the corresponding fuel element. Therefore, data extracted from these simulations are limited to azimuthally averaged quantities. To determine the reactivity and physics impacts of an as-built outer fuel element and generate azimuthally dependent data in the element, 369 unique fuel plate models were generated and positioned. This model generates the three-dimensional (i.e., radial–axial–azimuthal) plate power profile, where the azimuthal profile is impacted by features within the adjacent control element region and beryllium reflector. For an as-built model of the outer fuel element, plate-specific homogeneity data, 235 U loading, enrichment, and channel thickness measurements were translated into the model, yielding a much more varied azimuthal power profile encompassed by uncertainty factors in analyses. These models were run with the ORNL-TN and Shift Monte Carlo tools, and they contained upwards of 500,000 cells and 100,000 unique tallies.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Development of a Comprehensive Two-Phase Flow Database for the Validation of NEK-2P

Three-dimensional (3-D) two-phase Computational Fluid Dynamics (CFD) codes are emerging as a powerful and potentially practical tool for applications in which detailed local flow information is needed. However, two-phase flow models and associated closure relations are not well established for CFD applications, which is partly due to the lack of high-quality validation data. The main objective of this work is to develop a comprehensive database of two-phase flows that can be used to validate two-phase CFD codes such as NEK-2P. In this project, four advanced local measurement systems, including Particle Image Velocimetry and Planar Laser-Induced Fluorescence (PIV-PLIF), high-speed imaging, x-ray densitometry, and multi-sensor conductivity probe are employed to measure the local two-phase flow parameters of both gas and liquid phases. By combining these techniques, the local void fraction, bubble velocity, interfacial area concentration, bubble frequency, liquid velocity, turbulence intensity, etc., in various two-phase flow regimes can be obtained. These local measurement techniques are first used in a 25.4 mm circular pipe test section. Seven air-water two-phase flow conditions spanning the bubbly, slug, churn-turbulent, and annular flow regimes are measured in this facility. The obtained database contains the radial profiles of both gas- and liquid-phase parameters at three axial locations along the test section. The second facility used in this work contains a 30 mm × 10 mm rectangular test section, in which three two-phase flow and two single-phase flow conditions are measured. Two-dimensional distributions of local two-phase flow parameters in the cross-sectional plane are measured in this facility at three axial locations as well. A facility featuring a 3×3 electrically heated rod bundle is also designed and being constructed in this project. This facility is specially designed for optical measurements and is expected to provide high-quality boiling data in the future. Preliminary analyses have been performed for the data taken in the 25.4 mm circular pipe. Both center-peaked and wall-peaked void fraction profiles have been observed in the data depending on the two-phase flow conditions and/or developing lengths. The 1-D drift-flux model was evaluated with the newly obtained datasets, in which both gas- and liquid-phases data were directly measured. The distribution parameter model has been optimized based on a new void-profile classification method proposed in this study. The optimized drift-flux model shows a significant improvement in predicting both gas velocity and void fraction. The measured liquid-phase turbulence was used to benchmark Sato’s turbulence model considering the bubble-induced shear stress for the three tested bubbly flows. The benchmark results showed good agreement between the PIV measurements and model predictions. In the bubbly flows tested that have low void fractions less than 3%, the effect of the bubble-induced turbulence was found not significant. However, the bubble-induced shear stress becomes important with the increase of the void fraction. The Conjugate Heat Transfer (CHT) model was developed and implemented in NEK-2P. This model allows the coupled simulation of the solid domain and two-phase fluid domain, allowing the specification of realistic boundary conditions. The CHT implementation was verified first with non-boiling simulations. The predicted temperatures in the fluid domain were shown to be identical in simulations with or without the CHT model. The CHT model was then validated through simulations of three Becker benchmark CHF tests performed under both Dryout (DO) and Departure from Nucleate Boiling (DNB) conditions. Reasonably good agreement was obtained between calculated wall temperatures and corresponding experimental data.

42 ENGINEERING↗
DOE OSTI2021

Quantitative modeling of carcinogenesis induced by single beams or mixtures of space radiations using targeted and non-targeted effects

Abstract Ionizing radiations encountered by astronauts on deep space missions produce biological damage by two main mechanisms: (1) Targeted effects (TE) due to direct traversals of cells by ionizing tracks. (2) Non-targeted effects (NTE) caused by release of signals from directly hit cells. The combination of these mechanisms generates non-linear dose response shapes, which need to be modeled quantitatively to predict health risks from space exploration. Here we used a TE + NTE model to analyze data on APC (1638N/+) mouse tumorigenesis induced by space-relevant doses of protons, 4 He, 12 C, 16 O, 28 Si or 56 Fe ions, or γ rays. A customized weighted Negative Binomial distribution was used to describe the radiation type- and dose-dependent data variability. This approach allowed detailed quantification of dose–response shapes, NTE- and TE-related model parameters, and radiation quality metrics (relative biological effectiveness, RBE, and radiation effects ratio, RER, relative to γ rays) for each radiation type. Based on the modeled responses for each radiation type, we predicted the tumor yield for a Mars-mission-relevant mixture of these radiations, using the recently-developed incremental effect additivity (IEA) synergy theory. The proposed modeling approach can enhance current knowledge about quantification of space radiation quality effects, dose response shapes, and ultimately the health risks for astronauts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Heavy-Ion-Induced Lung Tumors: Dose- & LET-Dependence

There is a limited published literature reporting dose-dependent data for in vivo tumorigenesis prevalence in different organs of various rodent models after exposure to low, single doses of charged particle beams. The goal of this study is to reduce uncertainties in estimating particle-radiation-induced risk of lung tumorigenesis for manned travel into deep space by improving our understanding of the high-LET-dependent dose-response from exposure to individual ion beams after low particle doses (0.03 - 0.80 Gy). Female CB6F1 mice were irradiated with low single doses of either oxygen, silicon, titanium, or iron ions at various energies to cover a range of dose-averaged LET values from 0.2 - 193 keV/µm, using 137Cs γ-rays as the reference radiation. Sham-treated controls were included in each individual experiment totally 398 animals across the 5 studies reported. Based on power calculations, between 40 - 156 mice were included in each of the treatment groups. Tumor prevalence at 16 months after radiation exposure was determined and compared to the age-matched, sham-treated animals. Results indicate that lung tumor prevalence is non-linear as a function of dose with suggestions of threshold doses depending on the LET of the beams. Histopathological evaluations of the tumors showed that the majority of tumors were benign bronchioloalveolar adenomas with occasional carcinomas or lymphosarcomas which may have resulted from metastases from other sites.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

waveSZ: A Hardware-Algorithm Co-Design of Efficient Lossy Compression for Scientific Data

Error-bounded lossy compression is critical to the success of extreme-scale scientific research because of ever-increasing volumes of data produced by today's high-performance computing (HPC) applications. Not only can error-controlled lossy compressors significantly reduce the I/O and storage burden but they can retain high data fidelity for post analysis. Existing state-of-the-art lossy compressors, however, generally suffer from relatively low compression and decompression throughput (up to hundreds of megabytes per second on a single CPU core), which considerably restrict the adoption of lossy compression by many HPC applications especially those with a fairly high data production rate. In this paper, we propose a highly efficient lossy compression approach based on field programmable gate arrays (FPGAs) under the state-of-the-art lossy compression model SZ. Our contributions are fourfold. (1) We adopt a wavefront memory layout to alleviate the data dependency during the prediction for higher-dimensional predictors, such as the Lorenzo predictor. (2) We propose a co-design framework named WAVESZ based on the wavefront memory layout and the characteristics of SZ algorithm and carefully implement it by using high-level synthesis. (3) We propose a hardware-algorithm co-optimization method to improve the performance. (4) We evaluate our proposed WAVESZ on three real-world HPC simulation datasets from the Scientific Data Reduction Benchmarks and compare it with other state-of-the-art methods on both CPUs and FPGAs. Experiments show that our WAVESZ can improve SZ's compression throughput by 6.9x similar to 8.7x over the production version running on a state-of-the-art CPU and improve the compression ratio and throughput by 2.1x and 5.8x on average, respectively, respectively, compared with the state-of-the-art FPGA design.

Compression Ratio↗
DOE OSTI2026

Mono-mix strategy enables comparative proteomics of a cross-kingdom microbial symbiosis

Cross-kingdom microbial symbioses, such as those between algae and bacteria, are key players in biogeochemical cycles. The molecular changes during initiation and establishment of symbiosis are of great interest, but quantitatively monitoring such changes can be challenging, particularly when the microorganisms differ greatly in size or are intimately associated. Here, we analyze output from label-free, data-dependent acquisition (DDA) LC-MS/MS proteomics experiments investigating the well-studied interaction between the alga Chlamydomonas reinhardtii and the heterotrophic bacterium Mesorhizobium japonicum. We found that detection of bacterial proteins decreased in coculture by 50% proteome-wide due to the abundance of algal proteins. As a result, standard differential expression analysis led to numerous false-positive reports of significantly downregulated proteins, where it was not possible to distinguish meaningful biological responses to symbiosis from artifacts of the reduced protein detection in coculture relative to monoculture. We show that data normalization alone does not eliminate the impact of altered detection on differential expression analysis of the cross-kingdom symbiosis. We assessed two additional strategies to overcome this methodological artifact inherent to DDA proteomics. In the first, we combined algal and bacterial monocultures at a relative abundance that mimicked the coculture, creating a “mono-mix” control to which the coculture could be compared. This approach enabled comparable detection of bacterial proteins in the coculture and the monoculture control. In the second strategy, we enhanced detection of lowly abundant bacterial proteins by using sample fractionation upstream of LC-MS/MS analysis. When these simple approaches were combined, they allowed for meaningful comparisons of nearly 10,000 algal proteins and over 4,000 bacterial proteins in response to symbiosis by DDA. They successfully recovered expected changes in the bacterial proteome in response to algal coculture, including upregulation of sugar-binding proteins and transporters. They also revealed novel proteomic responses to coculture that guide hypotheses about algal-bacterial interactions.

Dupuis, Sunnyjoy [University of California, Berkel↗
DOE OSTI2021

The Stellar decomposition: A compact representation for simplicial complexes and beyond

Here, we introduce the Stellar decomposition, a model for efficient topological data structures over a broad range of simplicial and cell complexes. A Stellar decomposition of a complex is a collection of regions indexing the complex’s vertices and cells such that each region has sufficient information to locally reconstruct the star of its vertices, i.e., the cells incident in the region’s vertices. Stellar decompositions are general in that they can compactly represent and efficiently traverse arbitrary complexes with a manifold or non-manifold domain. They are scalable to complexes in high dimension and of large size, and they enable users to easily construct tailored application-dependent data structures using a fraction of the memory required by a corresponding global topological data structure on the complex. As a concrete realization of this model for spatially embedded complexes, we introduce the Stellar tree, which combines a nested spatial tree with a simple tuning parameter to control the number of vertices in a region. Stellar trees exploit the complex’s spatial locality by reordering vertex and cell indices according to the spatial decomposition and by compressing sequential ranges of indices. Stellar trees are competitive with state-of-the-art topological data structures for manifold simplicial complexes and offer significant improvements for cell complexes and non-manifold simplicial complexes. We conclude with a high-level description of several mesh processing and analysis applications that utilize Stellar trees to process large datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Data-flow parallelism for high-energy and nuclear physics frameworks

The processing tasks of an event-processing workflow in high-energy and nuclear physics (HENP) can typically be represented as a directed acyclic graph formed according to the data flow—i.e. the data dependencies among algorithms executed as part of the workflow. With this representation, an HENP framework can optimally execute a workflow, exploiting the parallelism inherent among independent tasks. Despite such a natural description of a workflow, most HENP frameworks do not make use of technologies that provide concurrent execution of graph-based tasking structures. In this talk, we describe Fermilab efforts to adopt a graph-based technology (specifically Intel’s oneTBB flow graph) for meeting the framework needs of its experiments, notably DUNE. Building on the Meld project as presented at CHEP2023, we demonstrate that all common processing idioms supported by current frameworks can naturally be supported by oneTBB’s data-flow technology, optimally leveraging the concurrent capabilities of the machine. In addition, we discuss collaborative efforts between Fermilab and the Intel oneTBB development team, who is considering improvements to the flow-graph technology to better support HENP use cases.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Data-flow parallelism for high-energy and nuclear physics computing frameworks

The processing tasks of a scientific workflow in high-energy and nuclear physics (HENP) can typically be represented as a directed acyclic graph formed according to the data flow—i.e. the data dependencies among algorithms executed as part of the workflow. With this representation, an HENP computing framework can optimally execute a workflow, exploiting the parallelism inherent among independent tasks. Despite such a natural description of a workflow, most HENP frameworks do not make use of technologies that provide concurrent execution of graph-based tasking structures. In this session, we describe Fermilab efforts to adopt a graph-based technology (specifically Intel’s oneTBB flow graph) for meeting the framework needs of its experiments, notably DUNE. After introducing the physics DUNE intends to explore, we will show that all common processing idioms supported by current HENP frameworks can naturally be supported by oneTBB’s data-flow technology, optimally leveraging the concurrent capabilities of the machine. In addition, we discuss collaborative efforts between Fermilab and the Intel oneTBB development team, who is considering improvements to the flow-graph technology to better support HENP use cases.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Results from a multi-laboratory ocean metaproteomic intercomparison: effects of LC-MS acquisition and data analysis procedures

Metaproteomics is an increasingly popular methodology that provides information regarding the metabolic functions of specific microbial taxa and has potential for contributing to ocean ecology and biogeochemical studies. A blinded multi-laboratory intercomparison was conducted to assess comparability and reproducibility of taxonomic and functional results and their sensitivity to methodological variables. Euphotic zone samples from the Bermuda Atlantic Time-series Study (BATS) in the North Atlantic Ocean collected by in situ pumps and the autonomous underwater vehicle (AUV) Clio were distributed with a paired metagenome, and one-dimensional (1D) liquid chromatographic data-dependent acquisition mass spectrometry analysis was stipulated. Analysis of mass spectra from seven laboratories through a common bioinformatic pipeline identified a shared set of 1056 proteins from 1395 shared peptide constituents. Quantitative analyses showed good reproducibility: pairwise regressions of spectral counts between laboratories yielded R 2 values averaged 0.62±0.11, and a Sørensen similarity analysis of the top 1000 proteins revealed 70 %–80 % similarity between laboratory groups. Taxonomic and functional assignments showed good coherence between technical replicates and different laboratories. A bioinformatic intercomparison study, involving 10 laboratories using eight software packages, successfully identified thousands of peptides within the complex metaproteomic datasets, demonstrating the utility of these software tools for ocean metaproteomic research. Lessons learned and potential improvements in methods were described. Future efforts could examine reproducibility in deeper metaproteomes, examine accuracy in targeted absolute quantitation analyses, and develop standards for data output formats to improve data interoperability. Together, these results demonstrate the reproducibility of metaproteomic analyses and their suitability for microbial oceanography research, including integration into global-scale ocean surveys and ocean biogeochemical models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Infrasonic directivity of monopole, dipole and bipole ground-surface reflected sources

Infrasound (acoustic waves below 20 Hz) can be used to detect, locate and quantify activity in the atmosphere such as volcanic eruptions and anthropogenic explosions. Attempts to quantify volcanic eruption parameters such as exit velocity, plume height and mass flow rate using infrasound data depend strongly on assumptions of the acoustic source type. Infrasonic sources may produce omnidirectional or directional wavefields, while propagation effects, such as interaction with topography, can induce further wavefield directivity that is measured by field instrumentation. Limited sampling of these wavefields can hinder our ability to infer the underlying source, and thus our understanding of the eruption characteristics. Equivalent sources are often used to represent acoustic source mechanisms and resultant wavefields. In this study, we review equivalent acoustic sources as they pertain to infrasonic scale and wavelengths commonly encountered in very local (⁠<5 km range) geophysical field deployments. We highlight the equivalent infrasonic bipole source that can be induced by ground-reflection of an elevated monopole; we are not aware of any prior infrasound studies that use the bipole source concept. We use analytical and numerical methods to explore source directivity of monopole, dipole and bipole ground-reflected sources at infrasonic frequencies as well as the additional directivity complications introduced by interactions with topography. We illustrate that for typical volcano-infrasound wavelengths, increasing height above the ground as well as increasing source frequency leads to increased wavefield directivity. Numerical modelling using a simple omnidirectional monopole source embedded in topography further illustrates that both horizontal and vertical infrasound directionality can be induced by topography at the distance scales appropriate for local volcano infrasound monitoring. Information summarized in this analytical and numerical exploration of infrasound directivity may be used to help guide future volcano-infrasound field deployments intended to estimate source parameters or quantify wavefield directivity. Analytic solutions for simple whole-space or half-space atmospheres provide useful formulations for planning or initially analysing geophysical field-scale experimental data; however, especially at very local distances from the source (⁠<5 km), 3-D simulations are necessary to account for complex topography commonly encountered in volcano-infrasound applications.

Infrasound↗
DOE OSTI2020

On the statistical treatment of the Cabibbo angle anomaly

We point out that testing the equality of the Cabibbo angle as extracted from $\Gamma(K\rightarrow \pi l\nu)$, the ratio $\Gamma(K\rightarrow l\nu)/\Gamma(\pi\rightarrow l\nu)$ and nuclear $\beta$ decays is not identical to a test of first row unitarity of the Cabibbo-Kobayashi-Maskawa (CKM) matrix. The reason is that a CKM unitarity test involves only two parameters, while the degrees of freedom for the assessment of the goodness-of-fit of the universality of the Cabibbo angle entailed by the Standard Model (SM) is equal to the number of measurements minus one. Beyond the SM all different processes could in principle give different Cabibbo angles. Consequently, the difference between the two tests becomes relevant starting from three observables giving results for the Cabibbo angle that are in tension with each other. With current data, depending on the treatment of the nuclear $\beta$ decays, we find that New Physics is favored over the SM at $5.1\,\sigma$ or $3.6\,\sigma$ while CKM unitarity is rejected at $4.8\sigma$ or $3.0\sigma$, respectively. We argue that the best method to test the SM is to test the equality of the Cabibbo angle, because CKM unitarity is only one aspect of the SM.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

The deep-DRT: A deep neural network approach to deconvolve the distribution of relaxation times from multidimensional electrochemical impedance spectroscopy data

Electrochemical impedance spectroscopy (EIS) is an experimental technique ubiquitously used to study electrochemical systems. However, conventional EIS data interpretation through physical and equivalent circuit models is challenging because physical models are problem-specific, and equivalent circuits are often just lumped-element analogs lacking physical meaning. The distribution of relaxation times (DRT) has emerged as a complementary approach to resolve these issues. One drawback of conventional DRT deconvolution is that the EIS data is understood to be (only) a function of frequency (i.e. 1D data) and deconvolved accordingly. This work proposes a novel deconvolution method based on deep neural networks (DNNs), allowing the analysis of multidimensional EIS spectra to bridge data dependency on both frequencies and experimental conditions. Two particularly appealing traits of the deep-DRT method developed in this article are that neither regularization nor specific spacing on the state variables defining the experiment are required. Finally, leveraging DNN to examine complex EIS spectra and their dependence on experimental conditions, this work opens a new research direction in the area of EIS analysis and DRT deconvolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Observation of a Large Magnetic Anisotropy and a Field-Induced Magnetic State in SrCo(VO 4 )(OH): A Structure with a Quasi One-Dimensional Magnetic Chain

A new member of the descloizite family, a cobalt vanadate, SrCo(VO 4 )(OH), has been synthesized as large single crystals using high-temperature and high-pressure hydrothermal methods. SrCo(VO 4 )(OH) crystallizes in the orthorhombic crystal system in space group P 2 1 2 1 2 1 with the following unit cell parameters: a = 6.0157(2) Å, b = 7.645(2) Å, c = 9.291(3) Å, V = 427.29(2) Å 3 , and Z = 4. It contains one-dimensional Co–O–Co chains of edge-sharing CoO 6 octahedra along the a -axis connected to each other via VO 4 tetrahedra along the b -axis forming a three-dimensional structure. The magnetic susceptibility of SrCo(VO 4 )(OH) indicates an antiferromagnetic transition at 10 K as well as unusually large spin orbit coupling. Single-crystal magnetic measurements in all three main crystallographic directions displayed a significant anisotropy in both temperature- and field-dependent data. Single-crystal neutron diffraction at 4 K was used to characterize the magnetically ordered state. The Co 2+ magnetic spins are arranged in a staggered configuration along the chain direction, with a canting angle that follows the tipping of the CoO 6 octahedra. The net magnetization along the chain direction, resulting in ferromagnetic coupling of the a -axis spin components in each chain, is compensated by an antiferromagnetic interaction between nearest neighbor chains. A metamagnetic transition appears in the isothermal magnetization data at 2 K along the chain direction, which seems to correspond to a co-alignment of the spin directions of the nearest neighbor chain. We propose a phenomenological spin Hamiltonian that describes the canted spin configuration of the ground state and the metamagnetic transition in SrCo(VO 4 )(OH).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Plasmon-Induced Hot-Carrier Excited-State Dynamics in Plasmonic Semiconductor Nanocrystals

The variance of carrier relaxation pathways for WO 3–x plasmonic semiconductor nanocrystals (PSNCs) is monitored by transient absorption spectroscopy following excitation of the localized surface plasmon resonance (LSPR) versus the optical band gap (E g,opt ). Excitation of the LSPR leads to efficient hot carrier population above the Fermi level in WO 3–x via Landau damping, in analogy to noble metal LSPR relaxation mechanisms. Hot carrier depopulation occurs on the femtosecond timescale, observed as the concomitant recovery of an LSPR bleach with the appearance of discrete interband and intraband photoinduced absorption features. Further, by comparison, the direct excitation of E g,opt results in trion recombination at donor–acceptor sites within the WO 3–x NC, consistent with exciton decay dynamics observed for typical wide-band-gap semiconductor NCs. From the analysis of pump power dependency data, a hot-carrier electron–phonon coupling constant of 1.47 × 10 11 J K –1 s –1 cm –3 is extracted. The direct comparison of the decay dynamics following E g,opt versus LSPR excitation confirms that the observed plasmon in trioctylphosphine oxide passivated, spherical WO 3–x is a resonance state in which hot carriers are generated only from excitation on resonance with the LSPR frequency. This study on WO 3–x PSNCs provides a toolset that can be used to evaluate the role of hot carriers following LSPR excitation of n-type, plasmonic transparent conducting oxide NCs, where enhancement of photocatalysis, photovoltaic performance, and optical enhancement has been reported.

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

Anomalous softening of 3D printed elastomeric foam irradiated under compressive strain

Elastomeric foam is an essential component in many industrial and technological settings, primarily as thermal insulators and as positional/mechanical support cushions. In particular, silicone foam is utilized in harsh environments due to exceptional thermal and chemical stability. Under service conditions within certain applications such material gets exposed to a high dosage of gamma radiation, which can permanently alter the material’s structural and mechanical response properties. Most studies on gamma-exposure under inert or oxidative atmosphere indicate hardening of silicone foam, which is attributed to radiation-induced enhancement in chemical cross-linking. Here we report two contrasting effects depending on whether (non-oxidative) radiation exposure is carried out with the foam under zero or finite compressive strain. While in the former case we observe radiation-hardening consistent with previous studies, in the latter case (50% porous foam under 30% uniaxial compression) we see a monotonic decrease in Young’s modulus with increasing dosage, although solvent swelling experiments on the constituent rubber indicate a net increase in cross-link density independent of the state of strain. We quantitatively model all dose-dependent data using the Ogden Hyperfoam strain-energy function within the framework of Tobolsky two-network scheme and attribute the above anomaly to a combined effect of radiation-induced thickness change (compression set) and inherent nonlinearity in the foam’s stress-strain response.

Coarse-grained models↗
DOE OSTI2020

Understanding ICF hohlraums using NIF gated laser-entrance-hole images

The newly available ns-gated laser-entrance-hole (LEH) imager on the National Ignition Facility provides routine, non-perturbative measurements of the x-ray emission from laser-heated plasmas inside the hohlraum as viewed at 19° to the hohlraum axis through one of its LEHs. Multiple images are acquired for a series of times and filter-selected x-ray energy bands within a single shot. The images provide time dependent data on phenomena including the effective radius of the LEH, the length of the gold-plasma “bubble” evolving off the interior wall surface heated by the outer beams, the evolving radius of the x-ray heated hohlraum wall, and the radius of the ablation front of the fusion capsule. Here, these measurements are explained and illustrated with sample data. These techniques are then applied to understand hohlraum behavior as a function of gas fill. For hohlraums with helium gas fill densities of 0.15 to 0.30 mg/cm 3 , synthetic images computed from simulations agree well with experimental gated LEH images when an inhibited heat transport model [Jones et al., Phys. Plasmas 24, 056312 (2017)] is used. This model can be adjusted to reproduce the expansion rate of the laser-heated plasma bubble in such a way as to improve agreement with the images. At the higher 0.6 mg/cc gas fill, the experimental images show more pronounced 3D features, resulting in slightly less good agreement with the 2D simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Electronic structure of NdO via slow photoelectron velocity-map imaging spectroscopy of NdO –

Electronically excited NdO is a possible product of the chemistry associated with the release of Nd into the ionosphere, and emission from these states may contribute to the observations following such experiments. To better characterize the energetics and spectroscopy of NdO, we report a combined experimental and theoretical study using slow photoelectron velocity-map imaging spectroscopy of cryogenically cooled NdO – anions (cryo-SEVI) supplemented by wave function-based quantum-chemical calculations. Using cryo-SEVI, we measure the electron affinity of NdO to be 1.0091(7) eV and resolve numerous transitions to low-lying electronic and vibrational states of NdO that are assigned with the aid of the electronic structure calculations. Additionally, temperature-dependent data suggest contributions from the (2)4.5 state of NdO – residing 2350 cm –1 above the ground anion state. Finally, photodetachment to higher-lying excited states of NdO is also reported, which may help to clarify observations from prior release experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗