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At least 919 records · Page 51

Science Validation for Dark Energy Research with Optical Imaging Surveys

The Universe has been expanding at an accelerating rate over the past several billion years, as though an unknown form of dark energy permeates all of space. The ultimate scientific goal of the proposed research is to distinguish between different physical mechanisms that could account for this observed accelerated expansion, for example, the zero-point energy of the vacuum, a dynamical form of energy that varies in time and/or space, or a modification to our theory of gravity. Wide- field optical imaging surveys of the night sky can test these competing models by measuring both the cosmic expansion history and the growth of large-scale structure. To this end, the Dark Energy Survey (DES) has cataloged several hundred million galaxies and thousands of supernovae. The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), will enlarge the census to billions of galaxies and hundreds of thousands of supernovae. A critical question for these dark energy experiments is whether systematic uncertainties can continue to be controlled at a level to keep pace with the statistical precision offered by such enormous datasets. The immediate research objectives of this project were (1) to prepare and validate input datasets that are the foundation of cosmological analyses with DES, and (2) to prepare for value-added characterization of Rubin Observatory commissioning data to inform early operations and accelerate the realization of dark energy science from LSST data products. For DES, we assembled and curated cosmology-ready data releases that include value-added components such as enhanced photometric and astrometric calibrations, alternative source extraction algorithms, maps of the survey coverage and survey conditions, object classifications, object quality selections, galaxy shapes, and photometric redshifts. We used the galaxy clustering technique to validate the photometric redshift distributions of various galaxy samples to be used as lenses in combined studies of galaxy clustering and weak gravitational lensing. The galaxy clustering redshift analysis was enhanced by use of a larger sample of reference galaxies from the eBOSS spectroscopic survey that extends to higher redshifts. For LSST, we prepared for science validation studies of commissioning data aimed at dark energy science capability that extend beyond the normative system-level tests to be done by the Rubin Observatory Construction Project. We identified a set of proposed survey strategies and candidate target fields that could be observed during the commissioning period to enhance science validation activities related to studies of dark energy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Exploration of Options for Ultra-Fast Mass Spectroscopy for Pulsed Power Applications

Mega-ampere class pulsed power machines drive intense currents into small volumes to study high energy and density environments. Power lost during these events is a difficult and paramount problem to solve. For example, facilities such as Sandia National Laboratories’ Z machine experience meaningful power loss, which can be linked to non-linear ohmic heating at high currents (i.e., 26 MA on Z) leading to thermal desorption of contaminants and subsequent shunt plasma formation. Characterizing and understanding this type of thermal desorption is key to design optimizations necessary to minimize current loss, which will be even more important for next generation pulsed power. This type of characterization requires the ability to identify and determine concentration of analytes with nanosecond resolution given the pulse width of Z is on the order of 100 ns. This report summarizes progress on a small exploratory project focused on investigating options to meet this challenge using mass spectrometry. The main focus of these efforts utilized an Energy and Velocity Analyzer for Distributions of Electric Rockets intending to determine how quickly transient data could be resolved. This probe combines an electrostatic analyzer with a Wien velocity filter (ExB) to obtain ion energy and velocity distributions. Primary results from this exploratory project indicate significant additional work is needed to demonstrate a nanosecond time scale mass spectrometer for this application and also highlight that alternative detection methods such as laser-based diagnostics should be considered to meet the need for ultra-fast detection.

42 ENGINEERING↗

Substrate-independent expression of key functional genes in Cycloclasticus pugetii strain PS-1 limits their use as markers for PAH biodegradation

Microbial degradation of petroleum hydrocarbons is a crucial process for the clean-up of oil-contaminated environments. Cycloclasticus spp. are well-known polycyclic aromatic hydrocarbon (PAH) degraders that possess PAH-degradation marker genes including rhd3α, rhd2α, and pahE. However, it remains unknown if the expression of these genes can serve as an indicator for active PAH degradation. Here, we determined transcript-to-gene (TtG) ratios with (reverse transcription) qPCR in cultures of Cycloclasticus pugetii strain PS-1 grown with naphthalene, phenanthrene, a mixture of these PAHs, or alternate substrates (i.e., no PAHs). Mean TtG ratios of 1.99 × 10 −2 , 1.80 × 10 −3 , and 3.20 × 10 −3 for rhd3α, rhd2α, and pahE, respectively, were measured in the presence or absence of PAHs. The TtG values suggested that marker-gene expression is independent of PAH degradation. Measurement of TtG ratios in Arctic seawater microcosms amended with water-accommodated crude oil fractions, and incubated under in situ temperature conditions (i.e., 1.5°C), only detected Cycloclasticus spp. rhd2α genes and transcripts (mean TtG ratio of 4.15 × 10 −1 ). The other marker genes—rhd3α and pahE—were not detected, suggesting that not all Cycloclasticus spp. carry these genes and a broader yet-to-be-identified repertoire of PAH-degradation genes exists. The results indicate that the expression of PAH marker genes may not correlate with PAH-degradation activity, and transcription data should be interpreted cautiously.

59 BASIC BIOLOGICAL SCIENCES↗

Understanding neutron capture processes in uranium deposits using combined U-Sm-Nd isotopic compositions

Valuable insights into the history and evolution of a geologic deposit can be found by investigating neutron capture reactions. Thermal neutron capture reactions occur within both the samarium (Sm) and the uranium (U) systems, where 149 Sm and 235 U can capture neutrons to become 150 Sm and 236 U, respectively. Although largely unexplored, paired measurements of 150 Sm and 236 U could be important for understanding neutron capture effects within uranium ore bodies, and such measurements are potentially useful in nuclear forensics for assessing a material's provenance or mineral exploration. In this work, we refined measurement procedures of Sm isotope compositions utilizing MC-ICPMS. While geologic reference materials were found to have indistinguishable Sm isotope compositions, we found significant isotope variations consistent with nuclear field shift among synthetic Sm standards. Here, this observation highlights that future high-precision Sm isotope investigations need to carefully evaluate synthetic standard(s) against geologic reference materials until an unfractionated and agreed-upon standard is identified. Here, we applied this method to a set of nine uranium ores from the South Australian Beverley North uranium deposits. Although 236 U excesses had been previously reported for these U ores, we found no measurable isotopic shifts in 149 Sm- 150 Sm at the current level of precision (±5 parts per million). One possible explanation for this disparity in the observed neutron capture signatures between U and Sm is that the source(s) of the U and Sm in these ores may be decoupled. This is consistent with the finding that these ores have variable 143 Nd/ 144 Nd, thus demonstrating that diverse sources were involved in the formation of the Beverley North deposits. Alternatively, this deposit may be too young (<50Ma) to have accumulated measurable neutron capture effects in Sm to be detected with the methods employed here.

Mineral exploration↗

Modern deep neural networks for Direct Normal Irradiance forecasting: A classification approach

The escalating energy demand and the adverse environmental impacts of fossil-fuel use necessitate a shift towards cleaner and renewable alternatives. Concentrated Solar Power (CSP) technology emerges as a promising solution, offering a carbon-free alternative for power generation. The efficiency and profitability of CSP depend on the Direct Normal Irradiance (DNI) component of solar radiation; hence, accurate DNI forecasting can help optimize CSP plants’ operations and performance. The unpredictable nature of weather phenomena, particularly cloud cover, introduces uncertainty into DNI projections. Existing DNI forecasting models use meteorological factors, which are both challenging to estimate numerically over short prediction windows and expensive to model through data at a sufficiently high spatial and temporal resolution. This research addresses the challenge by presenting a novel approach that formulates DNI prediction as a multi-class classification problem, departing from conventional regression-based methods. The primary objective of this classification framework is to identify optimal periods aligning with specific operational thresholds for CSP plants, contributing to enhanced dispatch optimization strategies. We model the DNI classification problem using four advanced deep neural networks – rectified linear unit (ReLU) networks, 1D residual networks (ResNets), bidirectional long short-term memory (BiLSTM) networks, and transformers – achieving accuracies up to 93.5% without requiring meteorological parameters.

14 SOLAR ENERGY↗

Structural Models and Sequence Alignment Results of the Desulfovibrio vulgaris Proteome

This dataset contains the structural models for the primary transcripts of the Desulfovibrio vulgaris proteome as well as sequence alignment results for a subset of the encoded proteins. For each protein, the five models inferred from AlphaFold 2 are provided. The largest pTM-scoring model for each protein was energy minimized; this minimized structure as well as its AlphaFold pickle output file are also provided. This set of structures represent an alternate source of models for the D. vulgaris proteome to those available in the AlphaFold Protein Structure Database (AFDB). This is a bit more complicated since the proteins reporting in the AFDB originate from an outdated form of the D. vulgaris sequence. The different versions of the D. vulgaris gene annotation are collected in the Chronology subdirectory; further consideration of these changes on the structural space of the proteome are currently underway. For proteins that have been annotated as hypothetical, sequence alignment results from the HHblits and SAdLSA alignment methods are provided. These methods are often more capable to resolve sequence homology than other methods. Therefore, the results from both HHblits and SAdLSA are provided to identify possible homologs for these challenging proteins. Numerous sequence databases are utilized for these alignments. References AlphaFold v2 Multimer: https://doi.org/10.1101/2021.10.04.463034. References HHblits: hhtps://doi.org/10.1186/s12859-019-3019-7. References SAdLSA: hhtps://doi.org/10.3389/fbinf.2021.689960.

59 BASIC BIOLOGICAL SCIENCES↗

Large-eddy simulation and Reynolds-averaged Navier-Stokes modeling of three Rayleigh-Taylor mixing configurations with gravity reversal

In this work, high-fidelity large-eddy simulation (LES) is performed of Rayleigh-Taylor (RT) mixing in three different configurations involving gravity reversal. In each configuration, LES results are compared with one-dimensional Reynolds-averaged Navier-Stokes (RANS) results, and a deficiency in a commonly used transport equation for the mass-flux velocity, $a_j$, is identified. In the first configuration, a classical two-component RT mixing layer is allowed to develop before it is subjected to rapid acceleration reversal. In the second configuration, a three-component RT mixing layer with an intermediate density layer is allowed to develop before being subjected to rapid acceleration reversal. Finally, in the third configuration, a light layer is interposed between two heavy layers; in this configuration, only one interface is RT-unstable at a time as it undergoes rapid acceleration reversal. In all cases, a commonly used buoyancy production closure in the $a_j$ transport equation is shown to lead to significant over-prediction of mixing layer growth after gravity reversal. An alternative formulation for this closure is then presented which is shown to more accurately capture the stabilization effect of gravity reversal.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Connecting Nitrogen Transformations Mediated by the Rhizosphere Microbiome to Perennial Cropping System Productivity in Marginal Lands

The demand for energy from biofuel production is increasing, prompting concerns about the environmental impact and long-term sustainability of bioenergy cropping systems. These cropping systems will make up much of our future landscapes, and threaten to take the place of food cropping systems. Many life cycle analyses of bioenergy sustainability focus on carbon accrual and budgets, since they want to maximize carbon accrual while producing alternative fuel. Less attention has been given to nitrogen (N) dynamics in these systems. N is the most commonly limiting nutrient for plants, but applying nitrogen fertilizer- as we do for most cropping systems – is harmful to the environment, energetically costly, and produces greenhouse gases. In other words, adding nitrogen by fertilizer bioenergy systems could add to the very problems (climate change) it is trying to address. This is especially true for the areas that are proposed for bioenergy systems: marginal lands. These more degraded lands do not complete with food crops, but do have limited nitrogen. If we are to use these marginal lands for bioenergy, we need to understand the mechanisms regulating nutrient acquisition, and identify ways that bioenergy crops can get nitrogen in sustainable ways. Nutrient acquisition in the soil is performed by microbes in the root zone, or rhizosphere. Microbes can either mineralize nitrogen in the soil (from organic forms) or fix nitrogen from the air, in a process called nitrogen fixation. The goal of our project was thus to understand how the rhizosphere microbiome provides nutrients to bioenergy crops on marginal lands. We focus especially on the process of nitrogen fixation, since it has potential to get “fertilizer for free” that has much less environmental harm. We investigated this goal using sites from the DOE Great Lakes Bioenergy Research Center (GLBRC) in the upper Midwest, and associated lab and ‘omics methods. We group our findings into three major areas. First, we showed that nitrogen fixation, the conversion of N2 gas from the air to ammonium that is usable by plants, is performed in bioenergy soils, and benefits switchgrass crops. While more well-studied in leguminous plants, free-living nitrogen fixation can occur in some systems, and represents a potential opportunity to gain ‘free’ sustainable nitrogen source. We identified the nitrogen fixing bacteria that were most active in providing switchgrass with N, and showed that the drivers of nitrogen fixation occurred at a microscale; it is not well-predicted by bulk variables like soil moisture or plant phenology. Second, we showed that nitrogen fixation is not suppressed by long-term fertilizer. We expected that plentiful nitrogen would reduce the symbiotic relationship between nitrogen fixers and plants, and ‘downregulate’ fixation. We did not find evidence for this, either after long-term fertilizer in the field, or short-term fertilizer in the greenhouse. Finally, we identified the root exudates, carbon compounds that are emitted from the root, that best stimulate nitrogen fixation. We found that carbohydrates were better at stimulating fixation than organic acids. We expected these exudates to be emitted from the plant in periods of high N demand, but we found they are emitted when N is plentiful. This suggests that the stimulation of N fixation by plants is a passive process. Overall, we show that nitrogen fixation has potential to support bioenergy cropping system, and future management could develop ways to maximize it. However, this may not be best achieved via the plant – we found very little evidence of a ‘transactional’ system by which plants are controlling when and where nitrogen fixation is stimulated. It will be better to understand how management practices like planting and fertilizer application affect the microscale soil dynamics, which will determine nitrogen fixation rates.

59 BASIC BIOLOGICAL SCIENCES↗

Autocalibration of the E3SM Version 2 Atmosphere Model Using a PCA-Based Surrogate for Spatial Fields

Global Climate Model tuning (calibration) is a tedious and time-consuming process, with high-dimensional input and output fields. Experts typically tune by iteratively running climate simulations with hand-picked values of tuning parameters. Many, in both the statistical and climate literature, have proposed alternative calibration methods, but most are impractical or difficult to implement. We present a practical, robust, and rigorous calibration approach on the atmosphere-only model of the Department of Energy's Energy Exascale Earth System Model (E3SM) version 2. Our approach can be summarized into two main parts: (a) the training of a surrogate that predicts E3SM output in a fraction of the time compared to running E3SM, and (b) gradient-based parameter optimization. To train the surrogate, we generate a set of designed ensemble runs that span our input parameter space and use polynomial chaos expansions on a reduced output space to fit the E3SM output. We use this surrogate in an optimization scheme to identify values of the input parameters for which our model best matches gridded spatial fields of climate observations. To validate our choice of parameters, we run E3SMv2 with the optimal parameter values and compare prediction results to expertly-tuned simulations across 45 different output fields. This flexible, robust, and automated approach is straightforward to implement, and we demonstrate that the resulting model output matches present day climate observations as well or better than the corresponding output from expert tuned parameter values, while considering high-dimensional output and operating in a fraction of the time.

54 ENVIRONMENTAL SCIENCES↗

Near-cryogenic direct air capture using adsorbents

Direct air capture (DAC) of CO 2 is a key component in the portfolio of negative emissions technologies for mitigating global warming. However, even with the most potent amine sorbents, large-scale DAC deployment remains limited by high energy and capital costs. Recently, adsorbents relying on weak interactions with CO 2 have emerged as a potential alternative, thanks to their rapid adsorption kinetics and superior long-term stability, particularly under sub-ambient conditions (∼253 K). Despite these advantages, their use is hindered by the need for a water-removal process, location-specific constraints, and insufficient working capacity even in cold climates. In this study, we hypothesized that further reducing the adsorption temperature to a near-cryogenic range (160–220 K) could enable cost-effective DAC by utilizing the full potential of physisorbents. We primarily consider integrating DAC with a relatively untapped source of cold energy—liquified natural gas (LNG) regasification—to perform near-cryogenic DAC. From large-scale molecular simulations, Zeolite 13X and CALF-20 were identified as promising candidates. These materials were subsequently examined through experiments, including breakthrough analyses at 195 K. Their high CO 2 sorption capacity (4.5–5.5 mmol g −1 ), combined with a low desorption enthalpy and robust long-term stability, led to a threefold reduction in the levelized cost of capture (down to 68.2 USD per tonne CO 2 ). Estimates of the global LNG regasification resource suggest that LNG–DAC coupling could potentially enable the capture of 103–142 megatonnes of CO 2 annually as of 2050.

Kim, Seo-Yul [Georgia Institute of Technology, Atl↗

On the Importance of Chemical Precision in Organic Electronics: Fullerene Intercalation in Perfectly Alternating Conjugated Polymers

Abstract The true structure of alternating conjugated polymers—the state‐of‐the‐art materials for many organic electronics—often deviates from the idealized picture. Homocoupling defects are in fact inherent to the widely used cross‐coupling polymerization methods. Nevertheless, many polymers still perform excellently in the envisaged applications, which raises the question if one should really care about these imperfections. This article looks at the relevance of chemical precision (and lack thereof) in conjugated polymers covering the entire spectrum from the molecular scale, to the micro and mesostructure, up to the device level. The different types of polymerization errors for the alkoxylated variant of the benchmark (semi)crystalline polymer poly[2,5‐bis(3‐tetradecylthiophen‐2‐yl)thieno[3,2‐ b ]thiophene (PBTTT) are identified, visualized, and quantified and a general strategy to avoid homocoupling is introduced. Through a combination of experiments and supported by simulations, it is shown that these coupling defects hinder fullerene intercalation and limit device performance as compared to the homocoupling‐free analog. This clearly demonstrates that structural defects do matter and should be generally avoided, in particular when the geometrical regularity of the polymer is essential. These insights likely go beyond the specific PBTTT derivatives studied here and are of general relevance for the wider organic electronics field.

36 MATERIALS SCIENCE↗

Does H 2 Temperature‐Programmed Reduction Always Probe Solid‐State Redox Chemistry? The Case of Pt/CeO 2

Abstract Redox reactions on the surface of transition metal oxides are of broad interest in thermo, photo, and electrocatalysis. H 2 temperature‐programmed reduction (H 2 ‐TPR) is commonly used to probe oxide reducibility by measuring the rate of H 2 consumption during temperature ramps, assuming that this rate is controlled by oxide reduction. However, oxide reduction involves several elementary steps, such as H 2 dissociation and H‐spillover, before surface reduction and H 2 O formation occur. In this study, we evaluated the kinetics of H 2 consumption over CeO 2 and Pt/CeO 2 with varying Pt loadings and structures to identify the elementary steps probed by H 2 ‐TPR. Literature often attributes changes in H 2 ‐TPR characteristics with Pt addition to increased CeO 2 reducibility. However, our analysis revealed that the H 2 consumption rate is measurement of the rate of H‐spillover at Pt‐CeO 2 interfaces and is determined by the concentration of Pt species on Pt nanoclusters that dissociate H 2 . Therefore, lower temperature H 2 consumption observed with Pt addition does not indicate higher CeO 2 reducibility. Measurements on samples with mixtures of Pt single‐atoms and nanoclusters demonstrated that H 2 ‐TPR can effectively quantify dilute Pt nanocluster concentrations, suggesting caution in directly linking H 2 ‐TPR characteristics to oxide reducibility while highlighting alternative material insights that can be gleaned.

Lee, Jaeha↗

A Multi-Model Framework for Assessing Long- and Short-Term Climate Influences on the Electric Grid

Climate change influences many aspects of the electric grid, but prior work and industry practices often ignore the potential effects of changing climate, or they only consider a single effect or individual effects in isolation. Challenges vary with each grid and include adapting to long-term trends such as changing temperature and precipitation or shorter-term events such as drought or storms that could increase in frequency or intensity. Here we present a multi-model framework designed to analyze the effects of long and short-term climate impacts in combination. This framework couples capacity expansion and production cost models with hydrologic models and future climate scenario data to analyze alternative climate and energy futures at high spatial, temporal, and process resolutions. Furthermore, we constructed and evaluated the results of a suite of simulated scenarios exploring climate impacts on capacity investment and stress-tested the resulting future infrastructures using hourly dispatch modeling under alternative drought and load conditions. We demonstrate the approach through a case study of the U.S. Western Interconnection, where climate impacts depend on interactions between temperature-induced load, water availability for hydropower, technology competitiveness, and demand flexibility. Changes in 2038 generating capacity range from -8.5-16.6 GW, and changes in 2038 transmission capacity range from -1-2 GW. Capacity increases are driven by higher load from higher temperatures, while capacity reductions can be achieved in scenarios with higher future hydropower availability and increased demand flexibility. Scenarios requiring additional capacity cost an additional $\$5$-$\$17$ billion (discounted) from 2018 to 2038; however, scenarios with capacity reductions cost $\$1$-$\$18$ billion less. Stress tests on four 2038 infrastructures demonstrated that the identified systems were able to serve at least 99.999% of load and 99.96% of reserves. However, drought and unexpected high-load conditions can result in reduced capacity to respond to contingency events we did not model. Although these results are system and scenario specific, they highlight the importance of considering multiple climate change impacts simultaneously in long-term planning efforts and demonstrate a multi-model, multiscale approach that can be flexibly applied to any system and set of climate change concerns.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Process modeling, techno-economic assessment, and life cycle assessment of the electrochemical reduction of CO 2 : a review

The electrochemical reduction of CO 2 has emerged as a promising alternative to traditional fossil-based technologies for the synthesis of chemicals. Its industrial implementation could lead to a reduction in the carbon footprint of chemicals and the mitigation of climate change impacts caused by hard-to-decarbonize industrial applications, among other benefits. However, the current low technology readiness levels of such emerging technologies make it hard to predict their performance at industrial scales. During the past few years, researchers have developed diverse techniques to model and assess the electrochemical reduction of CO 2 toward its industrial implementation. The aim of this literature review is to provide a comprehensive overview of techno-economic and life cycle assessment methods and pave the way for future assessment approaches. First, we identify which modeling approaches have been conducted to extend analysis to the production scale. Next, we explore the metrics used to evaluate such systems, regarding technical, environmental, and economic aspects. Finally, we assess the challenges and research opportunities for the industrial implementation of CO 2 reduction via electrolysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of Porous Crystalline Materials for Selective Binding of O 2 from Air

Porous materials that take advantage of different chemisorptive behaviors of O 2 and N 2 could be an effective alternative to approaches based on physisorption for this important separation. Recently, the tetra-nuclear cobalt complex [(Co(III) 2 (bpbp)O 2 ) 2 bdc](PF 6 ) 4 (CSD code: GAMVIB; bpbp – = 2,6-bis(N,N-bis(2-pyridylmethyl)aminomethyl)-4-tert-butylphenolato; bdc 2– = 1,4-benzenedicarboxylato) was shown to have potential for O 2 /N 2 separations based on this concept. This observation raises the question of what other known materials have similar properties. Here, we combine structure screening with a high-throughput periodic density functional theory (DFT) workflow to investigate O 2 and N 2 adsorption in materials from validated crystal structure databases (e.g., CoRE-MOF database and CSD database). These calculations identify multiple materials that have similar di-Co clusters to GAMVIB that are predicted to selectively bind O 2 over N 2 , and suggest design rules that can be used to tune the O 2 and N 2 affinities in materials of this kind.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Key metrics of progress in the NIF ignition implosions and future challenges on the path to higher yields

Successful demonstration of an implosion that meets the physics metrics for ignition on the National Ignition Facility (NIF) in August 2021 and demonstration of target energy gain G > 1 in December 2022 represented the culmination of more than a decade of research on the NIF. An in-depth analysis of the key ignition metrics achieved on the NIF over the past decade shows sustained progress toward identifying and mitigating degradation effects. Ignition implosions on the NIF have progressed from early experiments whose compressed fuel conditions were degraded by a factor of 10–20 below the ignition threshold with yields of only 1%–2% of the laser energy, to current experiments that significantly exceed the ignition threshold and in the best experiments achieve yields greater than twice the laser energy. It is very likely that NIF can get more than 20 MJ of yield and possibly 50–70 MJ yields when fully optimized at an ultraviolet laser energy of 2.6 MJ following the completion of the NIF Extended Yield Capability Project. Achieving these higher yields will also require improvements to capsules at larger size and possibly with alternate materials, as well as an improved understanding of hohlraum and capsule physics. Now that NIF has achieved ignition, the design of a Next Generation High Energy Density Facility that could achieve the National Nuclear Security Administration long-term goal of substantially higher yields than the NIF can proceed with a more confident physics base. We evaluate these opportunities including possible applications for inertial fusion energy and likely challenges to achieving this level of performance over the next decade.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Effects of a refractory metal protective barrier on uranium carbonitride ceramic–metallic composites exposed to a high temperature hydrogen environment

Uranium nitride has been under consideration at NASA and the Department of Energy for nuclear thermal propulsion applications intended for deep space exploration vehicles. It is critical to the success of the technology development that the behavior of the fuel system is properly characterized in operational environments. This body of work fabricated ceramic metal composites consisting of uranium ceramic fuel in a molybdenum and molybdenum–tungsten metal matrix, both with and without an exterior molybdenum barrier. Specimens were introduced to a high temperature hydrogen environment and characterized through x-ray diffraction, scanning electron microscopy, and energy dispersive spectroscopy to identify characteristic changes. A portion of the specimens was fabricated with a 1.27 mm thick molybdenum barrier in order to isolate the material from the hydrogen environment. Instability of the uranium nitride occurred as low as 2073 K, leading to aggressive instability approaching 2658 K. Carbon reactions with the metal matrix were observed as well as alloying between the uranium and metal matrix constituents. The liquid uranium resulting from the instability of the uranium nitride was observed to attack the grain boundaries of the refractory metal, resulting in the formation of a liquid uranium molybdenum eutectic melt. Specimens encased in a barrier experienced similar results. The authors conclude this is a significant challenge to applications of this cermet at these temperatures. Alternate configurations with resilient hermetic seals or lower temperature applications such as power reactors may have more success.

36 MATERIALS SCIENCE↗

Collapsar R-process Yields Can Reproduce [Eu/Fe] Abundance Scatter in Metal-poor Stars

It is unclear if neutron star mergers can explain the observed r-process abundances of metal-poor stars. Collapsars, defined here as rotating massive stars whose collapse results in a rapidly accreting disk around a black hole that can launch jets, are a promising alternative. We find that we can produce a self-consistent model in which a population of collapsars with stochastic europium yields synthesizes all of the r-process material in metal-poor ([Fe/H] < - 2.5) stars. Our model reproduces the observed scatter and evolution of scatter of [Eu/Fe] abundances. We find that if collapsars are the dominant r-process site for metal-poor stars, r-process synthesis may be linked to supernovae that produce long γ-ray bursts. Our results also allow for the possibility that core-collapse supernovae beyond those that launch γ-ray bursts also produce r-process material (e.g., potentially a subset of Type Ic-BL supernovae). Furthermore, we identify collapsar jet properties (isotropic energy, engine luminosity, or engine time) that may trace r-process yield and verify that the amount of r-process yield produced per collapsar in our model ( ~ 0.07M⊙) is consistent with other independent estimates. In the future, achieving 0.05 dex precision on distribution scatter or a reliable selection function would further constrain our probe of r-process production. Our model would also hold for another prompt r-process site with a power-law yield, and work is needed to determine if, for example, fast-merging neutron stars can also explain abundance scatter.

Astronomy & Astrophysics↗