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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Modular nuclear reactors including fuel elements and heat pipes extending through grid plates, and methods of forming the modular nuclear reactors

A modular nuclear reactor comprises a plurality of sections arranged in a pattern and a side reflector material surrounding the plurality of sections. Each section includes a tank comprising a front plate, a back plate, side plates, a top plate, and a bottom plate. A plurality of grid plates are located within the tank. Each grid plate comprises a plurality of apertures and is vertically separated from an adjacent grid plate. The tank further includes a plurality of fuel elements extending through each grid plate. A plurality of heat pipes extend through each grid plate, the top plate, and an upper reflector. Methods of forming the modular nuclear reactor are also disclosed.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Interpreting the spatial distribution of soil properties with a physically-based distributed hydrological model

Digital soil maps are commonly data-driven as the development of physically-based models for soil mapping is difficult due to the complexity of soils. However, physically-based hydrologic models have been successful in simulating water dynamics. Since water movement is a major driver of pedogenesis, the physical rules that govern water movement might help explain and predict the spatial variation of soil properties. Here, we demonstrate the novel use of a physically-based, distributed hydrologic model to inform the spatial distribution of soil properties. The Distributed Hydrology Soil Vegetation Model (DHSVM) was utilized to simulate soil moisture content (SM) and water table depth (WTD) in two hillslope catchments under pasture and forest management wherein hydrologic model outputs were then compared with soil properties measured in situ. SM sensors and wells were installed in both catchments to validate simulations of soil water movement via Nash-Sutcliffe Efficiency (E). In-situ observations were made at 87 sites within both catchments to study the connection between simulated water movement (SM and WTD) and observed soil properties, namely the depth and thickness of the argillic (Bt), fragic (Btx), and C horizons, and the depth of redoximorphic features. The simulated time series of SM and WTD were also clustered per season using Dynamic Time Warping (DTW), which identified similarity among time series at varying timescales. Model validation suggested that simulations of surficial SM (0–20 cm) were reasonable (E = 0.45), however, simulated subsurface SM (45–60 cm) and WTD were not sufficiently accurate. The thickness of Btx horizons were spatially grouped into different populations by SM clusters from every season except spring. For the other properties, only SM dynamics of specific seasons grouped into significantly different populations, suggesting that the explanatory power of simulated water movement varies seasonally and was greater during winter. Here, we show clusters of simulated SM separated soil properties into statistically different populations, showing that hydrologic models could inform areas that followed different water dynamics related to pedogenic trajectories and related biogeochemical processes not necessarily simulated by the model. As such, physically-based modeling of water dynamics can, therefore, inform and advance digital soil mapping by linking water movement patterns stemming from hydrologic model outputs to spatial patterns of soil properties and pedogenesis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

How drag force evolves in global common envelope simulations

ABSTRACT We compute the forces, torque, and rate of work on the companion-core binary due to drag in global simulations of common envelope (CE) evolution for three different companion masses. Our simulations help to delineate regimes when conventional analytic drag force approximations are applicable. During and just prior to the first periastron passage of the in-spiral phase, the drag force is reasonably approximated by conventional analytic theory and peaks at values proportional to the companion mass. Good agreement between global and local 3D ‘wind tunnel’ simulations, including similar net drag force and flow pattern, is obtained for comparable regions of parameter space. However, subsequent to the first periastron passage, the drag force is up to an order of magnitude smaller than theoretical predictions, quasi-steady, and depends only weakly on companion mass. The discrepancy is exacerbated for larger companion mass and when the inter-particle separation reduces to the Bondi–Hoyle–Lyttleton accretion radius, creating a turbulent thermalized region. Greater flow symmetry during this phase leads to near balance of opposing gravitational forces in front of and behind the companion, hence a small net drag. The reduced drag force at late times helps explain why companion-core separations necessary for envelope ejection are not reached by the end of limited duration CE simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Ferroelectric HfO 2 and the importance of strain

Ferroelectric oxides based on HfO 2 show tremendous promise for the next generation of memory and logic devices. The ferroelectric polymorph is one of several that can be derived from the high symmetry cubic fluorite structure of HfO 2 . A single grain of HfO 2 may consist of a coherent mixture of multiple orientational and translational variants of different polymorphs. Here, we use symmetry-adapted strain-order parameters to elucidate the relationship between the different HfO 2 polymorphs and their symmetrically equivalent variants. We use first-principles electronic structure methods to identify minimum energy pathways and map them in subspaces of the symmetry-adapted strain order parameters. We next investigate the atomic structure of domain boundaries that separate coexisting variants of ferroelectric HfO 2 . Further, we rely on Gibbsian excess quantities and a precise specification of mechanical boundary conditions to describe the thermodynamic properties of domain boundaries. Our first-principles calculations show that the O and Hf shuffle arrangement within a domain boundary is closely related to the intermediate shuffle patterns of the homogeneous pathways between ferroelectric variants. Furthermore, the preferred structure within a boundary is very sensitive to local strain constraints imposed by the adjacent ferroelectric variants, leading to highly anisotropic domain boundary energies.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Exploring the mass surface near the rare-earth abundance peak via precision mass measurements at JYFLTRAP

The JYFLTRAP double Penning trap at the Ion Guide Isotope Separator On-Line facility has been used to measure the atomic masses of 13 neutron-rich rare-earth isotopes. Eight of the nuclides, 161 Pm, 163 Sm, 164,165 Eu, 167 Gd, and 165,167,168 Tb, were measured for the first time. The systematics of the mass surface has been studied via one- and two-neutron separation energies as well as neutron pairing-gap and shell-gap energies. The proton-neutron pairing strength has also been investigated. Furthermore, the impact of the new mass values on the astrophysical rapid neutron capture process has been studied. The calculated abundance distribution results in a better agreement with the solar abundance pattern near the top of the rare-earth abundance peak at around A≈165.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2017

Fluid dynamics analysis of a gas attenuator for X-ray FELs under high-repetition-rate operation

Newtonian fluid dynamics simulations were performed using the Navier–Stokes–Fourier formulations to elucidate the short time-scale (µs and longer) evolution of the density and temperature distributions in an argon-gas-filled attenuator for an X-ray free-electron laser under high-repetition-rate operation. Both hydrodynamic motions of the gas molecules and thermal conductions were included in a finite-volume calculation. It was found that the hydrodynamic wave motions play the primary role in creating a density depression (also known as a filament) by advectively transporting gas particles away from the X-ray laser–gas interaction region, where large pressure and temperature gradients have been built upon the initial energy deposition via X-ray photoelectric absorption and subsequent thermalization. Concurrent outward heat conduction tends to reduce the pressure in the filament core region, generating a counter gas flow to backfill the filament, but on an initially slower time scale. If the inter-pulse separation is sufficiently short so the filament cannot recover, the depth of the filament progressively increases as the trailing pulses remove additional gas particles. Since the rate of hydrodynamic removal decreases while the rate of heat conduction back flow increases as time elapses, the two competing mechanisms ultimately reach a dynamic balance, establishing a repeating pattern for each pulse cycle. Finally, by performing simulations at higher repetition rates but lower per pulse energies while maintaining a constant time-averaged power, the amplitude of the hydrodynamic motion per pulse becomes smaller, and the evolution of the temperature and density distributions approach asymptotically towards, as expected, those calculated for a continuous-wave input of the equivalent power.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Machine Learning in Multimodal Medical Imaging

Machine learning techniques have been increasingly applied in the medical imaging field for developing computer-aided diagnosis and prognosis models. Multimodal medical imaging can provide us with separate yet complementary structure and function information of a patient study and hence has transformed the way we study living bodies. Therefore, using machine learning techniques to deal with multimodal medical images is much more challenging due to the diversity of biophysical-biochemical mechanisms. In these years, researchers mainly adapt modern machine learning and pattern recognition techniques such as supervised, unsupervised, semi-supervised, and deep learning to solve multimodal medical imaging related problems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

A selection of giant radio sources from NVSS

Results of the application of pattern-recognition techniques to the problem of identifying giant radio sources (GRSs) from the data in the NVSS catalog are presented, and issues affecting the process are explored. Decision-tree pattern-recognition software was applied to training-set source pairs developed from known NVSS large-angular-size radio galaxies. The full training set consisted of 51,195 source pairs, 48 of which were known GRSs for which each lobe was primarily represented by a single catalog component. The source pairs had a maximum separation of $20^{\prime} $ and a minimum component area of 1.87 square arcmin at the 1.4 mJy level. The importance of comparing the resulting probability distributions of the training and application sets for cases of unknown class ratio is demonstrated. The probability of correctly ranking a randomly selected (GRS, non-GRS) pair from the best of the tested classifiers was determined to be 97.8 ± 1.5%. The best classifiers were applied to the over 870,000 candidate pairs from the entire catalog. Images of higher-ranked sources were visually screened, and a table of over 1600 candidates, including morphological annotation, is presented. These systems include doubles and triples, wide-angle tail and narrow-angle tail, S- or Z-shaped systems, and core-jets and resolved cores. In conclusion, while some resolved-lobe systems are recovered with this technique, generally it is expected that such systems would require a different approach.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Enzalutamide response in a panel of prostate cancer cell lines reveals a role for glucocorticoid receptor in enzalutamide resistant disease

Representative in vitro model systems that accurately model response to therapy and allow the identification of new targets are important for improving our treatment of prostate cancer. Here we describe molecular characterization and drug testing in a panel of 20 prostate cancer cell lines. The cell lines cluster into distinct subsets based on RNA expression, which is largely driven by functional Androgen Receptor (AR) expression. KLK3 , the AR-responsive gene that encodes prostate specific antigen, shows the greatest variability in expression across the cell line panel. Other common prostate cancer associated genes such as TMPRSS2 and ERG show similar expression patterns. Copy number analysis demonstrates that many of the most commonly gained (including regions containing TERC and MYC ) and lost regions (including regions containing TP53 and PTEN) that were identified in patient samples by the TCGA are mirrored in the prostate cancer cell lines. Assessment of response to the anti-androgen enzalutamide shows a distinct separation of responders and non-responders, predominantly related to status of wild-type AR. Surprisingly, several AR-null lines responded to enzalutamide. These AR-null, enzalutamide-responsive cells were characterized by high levels of expression of glucocorticoid receptor (GR) encoded by NR3C1 . Treatment of these cells with the anti-GR agent mifepristone showed that they were more sensitive to this drug than enzalutamide, as were several of the enzalutamide non-responsive lines. This is consistent with several recent reports that suggest that GR expression is an alternative signaling mechanism that can bypass AR blockade. This study reinforces the utility of large cell line panels for the study of cancer and identifies several cell lines that represent ideal models to study AR-null cells that have upregulated GR to sustain growth.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Faraday rotation study of plasma bubbles in GeV wakefield accelerators

We visualize plasma bubbles driven by 0.67 PW laser pulses in a plasma of density ne≈5×1017cm−3 by imaging Faraday rotation patterns imprinted on linearly polarized probe pulses of wavelength λpr=1.05 μm and duration τpr=2 or 1 ps that cross the bubble's path at right angles. When the bubble captures and accelerates tens to hundreds of pC of electron charges, we observe two parallel streaks of length cτpr straddling the drive pulse propagation axis, separated by ∼45 μm, in which probe polarization rotates by 0.3° to more than 5° in opposite directions. Accompanying simulations show that they result from Faraday rotation within portions of dense bubble side walls that are pervaded by the azimuthal magnetic field of accelerating electrons during the probe transit across the bubble. Analysis of the width of the streaks shows that quasi-monoenergetic high-energy electrons and trailing lower energy electrons inside the bubble contribute distinguishable portions of the observed signals, and relativistic flow of sheath electrons suppresses Faraday rotation from the rear of the bubble. The results demonstrate favorable scaling of Faraday rotation diagnostics to 40× lower plasma density than previously demonstrated.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Conifer water use patterns in the East River Watershed, Colorado US, based on stable water isotopes and cellulose isotopes

This data package contains a series of datasets aimed at understanding the seasonal origins of water used by the dominant conifer species, Abies lasiocarpa and Picea engelmannii, in the East River Watershed. There is a distinct difference in the stable isotopic ratio of summer rain and snowpack and thus by tracking the isotopic ratio of the xylem water in trees, it is possible to separate when a tree is using snow vs. summer rain. Following typical protocols, we sampled and extracted water from soils in the "Research Meadow" near Gothic, CO within the East River Watershed through the 2016 growing season. The stable isotopic ratio of these waters were then measured. Using values of the isotopic ratio of precipitation and snowpack from that season, we develop a mixing model to show how the trees transitioned from use of snowpack to summer in late July. We extended the information on the seasonal origins of water from 2016 back until 1980 by using measurements of the isotopic ratio of cellulose from trees in the Research Meadow. The isotopic ratio of tree ring cellulose records a signal both of the Vapor Pressure Deficit at the leaf-atmosphere boundary and also the source water for the trees. We concluded from this extended analysis that the trees underwent transitions between periods where snow was the dominant water source and summer rain was the dominant water source. More details on this analysis can be found in the publication: Persistence and Plasticity in Conifer Water Use Strategies. JGR Biogeoscience. DOI 10.1029/2018JG004845. The dataset specifically includes stable isotope measurements of xylem and soil water for Spruce and Fir trees at the Rocky Mountain Biological Lab's Research Meadow as well as snowpack and precipitation stable isotopes from nearby National Atmospheric Deposition Program sites. Associated meteorological data is included, which is needed to understand the source water for the trees based on the cellulose measurements.This dataset was updated in June 2021 also include intra-ring measurements of the d18O and d13C of cellulose these same species of trees at the Ziegler Reservoir site in Snowmass, CO. These are listed as files: "Interglaciald18OCellulose.csv", "Interglaciald13OCellulose.csv" and "Modernd13CCellulose.csv". The intent of these measurements was to assess whether common conifers (abies and picea) had undergone ecophysiological or ecohydrological changes during the last period in Earth's history was warmer than today, i.e. the last Interglacial (116,000 to 130,000 years ago). This site was chosen because it is a location where subfossil wood from this critical warm period was discovered. We measured the d18O and d13C of the subfossil trees following the same protocol as the modern samples which included chemical extraction of cellulose and isotope ratio mass spectrometry. We found that the trees showed little difference in water use efficiency but utilized more summer rain during the interglacial period. This analysis and detailed methods are provided in the following manuscript: Wetter summers mitigated temperature stress on Rocky Mountain forests during the last interglacial warm period which is in revision at GRL but is available as a preprint here: 10.1002/essoar.10506740.2

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

PdAu/YSZ composite hydrogen separation membranes with enhanced stability in the presence of CO

The effects of gold composition on the tolerance of palladium-based composite membranes to CO exposure was studied under the presence of high CO concentrations. Membranes with PdAu compositions ranging up to 41% by mass were exposed to binary 50/50 H 2 /CO gas atmospheres and both hydrogen flux and purity were monitored over time. It was observed that the highest gold composition (41%) suffered no degradation in membrane performance in terms of permeate hydrogen purity and hydrogen permeation flux during the 48 h exposure. Furthermore, for lower gold compositions, X-ray diffraction patterns suggested that carbon entered the film and could be removed by exposure to a non-CO containing gas mixture over time. However, removal of the carbon adversely affected purity; interestingly, some of the purity decline could be reversed upon re-exposure to the CO gas mixture. It is hypothesized that carbon loading in the palladium films causes lattice expansion and may even fill pore defects, thus lowering leaks through the Pd films. Furthermore, this study suggests that a membrane exposed to a CO mixture should not be cycled between CO and non-CO environments, but rather run continuously for best performance. Additionally, the choice of Pd-alloy and metal composition should be considered in regard to its carbon solubility to best predict lifetime performance.

08 HYDROGEN↗
DOE OSTI2022

Using neural network ensembles to separate ocean biogeochemical and physical drivers of phytoplankton biogeography in Earth system models

Abstract. Earth system models (ESMs) are useful tools for predicting and understanding past and future aspects of the climate system. However, the biological and physical parameters used in ESMs can have wide variations in their estimates. Even small changes in these parameters can yield unexpected results without a clear explanation of how a particular outcome was reached. The standard method for estimating ESM sensitivity is to compare spatiotemporal distributions of variables from different runs of a single ESM. However, a potential pitfall of this method is that ESM output could match observational patterns because of compensating errors. For example, if a model predicts overly weak upwelling and low nutrient concentrations, it might compensate for this by allowing phytoplankton to have a high sensitivity to nutrients. Recently, we demonstrated that neural network ensembles (NNEs) are capable of extracting relationships between predictor and target variables within ocean biogeochemical models. Being able to view the relationships between variables, along with spatiotemporal distributions, allows for a more mechanistically based examination of ESM outputs. Here, we investigated whether we could apply NNEs to help us determine why different ESMs produce different spatiotemporal distributions of phytoplankton biomass. We tested this using three cases. The first and second case used different runs of the same ESM, except that the physical circulations differed between them in the first case, while the biological equations differed between them in the second. Our results indicated that the NNEs were capable of extracting the relationships between variables for different runs of a single ESM, allowing us to distinguish between differences due to changes in circulation (which do not change relationships) from changes in biogeochemical formulation (which do change relationships). In the third case, we applied NNEs to two different ESMs. The results of the third case highlighted the capability of NNEs to contrast the apparent relationships of different ESMs and some of the challenges it presents. Although applied specifically to the ocean components of an ESM, our study demonstrates that Earth system modelers can use NNEs to separate the contributions of different components of ESMs. Specifically, this allows modelers to compare the apparent relationships across different ESMs and observational datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Determining the roles of the three alcohol dehydrogenases (AdhA, AdhB and AdhE) in Thermoanaerobacter ethanolicus during ethanol formation

Abstract Thermoanaerobacter ethanolicus is a promising candidate for biofuel production due to the broad range of substrates it can utilize and its high ethanol yield compared to other thermophilic bacteria, such as Clostridium thermocellum. Three alcohol dehydrogenases, AdhA, AdhB and AdhE, play key roles in ethanol formation. To study their physiological roles during ethanol formation, we deleted them separately and in combination. Previously, it has been thought that both AdhB and AdhE were bifunctional alcohol dehydrogenases. Here we show that AdhE has primarily acetyl-CoA reduction activity (ALDH) and almost no acetaldehyde reduction (ADH) activity, whereas AdhB has no ALDH activity and but high ADH activity. We found that AdhA and AdhB have similar patterns of activity. Interestingly, although deletion of both adhA and adhB reduced ethanol production, a single deletion of either one actually increased ethanol yields by 60–70%.

Zhou, Jilai↗
DOE OSTI2019

Simulated projections of boreal forest peatland ecosystem productivity are sensitive to observed seasonality in leaf physiology

We quantified seasonal CO 2 assimilation capacities for seven dominant vascular species in a wet boreal forest peatland then applied data to a land surface model parametrized to the site (ELM-SPRUCE) to test if seasonality in photosynthetic parameters results in differences in simulated plant responses to elevated CO 2 and temperature. We collected seasonal leaf-level gas exchange, nutrient content and stand allometric data from the field-layer community (i.e., Maianthemum trifolium (L.) Sloboda), understory shrubs ( Rhododendron groenlandicum (Oeder) Kron and Judd, Chamaedaphne calyculata (L.) Moench., Kalmia polifolia Wangenh. and Vaccinium angustifolium Alton.) and overstory trees ( Picea mariana (Mill.) B.S.P. and Larix laricina (Du Roi) K. Koch). We found significant interspecific seasonal differences in specific leaf area, nitrogen content (by area; N a ) and photosynthetic parameters (i.e., maximum rates of Rubisco carboxylation (V cmax25°C ), electron transport (J max25°C ) and dark respiration (R d25°C )), but minimal correlation between foliar Na and V cmax25°C , J max25°C or R d25°C , which illustrates that nitrogen alone is not a good correlate for physiological processes such as Rubisco activity that can change seasonally in this system. ELM-SPRUCE was sensitive to the introduction of observed interspecific seasonality in V cmax25°C , J max25°C and R d25°C , leading to simulated enhancement of net primary production (NPP) using seasonally dynamic parameters as compared with use of static parameters. This pattern was particularly pronounced under simulations with higher temperature and elevated CO 2 , suggesting a key hypothesis to address with future empirical or observational studies as climate changes. As a result, inclusion of species-specific seasonal photosynthetic parameters should improve estimates of boreal ecosystem-level NPP, especially if impacts of seasonal physiological ontogeny can be separated from seasonal thermal acclimation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

High-speed CMOS camera

A high-speed CMOS camera includes an array of pixel circuits coupled to a photodiode array, an oscillator circuit, and a pattern generator circuit. The pattern generator circuit includes a high speed shift register and a non-overlap generator. The shift register is programmable to produce a pulse train of trigger pulses that defines an interframe and a frame's shutter duration. The non-overlap generator deserializes the incoming pulse train of trigger pulses, and it produces a time-separated reset pulse based on the pulse train of trigger pulses. The shift register is configured to permit the frame durations and the interframe times to be selected arbitrarily over specified ranges in increments of a basic time unit that depends on the oscillator period.

42 ENGINEERING↗
DOE OSTI2020

Pattern generator circuit for high-speed pulse generation

A pattern generator circuit includes a high-speed shift register and a non-overlap generator. The shift register is programmable to produce a pulse train of pulses having a defined pulse duration and a defined pulse-to-pulse interval. The non-overlap generator deserializes the incoming pulse train, and it produces a time-separated reset pulse based on the pulse train. The shift register is configured to permit the pulse durations and pulse-to-pulse interval to be selected arbitrarily over specified ranges in increments of a basic time unit that depends on the oscillator period.

42 ENGINEERING↗
DOE OSTI2025

Computationally Guided and Experimentally Validated Design of Custom Chelators for Critical Mineral Recovery

Selective, high throughput separation of target critical metals from complex environments such as fly ash leachates and mining process streams presents a significant challenge for economical production. Custom chelators and sorbents are an attractive technology for selective metal extraction, however it can be difficult to predict their performance, and significant experimental efforts are often required to develop chelating technologies. Here, we present a computational strategy focused on modelling chelator-metal binding interactions and benchmark these results versus experimental data. A computational pipeline combining forcefield, semiempirical, and meta-GGA methods with a thermodynamic framework optimized for error cancellation has been developed to predict binding energies of chelator complexes towards critical mineral recovery applications. This approach, originally validated on [2.2.2] cryptates binding mono- and divalent cations, demonstrated robust predictive capabilities with an R2 of 0.850 against experimental aqueous binding energies. The workflow includes metadynamics for exploring high-dimensional potential energy surfaces and a cluster-continuum model for accurate yet computationally efficient solvation modeling. Error cancellation between solvation energies of free and chelator-coordinated ions enables faster convergence, even with finite cluster sizes. Initial studies on the cryptates revealed consistent metal-ligand coordination patterns, with systematic variations influenced by ion size and charge, highlighting key structural features linked to binding selectivity. Further studies of a proprietary chelator have resulted in identification of previously unreported selectivity towards economically significant metals, which in-house experiments have confirmed, demonstrating the feasibility of this approach. By applying this methodology to new chelators targeting critical minerals such as lithium, cobalt, nickel and other strategic metals, we aim to accelerate the discovery of next-generation chelators for efficient recovery, recycling, and separation processes. This computational framework serves as the backbone of a high-throughput design pipeline tailored for sustainable resource utilization and may be applied to a wide range of systems to meet experimental needs.

computational materials↗