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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A measurement of the equation of state of carbon envelopes of white dwarfs

White dwarfs represent the final state of evolution for most stars. Certain classes of white dwarfs pulsate, leading to observable brightness variations, and analysis of these variations with theoretical stellar models probes their internal structure. Modelling of these pulsating stars provides stringent tests of white dwarf models and a detailed picture of the outcome of the late stages of stellar evolution. However, the high-energy-density states that exist in white dwarfs are extremely difficult to reach and to measure in the laboratory, so theoretical predictions are largely untested at these conditions. In this paper we report measurements of the relationship between pressure and density along the principal shock Hugoniot (equations describing the state of the sample material before and after the passage of the shock derived from conservation laws) of hydrocarbon to within five per cent. The observed maximum compressibility is consistent with theoretical models that include detailed electronic structure. This is relevant for the equation of state of matter at pressures ranging from 100 million to 450 million atmospheres, where the understanding of white dwarf physics is sensitive to the equation of state and where models differ considerably. The measurements test these equation-of-state relations that are used in the modelling of white dwarfs and inertial confinement fusion experiments, and we predict an increase in compressibility due to ionization of the inner-core orbitals of carbon. We also find that a detailed treatment of the electronic structure and the electron degeneracy pressure is required to capture the measured shape of the pressure–density evolution for hydrocarbon before peak compression. Our results illuminate the equation of state of the white dwarf envelope (the region surrounding the stellar core that contains partially ionized and partially degenerate non-ideal plasmas), which is a weak link in the constitutive physics informing the structure and evolution of white dwarf stars.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

A lanthanide-rich kilonova in the aftermath of a long gamma-ray burst

Observationally, kilonovae are astrophysical transients powered by the radioactive decay of nuclei heavier than iron, thought to be synthesized in the merger of two compact objects. Over the first few days, the kilonova evolution is dominated by a large number of radioactive isotopes contributing to the heating rate. On timescales of weeks to months, its behaviour is predicted to differ depending on the ejecta composition and the merger remnant. Previous work has shown that the kilonova associated with gamma-ray burst 230307A is similar to kilonova AT2017gfo, and mid-infrared spectra revealed an emission line at 2.15 micrometres that was attributed to tellurium. Here, in this study, we report a multi-wavelength analysis, including publicly available James Webb Space Telescope data and our own Hubble Space Telescope data, for the same gamma-ray burst. We model its evolution up to two months after the burst and show that, at these late times, the recession of the photospheric radius and the rapidly decaying bolometric luminosity (L bol ∝ t −2.7±0.4 , where t is time) support the recombination of lanthanide-rich ejecta as they cool.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

An evaporite sequence from ancient brine recorded in Bennu samples

Evaporation or freezing of water-rich fluids with dilute concentrations of dissolved salts can produce brines, as observed in closed basins on Earth and detected by remote sensing on icy bodies in the outer Solar System. The mineralogical evolution of these brines is well understood in regard to terrestrial environments, but poorly constrained for extraterrestrial systems owing to a lack of direct sampling. Here we report the occurrence of salt minerals in samples of the asteroid (101955) Bennu returned by the OSIRIS-REx mission. These include sodium-bearing phosphates and sodium-rich carbonates, sulfates, chlorides and fluorides formed during evaporation of a late-stage brine that existed early in the history of Bennu’s parent body. Discovery of diverse salts would not be possible without mission sample return and careful curation and storage, because these decompose with prolonged exposure to Earth’s atmosphere. Similar brines probably still occur in the interior of icy bodies Ceres and Enceladus, as indicated by spectra or measurement of sodium carbonate on the surface or in plumes.

58 GEOSCIENCES↗
DOE OSTI2023

Model metamers reveal divergent invariances between biological and artificial neural networks

Deep neural network models of sensory systems are often proposed to learn representational transformations with invariances like those in the brain. To reveal these invariances, we generated ‘model metamers’, stimuli whose activations within a model stage are matched to those of a natural stimulus. Metamers for state-of-the-art supervised and unsupervised neural network models of vision and audition were often completely unrecognizable to humans when generated from late model stages, suggesting differences between model and human invariances. Targeted model changes improved human recognizability of model metamers but did not eliminate the overall human–model discrepancy. The human recognizability of a model’s metamers was well predicted by their recognizability by other models, suggesting that models contain idiosyncratic invariances in addition to those required by the task. Metamer recognizability dissociated from both traditional brain-based benchmarks and adversarial vulnerability, revealing a distinct failure mode of existing sensory models and providing a complementary benchmark for model assessment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

MFRED, 10 second interval real and reactive power for groups of 390 US apartments of varying size and vintage

Abstract Building electricity is a major component of global energy use and its environmental impacts. Detailed data on residential electricity use have many interrelated research applications, from energy conservation to non-intrusive load monitoring, energy storage, integration of renewables, and electric vs. fossil-based heating. The dataset presented here, Multifamily Residential Electricity Dataset (MFRED), contains the electricity use of 390 apartments, ranging from studios to four-bedroom units. All apartments are located in the Northeastern United States (IECC-climate-zone 4 A), but differ in their heating/cooling system and construction year (early to late 20 th century). To adhere to privacy guidelines, data were averaged across 15 apartments each, based on annual electricity use. MFRED includes real and reactive power, at 10-second resolution, for January to December 2019 (246 million data points). The annual average real power per apartment is 343 W (3.27 W/m 2 of floor area), with strong variation between seasons and apartment size. Considering its large number of apartments, high time resolution, real and reactive power, and 12-month duration, MFRED is currently unique for the multifamily-sector.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Two decades of fumigation data from the Soybean Free Air Concentration Enrichment facility

Abstract The Soybean Free Air Concentration Enrichment (SoyFACE) facility is the longest running open-air carbon dioxide and ozone enrichment facility in the world. For over two decades, soybean, maize, and other crops have been exposed to the elevated carbon dioxide and ozone concentrations anticipated for late this century. The facility, located in East Central Illinois, USA, exposes crops to different atmospheric concentrations in replicated octagonal ~280 m 2 Free Air Concentration Enrichment (FACE) treatment plots. Each FACE plot is paired with an untreated control (ambient) plot. The experiment provides important ground truth data for predicting future crop productivity. Fumigation data from SoyFACE were collected every four seconds throughout each growing season for over two decades. Here, we organize, quality control, and collate 20 years of data to facilitate trend analysis and crop modeling efforts. This paper provides the rationale for and a description of the SoyFACE experiments, along with a summary of the fumigation data and collation process, weather and ambient data collection procedures, and explanations of air pollution metrics and calculations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

The Arctic Plant Aboveground Biomass Synthesis Dataset

Plant biomass is a fundamental ecosystem attribute that is sensitive to rapid climatic changes occurring in the Arctic. Nevertheless, measuring plant biomass in the Arctic is logistically challenging and resource intensive. Lack of accessible field data hinders efforts to understand the amount, composition, distribution, and changes in plant biomass in these northern ecosystems. Here, we present The Arctic plant aboveground biomass synthesis dataset, which includes field measurements of lichen, bryophyte, herb, shrub, and/or tree aboveground biomass (g m -2 ) on 2,327 sample plots from 636 field sites in seven countries. We created the synthesis dataset by assembling and harmonizing 32 individual datasets. Aboveground biomass was primarily quantified by harvesting sample plots during mid- to late-summer, though tree and often tall shrub biomass were quantified using surveys and allometric models. Each biomass measurement is associated with metadata including sample date, location, method, data source, and other information. This unique dataset can be leveraged to monitor, map, and model plant biomass across the rapidly warming Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Enhanced purification coupled with biophysical analyses shows cross-β structure as a core building block for Streptococcus mutans functional amyloids

Streptococcus mutans is an etiologic agent of human dental caries that forms dental plaque biofilms containing functional amyloids. Three amyloidogenic proteins, P1, WapA, and Smu_63c were previously identified. C123 and AgA are naturally occurring amyloid-forming fragments of P1 and WapA, respectively. We determined that four amyloidophilic dyes, ThT, CDy11, BD-oligo, and MK-H4, differentiate C123, AgA, and Smu_63c amyloid from monomers, but non-specific binding to bacterial cells in the absence of amyloid precludes their utility for identifying amyloid in biofilms. Congo redinduced birefringence is a more specific indicator of amyloid formation and differentiates biofilms formed by wild-type S. mutans from a triple ΔP1/WapA/Smu_63c mutant with reduced bioiflm forming capabilities. Amyloid accumulation is a late event, appearing in older S. mutans biofilms after 60hours of growth. Amyloid derived from pure preparations of all three proteins is visualized by electron microscopy as mat-like structures. Typical amyloid fibers become evident following protease digestion to eliminate non-specific aggregates and monomers. Amyloid mats, similar in appearance to those reported in S. mutans biofilm extracellular matrices, are reconstituted by co-incubation of monomers and amyloid fibers. X-ray fiber diffraction of amyloid mats and fibers from all three proteins demonstrate patterns reflective of a cross-β amyloid structure.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

An infrared spectral biomarker accurately predicts neurodegenerative disease class in the absence of overt symptoms

Although some neurodegenerative diseases can be identified by behavioral characteristics relatively late in disease progression, we currently lack methods to predict who has developed disease before the onset of symptoms, when onset will occur, or the outcome of therapeutics. New biomarkers are needed. Here we describe spectral phenotyping, a new kind of biomarker that makes disease predictions based on chemical rather than biological endpoints in cells. Spectral phenotyping uses Fourier Transform Infrared (FTIR) spectromicroscopy to produce an absorbance signature as a rapid physiological indicator of disease state. FTIR spectromicroscopy has over the past been used in differential diagnoses of manifest disease. Here, we report that the unique FTIR chemical signature accurately predicts disease class in mouse with high probability in the absence of brain pathology. In human cells, the FTIR biomarker accurately predicts neurodegenerative disease class using fibroblasts as surrogate cells.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Structural insight into host plasma membrane association and assembly of HIV-1 matrix protein

Oligomerization of Pr55 Gag is a critical step of the late stage of the HIV life cycle. It has been known that the binding of IP6, an abundant endogenous cyclitol molecule at the MA domain, has been linked to the oligomerization of Pr55 Gag . However, the exact binding site of IP6 on MA remains unknown and the structural details of this interaction are missing. Here, we present three high-resolution crystal structures of the MA domain in complex with IP6 molecules to reveal its binding mode. Additionally, extensive Differential Scanning Fluorimetry analysis combined with cryo- and ambient-temperature X-ray crystallography and GNM-based transfer entropy calculations identify the key residues that participate in IP6 binding. Our data provide novel insights about the multilayered HIV-1 virion assembly process that involves the interplay of IP6 with PIP2, a phosphoinositide essential for the binding of Pr55 Gag to membrane. IP6 and PIP2 have neighboring alternate binding sites within the same highly basic region (residues 18–33). This indicates that IP6 and PIP2 bindings are not mutually exclusive and may play a key role in coordinating virion particles’ membrane localization. Based on our three different IP6-MA complex crystal structures, we propose a new model that involves IP6 coordination of the oligomerization of outer MA and inner CA domain’s 2D layers during assembly and budding.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Pollen antigens and atmospheric circulation driven seasonal respiratory viral outbreak and its implication to the Covid-19 pandemic

Abstract The patterns of respiratory virus illness are expressed differently between temperate and tropical climates. Tropical outbreaks often peak in wet seasons. Temperate outbreaks typically peak during the winter. The prevailing causal hypotheses focus on sunlight, temperature and humidity variations. Yet no consistent factors have been identified to sufficiently explain seasonal virus emergence and decline at any latitude. Here we demonstrate close connections among global-scale atmospheric circulations, IgE antibody enhancement through seasonal pollen inhalation, and respiratory virus patterns at any populated latitude, with a focus on the US. Pollens emerge each Spring, and the renewed IgE titers in the population are argued to terminate each winter peak of respiratory illness. Globally circulated airborne viruses are postulated to subsequently deposit across the Southern US during lower zonal geostrophic winds each late Summer. This seasonally refreshed viral load is postulated to trigger a new influenza outbreak, once the existing IgE antibodies diminish to a critical value each Fall. Our study offers a new and consistent explanation for the seasonal diminishment of respiratory viral illnesses in temperate climates, the subdued seasonal signature in the tropics, the annually circulated virus phenotypes, and the northerly migration of influenza across the US every year. Our integrated geospatial and IgE hypothesis provides a new perspective for prediction, mitigation and prevention of the outbreak and spread of seasonal respiratory viruses including Covid-19 pandemic.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Projected U.S. drought extremes through the twenty-first century with vapor pressure deficit

Global warming is expected to enhance drought extremes in the United States throughout the twenty-first century. Projecting these changes can be complex in regions with large variability in atmospheric and soil moisture on small spatial scales. Vapor Pressure Deficit (VPD) is a valuable measure of evaporative demand as moisture moves from the surface into the atmosphere and a dynamic measure of drought. Here, VPD is used to identify short-term drought with the Standardized VPD Drought Index (SVDI); and used to characterize future extreme droughts using grid dependent stationary and non-stationary generalized extreme value (GEV) models, and a random sampling technique is developed to quantify multimodel uncertainties. The GEV analysis was performed with projections using the Weather Research and Forecasting model, downscaled from three Global Climate Models based on the Representative Concentration Pathway 8.5 for present, mid-century and late-century. Results show the VPD based index (SVDI) accurately identifies the timing and magnitude short-term droughts, and extreme VPD is increasing across the United States and by the end of the twenty-first century. The number of days VPD is above 9 kPa increases by 10 days along California’s coastline, 30–40 days in the northwest and Midwest, and 100 days in California’s Central Valley.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Counting generations in birth and death processes with competing Erlang and exponential waiting times

Lymphocyte populations, stimulated in vitro or in vivo, grow as cells divide. Stochastic models are appropriate because some cells undergo multiple rounds of division, some die, and others of the same type in the same conditions do not divide at all. If individual cells behave independently, then each cell can be imagined as sampling from a probability density of times to division and death. The exponential density is the most mathematically and computationally convenient choice. It has the advantage of satisfying the memoryless property, consistent with a Markov process, but it overestimates the probability of short division times. With the aim of preserving the advantages of a Markovian framework while improving the representation of experimentally-observed division times, we consider a multi-stage model of cellular division and death. We use Erlang-distributed (or, more generally, phase-type distributed) times to division, and exponentially distributed times to death. We classify cells into generations, using the rule that the daughters of cells in generation n are in generation n + 1. In some circumstances, our representation is equivalent to established models of lymphocyte dynamics. We find the growth rate of the cell population by calculating the proportions of cells by stage and generation. The exponent describing the late-time cell population growth, and the criterion for extinction of the population, differs from what would be expected if N steps with rate λ were equivalent to a single step of rate λ/N. We link with a published experimental dataset, where cell counts were reported after T cells were transferred to lymphopenic mice, using Approximate Bayesian Computation. In the comparison, the death rate is assumed to be proportional to the generation and the Erlang time to division for generation 0 is allowed to differ from that of subsequent generations. The multi-stage representation is preferred to a simple exponential in posterior distributions, and the mean time to first division is estimated to be longer than the mean time to subsequent divisions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Advanced characterization-informed machine learning framework and quantitative insight to irradiated annular U-10Zr metallic fuels

Abstract U-10Zr Metal fuel is a promising nuclear fuel candidate for next-generation sodium-cooled fast spectrum reactors. Since the Experimental Breeder Reactor-II in the late 1960s, researchers accumulated a considerable amount of experience and knowledge on fuel performance at the engineering scale. However, a mechanistic understanding of fuel microstructure evolution and property degradation during in-reactor irradiation is still missing due to a lack of appropriate tools for rapid fuel microstructure assessment and property prediction based on post irradiation examination. This paper proposed a machine learning enabled workflow, coupled with domain knowledge and large dataset collected from advanced post-irradiation examination microscopies, to provide rapid and quantified assessments of the microstructure in two reactor irradiated prototypical annular metal fuels. Specifically, this paper revealed the distribution of Zr-bearing secondary phases and constitutional redistribution across different radial locations. Additionally, the ratios of seven different microstructures at various locations along the temperature gradient were quantified. Moreover, the distributions of fission gas pores on two types of U-10Zr annular fuels were quantitatively compared.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Multi-variate model of T cell clonotype competition and homeostasis

Abstract Diversity of the naive T cell repertoire is maintained by competition for stimuli provided by self-peptides bound to major histocompatibility complexes (self-pMHCs). We extend an existing bi-variate competition model to a multi-variate model of the dynamics of multiple T cell clonotypes which share stimuli. In order to understand the late-time behaviour of the system, we analyse: (i) the dynamics until the extinction of the first clonotype, (ii) the time to the first extinction event, (iii) the probability of extinction of each clonotype, and (iv) the size of the surviving clonotypes when the first extinction event takes place. We also find the probability distribution of the number of cell divisions per clonotype before its extinction. The mean size of a new clonotype at quasi-steady state is an increasing function of the stimulus available to it, and a decreasing function of the fraction of stimuli it shares with other clonotypes. Thus, the probability of, and time to, extinction of a new clonotype entering the pool of T cell clonotypes is determined by the extent of competition for stimuli it experiences and by its initial number of cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Prediction of chronic kidney disease progression using recurrent neural network and electronic health records

Chronic kidney disease (CKD) is a progressive loss in kidney function. Early detection of patients who will progress to late-stage CKD is of paramount importance for patient care. To address this, we develop a pipeline to process longitudinal electronic heath records (EHRs) and construct recurrent neural network (RNN) models to predict CKD progression from stages II/III to stages IV/V. The RNN model generates predictions based on time-series records of patients, including repeated lab tests and other clinical variables. Our investigation reveals that using a single variable, the recorded estimated glomerular filtration rate (eGFR) over time, the RNN model achieves an average area under the receiver operating characteristic curve (AUROC) of 0.957 for predicting future CKD progression. When additional clinical variables, such as demographics, vital information, lab test results, and health behaviors, are incorporated, the average AUROC increases to 0.967. In both scenarios, the standard deviation of the AUROC across cross-validation trials is less than 0.01, indicating a stable and high prediction accuracy. Our analysis results demonstrate the proposed RNN model outperforms existing standard approaches, including static and dynamic Cox proportional hazards models, random forest, and LightGBM. The utilization of the RNN model and the time-series data of previous eGFR measurements underscores its potential as a straightforward and effective tool for assessing the clinical risk of CKD patients concerning their disease progression.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Open questions in transplutonium coordination chemistry

Over the past decade, momentous progress has been made in the characterization of late actinide compounds. Here the authors highlight how advances in spectroscopic and computational tools have developed our understanding of fundamental transplutonium bonding interactions, and discuss whether covalency and heterogeneity changes in 5f-orbital bonding could be harnessed in environmentally and industrially relevant systems.

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

Realization of two-sublattice exchange physics in the triangular lattice compound Ba 3 Er(BO 3 ) 3

Geometric frustration commonly occurs in materials where magnetic rare-earth ions are arranged on a two-dimensional triangular lattice. These compounds have been gaining significant attention lately, as they hold the promise of revealing unique quantum states of matter. However, little attention has been devoted to cases where spin-$\frac{1}{2}$ rare-earth ions are substituted with ions exhibiting higher spin multiplicities. Here, we successfully synthesize high-quality single crystal samples of Ba 3 Er(BO 3 ) 3 , which is part of the family of triangular lattice compounds. In our experiments, conducted at extremely low temperatures (around 100 millikelvin), we observe two sublattice exchange interactions in Ba 3 Er(BO 3 ) 3 , resulting in the hexagonal lattice spins exhibiting a mixture of ferromagnetic and antiferromagnetic tendencies. Our theoretical analysis suggest that this behavior may be attributed to the distinct positions of magnetic ions within the crystal lattice. However, the presence of quantum effects adds an extra layer of complexity to our findings, calling for further exploration.

36 MATERIALS SCIENCE↗