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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Spatially and momentum resolved energy electron loss spectra from an ultra-thin PrNiO{sub 3} layer

We present an experimental approach which allows for the acquisition of spectra from ultra-thin films at high spatial, momentum, and energy resolutions. Spatially and momentum (q) resolved electron energy loss spectra have been obtained from a 12 nm ultra-thin PrNiO{sub 3} layer using a nano-beam electron diffraction based approach which enabled the acquisition of momentum resolved spectra from individual, differently oriented nano-domains and at different positions of the PrNiO{sub 3} thin layer. The spatial and wavelength dependence of the spectral excitations are obtained and characterized after the analysis of the experimental spectra using calculated dielectric and energy loss functions. The presented approach makes a contribution towards obtaining momentum-resolved spectra from nanostructures, thin film, heterostructures, surfaces, and interfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Liquid optical phantoms mimicking spectral characteristics of laboratory mouse biotissues

Optical phantoms mimicking optical properties of real biotissues in the visible and IR spectral regions are developed based on measurements of the spectral characteristics of ex vivo samples of laboratory mouse biotissues. The phantoms are composed of aqueous solutions of Lipofundin, Indian ink and red ink with different spectral characteristics. The deviations of the measured absorption and scattering coefficients of phantoms in the wavelength range 480 – 580 nm from the corresponding values for real biotissues do not exceed 25% and 2%, respectively. For phantoms in the wavelength region 580 – 880 nm, the deviations of the absorption coefficient do not exceed 40% and the deviations of the scattering coefficient do not exceed 25%. These values, in general, fall within the range of variations for different individual mice of one strain. (laser biophotonics)

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

The chemical compositions of accreted and in situ galactic globular clusters according to SDSS/APOGEE

ABSTRACT Studies of the kinematics and chemical compositions of Galactic globular clusters (GCs) enable the reconstruction of the history of star formation, chemical evolution, and mass assembly of the Galaxy. Using the latest data release (DR16) of the SDSS/APOGEE survey, we identify 3090 stars associated with 46 GCs. Using a previously defined kinematic association, we break the sample down into eight separate groups and examine how the kinematics-based classification maps into chemical composition space, considering only α (mostly Si and Mg) elements and Fe. Our results show that (i) the loci of both in situ and accreted subgroups in chemical space match those of their field counterparts; (ii) GCs from different individual accreted subgroups occupy the same locus in chemical space. This could either mean that they share a similar origin or that they are associated with distinct satellites which underwent similar chemical enrichment histories; (iii) the chemical compositions of the GCs associated with the low orbital energy subgroup defined by Massari and collaborators is broadly consistent with an in situ origin. However, at the low-metallicity end, the distinction between accreted and in situ populations is blurred; (iv) regarding the status of GCs whose origin is ambiguous, we conclude the following: the position in Si–Fe plane suggests an in situ origin for Liller 1 and a likely accreted origin for NGC 5904 and NGC 6388. The case of NGC 288 is unclear, as its orbital properties suggest an accretion origin, its chemical composition suggests it may have formed in situ.

Horta, Danny↗
DOE OSTI2017

Phylodynamic Inference across Epidemic Scales

Within-host genetic diversity and large transmission bottlenecks confound phylodynamic inference of epidemiological dynamics. Conventional phylodynamic approaches assume that nodes in a time-scaled pathogen phylogeny correspond closely to the time of transmission between hosts that are ancestral to the sample. However, when hosts harbor diverse pathogen populations, node times can substantially pre-date infection times. Imperfect bottlenecks can cause lineages sampled in different individuals to coalesce in unexpected patterns. To address realistic violations of standard phylodynamic assumptions we developed a new inference approach based on a multi-scale coalescent model, accounting for nonlinear epidemiological dynamics, heterogeneous sampling through time, non-negligible genetic diversity of pathogens within hosts, and imperfect transmission bottlenecks. We apply this method to HIV-1 and Ebola virus (EBOV) outbreak sequence data, illustrating how and when conventional phylodynamic inference may give misleading results. Within-host diversity of HIV-1 causes substantial upwards bias in the number of infected hosts using conventional coalescent models, but estimates using the multi-scale model have greater consistency with reported number of diagnoses through time. In contrast, we find that within-host diversity of EBOV has little influence on estimated numbers of infected hosts or reproduction numbers, and estimates are highly consistent with the reported number of diagnoses through time. The multi-scale coalescent also enables estimation of within-host effective population size using single sequences from a random sample of patients. We find within-host population genetic diversity of HIV-1 p17 to be 2Nμ=0.012 (95% CI 0.0066–0.023), which is lower than estimates based on HIV envelope serial sequencing of individual patients.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Quantum error mitigation by layerwise Richardson extrapolation

A widely used method for mitigating errors in noisy quantum computers is Richardson extrapolation, a technique in which the overall effect of noise on the estimation of quantum expectation values is captured by a single parameter that, after being scaled to larger values, is eventually extrapolated to the zero-noise limit. We generalize this approach by introducing layerwise Richardson extrapolation (LRE), an error mitigation protocol in which the noise of different individual layers (or larger chunks of the circuit) is amplified and the associated expectation values are linearly combined to estimate the zero-noise limit. The coefficients of the linear combination are analytically obtained from the theory of multivariate Lagrange interpolation. LRE leverages the flexible configurational space of layerwise unitary folding, allowing for a more nuanced mitigation of errors by treating the noise level of each layer of the quantum circuit as an independent variable. Furthermore, we provide numerical simulations demonstrating scenarios where LRE achieves superior performance compared to traditional (single-variable) Richardson extrapolation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Joint Estimation of Behind-the-Meter Solar Generation in a Community

Distribution grid planning, control, and optimization require accurate estimation of solar photovoltaic (PV) generation and electric load in the system. Most of the small residential solar PV systems are installed behind-the-meter making only the net load readings available to the utilities. This paper presents an unsupervised framework for joint disaggregation of the net load readings of a group of customers into the solar PV generation and electric load. Our algorithm synergistically combines a physical PV system performance model for individual solar PV generation estimation with a statistical model for joint load estimation. The electric loads for a group of customers are estimated jointly by a mixed hidden Markov model (MHMM) which enables modeling the general load consumption behavior present in all customers while acknowledging the individual differences. At the same time, the model can capture the change in load patterns over a time period by the hidden Markov states. The proposed algorithm is also capable of estimating the key technical parameters of the solar PV systems. Our proposed method is evaluated using the net load, electric load, and solar PV generation data gathered from residential customers located in Austin, Texas. Testing results show that our proposed method reduces the mean squared error of state-of-the-art net-load disaggregation algorithms by 67%.

behind-the-meter solar generation↗
DOE OSTI2023

Highly multicolored light-emitting arrays for compressive spectroscopy

Miniaturized, multicolored light-emitting device arrays are promising for applications in sensing, imaging, computing, and more, but the range of emission colors achievable by a conventional light-emitting diode is limited by material or device constraints. In this work, we demonstrate a highly multicolored light-emitting array with 49 different, individually addressable colors on a single chip. The array consists of pulsed-driven metal-oxide-semiconductor capacitors, which generate electroluminescence from microdispensed materials spanning a diverse range of colors and spectral shapes, enabling facile generation of arbitrary light spectra across a broad wavelength range (400 to 1400 nm). When combined with compressive reconstruction algorithms, these arrays can be used to perform spectroscopic measurements in a compact manner without diffractive optics. As an example, we demonstrate microscale spectral imaging of samples using a multiplexed electroluminescent array in conjunction with a monochrome camera.

42 ENGINEERING↗
DOE OSTI2015

Web-Based Reanalysis Intercomparison Tools (WRIT) for Analysis and Comparison of Reanalyses and Other Datasets

While atmospheric reanalysis datasets are widely used in climate science, many technical issues hinder comparing them to each other and to observations. The reanalysis fields are stored in diverse file architectures, data formats, and resolutions. Their metadata, such as variable name and units, can also differ. Individual users have to download the fields, convert them to a common format, store them locally, change variable names, regrid if needed, and convert units. Even if a dataset can be read via the Open-Source Project for a Network Data Access Protocol (commonly known as OPeNDAP) or a similar protocol, most of this work is still needed. All of these tasks take time, effort, and money. Our group at the Cooperative Institute for Research in the Environmental Sciences at the University of Colorado and affiliated colleagues at the NOAA's Earth System Research Laboratory Physical Sciences Division have expertise both in making reanalysis datasets available and in creating web-based climate analysis tools that have been widely used throughout the meteorological community. To overcome some of the obstacles in reanalysis intercomparison, we have created a set of web-based Reanalysis Intercomparison Tools (WRIT) at www.esrl.noaa.gov/psd/data/writ/. WRIT allows users to easily plot and compare reanalysis datasets, and to test hypotheses. For standard pressure-level and surface variables there are tools to plot trajectories, monthly mean maps and vertical cross sections, and monthly mean time series. Some observational datasets are also included. Users can refine date, statistics, and plotting options. WRIT also facilitates the mission of the Reanalyses.org website as a convenient toolkit for studying the reanalysis datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Aging Affects Dopaminergic Neural Mechanisms of Cognitive Flexibility

Aging is accompanied by profound changes in the brain’s dopamine system that affect cognitive function. Evidence of powerful individual differences in cognitive aging has sharpened focus on identifying biological factors underlying relative preservation versus vulnerability to decline. Dopamine represents a key target in these efforts. Alterations of dopamine receptors and dopamine synthesis are seen in aging, with receptors generally showing reduction and synthesis demonstrating increases. Using the PET tracer 6-[ 18 F]fluoro-L- m -tyrosine, we found strong support for upregulated striatal dopamine synthesis capacity in healthy older adult humans free of amyloid pathology, relative to young people. We next used fMRI to define the functional impact of elevated synthesis capacity on cognitive flexibility, a core component of executive function. We found clear evidence in young adults that low levels of synthesis capacity were suboptimal, associated with diminished cognitive flexibility and altered frontoparietal activation relative to young adults with highest synthesis values. Critically, these relationships between dopamine, performance, and activation were transformed in older adults with higher synthesis capacity. Variability in synthesis capacity was related to intrinsic frontoparietal functional connectivity across groups, suggesting that striatal dopamine synthesis influences the tuning of networks underlying cognitive flexibility. Altogether, these findings define striatal dopamine’s association with cognitive flexibility and its neural underpinnings in young adults, and reveal the alteration in dopamine-related neural processes in aging.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Plant Characteristics, Porewater, Gas Flux, and Soil Biogeochemistry at Council Road Site Mile Marker 71, Seward Peninsula, Alaska, 2023

Data collected at Council, AK (64°51’35.0”N 163°41’59.1”W) during a summer campaign in 2023. Water data consists of soil porewater collected by centrifuging soil cores and also by field collection with porewater samplers (rhizons). Gas data consists of CO2, CH4 and N2O surface soil fluxes measured with a portable FTIR analyzer. Plant and root data consists of biomass, root length, diameter and mass. Soil data consists of total C and N. Air, water and soil samples span two main locations: a thermokarst wetland and an upland tussock. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).This dataset was generated to broadly address the following research question: how will climate change (i.e., thawing permafrost, landscape change) alter the ecosystem flux (sink versus source) of important greenhouse gases such as CO2, CH4 and N2O?Description of the contents of this data package: This dataset contains 5 different individual .csv files containing plant, soil, water and gas data. No software is needed to utilize them. PFTCover: Plant functional type ground cover in 1x1 meter plots. SoilCores: Solidphase and porewater phase soil biogeochemical variablesPlantData: Above and belowground plant traits. GasFlux: Surface plant-soil gas measurementsFieldPorewater: Field collected porewater biogeochemical variables

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Feral Cattle in the White Rock Canyon Reserve at Los Alamos National Laboratory

At the request of the Los Alamos Field Office (the Field Office), Los Alamos National Security (LANS) biologists placed remote-triggered wildlife cameras in and around the mouth of Ancho Canyon in the White Rock Canyon Reserve (the Reserve) to monitor use by feral cattle. The cameras were placed in October 2012 and retrieved in January 2013. Two cameras were placed upstream in Ancho Canyon away from the Rio Grande along the perennial flows from Ancho Springs, two cameras were placed at the north side of the mouth to Ancho Canyon along the Rio Grande, and two cameras were placed at the south side of the mouth to Ancho Canyon along the Rio Grande. The cameras recorded three different individual feral cows using this area as well as a variety of local native wildlife. This report details our results and issues associated with feral cattle in the Reserve. Feral cattle pose significant risks to human safety, impact cultural and biological resources, and affect the environmental integrity of the Reserve. Regional stakeholders have communicated to the Field Office that they support feral cattle removal.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Techno-Economic Case Study: Low-Temperature Conversion Performance Based on Isolated Anatomical Fractions of Corn Stover

This report summarizes analysis conducted to support a case study under the Feedstock-Conversion Interface Consortium (FCIC) focused on techno-economic analysis (TEA) modeling to quantify the yield and cost ramifications for processing isolated anatomical fractions of corn stover through a low-temperature conversion (biochemical pathway) biorefinery. It is hypothesized that different individual anatomical fractions of corn stover vary in composition and recalcitrance, such that processing each fraction on its own e.g. through dedicated campaigns may enable economic benefits relative to processing the whole stover material. To investigate this concept, we worked with FCIC researchers to obtain data on compositional analysis, as well as processing conditions and yields, for conversion of whole corn stover plus three individual anatomical fractions (cobs, husks, and stalks) across key steps of the biorefinery conversion process within FCIC research scope, namely pretreatment and enzymatic hydrolysis. After running the data through the TEA models, fractionated cobs and husks achieved higher fuel yields and lower minimum fuel selling prices than whole corn stover, but stalks fared worse than whole stover on both metrics. The most direct takeaway from this assessment is that a biorefinery would stand to benefit economically from maximizing the use of cob and husk fractions while avoiding or minimizing the use of stalks, though recognizing practical constraints with this approach in maintaining an equivalent processing capacity (fixed at 2,000 dry metric tonne per day in all cases).

09 BIOMASS FUELS↗
DOE OSTI2025

Verifying LLM generative agents reflect human behavior in contested information environments to effectively simulate disinformation campaigns (Proteus)

Disinformation poses a significant and evolving threat to today’s online environment. Individuals encounter challenges in detecting disinformation, subsequently influencing their behavior and decision-making processes. Our research examines the potential use of large language model (LLM) generative agents (LGAs) to replicate human behavior to better understand how disinformation is spread in online environments. Using human subjects research, we first investigate how personality traits, individual differences, and demographic factors relate to decision-making in simulated online disinformation environments. Then, we examine whether LGAs can effectively replicate human responses in the same simulated online environments when assigned personality traits, demographic characteristics and behavioral attributes. Our findings indicate that LGAs can align with human decisions in these scenarios; however, alignment is contingent upon scenario context, persona settings and LLM selection. Results provide valuable insights for methodology refinement in future research and in utilizing LGAs to model complex national security challenges such as disinformation campaigns.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Environmental enrichment alters protein expression as well as the proteomic response to cocaine in rat nucleus accumbens

Prior research demonstrated that environmental enrichment creates individual differences in behavior leading to a protective addiction phenotype in rats. Understanding the mechanisms underlying this phenotype will guide selection of targets for much-needed novel pharmacotherapeutics. The current study investigates differences in proteome expression in the nucleus accumbens of enriched and isolated rats and the proteomic response to cocaine self-administration using a liquid chromatography mass spectrometry (LCMS) technique to quantify 1917 proteins. Results of complementary Ingenuity Pathways Analyses (IPA) and gene set enrichment analyses (GSEA), both performed using protein quantitative data, demonstrate that cocaine increases vesicular transporters for dopamine and glutamate as well as increasing proteins in the RhoA pathway. Further, cocaine regulates proteins related to ERK, CREB and AKT signaling. Environmental enrichment altered expression of a large number of proteins implicated in a diverse number of neuronal functions (e.g., energy production, mRNA splicing, and ubiquitination), molecular cascades (e.g., protein kinases), psychiatric disorders (e.g., mood disorders), and neurodegenerative diseases (e.g., Huntington’s and Alzheimer’s diseases). Upregulation of energy metabolism components in EC rats was verified using RNA sequencing. Most of the biological functions and pathways listed above were also identified in the Cocaine X Enrichment interaction analysis, providing clear evidence that enriched and isolated rats respond quite differently to cocaine exposure. The overall impression of the current results is that enriched saline-administering rats have a unique proteomic complement compared to enriched cocaine-administering rats as well as saline and cocaine-taking isolated rats. These results identify possible mechanisms of the protective phenotype and provide fertile soil for developing novel pharmacotherapeutics. Proteomics data are available via ProteomeXchange with identifier PXD000990.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Tractometry of the Human Connectome Project: resources and insights

The Human Connectome Project (HCP) has become a keystone dataset in human neuroscience, with a plethora of important applications in advancing brain imaging methods and an understanding of the human brain. We focused on tractometry of HCP diffusion-weighted MRI (dMRI) data. We used an open-source software library (pyAFQ; https://yeatmanlab.github.io/pyAFQ) to perform probabilistic tractography and delineate the major white matter pathways in the HCP subjects that have a complete dMRI acquisition (n = 1,041). We used diffusion kurtosis imaging (DKI) to model white matter microstructure in each voxel of the white matter, and extracted tract profiles of DKI-derived tissue properties along the length of the tracts. We explored the empirical properties of the data: first, we assessed the heritability of DKI tissue properties using the known genetic linkage of the large number of twin pairs sampled in HCP. Second, we tested the ability of tractometry to serve as the basis for predictive models of individual characteristics (e.g., age, crystallized/fluid intelligence, reading ability, etc.), compared to local connectome features. To facilitate the exploration of the dataset we created a new web-based visualization tool and use this tool to visualize the data in the HCP tractometry dataset. Finally, we used the HCP dataset as a test-bed for a new technological innovation: the TRX file-format for representation of dMRI-based streamlines. We released the processing outputs and tract profiles as a publicly available data resource through the AWS Open Data program's Open Neurodata repository. We found heritability as high as 0.9 for DKI-based metrics in some brain pathways. We also found that tractometry extracts as much useful information about individual differences as the local connectome method. We released a new web-based visualization tool for tractometry—“Tractoscope” (https://nrdg.github.io/tractoscope). We found that the TRX files require considerably less disk space-a crucial attribute for large datasets like HCP. In addition, TRX incorporates a specification for grouping streamlines, further simplifying tractometry analysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Mortality correlates with tree functional traits across a wood density gradient in the Central Amazon

Introduction: Understanding the mechanisms of tree mortality in tropical ecosystems remains challenging, in part due to the high diversity of tree species and the inherently stochastic nature of mortality. Plant functional traits offer a mechanistic link between plant physiology and performance, yet their ability to predict growth and mortality remains poorly understood. Given recent increases in tree mortality rates in the Amazon forest following extreme drought and wind events, we tested if lower wood density and acquisitive plant functional traits were associated with increased growth and mortality for common co-occurring trees in the Central Amazon. Methods: Seventeen trees of different species with similar sizes but a range in wood density (WD) and wood traits were felled, then assessed for 27 different individual functional parameters, including whole tree architecture, stem xylem anatomical and hydraulic traits and leaf traits. Traits of the individual trees were related to stand-level growth and mortality rates collected periodically over 30 years from nearby permanent inventory plots. Results: Higher wood density was associated with smaller leaf size, lower foliar base cations, lower stem water content and sapwood fraction, in agreement with the fast-slow plant economics spectrum. Lower wood density was associated with more acquisitive characteristics with greater hydraulic capacity and foliar nutrient concentrations, correlating with greater growth and mortality rates. Discussion: Our results show that lower wood density is part of a coordinated suite of traits linked to high resource acquisition, fast growth, and increased mortality risk, providing a functional framework for predicting species performance and forest vulnerability under future climate stress.

demographics↗
DOE OSTI2022

Infrared-Fused Vision-Based Thermoregulation Performance Estimation for Personal Thermal Comfort-Driven HVAC System Controls

Thermal comfort is one of the primary factors influencing occupant health, well-being, and productivity in buildings. Existing thermal comfort systems require occupants to frequently communicate their comfort vote via a survey which is impractical as a long-term solution. Here, we present a novel thermal infrared-fused computer vision sensing method to capture thermoregulation performance in a non-intrusive and non-invasive manner. In this method, we align thermal and visible images, detect facial segments (i.e., nose, eyes, face boundary), and accordingly read the temperatures from the appropriate coordinates in the thermal image. We focus on the human face since it is often clearly visible to cameras and is not merged into a hot background (unlike hands). We use a regularized Gaussian Mixture model to track the thermoregulation changes over time and apply a heuristic algorithm to extract hot and cold indices. We present a personalized and a generalized comfort modeling method, selected based on the availability of the occupant historical indices measurements in a neutral environment, and use the time-series of the hot and cold indices to define corrections to HVAC system operations in the form of setpoint constraints. To evaluate the efficacy of our proposed approach in responding to thermal stimuli, we designed a series of controlled experiments to simulate exposure to cold and hot environments. While applying personalized modeling showed an acceptable average accuracy of 91.3%, the generalized model’s average accuracy was only 65.2%. This shows the importance of having access to physiological records in modeling and assessing comfort. We also found that individual differences should be considered in selecting the cooling and heating rates when some knowledge of the occupant’s overall thermal preference is available.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗