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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Predicting Liquid–Liquid Phase Separation of Submicrometer Proxies for Atmospheric Secondary Aerosol

Liquid–liquid phase separation (LLPS) of atmospheric aerosols can significantly impact climate, air quality, and human health. However, their complex composition, small size, and history-dependent properties result in great uncertainty in the modeling of aerosol phase state and atmospheric processes. Herein, using cryogenic transmission electron microscopy (cryo-TEM), we examined model submicron aerosols composed of organic compounds and ammonium sulfate, and established a parameterization for the separation relative humidity (SRH) that accounts for chemical composition, particle size, and equilibration time. We evaluated different variables that describe chemical composition: O/C ratio, partition coefficient, solubility, molar mass, and polarizability. The O/C ratio fits the SRH of micrometer droplets best, and by using a scaling factor to translate the micrometer SRH parameterization to submicron aerosols, we incorporate the effects of size and equilibration time. The measured scaling factor for the submicron mean SRH (30nm – 1μm, 20 min equilibration times) is 0.80, the factor becomes 1 with equilibration time over 1 hour, and is equal to 0, meaning that SRH is absent, when the aerosol dry diameter is smaller than 30 nm. Furthermore, our parameterization will aid in universal SRH modeling, potentially leading to more accurate predictions of aerosol mass, optical properties, hygroscopicity, and heterogeneous chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Separation of overlapping sources in bioacoustic mixtures

Source separation is an important step to study signals that are not easy or possible to record individually. Common methods such as deep clustering, however, cannot be applied to signals of an unknown number of sources and/or signals that overlap in time and/or frequency—a common problem in bioacoustic recordings. This work presents an approach, using a supervised learning framework, to parse individual sources from a spectrogram of a mixture that contains a variable number of overlapping sources. This method isolates individual sources in the time-frequency domain using only one function but in two separate steps, one for the detection of the number of sources and corresponding bounding boxes, and a second step for the segmentation in which masks of individual sounds are extracted. This approach handles the full separation of overlapping sources in both time and frequency using deep neural networks in an applicable manner to other tasks such as bird audio detection. This paper presents method and reports on its performance to parse individual bat signals from recordings containing hundreds of overlapping bat echolocation signals. This method can be extended to other bioacoustic recordings with a variable number of sources and signals that overlap in time and/or frequency.

Izadi, Mohammad Rasool↗
DOE OSTI2023

Multiclustering needlet ILC for CMB B -mode component separation

ABSTRACT The Cosmic Microwave Background (CMB) primordial B-mode signal is predicted to be much lower than the polarized Galactic emission (foregrounds) in any region of the sky pointing to the need for sophisticated component separation methods. Among them, the blind Needlet Internal Linear Combination (NILC) has great relevance given our current poor knowledge of the B-mode foregrounds. However, the expected level of spatial variability of the foreground spectral properties complicates the NILC subtraction of the Galactic contamination. We therefore propose a novel extension of the NILC approach, the Multiclustering NILC (MC-NILC), which performs NILC variance minimization on separate regions of the sky (clusters) properly chosen to have similar spectral properties of the B-mode Galactic emission within them. Clusters are identified thresholding either the ratio of simulated foregrounds-only B modes (ideal case) or the one of cleaned templates of Galactic emission obtained from realistic simulations. In this work we present an application of MC-NILC to the future LiteBIRD satellite, which targets the observation of both reionization and recombination peaks of the primordial B-mode angular power spectrum with a total error on the tensor-to-scalar ratio δr < 0.001. We show that MC-NILC provides a CMB solution with residual foreground and noise contamination that is significantly lower than the NILC one and the primordial signal targeted by LiteBIRD at all angular scales for the ideal case and at the reionization peak for a realistic ratio. Thus, MC-NILC will represent a powerful method to mitigate B-mode foregrounds for future CMB polarization experiments.

Astronomy & Astrophysics↗
DOE OSTI2021

Choice of 16S ribosomal RNA primers affects the microbiome analysis in chicken ceca

We evaluated the effect of applying different sets of 16S rRNA primers on bacterial composition, diversity, and predicted function in chicken ceca. Cecal contents from Ross 708 birds at 1, 3, and 5 weeks of age were collected for DNA isolation. Eight different primer pairs targeting different variable regions of the 16S rRNA gene were employed. DNA sequences were analyzed using open-source platform QIIME2 and the Greengenes database. PICRUSt2 was used to determine the predicted function of bacterial communities. Changes in bacterial relative abundance due to 16S primers were determined by GLMs. The average PCR amplicon size ranged from 315 bp (V3) to 769 bp (V4–V6). Alpha- and beta-diversity, taxonomic composition, and predicted functions were significantly affected by the primer choice. Beta diversity analysis based on Unweighted UniFrac distance matrix showed separation of microbiota with four different clusters of bacterial communities. Based on the alpha- and beta-diversity and taxonomic composition, variable regions V1–V3(1) and (2), and V3–V4 and V3–V5 were in most consensus. Our data strongly suggest that selection of particular sets of the 16S rRNA primers can impact microbiota analysis and interpretation of results in chicken as was shown previously for humans and other animal species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Optimization of screw design for continuous wet granulation: A case study of metoprolol succinate ER tablets

This study aimed at understanding the effect of screw design on the critical characteristics of granules and tablets of an extended-release (ER) formulation for twin screw granulation process. The screw design parameters assessed included number of kneading elements (KEs) per kneading zone, distance separating kneading zones, staggering angle (SA) of kneading elements and number of sizing elements (SEs). These input variables were varied using a design of experiment (DoE) approach to manufacture granules. Particle size distribution (PSD), flow and bulk properties of the granules, breaking strength and dissolution of tablets manufactured using these granules were characterized. The results of least square fitting showed that KEs, SA, and SEs of the screws significantly (p -values < 0.05) affected the PSD, cohesion, compressibility (CPS), conditioned bulk density (CBD) and permeability of the granules. The KEs and SEs significantly (p -value < 0.05) affected the dissolution, which was attributed to their effects on CPS and CBD of the granules. The distance between kneading zones had no significant effect on granules and tablet characteristics. Finally, these results may be used to further study the interaction of the identified critical screw design parameters with other processing parameters for continuous manufacturing of this ER matrix-based tablet formulation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Coordinated time variability of multi-phase ultra-fast outflows in J132216.25 + 052446.3

ABSTRACT We present a time variability analysis of broad absorption lines (BAL; spread over the velocity range of 5800–29 000 km s−1) seen in the spectrum of J132216.25 + 052446.3 (zem = 2.04806) at ten different epochs spanning over 19 yr. The strongest absorption component (BAL-A; spread over 5800–9900 km s−1) is made up of several narrow components having velocity separations close to C iv doublet splitting. The C iv, N v, and Si iv absorption from BAL-A show correlated optical depth variability without major changes in the velocity structure. A very broad and shallow absorption (BAL-C; spread over the velocity range 15 000–29 000 km s−1) emerged during our monitoring period coinciding with a dimming episode of J1322 + 0524. All the identified absorption lines show correlated variability with the equivalent widths increasing with decreasing flux. This together with the C iv emission line variability is consistent with ionization being the main driver of the correlated variability. The observed UV-continuum variations are weaker than what is required by the photoionization models. This together with a scatter in the C iv equivalent width at a given continuum flux can be understood if variations of the C iv ionizing photons are much larger than that of the UV continuum, the variations in the ionizing photon and UV fluxes are not correlated and/or the covering factor of the flow varies continuously. We suggest BAL-A is produced by a stable clumpy outflow located beyond the broad emission line region and BAL-C is a newly formed wind component located near the accretion disc and both respond to changes in the ionizing continuum.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Spectral variability of a sample of extreme variability quasars and implications for the MgII broad-line region

We present new Gemini/GMOS optical spectroscopy of 16 extreme variability quasars (EVQs) that dimmed bymore than 1.5mag in the g band between the Sloan Digital Sky Survey (SDSS) and the Dark Energy Survey epochs (separated by a few years in the quasar rest frame). These EVQs are selected from quasars in the SDSS Stripe 82 region, covering a redshift range of 0.5 < z < 2.1. Nearly half of these EVQs brightened significantly (by more than 0.5 mag in the g band) in a few years after reaching their previous faintest state, and some EVQs showed rapid (non-blazar) variations of greater than 1-2 mag on time-scales of only months. To increase sample statistics, we use a supplemental sample of 33 EVQs with multi-epoch spectra from SDSS that cover the broad Mg II lambda 2798 line. Leveraging on the large dynamic range in continuum variability between the multi-epoch spectra, we explore the associated variations in the broad MgII line, whose variability properties have not been well studied before. The broad MgII flux varies in the same direction as the continuum flux, albeit with a smaller amplitude, which indicates at least some portion of Mg II is reverberating to continuum changes. However, the full width at half-maximum (FWHM) of Mg II does not vary accordingly as continuum changes for most objects in the sample, in contrast to the case of the broad Balmer lines. Using the width of broad MgII to estimate the black hole mass with single epoch spectra therefore introduces a luminosity-dependent bias.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Carbon Capture through Membranes - Leveraging Multiphysics Modeling, Dimensional Analysis and Machine Learning to Scale up and Optimize Devices and Processes for Decarbonization

We study the separation performance using membrane modules through dimensional analysis (DA). We formulate the main process equations to identify relevant dimensionless numbers inherent in the physics. In particular, we identify that the critical step in the separation process is mass transfer through the selective layer. Remarkably, the dimensionless feed flow (DFfeed) emerges as a crucial factor in describing this process. Not only does DFfeed directly appear in the governing equations, but it also holds a physical significance associated with the time scales for the mass transfer across the feed side and through the selective layer. Regarding the output performance variables, we consider the recovery, stage cut, productivity and purity. In this context, we profit from experimental data and CFD simulations to evaluate the separation performance of the modules when varying the input flowrate, the scale of the module, and the CO2 permeance. These datasets enable us to establish correlations between performance metrics and the dimensionless feed flow (DFfeed). Using simple power functions of DFfeed, we obtain R2 coefficients exceeding 0.99, indicating the accuracy of the correlations built in the present work. In the future, we wish to use DA to understand key transport mechanisms, predict and control module performance, and challenge the universality of these findings by testing various gas separations across different membrane modules beyond our case study.

Pedrozo, Hector A.↗
DOE OSTI2024

Modeling and Scaling up of Membrane Modules Leveraging Dimensional Analysis

In the current analysis, we study the separation performance using membrane modules through dimensional analysis (DA). We formulate the main process equations to identify relevant dimensionless numbers inherent in the physics. In particular, we identify that the critical step in the separation process is mass transfer through the selective layer. Remarkably, the dimensionless feed flow (DFfeed) emerges as a crucial factor in describing this process. Not only does DFfeed directly appear in the governing equations, but it also holds a physical significance associated with the time scales for the mass transfer across the feed side and through the selective layer. Regarding the output performance variables, we consider the recovery, stage cut, productivity and purity. In this context, we profit from experimental data and CFD simulations to evaluate the separation performance of the modules when varying the input flowrate, the scale of the module, and the CO2 permeance. These datasets enable us to establish correlations between performance metrics and the dimensionless feed flow. Using simple power functions of DFfeed, we obtain R2 coefficients exceeding 0.99, indicating the accuracy of the correlations built in the present work. In the future, we wish to use DA to understand key transport mechanisms, predict and control module performance, and challenge the universality of these findings by testing various gas separations across different membrane modules beyond our case study.

Pedrozo, Hector A.↗
DOE OSTI2022

A Novel Hit-Based Method to Distinguish Tracks and Showers in ProtoDUNE Single Phase

Pandora is a pattern recognition software used in liquid argon time projection chamber (LArTPC) experiments such as MicroBooNE, DUNE, SBND, ICARUS, and ProtoDUNE Single Phase (SP). The output of a LArTPC can be considered a high-resolution 2D image and energy depositions, called hits, from particles in a LArTPC create complicated topologies that are broadly classified into tracks and showers. The event reconstruction is particularly challenging when there are multiple overlapping particles and in order to fully harness the imaging capabilities of thoseexperiments, Pandora needs to separate them. A hit-based approach to this problem is presented, which analyses small regions around each hit in events from DUNE Far Detector (FD) and from those regions it calculates local variables that are used subsequently in a machine learning approach. After this stage, it is given to each hit a probability to belong to a track or shower-like particle. Results will show the performance of separation between tracks and showers. This method is planned to be used for ProtoDUNE SP.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

SPRUCE High-Resolution Minirhizotrons in an Experimentally-Warmed Peatland Provide an Unprecedented Glimpse at Fine Roots and their Fungal Partners: Supporting Data

Images were collected using first of their kind, non-destructive, high-resolution automated minirhizotrons (RhizoSystems, LLC) to assess the response of plant fine-root and fungal mycelium dynamics to elevated temperatures after 4-6 years of whole-ecosystem warming and exposure to elevated carbon dioxide concentrations (e[CO2]) in a peat bog where the SPRUCE (Spruce and Peatland Responses Under Changing Environments) experiment is located. We focused on two SPRUCE experimental plots: Plot 10 has elevated temperature (+9°C) and plot 19 is a control (+0°C). Both have elevated carbon dioxide (e[CO2]). Changes in root and fungal abundance with warming were estimated from a timeseries of landscape-level mosaiced images for each plot by measuring the proportional abundance of five belowground classes: fine roots of vascular plants, ectomycorrhizas, fungal hyphae, fungal rhizomorphs, and fungal sporocarps. To examine root and fungal phenology responses to warming, the length per individual root or fungal structure (except fungal hyphae that did not grow linearly but rather increased in areal coverage) were measured per image area of a set of timeseries patch-level mosaiced images for each plot. The experimental work was conducted in a Picea mariana [black spruce] – Sphagnum spp. bog forest in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). This ecosystem, which is located at the southern margin of the boreal forest, is considered especially vulnerable to climate change and anticipated to be near its tipping point. These data were used in analyses published in Defrenne et al (2021). This dataset contains 5 data files in comma-separate values (*.csv) format and a compressed folder (*.zip) containing 383 JPEG (*.jpg) images. Data files contain landscape-level assessment of belowground class abundance, patch-level growth phenology, and environmental variables (originally published in Hanson et al., 2016 and Hanson et al 2020). Images were collected with automated minirhizotrons and analyzed for phenology. Additional metadata are provided: 5 data dictionaries and a file-level metadata file in comma-separate values (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Early calendar life and health prediction of silicon batteries via machine learning with uncertainty quantification

Lithium-ion batteries with silicon anodes promise high energy density but are limited by calendar lifetime. Reducing the long iteration time to obtain experimental results requires predicting calendar lifetime early in a cell's life. In this study, we demonstrate that lightweight machine learning models with feature engineering can provide calendar lifetime estimates from early electrochemical signals. After 1 month of electrochemical aging, the best models achieve 10% error in calendar-life prediction and can separate "bad" from "good" lifetime cells with a mean F1 score of 0.857. As battery systems exhibit inherent variability, four methods for uncertainty quantification are compared, and confidence intervals are demonstrated with an uncertainty of +-3.6 months in lifetime prediction. A feature importance analysis indicates that early patterns in voltage decay are the strongest indicators of calendar lifetime. Finally, this modeling approach has high error when generalizing to new electrode chemistries or testing conditions but with appropriately low confidence.

25 ENERGY STORAGE↗
DOE OSTI2022

MSW Variability Mapping and Conversion to Biofuel

MSW (Municipal Solid Waste) is a form of biomass which consists of categorized components of waste/trash. The general categories are paper, yard trash, construction & debris, appliances, tires, glass, metals, aluminum & steel cans, plastics, organics, inorganics, and HHW (Household Hazardous Waste). This project focuses on the factors within a region or population that contribute to variability in the composition of MSW and in turn MSW’s convertibility to biofuel. A list of contributors was determined (Social Vulnerability Index, Access to Public Transportation, Racial Distribution, GDP, Personal Income) and then JMP was used to perform a Multivariate analysis to determine correlations and a Partial Least-Squares regression to determine Variable Importance Plots for each MSW category. In addition to data analysis, the convertibility of MSW to biofuel was studied via microwave pyrolysis system in order to separate and characterize the various gaseous and bio-oil products.

09 BIOMASS FUELS↗
DOE OSTI2021

Dynamics in Flexible Pillar[ n ]arenes Probed by Solid-State NMR

Pillar[n]arenes are supramolecular assemblies that can perform a range of technologically important molecular separations which are enabled by their molecular flexibility. Here, we probe dynamical behavior by performing a range of variable-temperature solid-state NMR experiments on microcrystalline perethylated pillar[n]arene (n = 5, 6) and the corresponding three pillar[6]arene xylene adducts in the 100–350 K range. This was achieved either by measuring site-selective motional averaged 13 C 1 H heteronuclear dipolar couplings and subsequently accessing order parameters or by determining 1 H and 13 C spin–lattice relaxation times and extracting correlation times based on dipolar and/or chemical shift anisotropy relaxation mechanisms. We demonstrate fast motional regimes at room temperature and highlight a significant difference in dynamics between the core of the pillar[n]arenes, the protruding flexible ethoxy groups, and the adsorbed xylene guest. Additionally, unexpected and sizable 13 C 1 H heteronuclear dipolar couplings for a quaternary carbon were observed for p-xylene adsorbed in pillar[6]arene only, indicating a strong host–guest interaction and establishing the p-xylene location inside the host, confirming structural refinements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Influence of Intraseasonal Variability on the Development of Monsoon Depressions

Previous studies showed that the activity of monsoon low-pressure systems (LPS), which produce a large fraction of the South Asian monsoon's total rainfall, is modulated by intraseasonal variability. Using satellite-derived products and atmospheric reanalyzes, this study examines how the boreal summer intraseasonal oscillation (ISO) separately modulates the occurrence of weaker LPS (lows) and stronger LPS (depressions). It is found that the genesis of lows is insensitive to ISO phase, while depressions exhibit a strong preference for genesis during the phase that is convectively active over the northern Indian Ocean. Essentially, development of LPS into depressions depends upon the timing of genesis of the initial disturbance. Evidence is presented supporting the hypothesis that the development of lows into depressions is fostered by large-scale atmospheric conditions governed by the ISO. Furthermore, results also suggest that while lows have no preference for forming over ocean compared to land, depressions mostly form over ocean.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Younger facial looks are associate with a lower likelihood of several age-related morbidities in the middle-aged to elderly

Abstract Background Looking older for one’s chronological age is associated with a higher mortality rate. Yet it remains unclear how perceived facial age relates to morbidity and the degree to which facial ageing reflects systemic ageing of the human body. Objectives To investigate the association between ΔPA and age-related morbidities of different organ systems, where ΔPA represents the difference between perceived age (PA) and chronological age. Methods We performed a cross-sectional analysis on data from the Rotterdam Study, a population-based cohort study in the Netherlands. High-resolution facial photographs of 2679 men and women aged 51.5–87.8 years of European descent were used to assess PA. PA was estimated and scored in 5-year categories using these photographs by a panel of men and women who were blinded for chronological age and medical history. A linear mixed model was used to generate the mean PAs. The difference between the mean PA and chronological age was calculated (ΔPA), where a higher (positive) ΔPA means that the person looks younger for their age and a lower (negative) ΔPA that the person looks older. ΔPA was tested as a continuous variable for association with ageing-related morbidities including cardiovascular, pulmonary, ophthalmological, neurocognitive, renal, skeletal and auditory morbidities in separate regression analyses, adjusted for age and sex (model 1) and additionally for body mass index, smoking and sun exposure (model 2). Results We observed 5-year higher ΔPA (i.e. looking younger by 5 years for one’s age) to be associated with less osteoporosis [odds ratio (OR) 0.76, 95% confidence interval (CI) 0.62–0.93], less chronic obstructive pulmonary disease (OR 0.85, 95% CI 0.77–0.95), less age-related hearing loss (model 2; B = −0.76, 95% CI −1.35 to −0.17) and fewer cataracts (OR 0.84, 95% CI 0.73–0.97), but with better global cognitive functioning (g-factor; model 2; B = 0.07, 95% CI 0.04–0.10). Conclusions PA is associated with multiple morbidities and better cognitive function, suggesting that systemic ageing and cognitive ageing are, to an extent, externally visible in the human face.

Mekić, Selma↗
DOE OSTI2022

Dust and the intrinsic spectral index of quasar variations: hints of finite stress at the innermost stable circular orbit

ABSTRACT We present a study of 9 242 spectroscopically confirmed quasars with multiepoch ugriz photometry from the SDSS Southern Survey. By fitting a separable linear model to each quasar’s spectral variations, we decompose their five-band spectral energy distributions into variable (disc) and non-variable (host galaxy) components. In modelling the disc spectra, we include attenuation by dust on the line of sight through the host galaxy to its nucleus. We consider five commonly used attenuation laws, and find that the best description is by dust similar to that of the Small Magellanic Cloud, inferring a lack of carbonaceous grains from the relatively weak 2175-Å absorption feature. We go on to construct a composite spectrum for the quasar variations spanning 700–8000 Å. By varying the assumed power-law Lν ∝ να spectral slope, we find a best-fitting value α = 0.71 ± 0.02, excluding at high confidence the canonical Lν ∝ ν1/3 prediction for a steady-state accretion disc with a T ∝ r−3/4 temperature profile. The bluer spectral index of the observed quasar variations instead supports the model of Agol & Krolik, and Mummery & Balbus, in which a steeper temperature profile, T ∝ r−7/8, develops as a result of finite magnetically induced stress at the innermost stable circular orbit extracting energy and angular momentum from the black hole spin.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Refining perovskite structures to pair distribution function data using collective Glazer modes as a basis

Structural modelling of octahedral tilts in perovskites is typically carried out using the symmetry constraints of the resulting space group. In most cases, this introduces more degrees of freedom than those strictly necessary to describe only the octahedral tilts. It can therefore be a challenge to disentangle the octahedral tilts from other structural distortions such as cation displacements and octahedral distortions. This paper reports the development of constraints for modelling pure octahedral tilts and implementation of the constraints in diffpy-CMI, a powerful package to analyse pair distribution function (PDF) data. The model in the program allows features in the PDF that come from rigid tilts to be separated from non-rigid relaxations, providing an intuitive picture of the tilting. The model has many fewer refinable variables than the unconstrained space group fits and provides robust and stable refinements of the tilt components. It further demonstrates the use of the model on the canonical tilted perovskite CaTiO 3 which has the known Glazer tilt system α + β – β – . The Glazer model fits comparably to the corresponding space-group model Pnma below r = 14 Å and becomes progressively worse than the space-group model at higher r due to non-rigid distortions in the real material.

36 MATERIALS SCIENCE↗