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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Evaluation of the cytotoxic and cellular proteome impacts of food-grade TiO2 (E171) using simulated gastrointestinal digestions and a tri-culture small intestinal epithelial model

Engineered nanomaterials (ENMs) are widely used in the food industry; however, regulations for ENMs in food are still in the early stages of development due to insufficient health data. This study investigated the cytotoxicity and changes to the proteomic profile in an in vitro small intestinal epithelium model after exposure to digested food models containing the ubiquitous engineered particulate food additive, TiO2 (E171). TiO2 at 0.75% or 1.5% (w/w) concentrations in either a fasting food model (FFM) or a standardized food model (SFM) based on American diet were digested using an in vitro oral-gastric-small intestinal simulator, and the resulting digestas were applied to a small intestinal epithelium tri-culture cellular model. Effects on cell layer integrity, cytotoxicity, and oxidative stress were assessed. In order to explore impact on cellular processes beyond basic cytotoxicity, mass spectrometrybased quantitative proteomic analyses of control and exposed tri-culture cells was performed. TiO2 in FFM, but not in SFM, produced significant, dose-dependent cytotoxicity, and at the higher dose caused significant oxidative stress, indicative of a food matrix effect. No significant perturbations of the cellular proteome were observed with TiO2 in either FFM or SFM food models. However, proteins involved in the tricarboxylic acid (TCA) cycle, gluconeogenesis, and translation were up-regulated by digestas from SFM compared to those from FFM, also indicative of food matrix effects in the case of food models alone. Interestingly, the differences in profiles between the two food models was more pronounced in the presence of TiO2 indicative of food matrix effects. Together, these results indicate that TiO2 in a fasting diet may be slightly cytotoxic, and that ingested TiO2 does not significantly alter the epithelial proteome, whereas the food matrix alone can have a dramatic effect on the proteome.

Cao, Xiaoqiong↗
DOE OSTI2020

Charged particle track reconstruction with SπRIT Time Projection Chamber

In this work, we present a software framework, SπRITROOT, which is capable of track reconstruction and analysis of heavy-ion collision events recorded with the SRIT time projection chamber. The track-fitting toolkit GENFIT and the vertex reconstruction toolkit RAVE are applied to a box-type detector system. A pattern recognition algorithm which performs helix track finding and handles overlapping pulses is described. The performance of the software is investigated using experimental data obtained at the Radioactive Isotope Beam Facility (RIBF) at RIKEN. This work focuses on data from 132 Sn + 124 Sn collision events with beam energy of 270 AMeV. Particle identification is established using < dE/dx >and magnetic rigidity, with pions, hydrogen isotopes, and helium isotopes.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Street-level temperature estimation using graph neural networks: Performance, feature embedding and interpretability

Estimating street-level air temperature is a challenging task due to the highly heterogeneous urban surfaces, canyon-like street morphology, and the diverse physical processes in the built environment. Though pioneering studies have embarked on investigations via data-driven approaches, many questions remain to be answered. Here, in this study, we leveraged an innovative framework and redefined the street-level temperature estimation problem using Graph Neural Networks (GNN) with spatial embedding techniques. The results showed that GNN models are more capable and consistent of estimating street-level temperature among tested locations, benefiting from its unique strength in handling extensive data over unstructured graph topology. In addition, we conducted in-depth analysis of feature importance to enhance the model interpretability. Among the urban features analyzed in this study, the time-variant canopy density and meter-level land use data emerge as crucial factors. Our findings highlight GNN 's high potential in capturing the complex dynamics between urban elements and their impacts on microclimate, thus offering valuable insights for comprehensive urban data collection and urban climate modeling in general. Collectively, this study also contributes to urban planning and policy by providing avenues to enhance city resilience against climate change, thereby advancing the agenda for environmental stewardship and urban sustainability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Solvation Environment and Interface Dynamics of Li 2 B 12 H 12 and Li 2 B 12 F 12 Electrolytes Uncovered by Theory and Operando Optical and FTIR Spectroelectrochemistry

In this work, we evaluated two closo-borate salts (Li 2 B 12 H 12 and Li 2 B 12 F 12 ) in propylene carbonate from theoretical and experimental perspectives to understand how the coordination environment influences their spectroscopic and electrochemical properties. The coordination environments of the closo-borate salts were modeled via density functional theory (DFT) and molecular dynamics (MD). Vibrational spectra calculated from the predicted coordination environments are in agreement with experimentally measured steady-state FTIR data. This theoretical investigation also suggested that Li 2 B 12 F 12 would possess a higher ionic conductivity than Li 2 B 12 H 12 , which was corroborated experimentally. Additionally, an electrochemical cell was designed and fabricated that enabled operando optical and FTIR spectroelectrochemical (OP-IR-SEC) measurements. This allowed for the simultaneous measurement of the relative changes of species at a lithium electrode-liquid electrolyte interface and the visualization of lithium plating at the electrode surface. This technique could provide new chemical insights and potentially link optical changes at the electrode–electrolyte interface to specific chemical species in similar electrochemical systems. The Li 2 B 12 F 12 electrolyte was found to have a higher thermal stability, which may find utility in applications for batteries that are subject to high-temperature conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A Pd III Sulfate Dimer Initiates Rapid Methane Monofunctionalization by H Atom Abstraction

An electrogenerated Pd III 2 species in fuming sulfuric acid is competent for rapid and concurrent methane monohydroxylation to methyl bisulfate (CH 3 OSO 3 H) and methane sulfonation to methanesulfonic acid (CH 3 SO 3 H). In situ NMR at 50 °C is used to track methane transformation exclusively to CH 3 OSO 3 H and CH 3 SO 3 H at high conversions. Integrating a set of kinetic and computational studies, the mechanism of methane monofunctionalization by Pd III 2 is examined. Here, experimental rate laws and common kinetic isotope effects for CH 3 OSO 3 H and CH 3 SO 3 H formation suggest that both transformations proceed via a common rate-limiting C-H activation step. Introduction of O 2 or Pd II,III 2 suppresses CH 3 SO 3 H generation, indicating a radical chain sequence. Although the metal-metal bonded Pd III 2 complex is a net two-electron oxidant, our aggregate kinetic data point to a mechanistic model that features rate-limiting H atom abstraction by the Pd III 2 complex to generate a methyl radical intermediate. The CH 3 • intermediate then recombines with Pd II,III 2 to furnish a CH 3 Pd III 2 intermediate that reductively eliminates CH 3 OSO 3 H. Alternatively, the CH 3 intermediate can enter a chain reaction with SO 3 to generate CH 3 SO 3 H. DFT computations support the radical-based C-H activation by Pd III 2 and delineate H atom abstraction pathways with computed reaction barriers and kinetic isotope effects (KIEs) that are consistent with experimental data. These mechanistic investigations challenge the paradigm of electrophilic C-H activation and highlight H atom abstraction as a potent pathway for selective methane C-H oxidative functionalization at high reaction rates.

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

Relative Roles of Low‐Level Wind Speed and Moisture in the Diurnal Cycle of Rainfall Over a Tropical Island Under Monsoonal Flows

Abstract Using satellite observations and reanalysis data, this study investigates the relative roles of low‐level wind speed and moisture content in the rainfall diurnal cycle over a tropical island influenced by monsoonal winds. Results show that the spatiotemporal characteristics of rainfall over the island are evidently influenced by the two factors. Specifically, the spatial distribution of rainfall is primarily determined by the low‐level wind speeds, while the rainfall diurnal cycle is influenced by both factors. Weaker low‐level wind speed leads to stronger and wider inland convergence and afternoon precipitation, which are mainly produced by the inland penetrating sea breeze fronts. Nighttime rainfall over the island is closely related to the inertial oscillation. Stronger nocturnal rainfall can be found with higher low‐level moisture content and stronger monsoonal winds. The multiscale interactions between the large‐scale circulation, land–sea breezes, and inertial oscillation play essential roles in modulating the rainfall over this tropical island.

Zhu, Lei↗
DOE OSTI2020

Climate Sensitivity of Peatland Methane Emissions Mediated by Seasonal Hydrologic Dynamics

Peatlands are among the largest natural sources of atmospheric methane (CH 4 ) worldwide. Peatland emissions are projected to increase under climate change, as rising temperatures and shifting precipitation accelerate microbial metabolic pathways favorable for CH 4 production. However, how these changing environmental factors will impact peatland emissions over the long term remains unknown. Here, we investigate a novel data set spanning an exceptionally long 11 years to analyze the influence of soil temperature and water table elevation on peatland CH 4 emissions. We show that higher water tables dampen the springtime increases in CH 4 emissions as well as their subsequent decreases during late summer to fall. These results imply that any hydroclimatological changes in northern peatlands that shift seasonal water availability from winter to summer will increase annual CH 4 emissions, even if temperature remains unchanged. Furthermore, advancing hydrological understanding in peatland watersheds will be crucial for improving predictions of CH 4 emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Deciphering the Role of Total Water Storage Anomalies in Mediating Regional Flooding

Regional floods result from various flood generation mechanisms. Traditional analyses mainly link flooding to extreme rainfall, with limited input from soil moisture. Total water storage (TWS) is a holistic measure of basin wetness, including additional storage components from surface water, snow, and groundwater. Utilizing a new 5-day Gravity Recovery and Climate Experiment and its Follow On (GRACE(-FO)) data set, we investigated the linkage between short-term TWS anomaly (TWSA) and regional flooding. The 5-day TWSA solutions revealed flood signals missed by monthly TWSA solutions. Global basins exhibit distinct storage-discharge co-evolution patterns, offering new insights into flood mechanisms and propensity. Our bivariate event analyses show the annual maximum river discharges co-occur more often with the TWSA maxima than with precipitation in many basins. Further analyses revealed TWSA's time-lagged effect on river discharge, particularly in basins susceptible to floods triggered by saturation-excess runoff. The 5-day TWSA provides a new source of information for enhancing global flood preparedness.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Structural and thermal properties of ultralow thermal conductivity Ba 3 Cu 2 Sn 3 Se 10

The thermal properties of Ba 3 Cu 2 Sn 3 Se 10 were investigated by measurement of the thermal conductivity and heat capacity. The chemical bonding in this diamagnetic material was investigated using structural data from Rietveld refinement and calculated electron localization. This quaternary chalcogenide is monoclinic (P2 1 /c), has a large unit cell with 72 atoms in the primitive cell, and a high local coordination environment. Additionally, the Debye temperature (162 K) and average speed of sound (1666 m s -1 ) are relatively low with a very small electronic contribution to the heat capacity. Ultralow thermal conductivity (0.46 W m -1 K -1 at room temperature) is attributed to the relatively weak chemical bonding and intrinsic anharmonicity, in addition to a large unit cell. This work is part of the continuing effort to explore quaternary chalcogenides with intrinsically low thermal conductivity and identify the features that result in a low thermal conductivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Impact of environmental oxygen on nanoparticle formation and agglomeration in aluminum laser ablation plumes

Here, the role of ambient oxygen gas (O 2 ) on molecular and nanoparticle formation and agglomeration was studied in laser ablation plumes. As a lab-scale surrogate to a high explosion detonation event, nanosecond laser ablation of an aluminum alloy (AA6061) target was performed in atmospheric pressure conditions. Optical emission spectroscopy and two mass spectrometry techniques were used to monitor the early to late stages of plasma generation to track the evolution of atoms, molecules, clusters, nanoparticles, and agglomerates. The experiments were performed under atmospheric pressure air, atmospheric pressure nitrogen, and 20% and 5% O 2 (balance N 2 ), the latter specifically with in situ mass spectrometry. Electron microscopy was performed ex situ to identify crystal structure and elemental distributions in individual nanoparticles. We find that the presence of ≈20% O 2 leads to strong AlO emission, whereas in a flowing N 2 environment (with trace O 2 ), AlN and strong, unreacted Al emissions are present. In situ mass spectrometry reveals that as O 2 availability increases, Al oxide cluster size increases. Nanoparticle agglomerates formed in air are found to be larger than those formed under N 2 gas. High-resolution transmission electron microscopy demonstrates that Al 2 O 3 and AlN nanoparticle agglomerates are formed in both environments; indicating that the presence of trace O 2 can lead to Al 2 O 3 nanoparticle formation. The present results highlight that the availability of O 2 in the ambient gas significantly impacts spectral signatures, cluster size, and nanoparticle agglomeration behavior. These results are relevant to understanding debris formation in an explosion event, and interpreting data from forensic investigations.

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

Benchmarking machine learning strategies for phase-field problems

Abstract We present a comprehensive benchmarking framework for evaluating machine-learning approaches applied to phase-field problems. This framework focuses on four key analysis areas crucial for assessing the performance of such approaches in a systematic and structured way. Firstly, interpolation tasks are examined to identify trends in prediction accuracy and accumulation of error over simulation time. Secondly, extrapolation tasks are also evaluated according to the same metrics. Thirdly, the relationship between model performance and data requirements is investigated to understand the impact on predictions and robustness of these approaches. Finally, systematic errors are analyzed to identify specific events or inadvertent rare events triggering high errors. Quantitative metrics evaluating the local and global description of the microstructure evolution, along with other scalar metrics representative of phase-field problems, are used across these four analysis areas. This benchmarking framework provides a path to evaluate the effectiveness and limitations of machine-learning strategies applied to phase-field problems, ultimately facilitating their practical application.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: growth rate of structure measurement from cosmic voids

ABSTRACT We present a void clustering analysis in configuration-space using the completed Sloan Digital Sky Survey IV (SDSS-IV) extended Baryon Oscillation Spectroscopic Survey (eBOSS) DR16 samples. These samples consist of Luminous Red Galaxies (LRGs) combined with the high-redshift tail of the SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS) DR12 CMASS galaxies (called as LRG+CMASS sample), Emission Line Galaxies (ELGs), and quasars (QSOs). We build void catalogues from the three eBOSS DR16 samples using a ZOBOV-based algorithm, providing 2814 voids, 1801 voids, and 4347 voids in the LRG+CMASS, ELG, and QSO samples, respectively, spanning the redshift range 0.6 < z < 2.2. We measure the redshift space distortions around voids using the anisotropic void-galaxy cross-correlation function and we extract the distortion parameter β. We test the methodology on realistic simulations before applying it to the data, and we investigate all our systematic errors on these mocks. We find βLRG(z = 0.74) = 0.415 ± 0.087, βELG(z = 0.85) = 0.665 ± 0.125 and βQSO(z = 1.48) = 0.313 ± 0.134, for the LRG+CMASS, ELG, and QSO sample, respectively. The quoted errors include systematic and statistical contributions. In order to convert our measurements in terms of the growth rate fσ8, we use consensus values of linear bias from the eBOSS DR16 companion papers, resulting in the following constraints: fσ8(z = 0.74) = 0.50 ± 0.11, fσ8(z = 0.85) = 0.52 ± 0.10, and fσ8(z = 1.48) = 0.30 ± 0.13. Our measurements are consistent with other measurements from eBOSS DR16 using conventional clustering techniques.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Galaxy Cruise: Deep Insights into Interacting Galaxies in the Local Universe

Abstract We present the first results from GALAXY CRUISE, a community (or citizen) science project based on data from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). The current paradigm of galaxy evolution suggests that galaxies grow hierarchically via mergers, but our observational understanding of the role of mergers is still limited. The data from HSC-SSP are ideally suited to improve our understanding with improved identifications of interacting galaxies thanks to the superb depth and image quality of HSC-SSP. We launched a community science project, GALAXY CRUISE, in 2019 and have collected over two million independent classifications of 20686 galaxies at z < 0.2. We first characterize the accuracy of the participants’ classifications and demonstrate that it surpasses previous studies based on shallower imaging data. We then investigate various aspects of interacting galaxies in detail. We show that there is a clear sign of enhanced activities of super-massive black holes and star formation in interacting galaxies compared to those in isolated galaxies. The enhancement seems particularly strong for galaxies undergoing violent mergers. We also show that the mass growth rate inferred from our results is roughly consistent with the observed evolution of the stellar mass function. The second season of GALAXY CRUISE is currently underway and we conclude with future prospects. We make the morphological classification catalog used in this paper publicly available at the GALAXY CRUISE website, which will be particularly useful for machine-learning applications.

Tanaka, Masayuki↗
DOE OSTI2021

Detection of translational noncrystallographic symmetry in Patterson functions

Detection of translational noncrystallographic symmetry (TNCS) can be critical for success in crystallographic phasing, particularly when molecular-replacement models are poor or anomalous phasing information is weak. If the correct TNCS is detected then expected intensity factors for each reflection can be refined, so that the maximum-likelihood functions underlying molecular replacement and single-wavelength anomalous dispersion use appropriate structure-factor normalization and variance terms. Here, an analysis of a curated database of protein structures from the Protein Data Bank to investigate how TNCS manifests in the Patterson function is described. These studies informed an algorithm for the detection of TNCS, which includes a method for detecting the number of vectors involved in any commensurate modulation (the TNCS order). The algorithm generates a ranked list of possible TNCS associations in the asymmetric unit for exploration during structure solution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

An Open-Access Repository of Synchrophasor Data Quality Examples: Curation and Example Applications

Synchrophasor measurements are critical in providing wide-area situational awareness to power system operators. However, data artifacts may be introduced due to various issues such as loss of communication, loss of GPS signal, internal clock error, and vendor-specific implementation of phasor estimation algorithms. Tools designed to provide actionable insights from synchrophasor data, hence, must be designed to be robust to these data quality issues. In this work, two years of synchrophasor data sourced from multiple electric utilities in the United States were analyzed to identify examples of data quality problems. These examples were then labeled and published in the Grid Event Signature Library, a publicly available repository of power system measurements hosted by the Oak Ridge National Laboratory. This paper describes the data curation process, and illustrates two application use cases where the dataset can be valuable to the research community. In the first use case, a random forest classifier is trained to distinguish power system disturbance signatures from data anomalies introduced in synchrophasor measurements due to clock errors. The second use case studies the impact of data quality issues on an example synchrophasor application (specifically, event start time determination). The choice of data quality problems investigated is informed by the examples in the repository curated in this work.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

An Investigation on the Pollen-Induced Soiling Losses in Utility-Scale PV Plants

Here in this study, the impact of pollen as a PV soiling agent is investigated. The performance data of five utility-scale PV plants in North Carolina, USA, was collected and analyzed using two soiling extraction methods. Satellite and environmental data, including pollen counts, cropland, and vegetation, was also collected and analyzed to identify impacts to soiling losses. During the spring peak pollen season, performance losses of >15% were observed at all five sites. Partial performance recoveries following the pollen season were slow, with lack of correlation with rainfall. This means that the statistical soiling estimation methods that assume abrupt performance recovery from rain are not appropriate for pollen-impacted solar sites. When manual cleanings were performed on site the performance recovery ranged from 5% to 11% indicating persistent soiling impacts are present in this region. The results of this work provide new insights into the phenomenon of pollen deposition on PV systems, demonstrating that 1) soiling can also affect systems located in rainy locations and 2) that its effects cannot be determined using the current estimation methodologies.

14 SOLAR ENERGY↗
DOE OSTI2020

Metabolomics analysis reveals differences in evolution between maize and rice

SUMMARY Metabolites are the intermediate and final products of metabolism, which play essential roles in plant growth, evolution and adaptation to changing climates. However, it is unclear how evolution contributes to metabolic variation in plants. Here, we investigated the metabolomics data from leaf and seed tissues in maize and rice. Using principal components analysis based on leaf metabolites but not seed metabolites, metabolomics data could be clearly separated for rice Indica and Japonica accessions, while two maize subgroups, temperate and tropical, showed more visible admixture. Rice and maize seed exhibited significant interspecific differences in metabolic variation, while within rice, leaf and seed displayed similar metabolic variations. Among 10 metabolic categories, flavonoids had higher variation in maize than rice, indicating flavonoids are a key constituent of interspecific metabolic divergence. Interestingly, metabolic regulation was also found to be reshaped dramatically from positive to negative correlations, indicative of the differential evolutionary processes in maize and rice. Moreover, perhaps due to this divergence significantly more metabolic interactions were identified in rice than maize. Furthermore, in rice, the leaf was found to harbor much more intense metabolic interactions than the seed. Our result suggests that metabolomes are valuable for tracking evolutionary history, thereby complementing and extending genomic insights concerning which features are responsible for interspecific differentiation in maize and rice.

Deng, Min↗
DOE OSTI2024

ZFP: A compressed array representation for numerical computations

HPC trends favor algorithms and implementations that reduce data motion relative to FLOPS. We investigate the use of lossy compressed data arrays in place of traditional IEEE floating point arrays to store the primary data of calculations. Simulation is fundamentally an exercise in controlled approximation, and error introduced by finite-precision arithmetic (or lossy compression) is just one of several sources of error that need to be managed to ensure sufficient accuracy in a computed result. We describe ZFP, a compressed numerical format designed for in-memory storage of multidimensional arrays, and summarize theoretical results that demonstrate that the error of repeated lossy compression can be bounded and controlled. Furthermore, we establish a relationship between grid resolution and compression-induced errors and show that, contrary to conventional floating point, ZFP reduces finite-difference errors with finer grids. We present example calculations that demonstrate data reduction by 4x or more with negligible impact on solution accuracy. Our results further demonstrate several orders-of-magnitude increase in accuracy using ZFP over IEEE floating point and Posits for the same storage budget.

Lindstrom, Peter↗