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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Vicennial metagenomic time series unveils evolutionary dynamics of giant viruses in a freshwater ecosystem

Giant viruses play crucial ecological roles in aquatic ecosystems, yet their evolutionary dynamics in response to environmental changes, particularly in freshwater environments, are not well understood. We analyzed a 20-year time series (2000-2019) of 471 co-assembled metagenomes from Lake Mendota (USA) to reconstruct 1512 giant virus metagenome-assembled genomes, providing insights into viral genome evolution. Viruses in the order Imitervirales dominate the virome, remaining consistent across seasons and years. Our findings reveal gene duplication (23% of genes) and horizontal gene transfer (29% of genes) as key drivers of genomic innovation. A co-occurrence network analysis indicates increased virus-host interactions following the introduction of an invasive predatory zooplankton in 2009, highlighting potential hosts in Bigyra, Perkinsea, and Euglenozoa. While single nucleotide polymorphism analysis shows predominantly purifying selection in viral genes, there is a significant increase in positively selected genes post-invasion, particularly those related to infection. Comparative evolutionary analyses reveal that giant viruses exhibit genome-wide substitution rates similar to co-occurring bacteria but significantly slower than smaller dsDNA phages, suggesting both stability and adaptability. Our study demonstrates that freshwater giant viruses employ various evolutionary strategies to respond to environmental change. These results underscore their significant yet often underappreciated role in freshwater ecosystem dynamics.

Vasquez, Yumary M↗
DOE OSTI2021

Differences in c-Si Solar Cell Metallization and Susceptibility to Series Resistance Degradation

In this case study, we investigate a degradation mode occurring at the cell level in fielded multi-Si modules. Affected cells in the module show a progressive, series-resistance-related power degradation observed in module- and cell-level IV curves along with EL and PL imaging at the module, cell, and cell core sample scale. SEM and elemental analysis via EDS reveal a difference in the oxides in the silver paste used in screen printing of the finger contacts. This suggests that the cells were screen printed with different silver paste compositions and possibly firing conditions. One of these combinations leads to degradation of the contact at the interface between the cell and contact finger, causing severe series resistance across the cell that continues to progress over time.

acetic acid↗
DOE OSTI2021

Physics-Infused AI/ML Based Digital-Twin Framework for Flow-Induced-Vibration Damage Prediction in a Nuclear Reactor Heat Exchanger

This report summarizes some of the ongoing work related to the development of an expert-elicitation-digital-twin framework for real time damage state prediction in heat exchanger components of a nuclear reactor. The framework is targeted towards predicting damage associated with coupled low cycle fatigue (associated with regular heat-up, cool-down and power operation transients) and high cycle fatigue (associated with flow induced vibration transients). The overall framework will be based on a NoSQL based database, physics-infused-geometry-dependent virtual-sensor data, different AI/ML techniques-based data-driven-predictive-model applications (Apps) and real-time plant sensor measurements available through few existing sensors. Towards this overall goal, this report updates some of the ongoing work, such as on implementation of a NoSQL Database (such as MongoDB), FE based heat transfer analysis of a heat exchanger (e.g. of a PWR steam generator) for generating geometry-dependent virtual sensor data and evaluation of various AI/ML models such as based on multivariate linear regression, ensembled decision-tree based Random-Forest and Gradient-Boosting regression and high-dimensional-kernel-function-transformation based Support-Vector-Machine regression models. The AI/ML models were evaluated for predicting multi-time-series thermal states at thousands of 3D point-clouds

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Real-time biomass feedstock particle quality detection using image analysis and machine vision

Abstract A common and costly challenge in the nascent biorefinery industry is the consistent handling and conveyance of biomass feedstock materials, which can vary widely in their chemical, physical, and mechanical properties. Solutions to cope with varying feedstock qualities will be required, including advanced process controls to adjust equipment and reject feedstocks that do not meet a quality standard. In this work, we present and evaluate methods to autonomously assess corn stover feedstock quality in real time and provide data to process controls with low-cost camera hardware. We explore the use of neural networks to classify feedstocks based on actual processing behavior and pixel matrix feature parameterization to further assess particle attributes that may explain the variable processing behavior. We used the pretrained ResNet neural network coupled with a gated recurrent unit (GRU) time-series classifier trained on our image data, resulting in binary classification of feedstock anomalies with favorable performance. The textural aspects of the image data were statistically analyzed to determine if the textural features were predictive of operational disruptions. The significant textural features were angular second moment, prominence, mean height of surface profile, mean resultant vector, shade, skewness, variation of the polar facet orientation, and direction of azimuthal facets. Expansion of these models is recommended across a wider variety of labeled feedstock images of different qualities and species to develop a more robust tool that may be deployed using low-cost cameras within biorefineries.

09 BIOMASS FUELS↗
DOE OSTI2021

A molecular dynamics study of domain switching in BiFeO 3 nanofilm under DC electric field

The performance of ferroelectric materials is deeply rooted in the domain switching process triggered by an applied electric field. To understand the effect of controlling factors on the domain switching characteristics, nanoscale studies are essential. In this work, an atomistic-scale computational framework is developed to study the domain switching process of bismuth ferrite (BiFeO 3 ) nanofilms. Through a series of molecular dynamics simulations, the effects of duration and magnitude of an electric field, domain size and nanofilm thickness on the domain switching behavior are investigated. The evolution of domains under different magnitudes and durations of the applied electric field is studied, and the results of unswitched and switched cases are summarized in a switching map. Analysis of various nanofilms reveals that by increasing the film thickness, the switching time is increased. Additionally, the nanofilms with different domain sizes and configurations are examined, and the minimum domain size for complete reversal switching is obtained. Our results are helpful to predict and tune the switching process in ferroelectric materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Vegetation-induced asymmetric diurnal land surface temperatures changes across global climate zones

Unprecedented global vegetation greening during past decades is well known to affect annual and seasonal land surface temperatures (LST). However, the impact of observed vegetation cover change on diurnal LST across global climatic zones is not well understood. In this study, using global climatic time-series datasets, we investigated the long-term growing season daytime and nighttime LST changes globally and explored associated dominant contributors including vegetation and climate factors including air temperature, precipitation, and solar radiation. Results revealed asymmetric growing season mean daytime and nighttime LST warming (0.16 °C/10a and 0.30 °C/10a, respectively) globally from 2003 to 2020, as a result, the diurnal LST range (DLSTR) declined at 0.14 °C/10a. The sensitivity analysis indicated the LST response to changes in LAI, precipitation, and SSRD mainly concentrated during daytime instead of nighttime, however, which showed comparable sensitivities for air temperature. Combining the sensitivities results and the observed LAI and climate trends, we found rising air temperature contributes to 0.24 ± 0.11 °C/10a global daytime LST warming and 0.16 ± 0.07 °C/10a nighttime LST warming, turns to be the dominant contributor to the LST changes. Increased LAI cooled global daytime LST (–0.068 ± 0.096 °C/10a) while warmed nighttime LST (0.064 ± 0.046 °C/10a); hence LAI dominates declines in DLSTR trends (–0.12 ± 0.08 °C/10a), despite some daynight process variations across climate zones. In Boreal regions, reduced DLSTR was due to nighttime warming from LAI increases. In other climatic zones, daytime cooling, and DLSTR decline, was induced by increased LAI. Biophysically, the pathway from air temperature heats the surface through sensible heat and increased downward longwave radiation during day and night, while the pathway from LAI cools the surface by enhancing energy redistribution into latent heat rather than sensible heat during the daytime. These empirical findings of diverse asymmetric responses could help calibrate and improve biophysical models of diurnal surface temperature feedback in response to vegetation cover changes in different climate zones.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Coassembly and binning of a twenty-year metagenomic time-series from Lake Mendota

Abstract The North Temperate Lakes Long-Term Ecological Research (NTL-LTER) program has been extensively used to improve understanding of how aquatic ecosystems respond to environmental stressors, climate fluctuations, and human activities. Here, we report on the metagenomes of samples collected between 2000 and 2019 from Lake Mendota, a freshwater eutrophic lake within the NTL-LTER site. We utilized the distributed metagenome assembler MetaHipMer to coassemble over 10 terabases (Tbp) of data from 471 individual Illumina-sequenced metagenomes. A total of 95,523,664 contigs were assembled and binned to generate 1,894 non-redundant metagenome-assembled genomes (MAGs) with ≥50% completeness and ≤10% contamination. Phylogenomic analysis revealed that the MAGs were nearly exclusively bacterial, dominated by Pseudomonadota (Proteobacteria, N = 623) and Bacteroidota (N = 321). Nine eukaryotic MAGs were identified by eukCC with six assigned to the phylum Chlorophyta. Additionally, 6,350 high-quality viral sequences were identified by geNomad with the majority classified in the phylum Uroviricota. This expansive coassembled metagenomic dataset provides an unprecedented foundation to advance understanding of microbial communities in freshwater ecosystems and explore temporal ecosystem dynamics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Extending the Southern Shore of the Island of Inversion to F 28

Detailed spectroscopy of the neutron-unbound nucleus 28 F has been performed for the first time following proton/neutron removal from 29 Ne/ 29 F beams at energies around 230 MeV / nucleon . The invariant-mass spectra were reconstructed for both the 27 F(*) + n and 26 F(*) + 2n coincidences and revealed a series of well-defined resonances. A near-threshold state was observed in both reactions and is identified as the 28 F ground state, with S n ( 28 F) = -199(6) keV, while analysis of the 2n decay channel allowed a considerably improved S n ( 27 F) = 162(60) keV to be deduced. Comparison with shell-model predictions and eikonal-model reaction calculations have allowed spin-parity assignments to be proposed for some of the lower-lying levels of 28 F. Importantly, in the case of the ground state, the reconstructed 27 F + n momentum distribution following neutron removal from 29 F indicates that it arises mainly from the 1p 3/2 neutron intruder configuration. Finally, this demonstrates that the island of inversion around N = 20 includes 28 F, and most probably 29 F, and suggests that 28 O is not doubly magic.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Data-Driven Preemptive Voltage Monitoring and Control Using Probabilistic Voltage Sensitivities

Increased penetration levels of distributed variable renewable generation can cause random voltage fluctuations and violations at multiple nodes. Traditional methods of voltage control typically involve reactionary responses of capacitor banks, tap changers, and recently even smart inverters. But because of the lack of foresight in voltage violations, these controls are ineffective to completely mitigate the issue. Therefore, new methods of predicting voltage violations subject to random power injection changes in the distribution network are needed, which can be used to guide optimal and dynamic methods of voltage control. This work lays the foundation for such preemptive voltage monitoring and control by proposing an analytical and sensor data-driven voltage sensitivity analysis method. Driven by stochastic data and forecasts, the method can be used to develop probabilistic voltage sensitivities and consequently to predict system nodes with high likelihood of voltage limit violations. The effectiveness of this method is tested on IEEE 69-node distribution system integrated with distributed solar. The results demonstrate the proposed method's ability to successfully predict nodes with high probability of voltage violations for a specific time-series simulation. The results also demonstrate the ability to guide timely power injection control actions to mitigate future voltage violations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

What explains the year-to-year variation in growing season timing of boreal black spruce forests?

Amplified climate warming in high latitudes is expected to affect growing season timing of the vast boreal biome. It is unclear whether the presence of permafrost (perennially frozen ground) might have an influence on changes in growing season timing. Here, this study examined how different environmental variables explained, either directly or indirectly, the variation in growing season timing of boreal forest stands with and without permafrost. We expected that environmental variables explaining the variation in growing season timing differed or had different explanatory power depending on permafrost presence or absence. The growing season was delineated from daily gross primary productivity (GPP) time series derived from 40 site-year data of net ecosystem carbon dioxide exchange measured with eddy covariance techniques over five black spruce (Picea mariana [Mill.])-dominated boreal forest stands in North America. In permafrost-free forest stands, a combination of start in canopy ‘green-up’ in spring and the timing of air and soil temperature increasing above freezing explained the start-of-season (SOS GPP ). Results from commonality analysis and structural equation modeling suggest that canopy ‘green-up’ and air temperature directly affected SOS GPP in permafrost-free forest stands. In addition, soil temperature acted as mediator for an indirect effect of air temperature on SOS GPP . In contrast, none of the environmental variables, or their combination, explained the variation in SOS GPP in forest stands with permafrost. The explanatory power of environmental variables was more consistent regarding the end-of-season (EOS GPP ). In both, forest stands with and without permafrost, EOS GPP was directly explained by mean soil water content in the fall and the first day of continuous snowpack formation. A better understanding how environmental variables control SOS GPP and EOS GPP in forest stands with and without permafrost will help to refine parameterizations of the boreal biome in Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Multiphysics modeling of printed surface acoustic wave thermometers

Surface acoustic wave (SAW) transducers are a class of sensors and actuators that operate on the fundamental principle of piezoelectricity. Aerosol jet printing and other additive manufacturing techniques have resulted in the low-cost fabrication of low-power and small-footprint SAW devices that are suitable for sensing in high-temperature and radioactive environments. In this work, we developed a series of temperature-dependent finite element models for a SAW transducer consisting of printed silver interdigitated transducers (IDTs) deposited onto piezoelectric lithium niobate. Modeling accuracy was evaluated experimentally from room temperature to 200 °C using an aerosol-jet-printed SAW thermometer. A time-domain study enabled visualization of the wave propagation and successfully guided the denoising of the scattering parameter measurement. Additionally, frequency-domain models using traditional modal analysis or the unique port boundary condition feature in COMSOL Multiphysics accurately predicted the temperature-driven natural frequency drift in the SAW thermometer. The finite element models developed in this study serve to facilitate the computer-aided design of future SAW transducers for applications in harsh environments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Capture Instead of Release: Defect-Modulated Radionuclide Leaching Kinetics in Metal–Organic Frameworks

Comparison of defect-controlled leaching-kinetics modulation of metal–organic frameworks (MOFs) and porous functionalized silica-based materials was performed on the example of a radionuclide and radionuclide surrogate for the first time, revealing an unprecedented readsorption phenomenon. On a series of zirconium-based MOFs as model systems, we demonstrated the ability to capture and retain >99% of the transuranic 241 Am radionuclide after 1 week of storage. Here, we report the possibility of tailoring radionuclide release kinetics in MOFs through framework defects as a function of postsynthetically installed organic ligands including cation-chelating crown ether-based linkers. Based on comprehensive analysis using spectroscopy (EXAFS, UV–vis, FTIR, and NMR), X-ray crystallography (single crystal and powder), and theoretical calculations (nine kinetics models and structure simulations), we demonstrated the synergy of radionuclide integration methods, topological restrictions, postsynthetic scaffold modification, and defect engineering. This combination is inaccessible in any other material and highlights the advantages of using well-defined frameworks for gaining fundamental knowledge necessary for the advancement of actinide-based material development, providing a pathway for addressing upcoming challenges in the nuclear waste administration sector.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Measurements of radioxenon activities during periods of gaseous release from an advanced gas-cooled reactor

Activities of radioxenon isotopes are reported from an Advanced Gas-cooled Reactor (AGR) during periods of gaseous release. Xenon isotopes are relevant to the monitoring regime of the Comprehensive Nuclear-Test-Ban Treaty (CTBT). These releases may affect detections from the International Monitoring System (IMS) by influencing the radioxenon background. Time series activity plots have been produced from both in-core monitoring and direct measurement at the point of release using a stack monitor system. Ratio plots using both data sets have been produced with results compared with a commonly chosen nuclear explosion “discrimination line.” The reported results improve the understanding of radionuclide emissions from civil nuclear power plants. This work is being performed as part of the Xenon Environmental Nuclide Analysis at Hartlepool (XENAH) collaboration between the Atomic Weapons Establishment (AWE, UK), EDF Energy (UK), Pacific Northwest National Laboratory (PNNL, USA), and the Swedish Defence Research Agency (FOI).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Fe protein docking transduces conformational changes to MoFe nitrogenase active site in a nucleotide-dependent manner

The reduction of dinitrogen to ammonia catalyzed by nitrogenase involves a complex series of events, including ATP hydrolysis, electron transfer, and activation of metal clusters for N 2 reduction. Early evidence shows that an essential part of the mechanism involves transducing information between the nitrogenase component proteins through conformational dynamics. Here, millisecond time-resolved hydrogen-deuterium exchange mass spectrometry was used to unravel peptide-level protein motion on the time scale of catalysis of Mo-dependent nitrogenase from Azotobacter vinelandii. Normal mode analysis calculations complemented this data, providing insights into the specific signal transduction pathways that relay information across protein interfaces at distances spanning 100 Å. Together, these results show that conformational changes induced by protein docking are rapidly transduced to the active site, suggesting a specific mechanism for activating the metal cofactor in the enzyme active site.

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

Tank 27 Solids Disturbance Testing Using M-Star for the Impact of CSMP Usage on Blend Tank Mixing Effectiveness

Savannah River Mission Completion (SRMC) plans to operate Tank 27as a blend tank for future waste disposal operations. It is desirable to avoid additional worker exposure by using the planned commercial submersible mixing pump (CSMP) installations in Risers B2 and B4 to function as the blend pumps for prolonged blend tank operations. The purpose of this task is to evaluate the impacts to mixing across a range of pump installation heights from 1 to 201 inches above the tank floor. The CSMPs shall maintain adequate blending within a 24 hour maximum timeframe and an adequate nozzle discharge velocity as outlined in U-ESR-G-00030, using the specifications of the planned CSMPs listed in PO SRRA149971 and M-DS-G-00081. Specifications include: maximum pump diameter of D=22.5 in., dual nozzles placed tangentially opposed with nominal inside diameter of 2 in., total flow range (both nozzles combined) of 500 to 1950 GPM and maximum RPM of 1800. Tank 27 is expected to have a fill height maximum of 360". This analysis began by using results from the 2010 testing and applying them to the Tank 27 design to calculate a mixing time as a function of pump flow rate. These results were modified to account for the higher liquid level in Tank 27. Once the liquid level was increased to 360 inches, the results were modified to account for a higher viscosity in Tank 27 than in the testing. Once the viscosity was increased, the effect of changing pump elevation was applied to calculations of the mixing time in Tank 27. Finally, the uncertainty from the testing was included in the analysis to recommend a blend time as a function of pump flow rate and elevation. The conclusion from this study is that the particles in tank 27 will be suspended at both the 600 and 900 gpm flow rates. Only particles above 90 micron will not be suspended in significant amounts when the flow rate is 600 gpm. At 900 gpm even 100 micron particles were thoroughly suspended in the tank. From the series of simulations it has been concluded that it will not be possible to mix tank 27 at the proposed fluid flow rates and not suspend the solid particles at the bottom of the tank.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Skeletal reaction models for methane combustion

A local-sensitivity-analysis technique is employed to generate new skeletal reaction models for methane combustion from the foundational fuel chemistry model (FFCM-1). Here, the sensitivities of the thermo-chemical variables with respect to the reaction rates are computed via the forced-optimally time dependent (f-OTD) methodology. In this methodology, the large sensitivity matrix containing all local sensitivities is modeled as a product of two low-rank time-dependent matrices. The evolution equations of these matrices are derived from the governing equations of the system. The modeled sensitivities are computed for the auto-ignition of methane at atmospheric and high pressures with different sets of initial temperatures, and equivalence ratios. These sensitivities are then analyzed to rank the most important (sensitive) species. A series of skeletal models with different number of species and levels of accuracy in reproducing the FFCM-1 results are suggested. The performances of the generated models are compared against FFCM-1 in predicting the ignition delay, the laminar flame speed, and the flame extinction. The results of this comparative assessment suggest the skeletal models with 24 and more species generate the FFCM-1 results with an excellent accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Crustal Strain Rates in the Western United States and Their Relationship with Earthquake Rates

Abstract We present a suite of strain rate models for the western United States based on geologic and geodetic data. The geologic data consist of Quaternary fault-slip rates and the geodetic data consists of a new compilation of Global Positioning System (GPS) velocities derived from continuous, semicontinuous, and campaign measurements. We remove postseismic deformation from the GPS time series in order for our geodetic strain rate model to best capture the interseismic strain accumulation rate. We present models based on either geologic or geodetic data, but also create a hybrid model. Although there are some differences between the models, the large-scale features are the same, with the noticeable exception for the Pacific Northwest where interseismic strain is naturally more distributed than the long-term strain release. We also present a map of earthquake rate densities based on mainshocks, and the result has similar spatial features similar to the strain rate models (at least in the southwestern United States). We perform a general correlation analysis between strain rate and seismicity rate (south of Cascadia) and find a change in linearity between seismicity and strain rates from slow to faster deforming areas with seismicity rates relatively lower for the latter. The extent of that change depends a bit on assumptions made on the declustering and completeness of the catalog, but the finding of a change in slope is robust across the different strain rate models. Linearity for all areas is only expected when Gutenberg–Richter parameters and parameters involved in the conversion from strain to moment rate are uniform across the study area. We discuss these qualifications, but find no single satisfactory explanation for our observation. Moreover, when considering a rather short time and space, theoretical considerations of sampling from a power-law distribution actually predict there to be a power law instead of a linear relationship, generally consistent with our observation.

Geochemistry & Geophysics↗
DOE OSTI2024

Deep learning-enabled probing of irradiation-induced defects in time-series micrographs

Modeling time-series data with convolutional neural networks (CNNs) requires building a model to learn in batches as opposed to training sequentially. Coupling CNNs with in situ or operando techniques opens the possibility of accurately segmenting dynamic reactions and mass transport phenomena to understand how materials behave under the conditions in which they are used. In this article, in situ ion irradiation transmission electron microscopy (TEM) images are used as inputs into the CNN to assess the defect generation rate, defect cluster density, and saturation of defects. We then use the output segmentation maps to correlate with conventional TEM micrographs to assess the model’s ability to detail nanoscale interactions. Next, we discuss the implications of preprocessing and hyperparameters on model variability, accuracy when expanded to other datasets, and the role of regularization when controlling model variance. Ultimately, we eliminate human bias when extrapolating physical metrics, speed up analysis time, decouple reactions that happen at 100 ms intervals, and deploy models that are both accurate and transferable to similar experiments.

Burns, Kory (ORCID:0000000158019909)↗