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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Long‐Term Large‐Scale Atmospheric Forcing Data From Three‐Dimensional Constrained Variational Analysis for the ARM SGP Site

Here, this study presents a long‐term three‐dimensional large‐scale forcing data set (VARANAL3D) derived from the three‐dimensional constrained variational analysis (3DCVA) method at the Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP) site from 2004 to 2018. Building on the same input data sets as the conventional continuous forcing data set (VARANAL), VARANAL3D maintains overall consistency in domain‐averaged fields while introducing spatial variability, offering critical insights into the influence of mesoscale synoptic systems on cloud‐related processes. Evaluations are conducted across four cloud and precipitation regimes: Clear‐sky, Shallow‐clouds, Afternoon‐precipitation, and Nocturnal‐precipitation, presenting high consistency of the domain‐mean forcing data sets while emphasizing the role of subdomain forcing variability particularly in precipitating regimes. Single column model (SCM) simulations demonstrate that subdomain VARANAL3D forcing improves cloud and precipitation representation, with the ensemble outperforming domain‐mean forcing in three cloudy and precipitating regimes. Overall, these results highlight VARANAL3D's value for investigating the impacts of spatial variability of large‐scale forcing on atmospheric processes. The VARANAL3D data set provides new opportunities for evaluating model physics, advancing the development of scale‐aware parameterizations and deepening our understanding of cloud and precipitation dynamics.

Environmental sciences↗
NASA NTRS1983

Short-term and long-term clinostat and vibration-induced biochemical changes in dwarf marigold stems

Stems of 21-day dwarf marigold plants cultivated on the clinostat were compared with plants cultivated on vertical axis rotators ('vibrational controls') and stationary controls for long-term changes in cell wall composition. Stems of 21-day plants grown under stationary conditions and subsequently exposed to the clinostat for 24 hours were also analyzed. Among the long-term markers, calcium, lignin, and protein-bound hemicellulose (possibly cell wall glycoprotein) clearly differentiated the effects of vibration from those of the clinostat. Short-term differential responses included rate of ethylene production, nastic movement and peroxidase activity of the cell wall, but not of the protoplast.

Siegel, S. M.↗
DOE OSTI2022

Recurrent neural networks for short-term and long-term prediction of geothermal reservoirs

Accurate prediction of geothermal reservoir responses to alternative energy production scenarios is critical for optimizing the development of the underlying resources. While the conventional physics-based models offer a comprehensive prediction tool, data-driven models provide an efficient alternative to build fit-for-purpose predictive models by extracting and using the statistical patterns in the collected data to make predictions. The recurrent neural network (RNN) is a data-driven model that is commonly applied to predict time series sequences. This paper presents a variant of RNN that also utilizes the efficiency of convolutional neural networks (CNN) for the prediction of energy production from geothermal reservoirs. Specifically, a CNN–RNN architecture is developed that takes historical well controls as input (features) and their corresponding production response data as output (labels) to learn an input-output mapping that can predict the future well production responses/performance for any given future well control inputs. The model is paired with a labeling scheme to handle real field disturbances that create data gaps. In addition to the model structure, we introduce a thorough workflow for applying the model, which includes data pre-processing, feature selection, as well as different training strategies for short-term and long-term prediction. Finally, the performance and accuracy of the model are evaluated by applying it to multiple datasets, including a field reservoir model.

15 GEOTHERMAL ENERGY↗
NASA NTRS2001

Effect of short-term microgravity and long-term hindlimb unloading on rat cardiac mass and function

The purpose of this study was to test the hypothesis that exposure to short-term microgravity or long-term hindlimb unloading induces cardiac atrophy in male Sprague-Dawley rats. For the microgravity study, rats were subdivided into four groups: preflight (PF, n = 12); flight (Fl, n = 7); flight cage simulation (Sim, n = 6), and vivarium control (Viv, n = 7). Animals in the Fl group were exposed to 7 days of microgravity during the Spacelab 3 mission. Animals in the hindlimb-unloading study were subdivided into three groups: control (Con, n = 20), 7-day hindlimb-unloaded (7HU, n = 10), and 28-day hindlimb-unloaded (28HU, n = 19). Heart mass was unchanged in adult animals exposed to 7 days of actual microgravity (PF 1.33 +/- 0.03 g; Fl 1.32 +/- 0.02 g; Sim 1.28 +/- 0.04 g; Viv 1.35 +/- 0.04 g). Similarly, heart mass was unaltered with hindlimb unloading (Con 1.40 +/- 0.04 g; 7HU 1.35 +/- 0.06 g; 28HU 1.42 +/- 0.03 g). Hindlimb unloading also had no effect on the peak rate of rise in left ventricular pressure, an estimate of myocardial contractility (Con 8,055 +/- 385 mmHg/s; 28HU 8,545 +/- 755 mmHg/s). These data suggest that cardiac atrophy does not occur after short-term exposure to microgravity and that neither short- nor long-term simulated microgravity alters cardiac mass or function.

manned↗
DOE OSTI2026

Data for Immediate Impacts of Soybean Cover Crop on Bacterial Community Composition and Diversity in Soil Under Long-Term Saccharum Monoculture

Saccharum yield decline results from long-term monoculture practices. Changes in cropping management can improve soil health and productivity. Below-ground bacterial community diversity and composition across soybean (Glycine max (L.) Merr) cover crop, Saccharum monoculture (30+ year) and fallowed soil were determined. Near full length (~1,400 base pairs) of 16S rRNA gene sequences were extracted from the rhizospheres of sugarcane and soybean and fallowed soil were compared. Higher soil bacterial diversity was observed in the soybean cover crop than sugarcane monoculture across all measured indices (observed operationational taxonomic units, Chao1, Shannon, reciprocal Simpson and Jackknife). Acidocateria, Proteobacteria, Bacteroidetes and Planctomycetes were the most abundant bacterial phyla across the treatments. Indicator species analysis identified nine indicator phyla. Planctomycetes, Armatimonadetes and candidate phylum FBP were associated with soybean; Proteobacteria and Firmicutes were linked with sugarcane and Gemmatimonadetes, Nitrospirae, Rokubacteria and unclassified bacteria were associated with fallowed soil. Non-metric multidimensional scaling analysis showed distinct groupings of bacterial operational taxonomic units (97% identity) according to management system (soybean, sugarcane or fallow) indicating compositional differences among treatments. This is confirmed by the results of the multi-response permutation procedures (A = 0.541, p = 0.00045716). No correlation between soil parameters and bacterial community structure was observed according to Mantel test (r = 211865, p = 0.14). Use of soybean cover-crop fostered bacterial diversity and altered community structure. This indicates cover crops could have a restorative effect and potentially promote sustainability in long-term Saccharum production systems.

Field Data↗
DOE OSTI2021

Long-term variability of root production in bioenergy crops from ingrowth core measurements

Long-term determination of root biomass production upon land-use conversion to biofuel crops is rare. To assess land-use legacy influences on belowground biomass accumulation, we converted 22-year-old Conservation Reserve Program (CRP) grasslands and 50+-year-old agricultural (AGR) lands to corn (C), switchgrass (Sw) and restored prairie (Pr) biofuel crops. We maintained one CRP grassland as a reference (Ref). We hypothesized that land-use history and crop type have significant effects on root density, with perennial crops on CRP grasslands having a higher root biomass productivity, while corn grown on former agricultural lands produce the lowest root biomass. Methods The ingrowth core method was used to determine in situ ingrowth root biomass, alongside measurements of aboveground net primary productivity (ANPP). Ancillary measurements, including air temperature, growing season length and precipitation were used to examine their influences on root biomass production. Important Findings Root biomass productivity was the highest in unconverted CRP grassland (1716 g m-2 yr-1) and lowest in corn fields (526 g m-2 yr-1). All perennial sites converted from CRP and AGR lands had lower root biomass and ANPP in the first year of planting but peaked in 2011 for switchgrass and a year later for restored prairies. Ecosystem stability was higher in restored prairies (AGR-Pr: 4.3 ± 0.11; CRP-Pr: 4.1 ± 0.10), with all monocultures exhibiting a lower stability. Root biomass production was positively related to ANPP (R2 = 0.40). Overall, attention should be given to root biomass accumulation in large-scale biofuel production as it is a major source of carbon sequestration.

Environmental Sciences & Ecology↗
DOE OSTI2022

Fast Quasi-Static Time-Series Simulation for Accurate PV Inverter Semiconductor Fatigue Analysis with a Long-Term Solar Profile

Power system simulations with long-term data typically have large time steps varying from one second to a few minutes. However, for PV inverter semiconductors, the minimum thermal stress cycle occurs over the fundamental grid frequency (50 or 60 Hz). This requires the time step of the fatigue simulation to be around 100 µs. This small time step requires long computation times to process yearly power production profiles. This paper proposes a fast fatigue simulation for inverter semiconductors using the quasi-static time series (QSTS) simulation concept. The proposed simulation calculates the steady state of the semiconductor junction temperature by using a Fast Fourier Transform (FFT). The small thermal cycling during a switching period and even over the fundamental waveform is disregarded to further accelerate the simulation speed. The resulting time step of the fatigue simulation is 15 minutes, which is consistent with the solar dataset. The error of the proposed simulation is 0.16% compared to the fatigue simulation results using the complete thermal stress profile. A PV inverter that responds to a Transactive Energy System (TES) is simulated to demonstrate the use of the proposed fatigue simulation. The proposed simulation has the potential to co-simulate with system level simulation tools that also adopt the QSTS concept.

Liu, Yunting↗
DOE OSTI2020

Energy Storage in Long-Term System Models: A Review of Considerations, Best Practices, and Research Needs

Technological change and policy support have heightened expectations for the role of energy storage in power systems, creating a need to enhance representations of energy storage in long-term models to inform decision-making. Energy storage technologies have complex and diverse cost, value, and performance characteristics that make them challenging to model, but there is limited guidance about best practices and research gaps for energy storage analysis. This paper reviews the literature and draws upon our collective experience to provide recommendations to analysts on approaches for representing energy storage in long-term electric sector models, navigating tradeoffs in model development, and identifying research gaps for existing tools and data. The review focuses on national-scale models with technological, temporal, and regional detail given their prevalence in planning and policy, though many insights are transferable to other modeling contexts. It also offers guidance to consumers of model outputs on proper use and interpretation based on model strengths and limitations. In particular, this review demonstrates the importance of capturing how the values of energy storage and other resources change as the system composition changes (e.g. with different levels of storage, renewables deployment, and emissions outcomes). These considerations require model detail like high spatiotemporal resolutions and endogenous investments that global integrated assessment models and price-taker frameworks do not typically resolve. Research gaps include linking tools of different resolutions, developing reduced-form representations of value streams, incorporating hybrid energy storage and renewable systems, and representing longer-duration energy storage technologies.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Identifying Periodic Variable Stars and Eclipsing Binary Systems with Long-term Las Cumbres Observatory Photometric Monitoring of ZTF J0139+5245

We present the results of our search for variable stars using the long-term Las Cumbres Observatory (LCO) monitoring of white dwarf ZTF J0139+5245 with the two 1.0 m telescope nodes located at McDonald Observatory using the Sinistro imaging instrument. In this search, we find 38 variable sources, of which 27 are newly discovered or newly classified (71%) based on comparisons with previously published catalogs, thereby increasing the number of detections in the field of view under consideration by a factor of ≈2.5. We find that the improved photometric precision per exposure due to longer exposure time for LCO images combined with the greater time sampling of LCO photometry enables us to increase the total number of detections in this field of view. Each LCO image covers a field of view of 26' × 26' and observes a region close to the Galactic plane (b = -9.°4) abundant in stars with an average stellar density of ≈8 arcmin{sup -2}. We perform aperture photometry and Fourier analysis on over 2000 stars across 1560 LCO images spanning 537 days to find 28 candidate BY Draconis variables, three candidate eclipsing binaries of type EA, and seven candidate eclipsing binaries of type EW. In assigning preliminary classifications to our detections, we demonstrate the applicability of the Gaia color–magnitude diagram as a powerful classification tool for variable-star studies.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Data from: Short-Term Inhibition and Long-Term Enhancement of IrreversibleTrace Metal Binding to Goethite in Multi-Metal Systems

These files include the data used in all figures from the following paper: Short-Term Inhibition and Long-Term Enhancement of Irreversible Trace Metal Binding to Goethite in Multi-Metal Systems Below is a brief description of each of the figures and associated data. Fig 1. Ni adsorption isotherms to goethite in the presence and absence of Zn and Cd Fig 2. % of Ni, Zn, and Cd exchanged as a function of time in isotope exchange experiments conducted after 2 days, 30 days, and 60 days aging. Fig. 3. This shows the % of Ni, Cd, and Zn in single metal and mixed metal systems that is non-exchangeable, both in units of % non-exchangeable and in micromoles of metal per gram of goethite. Fig. 4. Particle size distributions of Ni-Zn and Ni-Cd systems after aging. Fig 5. Ni and Zn XANES fits for Ni-Cd and Ni-Zn systems after 30 and 60 days aging. Linear combination fits were performed between freshly adsorbed and incorporated phases (synthesized as Ni- or Zn-substituted goethite) to determine the proportions of each. Figure S1. Dissolved Metal Concentrations at the Start of Isotope Exchange Figure S2. Reactor pH with Aging Figure S3. Dissolved Cd and Ni Concentrations during Isotope Exchange Figure S4. Dissolved Zn and Ni Concentrations during Isotope Exchange Figure S5. Tracer Mole Fractions in Ni-Zn Isotope Exchange Experiments Figure S6. Tracer Mole Fractions in Ni-Cd Isotope Exchange Experiments

58 GEOSCIENCES↗
DOE OSTI2025

Long-term measurements of ice nucleating particles at Atmospheric Radiation Measurement (ARM) sites worldwide

Ice nucleating particles (INPs) play a critical role in cloud microphysics and precipitation formation, yet long-term, spatially extensive observational datasets remain limited. Here, we present one of the most comprehensive publicly available datasets of immersion-mode INP concentrations using a single analytical method, generated through the U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) user facility. INP filter samples have been collected across a broad range of environments – including agricultural plains, Arctic coastlines, high-elevation mountain sites, marine regions, and urban areas – via fixed observatories, mobile facility deployments, and vertically-resolved tethered balloon system operations. We describe the standardized processing and quality assurance pipeline, from filter collection and processing using the Ice Nucleation Spectrometer to final data products archived on the ARM Data Discovery portal. The dataset includes both total INP concentrations and selectively treated samples, allowing for classification of biological, organic, and inorganic INP types. It features a continuous 5-year record of INP measurements from a central U.S. site, with data collection still ongoing. Seasonal and site-specific differences in INP concentrations are illustrated through intercomparisons at −10 and −20 °C, revealing distinct regional sources and atmospheric drivers. We also outline mechanisms for researchers to access existing data, request additional sample analyses, and propose future field campaigns involving ARM INP measurements. This dataset supports a wide range of scientific applications, from observational and mechanistic studies to model development, and provides critical constraints on aerosol-cloud interactions across diverse atmospheric regimes (Creamean et al., 2024, 2020b; https://doi.org/10.5439/1770816).

Creamean, Jessie M. [Colorado State Univ., Fort Co↗
DOE OSTI2020

Characterization of Spent Purolite A530E Resin with Implications for Long-Term Radioactive Contaminant Removal

Direct removal of pertechnetate anion (TcO4-) from the subsurface contaminated plumes at legacy nuclear weapons production sites, is effective remediation strategy to prevent their spread to adjacent aquifers but is also challenging because TcO4- is a trace component of the contaminated groundwater typically containing large access of other anionic constituents, such nitrate, sulfate, chloride and others. It can be achieved through ion exchange treatment using Purolite A530E resin which to date however has only been evaluated under laboratory conditions and many questions regarding its long-term operational performance remain. To address this need, here we report comprehensive characterization of the spent Purolite A530E resin which processed over 5.38x109 L of contaminated groundwater and successfully removed about 3.78 Ci of Tc-99 during four years of operation at the 200 West Pump & Treat facility at the US DOE Hanford site. This Tc-99 loading constitutes however only about 0.034% of the theoretical capacity of the resin which retained significant amounts of sulfate. Among other radioactive contaminants, small quantities of U-238, Co-60, and I-129 were retained by the resin. The total loading of iodine (combined 1-127 and I-129) on the spent resin exceeded that of Tc-99. To elucidate the mechanism of iodine retention, ion exchange behavior of iodide and iodate was investigated. Purolite A530E resin exhibited highly efficient uptake of iodide and only moderate affinity for iodate in accord with their Gibbs energy of hydration. Sorption isotherms for both anions obeyed Freundlich model.

Levitskaia, Tatiana G.↗
DOE OSTI2020

Moving from residual lignocellulosic biomass into high–value products: Outcomes from a long–term international cooperation

Major progress in the bioprocessing of lignocellulose to fuels and value-added chemicals has created the possibility of a low carbon-footprint economy. However, the current complexity and associated costs of lignocellulose conversion result in a higher price for ethanol than for fossil fuels. The cost of cellulosic ethanol production will be lowered by further progress in development of biorefinery technology that produces both ethanol and high-value chemicals with bio-based products that are beginning to penetrate consumer markets in the USA, Brazil, and worldwide. The cost-effectiveness of low carbon-footprint bioproducts will benefit from advances in supplying large amounts of biomass solids to the biorefinery. We describe here outcomes from a successful long-term international cooperation between the Laboratory of Renewable Resources Engineering (LORRE) at Purdue University in the United States and Brazil's Agricultural Research Corporation (EMBRAPA) and Federal University of Sâo Carlos (UFSCar), which has contributed practical pathways to enhance the biorefinery concept. Furthermore, this paper gives an overview of developments that address fundamental knowledge of lignocellulosic biomass pretreatment hydrolysis under optimized operational conditions and bioreactor configurations, and the science and engineering that contributes to the effective production of fuel and ethanol and value-added products from biomass.

09 BIOMASS FUELS↗
DOE OSTI2020

Synthesis of LiNiO 2 at Moderate Oxygen Pressure and Long-Term Cyclability in Lithium-Ion Full Cells

The widespread adoption of electric vehicles necessitates higher-energy-density and longer-life cathode materials for Li-ion batteries. LiNiO 2 offers a higher energy density at a lower cost than other high-Ni-content cathodes containing additional transition-metal ions. However, detrimental phase transformations and impedance growth, resulting from structural defects formed during synthesis, lead to poor cyclability and limit the practical viability of LiNiO 2 . Herein, we demonstrate a considerably improved cycle life for LiNiO 2 by synthesizing it under a pressurized oxygen environment. The capacity retention in pouch-type full cells with a graphite anode after 1000 cycles is increased from 59 to 76% by applying a mere 1.7 atm of oxygen pressure during the synthesis of LiNiO 2 . With iodometric titration and inductively coupled plasma optical emission spectroscopy analysis, we provide clear evidence that oxygen pressure during synthesis reduces the occurrence of lattice oxygen vacancies and increases the content of Ni 3+ in LiNiO 2 , improving its structural integrity and cyclability. Post-mortem analysis of the cycled cathodes provides insights into the sources of degradation occurring during long-term cycling. Here, this work demonstrates a practically viable, synthetic approach combined with doping and coating to achieve improved performance with high-Ni layered oxide materials. Furthermore, this work represents the first report of extended cycling of LiNiO 2 in pouch full cells with graphite anode and will, therefore, serves as an important benchmark for future research on LiNiO 2 .

25 ENERGY STORAGE↗
DOE OSTI2025

Short-Term Inhibition and Long-Term Enhancement of Irreversible Trace Metal Binding to Goethite in Multi-Metal Systems

Iron (oxyhydr)oxide minerals are important sorbents of trace metals in aquatic environments. Adsorption–desorption hysteresis has been documented for trace metals after aging, suggesting that they become incorporated over time. We previously found that ion size controls the extent of irreversible metal binding of single metals to goethite. In this study, we evaluate how the presence of multiple metals influences irreversible binding. Mixed Ni–Zn and Ni–Cd solutions were aged with goethite at pH 7 for 2 days, 30 days, and 60 days, after which isotope exchange experiments were performed to assess the lability of the adsorbed metal pools. After 2 days of aging, Ni and Cd in mixed-metal systems were more labile than in single-metal systems, indicating that competitive adsorption may partially block irreversible binding on short time scales. After 60 days, all three metals had larger irreversibly bound fractions than in single-metal systems. X-ray absorption near-edge structure (XANES) spectroscopy indicates that irreversibly bound fractions correlate with incorporation into goethite. This study demonstrates that pools of coadsorbed metals are bioaccessible on a time scale of minutes. Cooperative effects promote the structural sequestration of even large trace metals, causing reactive transport models to likely overpredict metal mobility. Long-term metal entrapment processes hinder micronutrient availability, impact contaminant sequestration and critical mineral recovery, and yield complex pathways through which metal solubilization may be enhanced or hindered during redox cycling.

58 GEOSCIENCES↗
DOE OSTI2026

Soil microbiome resilience to short-term (30 days, 90 days) and long-term (1000 days) drought

This dataset contains data used for the paper "Drought duration does not impact soil microbiome resilience". The Related References will be updated with a full citation when available. Increasing global droughts exert large but poorly understood effects on the microbial communities and ecology of soil. Microbial communities generally show resilience and return to pre-drought conditions when short-term droughted soils are rewet; soils exposed to long-term drought, however, often show a lag upon rewetting, after which microbial communities may or may not return to their pre-stressed conditions. Though short-term droughts have been widely studied, long-term drought manipulation experiments remain rare, especially those that compare microbial response to short-term and long-term drought in tandem. We conducted a 1000-day drought simulation in controlled laboratory conditions with soil cores collected from a tidal freshwater ecosystem in Washington state, USA, and subsequently exposed them to rewetting for two weeks. We also included short-term (30-day and 90-day) drought and rewet treatments to directly compare microbial community and organic matter responses across drought durations. We found distinct microbial taxa belonging to Firmicutes and Actinobacteria enriched after the 1000-day drought, but not after the short-term droughts. While we hypothesized that the microbial community would recover from a short-term drought after rewetting to resemble pre-drought conditions, our results revealed community dissimilarities between rewet and pre-drought conditions across all drought durations. These findings suggest unique microbial life history strategies within certain microbial phyla that make them successful colonizers during an extended drought period, and the influence of environmental and physiological context on microbial responses to rewetting. The 16SrRNA gene amplicon dataset contains processed DNA sequences in the form of an ASV table with raw unrarefied read counts and representative sequences in .fasta format as described in the ESS-DIVE amplicon sequence reporting format (https://ess-dive.gitbook.io/amplicon-sequencing-reporting-format/instructions). The Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR-MS) dataset consists of processed files containing presence absence data of molecular formulae and molecular characterization of FTICR resolved peaks. The Nuclear Magnetic Resonance (NMR) dataset contains files relevant to NMR spectra and peaks. A sample key file and a sample metadata file is included for the FTICR/NMR and 16S dataset respectively.

1000-day drought↗