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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Mapping the Iron Oxidation State in Martian Meteorites

Several types of Martian igneous meteorites have been identified: clinopyroxenites (nakhlites), basaltic shergottites, peridotitic shergottites, dunites (chassignites) and orthopyroxenites [1,2]. In order to constrain the heterogeneity of the Martian mantle and crust, and their evolution through time, numerous studies have been performed on the iron oxidation state of these meteorites [3,4,5,6,7,8,9]. The calculated fO2 values all lie within the FMQ-5 to FMQ+0.5 range (FMQ representing the Fayalite = Magnetite + Quartz buffer); however, discrepancies appear between the various studies, which are either attributed to the choice of the minerals/melts used, or to the precision of the analytical/calculation method. The redox record in volcanic samples is primarily related to the oxidation state in the mantle source(s). However, it is also influenced by several deep processes: melting, crystallization, magma mixing [10], assimilation and degassing [11]. In addition, the oxidation state in Martian meteorites is potentially affected by several surface processes: assimilation of sediment/ crust during lava flowing at Mars' surface, low temperature micro-crystallization [10], weathering at the surface of Mars and low temperature reequilibration, impact processes (i.e. high pressure phase transitions, mechanical mixing, shock degassing and melting), space weathering, and weathering on Earth (at atmospheric conditions different from Mars). Decoding the redox record of Martian meteorites, therefore, requires large-scale quantitative analysis methods, as well as a perfect understanding of oxidation processes.

Martin, A. M.↗
DOE OSTI2024

Solar Farm’s Microclimates Effects: Predicting Abundance and Visiting Frequency of Pollinators

The solar farm is garnering attention for its contribution to ecosystem services, particularly in supporting pollinators. Although numerous studies have focused on the distinct microclimates of solar farms, there has been limited effort to validate and model the impact of these conditions on insects [1]. To effectively evaluate and leverage the ecosystem services from solar farms in policymaking, understanding how insects react to microclimate variations in diverse designs and management methods is essential. This study aims to validate and model the impact of temperature and shade at solar farms on pollinator populations and their frequency of pollination as well as compare the potential for increased pollination under different types of panels within a solar grazing setup.

Chung, Hyun Yong↗
DOE OSTI2024

Data Efficiency Assessment of Generative Adversarial Networks for Critical Heat Flux Synthetic Data Generation

This study investigates the application of generative artificial intelligence techniques, particularly conditional generative adversarial networks (cGAN), in real-world engineering contexts, with a specific focus on synthetic data generation for critical heat flux (CHF). Utilizing a dataset comprising more than 20,000 real experimental CHF measurements, we conduct a series of experiments to examine cGAN’s behavior. These experiments encompass varying sizes of the training dataset, training cGAN on data from diverse experimental sources to generate new data on unseen experimental setups, and assessing the impact of excluding various input features on cGAN’s data generation accuracy. Our findings underscore the pronounced data dependency of cGAN for reliable performance, with decreased efficacy observed with smaller training dataset sizes. Notably, cGAN exhibits varying performance when trained on data from different experiments, with superior predictive capabilities observed for certain experiment sources compared to others. For instance, when cGAN was trained on data from Smolin et al.’s experiments or Zenkevich et al., it exhibited relatively good performance in generating the data from Becker et al., Kirillov et al., and Alekseev et al. experiments. In contrast, when trained with Alekseev et al.’s data and tasked with generating other experimental setups, cGAN showed notably poor performance. In both scenarios, cGAN’s performance was inferior compared to training on samples from all experiments concurrently. A feature importance analysis highlights the significant influence of parameters such as mass flux and heated length on accurate CHF generation, while other parameters like diameter and pressure have less impact. Inlet temperature is identified as a moderating factor by cGAN.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Importance of the Heat Treatment Scheme on Self-Reducing Reactive Silver Inks

Self-reducing reactive silver inks can print high-quality silver at reasonable temperatures. While numerous studies have explored the impact of processing temperature on electrical properties, the role of the heat treatment scheme has not yet been studied. Common heat treatment schemes include printing and drying inks at room temperature before heat treatment, performing heat treatments while the inks are still wet, and directly printing the inks onto heated substrates. Each scheme generates distinct heat transfer and mass transport kinetics that can affect the silver morphology and electrical properties. However, to date, the impact of different schemes has not been systematically investigated. To address this knowledge gap, this work investigates how different heat treatment schemes impact metal formation, sintering, and the resultant electrical properties of printed self-reducing reactive silver inks. Heat treatment on room-temperature dried inks and wet inks, with top-down (oven) and bottom-up (hot plate) heating sources, were compared. Inks dried at room temperature resulted in extremely porous films that required high heat treatment temperatures (>100 °C) for silver densification. However, these dried films could only densify locally, and their high initial porosities resulted in voids and high resistances (~0.6 Ω mm –1 ) even after heat treatments above 300 °C. Inks that were wet during heat treatment showed moderate improvements in electrical properties with resistances on the order of 0.4 Ω mm –1 at heat treatments of 250 °C. Printing reactive inks directly onto heated substrates yielded the best low-temperature results, with 0.46 Ω mm –1 (5.5 × bulk silver) line resistances achieved at only 90 °C. Overall, this work’s experimental results provide detailed insights into why printing onto a heated substrate results in superior electrical performance compared to more common heat treatment schemes. Additionally, controlling where the precipitation reaction occurs is critical to controlling the film morphology and properties. As a result, this work shows that even an ammonia-based silver reactive ink can achieve good, low-temperature electrical properties with the proper heat treatment scheme.

14 SOLAR ENERGY↗
DOE OSTI2023

Elucidating the Effects of Temperature on Nonaqueous Redox Flow Cell Cycling Performance

The impact of cell temperature is a relatively underexplored area within the burgeoning field of nonaqueous redox flow batteries (NAqRFBs). Here, we investigate the effect of elevated temperature on the performance of nonaqueous redox electrolytes and associated flow cells. Using a model compound, N-(2-(2-methoxyethoxy)-ethyl)phenothiazine (MEEPT), in a propylene-carbonate-based electrolyte, we experimentally measure the temperature dependence of relevant physicochemical properties (i.e., electrolyte conductivity, viscosity, diffusivity) and electrochemical characteristics (i.e., chemical and electrochemical reversibility) across a temperature range of 30 °C to 70 °C. We then perform flow cell studies, finding that while ohmic and mass transport resistances decrease significantly with increases in temperature for the MEEPT/MEEPT +· redox couple, accessible electrolyte capacity gradually reduces at temperatures > 50 °C. Ex-situ, post-test characterization using microelectrode voltammetry suggests that this capacity fade is due to instability of the MEEPT radical cation. Finally, using MEEPT as a posolyte and a model viologen negolyte (bis(2-(2-methoxyethoxy)ethyl)viologen), we assemble a full cell and perform polarization analyses, observing a 2× increase in the peak power density when the operating temperature is increased from 30 °C to 70 °C. Broadly, this work highlights opportunities for systematic engineering of nonaqueous electrolytes and flow cells for higher power operation at elevated temperatures.

Electrochemistry↗
DOE OSTI2021

BETO 2021 Peer Review - FCIC Task 6: High Temperature Conversion

The impacts of feedstock variability on pyrolysis processes are significant but poorly defined. Current engineering designs are based on empirical guidelines, useful only over a narrow range of feedstock properties. The objectives of this project are to (1) Develop science-based knowledge of how feedstock attributes and operational parameters impact pyrolysis process reliability and product quality; and (2) Build an experimental and computational toolset that predicts these outcomes, enabling processes to optimize reliability and product quality. Biomass is a complex feedstock. Controlling for and testing the effects of individual attributes is very challenging. This project couples multiscale experimentation and modeling to accurately capture the fundamental physics and chemistry of biomass flow and conversion behavior in feeding and pyrolysis reactor operations. Our focus is on pine residue attributes – anatomical fraction (bark, needles, wood), particle morphology (size/shape distribution, density, porosity), and chemical composition (extractives, biopolymers, alkali metals) – that impact product quality for downstream catalytic upgrading. Because detailed pyrolysis product characterization is limited, cutting-edge analytical techniques are being developed to reveal impactful product attributes. The tools and knowledge developed here will enable integrated pyrolysis-based processes that are more robust, flexible, and market-responsive with respect to feedstock variability.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2020

Impacts of Water Clarity Variability on Temperature and Biogeochemistry in the Chesapeake Bay

Estuarine water clarity depends on the concentrations of aquatic constituents, such as colored dissolved organic matter, phytoplankton, inorganic suspended solids, and detritus, which are influenced by variations in riverine inputs. These constituents directly affect temperature because when water is opaque, sunlight heats a shallower layer of the water compared to when it is clear. Despite the importance of accurately predicting temperature variability, many numerical modeling studies do not adequately account for this key process. In this study, we quantify the effect of water clarity on heating by comparing two simulations of a hydrodynamic-biogeochemical model of the Chesapeake Bay for the years 2001–2005, in which (1) water clarity is constant in space and time for the computation of solar heating, compared to (2) a simulation where water clarity varies with modeled concentrations of light-attenuating materials. In the variable water clarity simulation, the water is more opaque, particularly in the northern region of the Bay. This decrease in water clarity reduces the total heat, phytoplankton, and nitrate throughout the Bay. During the spring and summer months, surface temperatures in the northern Bay are warmer by 0.1 °C and bottom temperatures are colder by 0.2 °C in the variable light attenuation simulation. Warmer surface temperatures encourage phytoplankton growth and nutrient uptake near the head of the Bay, and fewer nutrients are transported downstream. These impacts are greater during higher river flow years, when differences in temperature, nutrients, phytoplankton, and zooplankton extend further seaward compared to other years. This study demonstrates the consequences of utilizing different light calculations for estuarine heating and biogeochemistry.

water clarity↗
NASA NTRS1989

The impact of summer rainfall on the temperature gradient along the United States-Mexico border

The international border running through the Sonoran Desert in southern Arizona and northern Sonora is marked by a sharp discontinuity in albedo and grass cover. The observed differences in surface properties are a result of long-term, severe overgrazing of the Mexican lands. Recently, investigators have shown the Mexican side of the border to have higher surface and air temperatures when compared to adjacent areas in the United State. The differences in temperatures appear to be more associated with differential evapotranspiration rates than with albedo changes along the border. In this study, the impact of summer rainfall on the observed seasonal and daily gradient in maximum temperature is examined. On a seasonal time scale, the temperature gradient increases with higher moisture levels, probably due to a vegetative response on the United States' side of the border; at the daily level, the gradient in maximum temperature decreases after a rain event as evaporation rates equalize between the countries. The results suggest that temperature differences between vegetated and overgrazed landscapes in arid areas are highly dependent upon the amount of moisture available for evapotranspiration.

Balling, Robert C., Jr.↗
DOE OSTI2022

Long-term impact of light- and elevated temperature-induced degradation on photovoltaic arrays

Low levelized cost of electricity (LCOE) has been identified as critical for widespread adoption of photovoltaics (PV) without subsidies. Maintaining decades-long high-energy production is often an under-recognized opportunity in meeting cost goals because component lifetimes are not fully quantified at the time of manufacture. Whereas certain standardized tests minimize risk of early failure, there is little guidance to quantitatively predict degradation (or lack thereof) over decades, based on accelerated tests. In this article, we move toward bridging the understanding between indoor accelerated tests and outdoor performance data, with the goal of predicting energy yield with enough accuracy to inform financial decisions. Light- and elevated temperature-induced degradation (LETID) in p-type Si modules is analyzed in terms of impact on long-term module performance and thus LCOE. A method to predict the progression of LETID, using fixed kinetic constants and a numerical solution to the basic reaction rate equations, is detailed. Predictions are compared against both published data and that new to this study. These data include both indoor accelerated tests and fielded modules. We use the results in financial models to derive LCOE of modules in different climates with varying amounts of LETID, including uncertainty. Cost models based on the predictions indicate that LETID has a significant and climate-dependent impact on LCOE. Finally, we show that - even given the uncertainties identified in the study - these financial calculations can provide useful guidance to quantify risk based on accelerated test results. The analysis serves as an example of developing a predictive approach to PV reliability using physics of failure.

14 SOLAR ENERGY↗
NASA NTRS1987

A VAS-numerical model impact study using the Gal-Chen variational approach

A numerical study based on the use of a variational assimilation technique of Gal-Chen (1983, 1986) was conducted to assess the impact of incorporating temperature data from the VISSR Atmospheric Sounder (VAS) into a regional-scale numerical model. A comparison with the results of a control forecast using only conventional data indicated that the assimilation technique successfully combines actual VAS temperature observations with the dynamically balanced model fields without destabilizing the model during the assimilation cycle. Moreover, increasing the temporal frequency of VAS temperature insertions during the assimilation cycle was shown to enhance the impact on the model forecast through successively longer forecast periods. The incorporation of a nudging technique, whereby the model temperature field is constrained toward the VAS 'updated' values during the assimilation cycle, further enhances the impact of the VAS temperature data.

Aune, Robert M.↗
DOE OSTI2021

The effect of substrate temperature on the critical velocity in microparticle impact bonding

A number of nascent coating and micromanufacturing processes involve particles sprayed at a high velocity, which impact a substrate, deform, and adhere. Successful bonding between the particles and the substrate requires impact velocities higher than the so-called critical adhesion velocity. This critical velocity is influenced by the temperature of the substrate, a variable that we isolate in this work by conducting single-particle impacts on a variable-temperature substrate for three systems (Al–Al, Sn–Sn, and Ti–Ti) with particles individually selected within a narrow size distribution. Our results quantitatively connect the increase in substrate temperature to a significant lowering of the critical velocity, which we attribute to the lower dynamic strength of the thermally softened substrate. The data are generally consistent with expectations for bonding being controlled by a hydrodynamic process of jetting upon impact.

36 MATERIALS SCIENCE↗
DOE OSTI2026

MassIVE MSV000100641 - Multilayered regulation by RNA thermometers enables precise control of Cas9 expression in E. coli: Cas9-based genome editing technologies can rapidly generate mutations to probe a diverse array of mutant genotypes. However, aberrant Cas9 nuclease translation and activity can occur despite the use of inducible promoters to control expression, leading to extensive cell death. This background killing caused by promoter leakiness severely limits the application of Cas9 for generating mutant libraries because of the potential for population skew. We demonstrate the utility of temperature sensitive RNA elements as a layer of post-transcriptional regulation to reduce the impact of promoter leak. We observe significant temperature-dependent increases in cell survival when certain RNA thermometers (RNATs) are placed upstream of the cas9 coding sequence. We also show that the most highly repressing RNAT, hsp17rep, significantly reduces population skew with a library of characterized guide RNAs in Escherichia coli. This strategy should be applicable to all bacterial Cas9-based methods and technologies.

Explore the source record for details and available documents.

Alexander, William G. [Oak Ridge National Laborato↗
DOE OSTI2026

Higher Efficiency, Demand Flexible Refrigerator with On-Demand Micro-Vibrational De-icing Technology

Refrigerator technology has advanced significantly over the last couple of decades. Today’s refrigerators use only about 25% of the energy that was required to power models built in 1975. Even as they continually improve efficiency to meet standards, refrigerators have increased in size by almost 20%, added energy-consuming features such as through-the-door ice, and provide more benefits than ever before. However, a few challenges and technology gaps are preventing further improvement of the demand responsiveness and efficiency of the refrigerators. One of the major technology gaps in existing refrigerators is their outdated de-icing process. When the evaporator generates frost, an old-fashioned resistive heating element melts the ice. Most refrigerators have a timed defrost cycle, rather than an active system that could monitor the state of the frost. In these systems, not only is the precious electricity used at its least efficient form of conversion (direct conversion of electricity to heat), but also all the latent heat associated with the ice is wasted during the melting process. On top of that, the refrigerator needs to work harder to pull the temperature down after defrosting, and, last but not least, the food quality is severely impacted by the temperature swings during the defrost cycle. According to a study, the EU alone wastes 89 million tons of food in the supply chain every year. Any temperature swing during defrosting (about 6F according to Emerson for low-temperature cases) can negatively impact the shelf life of meat and other products for multiple days. All these issues can happen during the peak demand time of the electric grid. Unlike the conventional systems, the proposed novel advanced micro-vibrational deicing process uses no heat for defrosting. Instead, it uses the micro vibrations generated by a piezoelectric or vibration-generating module to mechanically break ice from the heat exchanger almost instantaneously. The project titled “Higher Efficiency, Demand Flexible Refrigerator with On-Demand Micro-Vibrational De-icing Technology, performed by Ultrasonic Technology Solutions, LLC (UTS) of Knoxville, TN, in collaboration with Emerson (now Copeland), represents the final phase of a multi-year effort funded under the U.S. Department of Energy’s Building Technologies Office (BTO) BENEFIT FOA 2020. Initiated on October 1, 2021, and completed after a nine-month no-cost extension ending September 30, 2025, this project aimed to develop and validate a novel micro-vibrational mechanical defrosting system, achieving more than 25% improvement in defrosting energy efficiency over conventional baseline defrosting technologies. Over sixteen quarters, the project advanced from fundamental ice-mechanical characterization and prototype development to full-scale system integration and validation. Initial efforts established project management infrastructure and characterized ice adhesion properties, followed by the design and fabrication of early aluminum-based prototypes for resonance frequency testing. Subsequent quarters saw rapid technical progression, including the identification of optimal piezoelectric and motor-based vibration mechanisms, the demonstration of effective de-icing over 6x6-inch aluminum surfaces. The team achieved its Go/No-Go milestone by exceeding the 25% energy-efficiency improvement target—reaching up to 3,340% under optimized conditions—and later confirmed that motor-driven systems offered superior performance and energy efficiency compared to piezoelectric alternatives. Continued refinement led to the development of amplifier systems on printed circuit boards, improved control and instrumentation hardware, and integration into full-scale heat exchanger (HX) prototypes at both UTS and Copeland facilities. Multiple vibration-mounting studies and frost-growth experiments guided mechanical optimization and noise-mitigation strategies, achieving a 17.5 dB reduction in sound pressure level and verifying robust mechanical performance. Advanced analyses, including modal and harmonic simulations, established a quantitative understanding of vibrational behavior and de-icing efficiency across >1000 cm² systems. The final project phase successfully demonstrated scalable integration within reach-in and chest freezer prototypes, confirmed >25% efficiency improvements in large-area systems, and completed a comprehensive business model and scale-up strategy identifying electric defrost systems as the primary beachhead market. The culmination of this DOE-supported effort establishes micro-vibrational defrosting as a viable, high-efficiency, low-noise, and demand-flexible de-icing technology, paving the way for commercial deployment and broader application in next-generation refrigeration systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2009

Impact of Lake Okeechobee Sea Surface Temperatures on Numerical Predictions of Summertime Convective Systems over South Florida

The NASA Short-term Prediction Research and Transition (SPoRT) Center, the Florida Institute of Technology, and the NOAA/NWS Weather Forecast Office at Miami, FL (MFL) are collaborating on a project to investigate the impact of using high-resolution, 2-km Moderate Resolution Imaging Spectroradiometer (MODIS) sea surface temperature (SST) composites within the Weather Research and Forecasting (WRF) prediction system. The NWS MFL is currently running WRF in real-time to support daily forecast operations, using the National Centers for Environmental Prediction Nonhydrostatic Mesoscale Model dynamical core within the NWS Science and Training Resource Center's Environmental Modeling System (EMS) software. Twenty-seven hour forecasts are run daily initialized at 0300, 0900, 1500, and 2100 UTC on a domain with 4-km grid spacing covering the southern half of Florida and adjacent waters of the Gulf of Mexico and Atlantic Ocean. The SSTs are initialized with the NCEP Real-Time Global (RTG) analyses at 1/12deg resolution. The project objective is to determine whether more accurate specification of the lower-boundary forcing over water using the MODIS SST composites within the 4-km WRF runs will result in improved sea fluxes and hence, more accurate e\~olutiono f coastal mesoscale circulations and the associated sensible weather elements. SPoRT conducted parallel WRF EMS runs from February to August 2007 identical to the operational runs at NWS MFL except for the use of MODIS SST composites in place of the RTG product as the initial and boundary conditions over water. During the course of this evaluation, an intriguing case was examined from 6 May 2007, in which lake breezes and convection around Lake Okeechobee evolved quite differently when using the high-resolution SPoRT MODIS SST composites versus the lower-resolution RTG SSTs. This paper will analyze the differences in the 6 May simulations, as well as examine other cases from the summer 2007 in which the WRF-simulated Lake Okeechobee breezes evolved differently due to the SST initialization. The effects on wind fields and precipitation systems will be emphasized, including validation against surface mesonet observations and Stage IV precipitation grids.

Case, Jonathan L.↗
NASA NTRS2017

Classifying Multi-Model Wheat Yield Impact Response Surfaces Showing Sensitivity to Temperature and Precipitation Change

Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (minus 2 to plus 9 degrees Centigrade) and precipitation (minus 50 to plus 50 percent). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses. The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern. The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description. Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the application of the EDA and SDA approaches revealed their capability to distinguish: (i) stronger yield responses to precipitation for winter wheat than spring wheat; (ii) differing strengths of response to climate changes for years with anomalous weather conditions compared to period-average conditions; (iii) the influence of site conditions on yield patterns; (iv) similarities in IRS patterns among models with related genealogy; (v) similarities in IRS patterns for models with simpler process descriptions of root growth and water uptake compared to those with more complex descriptions; and (vi) a closer correspondence of IRS patterns in models using partitioning schemes to represent yield formation than in those using a harvest index. Such results can inform future crop modelling studies that seek to exploit the diversity of multi-model ensembles, by distinguishing ensemble members that span a wide range of responses as well as those that display implausible behaviour or strong mutual similarities.

Classification; Climate change; Crop model; Ensemb↗
DOE OSTI2025

Toward an improved nonlocal thermodynamic equilibrium model for more predictive simulations of ignition scale hohlraums

Recently, nonlocal thermodynamic equilibrium (NLTE) modeling has been identified as the primary reason for discrepant predictions of the peak neutron production time in indirectly driven inertial confinement fusion (ICF) platforms. It has also been observed that predictions of collisional excitation rates differ by as much as 50% from measurements. Theoretical uncertainties in dielectronic recombination rates have also been posited as possibly contributing to errors in NLTE predictions. This work examines the impact of multipliers on collisional excitation and dielectronic recombination rates on simulations of a directly driven gold sphere and an indirect drive ICF implosion. It is found that multipliers on the collisional excitation rates have a strong impact on radiant intensity and electron temperature and a weaker impact on ionization state, whereas multipliers on dielectronic recombinations rates strongly impact ionization state with a smaller impact on radiant intensity and electron temperature. A self-consistent NLTE model which places multipliers on differing transitions, as motivated by experimental measurements and more detailed atomic physics predictions, improves agreement but does not completely eliminate discrepancies with measurements of the radiant intensity within the 2–4 keV spectral range.

Farmer, W. A. [Lawrence Livermore National Laborat↗