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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

US general aviation: The ingredients for a renaissance. A vision and technology strategy for US industry, NASA, FAA, universities

General aviation today is a vital component in the nation's air transportation system. It is threatened for survival but has enormous potential for expansion in utility and use. This potential for expansion is fueled by new satellite navigation and communication systems, small computers, flat panel displays, and advanced aerodynamics, materials and manufacturing methods, and propulsion technologies which create opportunities for new levels of environmental and economic acceptability. Expanded general aviation utility and use could have a large impact on the nation's jobs, commerce, industry, airspace capacity, trade balance, and quality of life. This paper presents, in viewgraph form, a general overview of U.S. general aviation. Topics covered include general aviation shipment and billings; airport and general aviation infrastructure; cockpit, airplane, and airspace technologies; market demand; air traffic operations and aviation accidents; fuel efficiency comparisons; and general aviation goals and strategy.

Holmes, Bruce↗
DOE OSTI2023

Domain Adaptive Graph Neural Networks for Constraining Cosmological Parameters Across Multiple Data Sets

Deep learning models have been shown to outperform methods that rely on summary statistics, like the power spectrum, in extracting information from complex cosmological data sets. However, due to differences in the subgrid physics implementation and numerical approximations across different simulation suites, models trained on data from one cosmological simulation show a drop in performance when tested on another. Similarly, models trained on any of the simulations would also likely experience a drop in performance when applied to observational data. Training on data from two different suites of the CAMELS hydrodynamic cosmological simulations, we examine the generalization capabilities of Domain Adaptive Graph Neural Networks (DA-GNNs). By utilizing GNNs, we capitalize on their capacity to capture structured scale-free cosmological information from galaxy distributions. Moreover, by including unsupervised domain adaptation via Maximum Mean Discrepancy (MMD), we enable our models to extract domain-invariant features. We demonstrate that DA-GNN achieves higher accuracy and robustness on cross-dataset tasks. Using data visualizations, we show the effects of domain adaptation on proper latent space data alignment. This shows that DA-GNNs are a promising method for extracting domain-independent cosmological information, a vital step toward robust deep learning for real cosmic survey data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Nitrogen-doped graphene-wrapped Cu 2 S as a superior anode in sodium-ion batteries

Sodium-ion batteries (SIBs) have been attracting an ever-growing research interest, mainly ascribed to their cost-effectiveness. However, SIBs have been significantly hindered by lack of a suitable anode. Herein, an exceptional Cu 2 S-based composite anode is developed via a facile ball-milling method, in which Cu 2 S particles are wrapped by nitrogen-doped graphene sheets (Cu 2 S@NG). This Cu 2 S@NG composite anode enables extremely long cycling life, ultra-stable cyclability with high capacity, and excellent rate capability. The superior performance of the Cu 2 S@NG composite is owing to its intriguing core-shell structure and the exceptional properties of both the Cu 2 S and NG. In this study, it is found that the NG shell yields multiple merits in improving the performance of Cu 2 S: (i) mitigating the loss of active materials, (ii) constituting a stable interface, (iii) providing improved electrical conductivity and good ionic transfer, and (iv) enhancing mechanical integrity. Additionally, the vital effects of different voltage windows and a surface coating via atomic layer deposition on further enhancing performance are clarified. Significantly, the electrochemical mechanism of Cu 2 S during sodiation/desodiation is unveiled using advanced synchrotron-based in-situ X-ray diffraction and X-ray adsorption spectroscopy. This work represents a great advance in seeking high-performance anodes in SIBs.

25 ENERGY STORAGE↗
DOE OSTI2023

Unrealized Critical Lanthanide Extraction from Sea Algae Mining (UNCLE SAM): Domestic production of critical minerals from seawater

The UNCLE-SAM project, under the Biotechnologies to Ensure a Robust Supply of Critical Materials for Clean Energy program, examined the biomining applications of seaweeds for sustainable, domestic production of critical mineral feedstocks. The ocean is a vast reserve of mineralogical wealth including rare earth elements (REEs) and platinum group metal (PGMs). These elements, categorized as “critical minerals”, are used in telecommunication devices, lasers, LED lighting, turbine generators, electric car motors, jet engine alloys, and many other applications. These critical elements are increasingly vital to a thriving, efficient and sustainable society. However, only a few countries in the global market currently produce and export REEs, leading to potential geopolitical supply disruptions. Marine macroalgae, often referred to as seaweeds, bioconcentrate critical minerals from seawater, including REEs and PGMs. Marine algae cultivation can generate a significant amount of biomass with minimal freshwater, fertilizer, and land requirements. In summary, the UNCLE-SAM project successfully evaluated the technological feasibility for marine macroalgal cultivation as a feedstock for critical minerals, explored the biological capacity of different seaweeds to provide economically relevant domestic mineral production, assessed processing techniques for thermal co-conversion of seaweeds into renewable fuel and mineral feedstocks, and executed techno-economic and lifecycle assessments for identifying the most critical gaps in our current understanding to move the technology into commercially relevant deployment. Further development of this technology could transform the bioproduct and REE mining industries and catalyze the development of a more sustainable future.

58 GEOSCIENCES↗
DOE OSTI2023

UNrealized Critical Lanthanide Extraction from Sea Algae Mining (UNCLE SAM)

The UNCLE-SAM project, under the Biotechnologies to Ensure a Robust Supply of Critical Materials for Clean Energy program, examined the biomining applications of seaweeds for sustainable, domestic production of critical mineral feedstocks. The ocean is a vast reserve of mineralogical wealth including rare earth elements (REEs) and platinum group metal (PGMs). These elements, categorized as “critical minerals”, are used in telecommunication devices, lasers, LED lighting, turbine generators, electric car motors, jet engine alloys, and many other applications. These critical elements are increasingly vital to a thriving, efficient and sustainable society. However, only a few countries in the global market currently produce and export REEs, leading to potential geopolitical supply disruptions. Marine macroalgae, often referred to as seaweeds, bioconcentrate critical minerals from seawater, including REEs and PGMs. Marine algae cultivation can generate a significant amount of biomass with minimal freshwater, fertilizer, and land requirements. In summary, the UNCLE-SAM project successfully evaluated the technological feasibility for marine macroalgal cultivation as a feedstock for critical minerals, explored the biological capacity of different seaweeds to provide economically relevant domestic mineral production, assessed processing techniques for thermal co-conversion of seaweeds into renewable fuel and mineral feedstocks, and executed techno-economic and lifecycle assessments for identifying the most critical gaps in our current understanding to move the technology into commercially relevant deployment. Further development of this technology could transform the bioproduct and REE mining industries and catalyze the development of a more sustainable future.

09 BIOMASS FUELS↗
DOE OSTI2020

Investigation of Exciton Delocalization and Exciton Coherence in Chromophores and Acoustic Nanostructures

Quantum materials have a rich potential for providing transformative energy technologies ranging from new energy efficient computation paradigms to lossless energy transport across the national grid. The field of quantum materials, however, is still in its infancy with many quantum materials systems requiring cyrogenic temperatures to be viable. Few viable, room-temperature quantum materials systems have been identified; therefore, identifying additional such systems is vitally important. This state of the science combined with the low number of potential systems that exhibit room-temperature quantum character make this field of research fertile ground for EPSCoR states (states eligible for funding under the Established Program to Stimulate Competitive Research program) such as Idaho to compete on a national level. As a result, this project proposed and accomplished two main goals in advancing two room-temperature quantum materials systems: (1) advance the science for demonstrating room temperature exciton delocalization in two excitonic systems and (2) build capacity and expertise in developing and understanding quantum materials at both Boise State University and Idaho National Laboratory. The work at Boise State focused mainly on the use of nucleic acid self-assembled chromophore molecule networks that offer a much easier and mature approach to construct aggregates of chromophores that can be tailored to specific two-dimensional and three-dimensional geometries and allow exciton manipulation towards achieving room-temperature quantum computation. A second complementary effort performed at Boise State and INL focused on confining excitons on quantum length scales using coherent surface acoustic phonons

36 MATERIALS SCIENCE↗
DOE OSTI2023

On-Chip Batteries as Distributed Energy Sources in Heterogeneous 2.5D/3D Integrated Circuits

Energy efficiency in digital systems faces challenges due to the constraints imposed by small-scale transistors. Moreover, the growing demand for portable consumer electronics necessitates the use of compact energy sources. To address these challenges, heterogeneous 3D IC technology has emerged as a promising solution for the former. Regarding the latter, we propose the concept of distributed batteries within a heterogeneous 3D IC. This approach involves utilizing multiple smaller batteries with different specifications among different modules of 3D ICs. This approach optimizes performance and overcomes limitations associated with both 3D ICs and conventional power delivery methods. Distributed batteries play a vital role in effectively managing the heat generated by energy sources and modules within a 3D IC. Furthermore, they contribute to achieving a uniform distribution of heat throughout the entire structure, which ultimately ensures the optimal performance of the batteries and modules. The simulation results indicate a 40 percent enhancement in achieving a more even distribution of generated heat. Additionally, the proposed distributed battery techniques improve power delivery, enhance reliability, and enable optimized voltage regulation while improving efficiency. In addition to the primary benefits, alternative configurations of the proposed approach can offer extra energy storage capacity and act as efficient electromagnetic shields, resulting in an impressive reduction of external electromagnetic noises by 60 dB.

47 OTHER INSTRUMENTATION↗
NASA NTRS2010

Calibration Modeling Methodology to Optimize Performance for Low Range Applications

Calibration is a vital process in characterizing the performance of an instrument in an application environment and seeks to obtain acceptable accuracy over the entire design range. Often, project requirements specify a maximum total measurement uncertainty, expressed as a percent of full-scale. However in some applications, we seek to obtain enhanced performance at the low range, therefore expressing the accuracy as a percent of reading should be considered as a modeling strategy. For example, it is common to desire to use a force balance in multiple facilities or regimes, often well below its designed full-scale capacity. This paper presents a general statistical methodology for optimizing calibration mathematical models based on a percent of reading accuracy requirement, which has broad application in all types of transducer applications where low range performance is required. A case study illustrates the proposed methodology for the Mars Entry Atmospheric Data System that employs seven strain-gage based pressure transducers mounted on the heatshield of the Mars Science Laboratory mission.

McCollum, Raymond A.↗
DOE OSTI2025

Improving the prediction of daily reservoir releases over the CONUS using conditioned LSTM

Reservoirs play a vital role in regulating streamflow timing and variability for hydroelectricity, flood control, water supply, irrigation, and recreation. Despite their importance, many reservoirs lack comprehensive operational guidelines, making their management complex due to conflicting operational objectives. Hence traditional policy-based reservoir models often fail to capture real-world conditions accurately and they depend on perfect streamflow predictions, which are not always available. In contrast, data-driven models like Long Short-Term Memory (LSTM) networks offer a robust alternative. This study introduces an approach that integrates reservoir characteristics—such as main use, climate, and maximum capacity—into the LSTM model to enhance reservoir release predictions. Using data from nearly 200 reservoirs in the contiguous United States (CONUS), our conditioned LSTM model (LSTM_cond) was compared with both the vanila LSTM and a traditional policy-based approach. Furthermore, our results show that while both LSTM_cond and LSTM perfoms better than the policy-based approach, LSTM_cond consistently outperforms LSTM for hydroelectric, water supply, irrigation, and recreation reservoirs. The KGE median values for LSTM_cond for out-sample reservoirs are 0.764, 0.565, 0.821, and 0.779, respectively, for the aforementioned reservoir types, which are consistently higher that the corresponding KGE values of 0.737, 0.413, 0.775, and 0.713 of LSTM, demonstrating its advantages in improving generalizability.

CONUS↗
NASA NTRS1998

Technology Assessment of High Capacity Data Storage Systems: Can We Avoid a Data Survivability Crisis?

This technology assessment of long-term high capacity data storage systems identifies an emerging crisis of severe proportions related to preserving important historical data in science, healthcare, manufacturing, finance and other fields. For the last 50 years, the information revolution, which has engulfed all major institutions of modem society, centered itself on data-their collection, storage, retrieval, transmission, analysis and presentation. The transformation of long term historical data records into information concepts, according to Drucker, is the next stage in this revolution towards building the new information based scientific and business foundations. For this to occur, data survivability, reliability and evolvability of long term storage media and systems pose formidable technological challenges. Unlike the Y2K problem, where the clock is ticking and a crisis is set to go off at a specific time, large capacity data storage repositories face a crisis similar to the social security system in that the seriousness of the problem emerges after a decade or two. The essence of the storage crisis is as follows: since it could take a decade to migrate a peta-byte of data to a new media for preservation, and the life expectancy of the storage media itself is only a decade, then it may not be possible to complete the transfer before an irrecoverable data loss occurs. Over the last two decades, a number of anecdotal crises have occurred where vital scientific and business data were lost or would have been lost if not for major expenditures of resources and funds to save this data, much like what is happening today to solve the Y2K problem. A pr-ime example was the joint NASA/NSF/NOAA effort to rescue eight years worth of TOVS/AVHRR data from an obsolete system, which otherwise would have not resulted in the valuable 20-year long satellite record of global warming. Current storage systems solutions to long-term data survivability rest on scalable architectures having parallel paths for data migration.

Halem, M.↗
DOE OSTI2024

Mitigating Calendar Aging in Si-NMC Batteries with Advanced Dual-Salt Glyme Electrolytes

In addressing the critical challenge of calendar aging in silicon (Si)-based lithium-ion batteries, this study introduces a groundbreaking strategy utilizing glyme-type dual-salt electrolytes (lithium bis(trifluoromethanesulfonyl)imide [LiTFSI] and lithium difluoro(oxalato)borate [LiDFOB]). These electrolytes are demonstrated to significantly mitigate parasitic reactions and capacity loss in Si-NMC (lithium nickel manganese cobalt oxide) full cells, especially when compared with traditional carbonate-based electrolytes. Further, our exhaustive mechanistic analysis reveals that such electrolytes not only preserve the integrity of the Si anode but also improve the cathode/electrolyte interphases (CEI) through the formation of a conformal coating on the high-voltage cathode surface. This dual-salt approach, enhanced by the addition of a phosphate additive, effectively decelerates calendar aging, marking a substantial advance in the quest for durable and reliable Si-based energy storage technologies. The findings underscore the vital role of electrolyte composition in extending the calendar life of Si batteries, offering an alternative avenue toward maximizing the performance and longevity of next-generation Li-Si batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Bridging the Gap between Cosmological Simulations with Graph Neural Networks and Domain Adaptation

Deep learning models have been shown to outperform methods that rely on summary statistics, like the power spectrum, in extracting information from complex cosmological data sets. However, due to differences in the subgrid physics implementation and numerical approximations across different simulation suites, models trained on data from one cosmological simulation show a drop in performance when tested on another. Similarly, models trained on any of the simulations would also likely experience a drop in performance when applied to observational data. Training on data from two different suites of the CAMELS hydrodynamic cosmological simulations, we examine the generalization capabilities of Domain Adaptive Graph Neural Networks (DA-GNNs). By utilizing GNNs, we capitalize on their capacity to capture structured scale-free cosmological information from galaxy distributions. Moreover, by including unsupervised domain adaptation via Maximum Mean Discrepancy (MMD), we enable our models to extract domain-invariant features. We demonstrate that DA-GNN achieves higher accuracy and robustness on cross dataset tasks (up to 28% better relative error and up to almost an order of magnitude better χ 2 ). Using data visualizations, we show the effects of domain adaptation on proper latent space data alignment. This shows that DA-GNNs are a promising method for extracting domain-independent cosmological information, a vital step toward robust deep learning for real cosmic survey data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Domain Adaptive Graph Neural Networks for Constraining Cosmological Parameters Across Multiple Data Sets

Deep learning models have been shown to outperform methods that rely on summary statistics, like the power spectrum, in extracting information from complex cosmological data sets. However, due to differences in the subgrid physics implementation and numerical approximations across different simulation suites, models trained on data from one cosmological simulation show a drop in performance when tested on another. Similarly, models trained on any of the simulations would also likely experience a drop in performance when applied to observational data. Training on data from two different suites of the CAMELS hydrodynamic cosmological simulations, we examine the generalization capabilities of Domain Adaptive Graph Neural Networks (DA-GNNs). By utilizing GNNs, we capitalize on their capacity to capture structured scale-free cosmological information from galaxy distributions. Moreover, by including unsupervised domain adaptation via Maximum Mean Discrepancy (MMD), we enable our models to extract domain-invariant features. We demonstrate that DA-GNN achieves higher accuracy and robustness on cross-dataset tasks (up to $28\%$ better relative error and up to almost an order of magnitude better $\chi^2$). Using data visualizations, we show the effects of domain adaptation on proper latent space data alignment. This shows that DA-GNNs are a promising method for extracting domain-independent cosmological information, a vital step toward robust deep learning for real cosmic survey data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Global variations in critical drought thresholds that impact vegetation

ABSTRACT Identifying the thresholds of drought that, if crossed, suppress vegetation functioning is vital for accurate quantification of how land ecosystems respond to climate variability and change. We present a globally applicable framework to identify drought thresholds for vegetation responses to different levels of known soil-moisture deficits using four remotely sensed vegetation proxies spanning 2001–2018. The thresholds identified represent critical inflection points for changing vegetation responses from highly resistant to highly vulnerable in response to drought stress, and as a warning signal for substantial vegetation impacts. Drought thresholds varied geographically, with much lower percentiles of soil-moisture anomalies in vegetated areas covered by more forests, corresponding to a comparably stronger capacity to mitigate soil water deficit stress in forested ecosystems. Generally, those lower thresholds are detected in more humid climates. State-of-the-art land models, however, overestimated thresholds of soil moisture (i.e. overestimating drought impacts), especially in more humid areas with higher forest covers and arid areas with few forest covers. Based on climate model projections, we predict that the risk of vegetation damage will increase by the end of the twenty-first century in some hotspots like East Asia, Europe, Amazon, southern Australia and eastern and southern Africa. Our data-based results will inform projections on future drought impacts on terrestrial ecosystems and provide an effective tool for drought management.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

Development of an Indexing Media Filtration System for Long Duration Space Missions

The effective maintenance of air quality aboard spacecraft cabins will be vital to future human exploration missions. A key component will be the air cleaning filtration system which will need to remove a broad size range of particles derived from multiple biological and material sources. In addition, during surface missions any extraterrestrial planetary dust, including dust generated by near-by ISRU equipment, which is tracked into the habitat will also need to be managed by the filtration system inside the pressurized habitat compartments. An indexing media filter system is being developed to meet the demand for long-duration missions that will result in dramatic increases in filter service life and loading capacity, and will require minimal crew involvement. The filtration system consists of three stages: an inertial impactor stage, an indexing media stage, and a high-efficiency filter stage, packaged in a stacked modular cartridge configuration. Each stage will target a specific range of particle sizes that optimize the filtration and regeneration performance of the system. An 1/8th scale and full-scale prototype of the filter system have been fabricated and have been tested in the laboratory and reduced gravity environments that simulate conditions on spacecrafts, landers and habitats. Results from recent laboratory and reduce-gravity flight tests data will be presented. The features of the new filter system may also benefit other closed systems, such as submarines, and remote location terrestrial installations where servicing and replacement of filter units is not practical.

Filtration↗
DOE OSTI2024

Development of a SnO 2 -based 44 Ti/ 44 Sc generator for medical applications

Towards application of 44 Sc for diagnostic nuclear medicine, a 44 Ti/ 44 Sc generator based on an inorganic resin has been evaluated. Unlike other radionuclide generators used for medical applications, the long-term retention of the parent 44 Ti is vital due to its long half life. In this work, tin dioxide (SnO 2 ), a robust inorganic-based resin, has been synthesized and used as the stationary phase for a 44 Ti/ 44 Sc generator. The sorption behavior of 44 Ti/ 44 Sc was tested on SnO 2 with varying acids, concentrations, and times. Preliminary batch study results showed >88 % 44 Ti retention to the resin at lower acid concentrations (0.05 M HNO 3 and 0.05 M HCl). A pilot generator was evaluated for a year, demonstrating 85.3 ± 2.8 % 44 Sc elution yields and 0.71 ± 0.14 % 44 Ti breakthrough in 5 M HNO 3 . Based on capacity studies, a 7.4 MBq (200 µCi) upscaled generator system was constructed for further evaluation of the SnO 2 resin stability and the efficacy of the eluted 44 Sc for radiolabeling. 44 Sc could be regularly eluted from this generator in 5 M HNO 3 with an overall average radiochemical yield 84.7 ± 9.5 %. Post-elution processing of the 44 Sc with DGA-normal resin removed all 44 Ti present and allowed for high 44 Sc-DOTA labeling yields of 94.2 ± 0.5 %. Overall, SnO 2 has been shown to be a viable material for a 44 Ti/ 44 Sc generator.

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS2017

Lightweight Multifunctional Planetary Probe for Extreme Environment Exploration and Locomotion

The demand to explore new worlds requires the development of advanced technologies that enable landed science on uncertain terrains or in hard to reach locations. As a result, contemporary Entry, Descent, Landing, (EDL) and additional locomotion (EDLL) profiles are becoming increasingly more complex, with the introduction of lifting/guided entries, hazard avoidance on descent, and a plethora of landing techniques including airbags and the skycrane maneuver. The inclusion of each of these subsystems into a mission profile is associated with a substantial mass penalty. This report explores the new all-in-one entry vehicle concept, TANDEM, a new combined EDLL concept, and compares it to the current state of the art EDL systems. The explored system is lightweight and collapsible and provides the capacity for lifting/guided entry, guided descent, hazard avoidance, omnidirectional impact protection and surface locomotion without the aid of any additional subsystems. This Phase I study explored: 1. The capabilities and feasibility of the TANDEM concept as an EDLL vehicle. 2. Extensive impact analysis to ensure mission success in unfavorable landing conditions, and safe landing in Tessera regions. 3. Development of a detailed design for a conceptual mission to Venus. As a result of our work it was shown that: 1. TANDEM provides additional benefits over the Adaptive, Deployable Entry Placement Technology (ADEPT) including guided descent and surface locomotion, while reducing the mass by 38% compared to the ADEPT-VITaL mission. 2. Demonstrated that the design of tensegrity structures, and TANDEM specifically, grows linearly with an increase in velocity, which was previously unknown. 3. Investigation of surface impact revealed a promising results that suggest a properly configured TANDEM vehicle can safely land and preform science in the Tessera regions, which was previously labeled by the Decadal Survey as, largely inaccessible despite its high scientific interest. This work has already resulted in a NASA TM and will be submitted to the Journal of Spacecraft and Rockets.

landing techniques↗
NASA NTRSDate not supplied

Improvements in Ionic Liquid Technology for Carbon Dioxide Removal Applications

Carbon dioxide removal from cabin air continues to be of vital importance for future space missions. Current and proposed approaches have employed solid sorbents, hollow fiber membrane separators, and direct liquid sorbent contactors. Recent developments in ionic liquids have potential to improve performance in all three of these technologies. Efficient encapsulation of ionic liquids by polymeric shell can enable their use in a solid sorbent-like configuration without significant integration intervention to the current space technology. Poly(ionic liquid)-ionic liquid membranes have the potential to cross over the Robeson selectivity-permeability upper bound, and thereby outperform traditional membranes used in hollow fibers. Advances in ionic liquid chemistry enables performance improvements in liquid sorbent contactors owing to the tunable gravimetric CO2 capacity, reaction enthalpy and liquid viscosity. This paper will describe recent work in each of these areas.

Ionic Liquid,Carbon Dioxide,Air Revitalization↗