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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Electric Sail Propulsion for Exploring Nearby Interstellar Space

An Electric Sail is a revolutionary propellant-less propulsion system that is ideal for deep space missions to the outer planets, the Heliopause, and beyond. It is revolutionary in that it uses momentum exchange with the hypersonic solar wind to propel a spacecraft within the heliosphere. The momentum exchange is affected by the deflection of charged solar wind particles by an array of electrically biased wires that extend outward up to 30 km from a slowly rotating spacecraft. A high-voltage, positive bias on the wires, which are oriented normal to the solar wind flow, deflects the streaming protons, resulting in a reaction force on the wires that is also directed radially away from the sun. Over a period of months, this small force can accelerate the spacecraft to enormous speeds-on the order of 100-150 km/s (approximately 20 to 30 AU/yr). Unlike solar sails, Electric Sails do not rely on a fixed area to produce thrust. In fact, as they move away from the Sun and solar wind pressure decreases, the area for solar proton momentum transfer becomes larger, increasing system efficiency. As a result, thrust decreases at ≈1/r**(7/6) instead of the ≈1/r**2 rate typical for solar sails. The net effect is that an increased radial range of operation, together with increased thrust, both contribute to higher velocities and shorter total trip times to distant destinations. The MSFC Advanced Concepts Office (ACO) was awarded a Phase II NASA Innovative Advanced Concepts (NIAC) study to mature the technology for possible future demonstration and implementation. Preliminary results indicate that the physics of the system is viable and that a spacecraft propelled by an Electric Sail could reach the Heliopause in less than 15 years - and could be developed within a decade.

Johnson, Les↗
DOE OSTI2022

The Contribution of Proton-Donor pKa on Reactivity Profiles of [FeFe]-hydrogenases

The [FeFe]-hydrogenases are enzymes that catalyze the reversible activation of H 2 coupled to the reduction–oxidation of electron carriers. Members of the different taxonomic groups of [FeFe]-hydrogenases display a wide range of preference, or bias, for H 2 oxidation or H 2 production reactions, despite sharing a common catalytic cofactor, or H-cluster. Identifying the properties that control reactivity remains an active area of investigation, and models have emerged that include diversity in the catalytic site coordination environments and compositions of electron transfer chains. The kinetics of proton-coupled electron transfer at the H-cluster might be expected to be a point of control of reactivity. To test this hypothesis, systematic changes were made to the conserved cysteine residue that functions in proton exchange with the H-cluster in the three model enzymes: CaI, CpII, and CrHydA1. CaI and CpII both employ electron transfer accessory clusters but differ in bias, whereas CrHydA1 lacks accessory clusters having only the H-cluster. Changing from cysteine to either serine (more basic) or aspartate (more acidic) modifies the sidechain pKa and thus the barrier for the proton exchange step. The reaction rates for H 2 oxidation or H 2 evolution were surveyed and measured for model [FeFe]-hydrogenases, and the results show that the initial proton-transfer step in [FeFe]-hydrogenase is tightly coupled to the control of reactivity; a change from cysteine to more basic serine favored H 2 oxidation in all enzymes, whereas a change to more acidic aspartate caused a shift in preference toward H 2 evolution. Overall, the changes in reactivity profiles were profound, spanning 10 5 in ratio of the H 2 oxidation-to-H 2 evolution rates. The fact that the change in reactivity follows a common trend implies that the effect of changing the proton-transfer residue pKa may also be framed as an effect on the scaling relationship between the H-cluster di(thiolmethyl)amine (DTMA) ligand pKa and E m values of the H-cluster. Experimental observations that support this relationship, and how it relates to catalytic function in [FeFe]-hydrogenases, are discussed.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2008

Methods of Controlling the Loop Heat Pipe Operating Temperature

The operating temperature of a loop heat pipe (LHP) is governed by the saturation temperature of its compensation chamber (CC); the latter is in turn determined by the balance among the heat leak from the evaporator to the CC, the amount of subcooling carried by the liquid returning to the CC, and the amount of heat exchanged between the CC and ambient. The LHP operating temperature can be controlled at a desired set point by actively controlling the CC temperature. The most common method is to cold bias the CC and use electric heater power to maintain the CC set point temperature. The required electric heater power can be large when the condenser sink is very cold. Several methods have been developed to reduce the control heater power, including coupling block, heat exchanger and separate subcooler, variable conductance heat pipe, by-pass valve with pressure regulator, secondary evaporator, and thermoelectric converter. The paper discusses the operating principles, advantages and disadvantages of each method.

Ku, Jentung↗
DOE OSTI2024

Predicting the Rate of Degradation Related to Oxygen Electrode Delamination in Solid Oxide-Ion Electrolyzers

One of the leading causes for the performance degradation in H 2 -producing solid oxide electrolytic cells (SOECs) is the gradual delamination of oxygen electrode (OE) from the electrolyte under a strong anodic polarization. Identification of the key factor that controls the rate of OE delamination is of paramount importance to achieve long-term stable operation of SOECs. Here we show from thousands of hours of testing data that the exchange current density (i°) of OE can be leveraged as a predictor for the rate of delamination. To obtain i°, we apply DC-biased electrochemical impedance spectroscopy on a three-electrode symmetrical cell to measure polarization resistance (R p ) of OE as a function of current density (i) and time (t). The collected R p -i-t raw data are then converted to overpotential ( η )-i-t, from which i° is extracted from the “low-field” approximation. An analytical relationship between i° and time-to-delamination (TTD) is further established from the established i°-i-t relationship. We show that under a constant anodic polarization current density i, the greater the ratio i/i°, the faster the delamination. Therefore, we conclude that the exchange current density of an OE, i°, can be used to predict the rate of OE degradation in solid oxide-ion electrolyzers.

25 ENERGY STORAGE↗
DOE OSTI2022

Methane and Carbon Dioxide Fluxes in a Temperate Tidal Salt Marsh: Comparisons Between Plot and Ecosystem Measurements

Tidal wetlands are comprised of complex interdependent pathways where measurements of carbon exchange are often scale dependent. Common data collection methods (i.e., chambers and eddy covariance) are inherently constrained to different spatial and temporal scales which could generate biased information for applications of carbon accounting, identifying functional relationships and predicting future responses to climate change. Consequently, it is needed to systematically evaluate measurements derived from multiple approaches to identify differences and how techniques complement each other to reconcile interpretations. For our study, to accomplish this, we tested ecosystem-scale eddy covariance with plot-scale chamber measurements within a temperate salt marsh. We found good agreement (R 2 = 0.71–0.95) when comparing measurements of CH 4 emissions and CO 2 exchange but this agreement was dependent upon canopy phenology with discrepancies mainly arising during senescence and dormancy phenophases. The environmental drivers for CH 4 and CO 2 fluxes were mostly preserved across different measurement techniques, but the number of drivers increases while their individual strength decreases at the ecosystem scale. Empirical upscaling models parameterized with chamber measurements overestimated annual net ecosystem exchange (NEE; 108%) and gross primary production (GPP; 12%) while underestimating ecosystem respiration (Reco; 14%) and CH 4 emissions (69%) compared to eddy covariance measurements. Our results suggest that the environmental complexity of CH 4 and CO 2 fluxes in salt marshes may be underestimated by chamber-based measurements, and highlights how different techniques are complementary while considering limitations at each level of measurement.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Clean quantum point contacts in an InAs quantum well grown on a lattice-mismatched InP substrate

Strong spin-orbit coupling, the resulting large g factor, and small effective mass make InAs an attractive material platform for inducing topological superconductivity. The surface Fermi level pinning in the conduction band enables highly transparent ohmic contact without excessive doping. In this study, we investigate electrostatically defined quantum point contacts (QPCs) in a deep-well InAs two-dimensional electron gas. Despite the 3.3% lattice mismatch between the InAs quantum well and the InP substrate, we report clean QPCs with up to eight pronounced quantized conductance plateaus at zero magnetic field. Source-drain dc bias spectroscopy reveals a harmonic confinement potential with a nearly 5 meV subband spacing. We find a many-body exchange interaction enhancement for the out-of-plane g factor |$g^{*}_{⊥}$|=27±1 , whereas the in-plane g factor is isotropic |$g^{*}_{x}$|=|$g^{*}_{y}$|=12±2 , close to the bulk value for InAs.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2011

Improvement of the GEOS-5 AGCM upon Updating the Air-Sea Roughness Parameterization

The impact of an air-sea roughness parameterization over the ocean that more closely matches recent observations of air-sea exchange is examined in the NASA Goddard Earth Observing System, version 5 (GEOS-5) atmospheric general circulation model. Surface wind biases in the GEOS-5 AGCM are decreased by up to 1.2m/s. The new parameterization also has implications aloft as improvements extend into the stratosphere. Many other GCMs (both for operational weather forecasting and climate) use a similar class of parameterization for their air-sea roughness scheme. We therefore expect that results from GEOS-5 are relevant to other models as well.

Garfinkel, C. I.↗
NASA NTRS1984

Ionic charge state measurements during He(+)-rich solar particle events

Ionic charge state measurements of carbon, oxygen, and iron in He(+)-rich energetic particle events are presented. The data have been obtained with the Max-Planck-Institut/University of Maryland sensor system on the ISEE 3 spacecraft. The ionic charge states cannot be explained in terms of a model in which the coronal temperature determines a charge equilibrium which is subsequently frozen-in nor in terms of charge exchange during transition through coronal matter after acceleration. It is concluded that the acceleration and probably also the injection process is biased against particles with high mass-to-charge ratios. The plasma injected into the acceleration process must consist of material of cold (not greater than 8.5 x 10 to the 4th K) as well as hot (2.5 x 10 to the 6th K) origin. The cold material must be more abundant than the hot material.

Hovestadt, D.↗
NASA NTRS1992

Ion engine endurance testing at high background pressures

Ion engine endurance testing at vacuum chamber pressures in the low 10 exp -3 Pa range is enabled through the use of a three-grid accelerator system with the decelerator grid biased 50 to 100 volts negative of neutralizer cathode potential. The negative decelerator grid serves to collect the facility induced charge exchange ion current which normally results in rapid erosion of the accelerator grid during testing at elevated vacuum chamber pressures. This screen, accelerator, negative decelerator (SAND) grid configuration enables an order of magnitude reduction in vacuum chamber pumping speeds relative to that required for endurance testing of ion engines with conventional two-grid accelerator systems. A 900-hr test of a 30-cm diameter engine at 6.5 kW and a tank pressure of 3.7 x 10 exp -3 Pa was performed to test the feasibility of the three-grid SAND accelerator system technology. Grid erosion rates from this test are compared to those from a 200-hr test performed with the same discharge chamber, in the same test facility, and at the same background pressure with a conventional two grid accelerator system. The SAND optics resulted in greater than a factor of 100 reduction in accelerator grid erosion rate relative to the two-grid system.

Brophy, John R.↗
DOE OSTI2026

Ir–Ru Particles Enable Low-Loading Acidic Oxygen Evolution for Integrated Solar Devices

Integrated photoelectrochemical (PEC) devices for water splitting represent a compelling pathway for sustainable hydrogen production, directly converting solar energy into chemical fuels. While alkaline systems have achieved state-of-the-art solar-to-hydrogen (STH) efficiencies above 20% using earth-abundant catalysts, acidic PEC architectures provide unique advantages for compact device integration, fast proton transport, and stable operation under highly dynamic solar conditions. Proton-exchange membrane (PEM)-based configurations enable high current densities, low gas crossover, and rapid ionic response, making them especially well-suited for intermittent, bias-free PEC operation, despite alkaline electrolysis being more technologically mature. A critical limitation of acidic PEC systems remains, the oxygen evolution reaction (OER), which currently relies on scarce and costly iridium catalysts, restricting scalability. Here, in this study, we report a series of low-iridium mixed-metal oxide catalysts synthesized via a surfactant-assisted borohydride reduction method. An optimized Ir 0.5 Ru 0.5 O x catalyst exhibits exceptional intrinsic activity (>400 A g –1 Ir at 1.55 V vs RHE) in 0.1 M HClO 4 and maintains stable operation for over 10 days in an integrated PEC flow-cell. Sustained hydrogen production is achieved at 1.65 V with a total iridium loading of only 0.1 mg cm –2 , substantially below commercial PEM benchmarks. These results demonstrate a viable pathway toward scalable, high-performance acidic PEC hydrogen technologies.

Acidic electrolysis↗
NASA NTRS2005

An Improved Analysis of Forest Carbon Dynamics using Data Assimilation

There are two broad approaches to quantifying landscape C dynamics - by measuring changes in C stocks over time, or by measuring fluxes of C directly. However, these data may be patchy, and have gaps or biases. An alternative approach to generating C budgets has been to use process-based models, constructed to simulate the key processes involved in C exchange. However, the process of model building is arguably subjective, and parameters may be poorly defined. This paper demonstrates why data assimilation (DA) techniques - which combine stock and flux observations with a dynamic model - improve estimates of, and provide insights into, ecosystem carbon (C) exchanges. We use an ensemble Kalman filter (EnKF) to link a series of measurements with a simple box model of C transformations. Measurements were collected at a young ponderosa pine stand in central Oregon over a 3-year period, and include eddy flux and soil C02 efflux data, litterfall collections, stem surveys, root and soil cores, and leaf area index data. The simple C model is a mass balance model with nine unknown parameters, tracking changes in C storage among five pools; foliar, wood and fine root pools in vegetation, and also fresh litter and soil organic matter (SOM) plus coarse woody debris pools. We nested the EnKF within an optimization routine to generate estimates from the data of the unknown parameters and the five initial conditions for the pools. The efficacy of the DA process can be judged by comparing the probability distributions of estimates produced with the EnKF analysis vs. those produced with reduced data or model alone. Using the model alone, estimated net ecosystem exchange of C (NEE)= -251 f 197g Cm-2 over the 3 years, compared with an estimate of -419 f 29gCm-2 when all observations were assimilated into the model. The uncertainty on daily measurements of NEE via eddy fluxes was estimated at 0.5gCm-2 day-1, but the uncertainty on assimilated estimates averaged 0.47 g Cm-2 day-1, and only exceeded 0.5gC m-2 day-1 on days where neither eddy flux nor soil efflux data were available. In generating C budgets, the assimilation process reduced the uncertainties associated with using data or model alone and the forecasts of NEE were statistically unbiased estimates. The results of the analysis emphasize the importance of time series as constraints. Occasional, rare measurements of stocks have limited use in constraining the estimates of other components of the C cycle. Long time series are particularly crucial for improving the analysis of pools with long time constants, such as SOM, woody biomass, and woody debris. Long-running forest stem surveys, and tree ring data, offer a rich resource that could be assimilated to provide an important constraint on C cycling of slow pools. For extending estimates of NEE across regions, DA can play a further important role, by assimilating remote-sensing data into the analysis of C cycles. We show, via sensitivity analysis, how assimilating an estimate of photosynthesis - which might be provided indirectly by remotely sensed data - improves the analysis of NEE.

Williams, Mathew↗
NASA NTRS2015

Heliopause Electrostatic Rapid Transit System (HERTS)

A recent six month investigation focused on: "Determining the benefits of propelling a scientific spacecraft by an 'Electric Sail' propulsion system to the edge of our solar system (the Heliopause), a distance of 100 to 120 AU, in ten years or less" has recently been completed by the Advance Concepts Office at NASA's MSFC. The concept investigated has been named the Heliopause Electrostatic Rapid Transit System (HERTS) by the MSFC team. The HERTS is a revolutionary propellant-less propulsion concept that is ideal for deep space missions to the Outer Planets, Heliopause, and beyond. It is unique in that it uses momentum exchange from naturally occurring solar wind protons to propel a spacecraft within the heliosphere. The propulsion system consists of an array of electrically positively-biased wires that extend outward 20 km from a rotating (one revolution per hour) spacecraft. It was determined that the HERTS system can accelerate a spacecraft to velocities as much as two to three times that possible by any realistic extrapolation of current state-of-the-art propulsion technologies- including solar electric and solar sail propulsion systems. The data produced show that a scientific spacecraft could reach distances of 100AU in less than 10 years. Moreover, it can be reasonably expected that this system could be developed within a decade and provide meaningful Heliophysics Science and Outer Planetary Science returns in the 2025-2035 timeframe.

Wiegmann, Bruce M.↗
DOE OSTI2026

Federated learning for 2D synchrotron x-ray diffractometry: a cross-institutional approach for phase quantification of Ti–6Al–4V alloy

High-energy Two dimensional (2D) synchrotron x-ray diffractometry provides important insights into the atomistic structure and phase evolution of materials, yet traditional analysis methods remain complex, knowledge-intensive, and computationally demanding. Deep-learning models offer a powerful alternative for automating their analysis. Institutions that hold these datasets may be unwilling to share their data due to privacy and security policies, as well as the challenges associated with large-scale data transfer. As a result, models trained on local datasets often perform well only on their own data but exhibit bias and poor generalization across different instruments or facilities. To overcome these limitations, we explore federated learning (FL) for 2D synchrotron diffractograms, enabling collaborative model training without exchanging raw data. In this study, 2D synchrotron diffractograms of Ti–6Al–4V alloy collected from two independent facilities are used to train convolutional neural networks for predicting the β-phase volume fraction. Experimental results show that federated global models significantly outperform locally trained models in terms of generalization and achieve accuracy comparable to centralized trained models. These findings demonstrate the potential of FL to enable secure, cross-institutional collaboration and enhance the scalability of deep-learning-based materials characterization.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Tuning magneto-optical zero reflection via dual-channel hybrid magnonics

Multichannel coupling in hybrid systems makes an attractive testbed not only because of the distinct advantages entailed by each constituent mode but also because the opportunity to leverage interference among the various excitation pathways. Here, via combined analytical calculation and experiment, we demonstrate that the phase of the magnetization precession at the interface of a coupled yttrium iron garnet (YIG)/permalloy (Py) bilayer is collectively controlled by the microwave photon field torque and the interlayer exchange torque, manifesting a coherent, dual-channel excitation scheme that effectively tunes the magneto-optical spectrum. Furthermore, the different torque contributions vary with frequency, external bias field, and type of interlayer coupling between YIG and Py, which further results in destructive or constructive interferences between the two excitation channels, and hence selective suppression or amplification of the hybridized magnon modes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2022

A New Snow Module Improves Predictions of the Isotope-Enabled MAIDENiso Forest Growth Model

The representation of snow processes in forest growth models is necessary to accurately predict the hydrological cycle in boreal ecosystems and the isotopic signature of soil water extracted by trees, photosynthates and tree-ring cellulose. Yet, most process-based models do not include a snow module; consequently, their simulations may be biased in cold environments. Here, we modified the MAIDENiso model to incorporate a new snow module that simulates snow accumulation, melting and sublimation, as well as thermal exchanges driving freezing and thawing of the snow and the soil. We tested these implementations in two sites in eastern and western Canada for black spruce (Picea mariana (Mill.) B.S.P.) and white spruce (Picea glauca (Moench) Voss) forests, respectively. The new snow module improves the skills of the model to predict components of the hydrological cycle. The MAIDENiso model is now able to reproduce the spring discharge peak and to simulate stable oxygen isotopes in tree-ring cellulose more realistically than in the original snow-free version of the model. The new implementation also results in simulations with a higher contribution from the source water on the oxygen isotopic composition of the simulated cellulose, leading to more accurate estimates of cellulose isotopic composition. Future work may include the development of inverse modelling with this new version of MAIDENiso to produce robust reconstructions of the hydrological cycle and isotope processes in cold environments.

Snow processes↗
NASA NTRS2022

Evaluation of remote sensing-based evapotranspiration products at low-latitude eddy covariance sites

Remote sensing-based evapotranspiration (ET) products have been evaluated primarily using data from northern middle latitudes; therefore, little is known about their performance at low latitudes. To address this bias, an evaluation dataset was compiled using eddy covariance data from 40 sites between latitudes 30° S and 30° N. The flux data were obtained from the emerging network in Mexico (MexFlux) and from openly available databases of FLUXNET, AsiaFlux, and OzFlux. This unique reference dataset was then used to evaluate remote sensing-based ET products in environments that have been underrepresented in earlier studies. The evaluated products were: MODIS ET (MOD16, both the discontinued collection 5 (C5) and the latest collection (C6)), Global Land Evaporation Amsterdam Model (GLEAM) ET, and Atmosphere-Land Exchange Inverse (ALEXI) ET. Products were compared with unadjusted fluxes (ETorig) and with fluxes corrected for the lack of energy balance closure (ETebc). Three common statistical metrics were used: coefficient of determination (R2), root mean square error (RMSE), and percent bias (PBIAS). The effect of a vegetation mismatch between pixel and site on product evaluation results was investigated by examining the relationship between the statistical metrics and product-specific vegetation match indexes. Evaluation results of this study and those published in the literature were used to examine the performance of the products across latitudes. Differences between the MOD16 collection 5 and 6 datasets were generally smaller than differences with the other products. Performance and ranking of the evaluated products depended on whether ETorig or ETebc was used. When using ETorig, GLEAM generally had the highest R2, smallest PBIAS, and best RMSE values across the studied land cover types and climate zones. Neither MOD16 nor ALEXI performed consistently better than the other. When using ETebc, none of the products stood out in terms of both low bias and strong correlations. The use of ETebc instead of ETorig affected the biases more than the correlations. The product evaluation results showed no significant relationship with the degree of match between the vegetation at the pixel and site scale. The latitudinal comparison showed tendencies of lower R2 (all products) but better PBIAS and normalized RMSE values (MOD16 and GLEAM) for forests at low latitudes than for forests at northern middle latitudes. For non-forest vegetation, the products showed no clear latitudinal differences in performance.

Diego Salazar-Martínez↗
DOE OSTI2022

Modeling the Joint Effects of Vegetation Characteristics and Soil Properties on Ecosystem Dynamics in a Panama Tropical Forest

Abstract In tropical forests, both vegetation characteristics and soil properties are important not only for controlling energy, water, and gas exchanges directly but also determining the competition among species, successional dynamics, forest structure and composition. However, the joint effects of the two factors have received limited attention in Earth system model development. Here we use a vegetation demographic model, the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) implemented in the Energy Exascale Earth System Model (E3SM) Land Model (ELM), ELM‐FATES, to explore how plant traits and soil properties affect tropical forest growth and composition concurrently. A large ensemble of simulations with perturbed vegetation and soil hydrological parameters is conducted at the Barro Colorado Island, Panama. The simulations are compared against observed carbon, energy, and water fluxes. We find that soil hydrological parameters, particularly the scaling exponent of the soil retention curve ( B sw ), play crucial roles in controlling forest diversity, with higher B sw values (>7) favoring late successional species in competition, and lower B sw values (1 ∼ 7) promoting the coexistence of early and late successional plants. Considering the additional impact of soil properties resolves a systematic bias of FATES in simulating sensible/latent heat partitioning with repercussion on water budget and plant coexistence. A greater fraction of deeper tree roots can help maintain the dry‐season soil moisture and plant gas exchange. As soil properties are as important as vegetation parameters in predicting tropical forest dynamics, more efforts are needed to improve parameterizations of soil functions and belowground processes and their interactions with aboveground vegetation dynamics.

54 ENVIRONMENTAL SCIENCES↗