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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Humming Trains in Seismology: An Opportune Source for Probing the Shallow Crust

Abstract Seismologists are eagerly seeking new and preferably low-cost ways to map and track changes in the complex structure of the top few kilometers of the crust. By understanding it better, they can build on what is known regarding important, practical issues. These include telling us whether imminent earthquakes and volcanic eruptions are generating telltale underground signs of hazard, about mitigation of induced seismicity such as from deep injection of wastewater, how the Earth and its atmosphere couple, and where accessible natural resources are. Passive seismic imaging usually relies on blind correlations within extended recordings of Earth’s ceaseless “hum” or coda of well-mixed, small vibrations. In this article, we propose a complementary approach. It is seismic interferometry using opportune sources—specifically ones not stationary in time and moving in a well-understood configuration. Its interpretation relies on an accurate understanding of how these sources radiate seismic waves, precise timing, careful placement of pairs of listening stations, and seismic phase differentiation (surface and body waves). Massive freight trains were only recently recognized as such a persistent, powerful cultural (human activity-caused) seismic source. One train passage may generate a tremor with an energy output of a magnitude 1 earthquake and be detectable for up to 100 km from the track. We discuss the source mechanisms of train tremors and review the basic theory on sources. Finally, we present case studies of body- and surface-wave retrieval as an aid to mineral exploration in Canada and to monitoring of a southern California fault zone. We believe noise recovery from this new signal source, together with dense data acquisition technologies such as nodes or distributed acoustic sensing, will deeply transform our ability to monitor activity in the shallow crust at sharpened resolution in time and space.

Geochemistry & Geophysics↗
DOE OSTI2020

Sensitivity evaluation of the Kudryavtsev permafrost model

Modeling is an important way to assess current and future permafrost spatial distribution and dynamics, especially in data poor areas like the Arctic region. Here, we evaluate a physics-based analytical model, Kudryavtsev's active layer model, which is widely used because it has relatively few data requirements. This model was recently incorporated into a component modeling toolbox, allowing for coupled modeling of permafrost and geomorphic processes over geological timescales. However, systematic quantitative assessment of the influence of its controlling parameters on permafrost temperature and active layer thickness predictions has not been undertaken before. In this work, we investigate the sensitivity of the Kudryavtsev's active layer model by Monte Carlo simulations to generate probability distributions for input parameters and compare predictions with a comprehensive benchmark dataset of in-situ permafrost observations over entire Alaska. Predicted permafrost surface temperature is highly dependent on mean annual air temperature (r = 0.78 on average), annual temperature amplitude (–0.41), and winter-averaged snow thickness (0.30). Uncertainty of predicted permafrost temperature is relatively small (RMSE = 1 °C), when air temperature and snow depth are well constrained. Similarly, RMSE between simulated and observed ALT at stations is ~0.08 m. However, under given air temperature and snow conditions, soil water content bias can significantly affect modeled active layer thickness (RMSE = 0.1 m or 40% of the observed active layer thickness). If soil water content has a large bias, improvements in other parameters may not significantly improve the active layer predictions of the Kudryavtsev's model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Nitrate-To-Ammonia Electroconversion at Neutral pH on Polycrystalline Vanadium Sulfide Derived from Vanadium Disulfide

The electrochemical nitrate reduction reaction (NO3RR) offers a pathway to produce NH3 for fuel and fertilizer from waste NO3-. In this work, a polycrystalline vanadium sulfide (VSx), which is derived from solvothermally grown and annealed VS2, is shown to exhibit excellent NO3RR activity (2.3 +- 0.6 mg.cm-2 geo..h-1 @ -0.92 VRHE) and Faradaic efficiency to NH4+ (69 +- 6% at -0.69 VRHE) in buffered neutral pH electrolyte containing 0.1 M NO3-. A variety of characterization techniques are leveraged to support the VSx assignment, including X-ray photoelectron spectroscopy, near-edge X-ray absorption fine structure spectroscopy, selected area electron diffraction, and X-ray diffraction measurements. The VS2 annealing step reduces the oxide character and generates VSx, which, based on the improved NO3RR activity, results in the creation of active sites for NO3- binding. To help shed light on NO3RR on VSx, VS2 is used as a model system, and a grand-canonical density functional theory (GC-DFT) investigation of VS2 shows strong evidence that S vacancies are active sites for NO3RR, where NO3- outcompetes H+ for adsorption at the S-vacancy sites. Moreover, GC-DFT results highlight a thermodynamically favorable reaction to generate NH4+ in an aqueous electrolyte at relevant cathodic potentials. As an annealed material, VSx may contain undersaturated V sites, which show an electronic structure similar to the theoretically calculated S-vacancy site of VS2, and these sites may contribute to the observed increase in NO3RR activity and selectivity for NH4+ on VSx versus unannealed VS2. Finally, kinetic isotope effect measurements suggest that the kinetic rate-limiting step of the NO3RR on VSx is not proton-coupled, indicating it may be the first electron transfer to adsorbed NO3*.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Removal of High Specific Activity Fission Products from Uranyl Sulfate Waste Solutions

The Savannah River National Laboratory (SRNL) is currently providing support to SHINE Medical Technologies (SHINE) which plans to deploy a low energy, accelerator-based neutron source to fission low enriched U in a uranyl sulfate target solution for 99 Mo production. The 99 Mo is initially separated from the fission products and target solution by an extraction column. Subsequent washing of the column will generate waste solutions containing residual U and fission product activity. A small number of high specific activity fission products (e.g., 90 Sr, 137 Cs, and 144 Ce) in these streams will likely control the classification of the low level waste (LLW). If a sufficient amount of the high specific activity isotopes are separated from the SHINE waste streams and concentrated into a waste form, it would be possible to treat a majority of the wash solutions from the column operations as a lower class of LLW (Class A versus Class B or C or Class B versus Class C). The high specific activity fission product elements could then be dispositioned as a much smaller volume of waste rather than requiring the disposal of the entire waste stream at the higher waste classification. The Savannah River Site (SRS) has experience with using monosodium titanate (MST) and crystalline silicotitanate (CST) to remove Cs and Sr from high salt content waste solutions generated during the reprocessing of nuclear fuels and targets. Both of these materials have worked very well for their intended purposes at the SRS where the fission product elements are removed from highly alkaline waste. On the other hand, SHINE waste streams from the extraction column contain H 2 SO 4 which makes the solution acidic. Additionally, the SRS waste streams do not contain other fission product elements such as transition metals or lanthanides because they precipitate upon neutralization of the SRS waste and are not present in the supernate which is dispositioned as LLW following treatment. As such, there are inherent differences between SHINE and SRS waste treatment strategies. Savannah River National Laboratory was tasked with performing scoping studies to see if MST and CST would remove Sr, Cs, and Ce from an acidic mixed metal simulant solution. Batch contact experiments were performed using MST and two CST type materials. The MST material is a 15 wt % powder in 0.15 M NaOH slurry. The MST showed low adsorption for elements of interest from acidic solution. Furthermore, the powder size makes MST non-ideal for column operations. A CST IE-911 ion exchange material had high Cs adsorption, moderate Sr, and marginal Ce adsorption. Based on adsorption of all species, the ion exchange capacity was found to be 0.032 meq/mL. A bench-top column experiment to measure elemental breakthrough curves was performed using CST IE-911 where chromatographic separations of the mixed simulant were expected to occur. While most elements behaved as expected, the lanthanide series, containing Ce, broke though the column earlier than expected. The second CST material, CST R9120, displayed high adsorption for all elements in the acidic mixed simulant solutions in a batch contact study, and had a calculated loading capacity of 0.091 meq/mL. Future studies to develop a waste treatment flowsheet should focus on CST R9120 to treat SHINE waste solutions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Atomic Layer Deposition for Enhanced Reactivity and Stability of Biomass Conversion Catalysts

Heterogeneous catalysts are an essential tool in the transition towards a sustainable, bio-based economy for fuels and chemicals. However, the harsh conditions (e.g., high temperatures, acidity, oxidizing/reducing environments) of many key biomass conversion processes give rise to nanoparticle sintering, support collapse, and metal leaching in conventional PGM catalysts. Active site poisoning due to the relatively high sulfur content of most biomass feedstocks further compounds these durability problems. Next-generation catalysts must be developed to address these stability challenges. In this work, we used a scalable atomic layer deposition (ALD) process to modify conventional Pd-based hydrogenation catalysts to generate significant performance improvements. TiO2 ALD coatings were found to increase the activity of Pd/Al2O3 catalysts towards naphthalene hydrogenation; additionally, these coatings improved the catalyst's resistance to sulfur poisoning and thermal stability under oxidative calcination. Additional work in which Al2O3 ALD coatings were applied to Pd/TiO2 catalysts for muconic acid hydrogenation found similar stability benefits, including improved resistance to Pd leaching in the acidic environment. ALD technology holds great potential in the development of next-generation catalysts for biofuels and bioproducts and this work constitutes an important examination of applying ALD coatings to supported Pd hydrogenation catalysts.

ALD↗
DOE OSTI2025

How the Arrangement of Platinum Atoms on Ruthenium Nanoparticles Improves Hydrogen Evolution Activity

The platinum‐ruthenium (PtRu) system is highly active for hydrogen evolution reaction (HER) in alkaline media with both Pt and Ru playing active roles in the water dissociation step that generates adsorbed hydrogen atoms. Precise control of the arrangement of Pt atoms on Ru nanoparticles can maximize the Pt‐Ru sites for water dissociation and Pt‐Pt sites for hydrogen production and can considerably improve HER catalytic performance. By directing the growth and distribution of Pt on Ru hourglass nanoparticles, the arrangement of Pt on Ru is controlled into forming Pt islands, small Pt clusters, and strings of a few Pt atoms. Calculations show that the unique atomic string arrangements of Pt on Ru is the thermodynamically favorable configuration. Additionally, these strings have a favorable combination of Pt‐Ru and Pt‐Pt sites, making the Pt‐string on Ru the most active catalyst with a more than fivefold increase in turnover frequency for alkaline HER compared to the Pt‐island on Ru catalyst. The results show how controlling the Pt atomic arrangement on Ru nanoparticle surfaces for the tuning of Pt‐Pt and Pt‐Ru neighboring sites can direct toward a more efficient HER mechanism and thereby significantly enhancing HER performance.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Broadband‐Tunable Third‐Harmonic Generation Using Phase‐Change Chalcogenides

Despite remarkable progress in passive nonlinear nanophotonics, dynamically controlled ultracompact nonlinear optical sources with high efficiency remain elusive. Nonvolatility, large refractive index contrast between amorphous and crystalline phases, low thermal threshold for crystallization, and particularly high‐third‐order nonlinear optical susceptibility of phase‐change alloy Ge 2 Sb 2 Te 5 (GST) make it a promising candidate for active subwavelength metaphotonic structures for realization of third‐harmonic generation (THG) devices. Herein, a GST‐based asymmetric Fabry–Perot cavity is numerically designed and experimentally demonstrated to show a dynamically reconfigurable structure with a large shift of the THG resonant band. In addition, continuous resonant spectral shifting bridged by a precisely controlled semicrystalline phase of GST is realized. Tunable THG with the fundamental wavelength ranging from 1150 to 1400 nm is presented, which corresponds to a broadband THG source in the violet‐blue visible wavelength range. Herein, the potential of GST subwavelength structures as a reliable platform for realization of the broadband‐tunable frequency‐conversion sources for applications such as THG microscopy and optical communication is indicated.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Active Learning for Rapid Targeted Synthesis of Compositionally Complex Alloys

The next generation of advanced materials is tending toward increasingly complex compositions. Synthesizing precise composition is time-consuming and becomes exponentially demanding with increasing compositional complexity. An experienced human operator does significantly better than a novice but still struggles to consistently achieve precision when synthesis parameters are coupled. The time to optimize synthesis becomes a barrier to exploring scientifically and technologically exciting compositionally complex materials. This investigation demonstrates an active learning (AL) approach for optimizing physical vapor deposition synthesis of thin-film alloys with up to five principal elements. We compared AL-based on Gaussian process (GP) and random forest (RF) models. The best performing models were able to discover synthesis parameters for a target quinary alloy in 14 iterations. We also demonstrate the capability of these models to be used in transfer learning tasks. RF and GP models trained on lower dimensional systems (i.e., ternary, quarternary) show an immediate improvement in prediction accuracy compared to models trained only on quinary samples. Furthermore, samples that only share a few elements in common with the target composition can be used for model pre-training. We believe that such AL approaches can be widely adapted to significantly accelerate the exploration of compositionally complex materials.

Chemistry↗
DOE OSTI2026

Optimizing HAARP Beam Pattern for Generation of Strong F‐Region Field‐Aligned Irregularities

Field-aligned irregularities (FAIs) are the signatures of plasma turbulence and convection in the mid- and high-latitude F-region ionosphere, and also provide coherent backscatter targets for HF radars. To serve irregularity generation and characterization studies, we conducted experiments at the High-frequency Active Auroral Research Program (HAARP) in August 2023 with the goal of identifying the optimal HAARP beam pattern for reliable generation of intense FAIs over a large geographic region. The HAARP beam patterns we tested were the commonly-used narrow beam, also known as L0, as well as the wider L1 and L2 “twisted” beam patterns. The size and intensity of the FAI region generated by each HAARP beam pattern was quantified using the Kodiak Island Super Dual Auroral Radar Network (SuperDARN) radar. Stimulated electromagnetic emissions (SEE) from heater wave-FAI scattering were also recorded using a receiver located near HAARP. The L1 beam pattern was found to produce the strongest SuperDARN backscatter over the largest region. Although the heater frequency was intended to be tuned a few hundred kHz below the F-region critical frequency (foF2) during each experiment, difficulty in estimating foF2 during the campaign likely resulted in HAARP heating at significantly different frequency ranges around foF2 during each experiment. Although this additional free parameter complicated data analysis for this study, the SuperDARN and SEE measurements have led to further inquiry into the role heater frequency plays in the artificial generation of FAIs.

58 GEOSCIENCES↗
DOE OSTI2024

Effects of Trigger Method on Fire Propagation during the Thermal Runaway Process in Li-ion Batteries

Lithium-ion batteries are prone to fire hazards due to the possibility of thermal runaway propagation. During battery product development and subsequent safety tests for design validation and safety certification, the thermal runaway onset is triggered by various test methods such as nail penetration, thermal ramp, or external short circuit. This failure initiation method affects the amount of heat contributions and the composition of gas generations. This study compares two such trigger methods, external heating and using a thermally-activated internal short circuit device (ISCD). The effects of the trigger method on total heat generation are experimentally investigated within 18650 cylindrical cells at single cell level as well as at multiple cell configuration level. The severity of failure was observed to be worse for cells with ISCDs at single cell level, whereas quite the opposite results were observed at multiple cell configuration level. A preliminary numerical analysis was performed to better understand the battery safety performance with respect to thermal runaway trigger methods and heat transfer conditions.

25 ENERGY STORAGE↗
DOE OSTI2021

Sequestration and release of nitrite and nitrate in alkali-activated slag: A route toward smart corrosion control

Intercalating the corrosion inhibitive ions in hydrotalcite is a promising approach to improve the long-term efficiency of inhibitors in corrosion protection of steel in reinforced concrete. In this work, the potential of autogenously generating nitrite- and nitrate-intercalated hydrotalcite in alkali-activated slag (AAS) is investigated. The results show that the added nitrite and nitrate ions are preferably uptaken in the interlayer structure of hydrotalcite in AAS, and the sequestered nitrite and nitrate are released upon chloride exposure in seawater and NaCl solution. The incorporation of nitrite and nitrate has little detrimental effects on the chloride binding capacity of AAS but slightly enhances the chloride ingress due to the pore coarsening effect. Similar to ordinary Portland cement (OPC), AAS is more permeable to the chloride in seawater than NaCl solution. However, unlike the release of bound chloride contributed by ettringite formation in seawater-exposed OPC, the enhanced chloride ingress in seawater-exposed AAS is primarily attributed to the aggravated pH reduction at the exposure front due to brucite formation. This study contributes to the design of alkali-activated binders with a smart inhibitor releasing ability for mitigating corrosion of steel in concrete.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Polyethylene Upcycling to Liquid Alkanes in Molten Salts under Neat and External Hydrogen Source-Free Conditions

Development of facile approaches to convert plastic waste into liquid fuels under neat conditions is highly desired but challenging, particularly without noble metal catalysts and an external hydrogen source. Herein, highly efficient and selective polyethylene-to-gasoline oil (branched C 6 –C 12 alkanes) conversion was achieved under mild conditions (<170 °C) using commercially available AlCl 3 -containing molten salts as reaction media and to provide catalytic sites (no extra solvents, additives, or hydrogen feeding). The high catalytic efficiency and selectivity was ensured by the abundant active Al sites with strong Lewis acidity (comparable to the Al type in acidic zeolite) and highly ionic nature of the molten salts to stabilize the carbenium intermediates. Dynamic genesis of the Al sites was elucidated via time-resolved Al K-edge soft X-ray and 27 Al NMR, confirming the tricoordinated Al 3+ as active sites and its coordination with the as-generated alkene/aromatic intermediates. Further, the carbenium formation and polyethylene chain variation was illustrated by inelastic neutron scattering (INS) and an isotope-labeling experiment. Theoretical simulations further demonstrated the successive hydride abstraction, β-scission, isomerization, and internal hydrogen transfer reaction pathway with AlCl 3 as active sites. This facile catalytic system can further achieve the conversion of robust, densely assembled, and high molecular weight plastic model compounds to liquid alkane products in the diesel range.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Accelerating Innovative Energy Solutions Using Combustion Simulations

Combustion-based transportation, electricity generation, and industrial heating in manufacturing constitute the three largest sectors of energy demand. Some of the recent technology development in these sectors are: switching to low-carbon fuels for the transportation sector, increasing energy efficiency in the power sector, and capturing carbon emissions from conventional power generators. Several teams at the National Renewable Energy Laboratory have been actively advancing research in these areas by leveraging computational modeling of combustion processes across the heavy-duty land based transportation, aviation, and power generation sectors. This article summarizes some of these efforts, demonstrating the potential of advanced computational techniques to generate technological solutions that will transform the global energy system.

08 HYDROGEN↗
DOE OSTI2022

Ig-VAE: Generative modeling of protein structure by direct 3D coordinate generation

While deep learning models have seen increasing applications in protein science, few have been implemented for protein backbone generation—an important task in structure-based problems such as active site and interface design. We present a new approach to building class-specific backbones, using a variational auto-encoder to directly generate the 3D coordinates of immunoglobulins. Our model is torsion- and distance-aware, learns a high-resolution embedding of the dataset, and generates novel, high-quality structures compatible with existing design tools. We show that the Ig-VAE can be used with Rosetta to create a computational model of a SARS-CoV2-RBD binder via latent space sampling. We further demonstrate that the model’s generative prior is a powerful tool for guiding computational protein design, motivating a new paradigm under which backbone design is solved as constrained optimization problem in the latent space of a generative model.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Dataset, Code, and Models for Training Deep Learning Potentials for Low Temperature Plasma-Surface Interactions

This repository contains datasets, training scripts, and finished models, and test simulations used in the development of DeepREBO— a machine-learned interatomic potential trained to emulate the REBO2 empirical potential. The data was generated to study deep potential development for simulations of plasma-surface interactions. It uses an active learning framework, starting from a minimal dataset and iteratively expanding it. Included are those generated datasets, the trained models, and simulations used to evaluate the performance of the training process. This resource supports reproducibility and provides a reference framework for training deep potentials in plasma-surface interaction studies.

active learning↗
DOE OSTI2023

Real-Time Regional PV Spinning Reserve Estimator with AGC Look-Ahead Windows

Curtailed PV generation is a zero-marginal cost spinning reserve that can be used for a number of active power control services. However, unlike the traditional spinning reserve providers, i.e., fossil-fueled generators, who have well-defined operating characteristics, e.g., available headroom or potential high limit (PHL), PV plants have by nature variable and uncertain operating characteristics. To ensure the effective coordination between PV plants and the system operator during an active power control event, accurate forecasts of the PV PHL are essential. A novel reference-control grouping based scaling method has been proposed by NREL to estimate the PV PHL in real-time. This work further enhances the methodology by: 1) improving the model accuracy through machine learning; 2) considering look-ahead windows introduced by the computation and communication latencies; 3) applying the method to regional spinning reserve estimation. A significant performance improvement, over 99% of estimation error reduction, has been observed based on real-world data collected by CAISO and PV plant operators.

potential high limit↗
DOE OSTI2023

Real-Time Regional PV Spinning Reserve Estimator with AGC Look-Ahead Windows: Preprint

Curtailed PV generation is a zero-marginal cost spinning reserve that can be used for a number of active power control services. However, unlike the traditional spinning reserve providers, i.e., fossil-fueled generators, who have well-defined operating characteristics, e.g., available headroom or potential high limit (PHL), PV plants have by nature variable and uncertain operating characteristics. To ensure the effective coordination between PV plants and the system operator during an active power control event, accurate forecasts of the PV PHL are essential. A novel reference-control grouping based scaling method has been proposed by NREL to estimate the PV PHL in real-time. This work further enhances the methodology by: 1) improving the model accuracy through machine learning; 2) considering look-ahead windows introduced by the computation and communication latencies; 3) applying the method to regional spinning reserve estimation. A significant performance improvement, over 1.6% of estimation error reduction, has been observed based on real-world data collected by CAISO and PV plant operators.

potential high limit↗
DOE OSTI2023

Physical and Flow Properties of Glass-Forming Chemicals (V 2 O 5 , SnO, SnO 2 , Cr 2 O 3 , FeCr 2 O 4 , and ZrSiO 4 ) and Mixtures

For an efficient nuclear waste vitrification process at the Waste Treatment and Immobilization Plant (WTP) on the Hanford Site, proper selection and consistent supply of glass-forming chemicals (GFCs) are crucial. Thorough characterization of the GFCs is required to reduce risks in operation of the vitrification facility. Low-activity waste (LAW) will be blended with GFCs to form slurry feeds and then fed to melters and vitrified. To enhance properties of waste glasses, new chemicals are being introduced to the current GFC mixture. In this study, three new GFCs were evaluated for enhanced LAW glass formulations: chromium oxide (Cr 2 O 3 ), vanadium oxide (V 2 O 5 ), and stannic oxide (SnO 2 ). These three oxide components are included in enhanced waste glass formulations, and GFCs with the appropriate physical and flow properties are needed. As a starting point, single metal oxide GFCs, Cr 2 O 3 , V 2 O 5 , and SnO 2 , were sourced and tested. Then, alternative sources of Sn and Cr (SnO and FeCr 2 O 4 ) were tested along with an alternative zircon source (ZrSiO 4 ). This report documents the work performed to collect physical and flow property data on these new GFCs and melter feed slurries generated using these GFCs and simulated low-activity wastes.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗