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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Deposition Height Prediction in Directed Energy Deposition

Using 316L stainless steel as a model material, reduced-order models are developed to predict capture efficiency, deposition height, and site-specific hardness in directed energy deposition. Capture efficiency is predicted over a 15 to 55 pct range using a dimensionless number derived from processing conditions and thermophysical properties. Deposition height is predicted over a 0.3 to 1.3 mm range without in situ sensing or prior training data, using two models based on the same mass and energy-balance principles. Predictions are compared with machine learning approaches. A quantitative relationship links deposition height, primary dendrite arm spacing (PDAS), and hardness: heights of 0.3 to 1.1 mm correspond to PDAS values of 2.7 to 5.1 µm and Vickers hardness (HV) of 160 to 219. Thinner layers cool more rapidly, producing finer microstructures and higher hardness. Samples fabricated with in situ variations in deposition height exhibited up to 55 HV differences between thick and thin regions, demonstrating that local control of deposition height enables predictive, site-specific hardness within a single build. These results establish deposition height prediction as a pathway for a priori process design and property control in directed energy deposition for 316L stainless steel.

Kunkel, William [Univ. of Wisconsin, Madison, WI (↗
DOE OSTI2022

Distributed Quantum Error Correction for Chip-Level Catastrophic Errors

Quantum error correction holds the key to scaling up quantum computers. Cosmic ray events severely impact the operation of a quantum computer by causing chip-level catastrophic errors, essentially erasing the information encoded in a chip. Here, in this work, we present a distributed error correction scheme to combat the devastating effect of such events by introducing an additional layer of quantum erasure error correcting code across separate chips. We show that our scheme is fault tolerant against chip-level catastrophic errors and discuss its experimental implementation using superconducting qubits with microwave links. Our analysis shows that in state-of-the-art experiments, it is possible to suppress the rate of these errors from 1 per 10 s to less than 1 per month.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Comparative genomics of pyrophilous fungi reveals a link between fire events and developmental genes

Forest fires generate a large amount of carbon that remains resident on the site as dead and partially ‘pyrolysed’ (i.e. burnt) material that has long residency times and constitutes a significant pool in fire–prone ecosystems. In addition, fire–induced hydrophobic soil layers, caused by condensation of pyrolysed waxes and lipids, increase post–fire erosion and can lead to long–term productivity losses. A small set of pyrophilous fungi dominate post–fire soils and are likely to be involved with the degradation of all these compounds, yet almost nothing is currently known about what these fungi do or the metabolic processes they employ. In this study, we sequenced and analyzed genomes from fungi isolated after Rim fire near Yosemite National Park in 2013 and showed the enrichment/expansion of CAZymes and families known to be involved in fruiting body initiation when compared to other basidiomycete fungi. We found gene families potentially involved in the degradation of the hydrophobic layer and pyrolysed organic matter, such as hydrophobic surface binding proteins, laccases (AA1_1), xylanases (GH10, GH11), fatty acid desaturases and tannases. Furthermore, pyrophilous fungi are important actors to restate the soil's functional capabilities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

2023 National Offshore Wind data set (NOW-23)

The 2023 National Offshore Wind data set (NOW-23) is the latest wind resource data set for offshore regions in the United States, which supersedes, for its offshore component, the Wind Integration National Dataset (WIND) Toolkit, which was published about a decade ago and is currently one of the primary resources for stakeholders conducting wind resource assessments in the continental United States. The NOW-23 data set was produced using the Weather Research and Forecasting Model (WRF) version 4.2.1. A regional approach was used: for each offshore region, the WRF setup was selected based on validation against available observations. The WRF model was initialized with the European Centre for Medium Range Weather Forecasts 5 Reanalysis (ERA-5) data set, using a 6-hour refresh rate. The model is configured with an initial horizontal grid spacing of 6 km and an internal nested domain that refined the spatial resolution to 2 km. The model is run with 61 vertical levels, with 12 levels in the lower 300m of the atmosphere, stretching from 5 m to 45 m in height. The MYNN planetary boundary layer and surface layer schemes were used the North Atlantic, Mid Atlantic, Great Lakes, Hawaii, and North Pacific regions. On the other hand, using the YSU planetary boundary layer and MM5 surface layer schemes resulted in a better skill in the South Atlantic, Gulf of Mexico, and South Pacific regions. A more detailed description of the WRF model setup can be found in the WRF namelist files linked at the bottom of this page. For all regions, the NOW-23 data set coverage starts on January 1, 2000. For Hawaii and the North Pacific regions, NOW-23 goes until December 31, 2019. For the South Pacific region, the model goes until 31 December, 2022. For all other regions, the model covers until December 31, 2020. Outputs are available at 5 minute resolution, and for all regions we have also included output files at hourly resolution. The NOW-23 data are provided here as HDF5 files. Examples of how to use the HSDS Service to Access the NOW-23 files are linked below. A list of the variables included in the NOW-23 files is also linked below. No filters have been applied to the raw WRF output.

Array↗
DOE OSTI2020

Carbide-Modified Pd on ZrO2 as Active Phase for CO2-Reforming of Methane—A Model Phase Boundary Approach

Starting from subsurface Zr0-doped “inverse” Pd and bulk-intermetallic Pd0Zr0 model catalyst precursors, we investigated the dry reforming reaction of methane (DRM) using synchrotron-based near ambient pressure in-situ X-ray photoelectron spectroscopy (NAP-XPS), in-situ X-ray diffraction and catalytic testing in an ultrahigh-vacuum-compatible recirculating batch reactor cell. Both intermetallic precursors develop a Pd0–ZrO2 phase boundary under realistic DRM conditions, whereby the oxidative segregation of ZrO2 from bulk intermetallic PdxZry leads to a highly active composite layer of carbide-modified Pd0 metal nanoparticles in contact with tetragonal ZrO2. This active state exhibits reaction rates exceeding those of a conventional supported Pd–ZrO2 reference catalyst and its high activity is unambiguously linked to the fast conversion of the highly reactive carbidic/dissolved C-species inside Pd0 toward CO at the Pd/ZrO2 phase boundary, which serves the role of providing efficient CO2 activation sites. In contrast, the near-surface intermetallic precursor decomposes toward ZrO2 islands at the surface of a quasi-infinite Pd0 metal bulk. Strongly delayed Pd carbide accumulation and thus carbon resegregation under reaction conditions leads to a much less active interfacial ZrO2–Pd0 state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

3D Quantification of Elemental Gradients within Heterostructured Particles of Battery Cathodes

Heterogenous architectures with elemental gradients tailored within particles have been pursued to combat the instabilities limiting Ni-rich cathode materials for lithium-ion batteries. The growth of different compositional layers is accomplished during the synthesis of hydroxide precursors. However, the extent to which these concentration gradients are modified during high-temperature reactions is difficult to establish in their intact, spherical form. Here, we show the entire three-dimensional structure of a secondary particle can be resolved nondestructively with differential X-ray absorption spectroscopy (XAS) through transmission X-ray microscopy (TXM). The relationship between particle location and elemental content was fully quantified, with high statistical significance, for heterostructures possessing different compositional gradients in the precursors with 90:5:5 Ni:Mn:Co core compositions. Reduced elemental heterogeneity was observed after high-temperature synthesis, but gradients remained. In conclusion, the methodology presented should be used to guide synthesis while assuring that gains in electrochemical performance are linked to precise elemental distributions at the nanoscale.

25 ENERGY STORAGE↗
DOE OSTI2021

Permafrost thaw with warming reduces microbial metabolic capacities in subsurface soils

Abstract Microorganisms are major constituents of the total biomass in permafrost regions, whose underlain soils are frozen for at least two consecutive years. To understand potential microbial responses to climate change, here we examined microbial community compositions and functional capacities across four soil depths in an Alaska tundra site. We showed that a 5‐year warming treatment increased soil thaw depth by 25.7% ( p = .011) within the deep organic layer (15–25 cm). Concurrently, warming reduced 37% of bacterial abundance and 64% of fungal abundances in the deep organic layer, while it did not affect microbial abundance in other soil layers (i.e., 0–5, 5–15, and 45–55 cm). Warming treatment altered fungal community composition and microbial functional structure ( p < .050), but not bacterial community composition. Using a functional gene array, we found that the relative abundances of a variety of carbon (C)‐decomposing, iron‐reducing, and sulphate‐reducing genes in the deep organic layer were decreased, which was not observed by the shotgun sequencing‐based metagenomics analysis of those samples. To explain the reduced metabolic capacities, we found that warming treatment elicited higher deterministic environmental filtering, which could be linked to water‐saturated time, soil moisture, and soil thaw duration. In contrast, plant factors showed little influence on microbial communities in subsurface soils below 15 cm, despite a 25.2% higher ( p < .05) aboveground plant biomass by warming treatment. Collectively, we demonstrate that microbial metabolic capacities in subsurface soils are reduced, probably arising from enhanced thaw by warming.

Wu, Linwei↗
DOE OSTI2022

Roll-to-Roll Advanced Materials Manufacturing DOE Laboratory Collaboration - Early Stage R&D: Phase 2 and FY21 (Final Report)

R2R processing is used to manufacture a wide range of products for various applications which span many industrial business sectors. The overall R2R methodology has been in use for decades and this continuous technique traditionally involves deposition of material(s) onto substrates or membranes that are on moving webs, carriers or other continuous belt-fed or conveyor-based processes that enable successive steps to build a final product. Established methods that typify R2R processing include tape casting, silk-screen printing, reel-to-reel vacuum deposition/coating, and R2R lithography. Products supported by R2R manufacturing include micro-electronics, electro-chromic window films, PVs, fuel cells for energy conversion, battery electrodes and electrolytes for energy storage, and barrier and membrane materials for decarbonization and air and water filtration. Due to innovation in materials and process equipment, high-quality yet very low-cost multilayer technologies have the potential to be manufactured on a very cost-competitive basis. To move energy-related products from high-cost niche applications to the commercial sector, the means must be available to enable manufacture of these products in a cost-competitive manner. Fortunately, products such as fuel cells, thin- and mid-film PVs, batteries, electrochromic and piezoelectric films, water separation membranes, and other energy saving technologies readily lend themselves to manufacture using R2R approaches. However, more early-stage research is needed to solve the challenge of linking the materials (particles, polymers, solvents, additives) used in ink and slurry formulations and the coating and heated drying processes to the ultimate performance of the final R2R product, especially for a process that uses multiple layers of deposition to achieve the end product.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Simulations of a hypersonic turbulent boundary layer over wavy surfaces

Here, we conduct large-eddy simulations of a Mach 5.84 cold wall turbulent boundary layer over one-dimensional wavy walls with varying amplitudes and wavelengths. Across all wall topologies, a series of alternating shock and expansion waves is shown to influence the entire boundary layer, and generate repeating wave patterns in the turbulent stresses, dispersive stresses, and turbulent kinetic energy budget. The series of alternating shocks and expansions imposes repeating adverse and favourable pressure gradients across the wavy wall, and at sufficient wall amplitude, triggers flow separation in the trough of the wave. Flow separation is demonstrated to influence the behaviour of wall pressure fluctuations over the wavy wall. In attached flows, the prominent frequencies are consistent with integral-scale boundary layer turbulence, whereas in separated flows, a two-decade frequency range is present, akin to two-dimensional shock–boundary layer interactions. Counter-rotating streamwise-oriented structures are observed on the windward side of the wave, which diminish over the wave crest. A conditional analysis demonstrates that these structures are present in the upstream boundary layer, and are amplified with increasing wall amplitude. An examination of the Görtler number and probability density function (PDF) of the fluctuating lateral wall shear stress demonstrates the strong correlation between a large Görtler number and growth of the PDF tail density, suggesting that the amplification of the counter-rotating streamwise-oriented structures are linked to centrifugal instabilities in regions of streamline concavity.

boundary layers↗
DOE OSTI2022

libwfa: Wavefunction analysis tools for excited and open‐shell electronic states

Abstract An open‐source software library for wavefunction analysis, libwfa, provides a comprehensive and flexible toolbox for post‐processing excited‐state calculations, featuring a hierarchy of interconnected visual and quantitative analysis methods. These tools afford compact graphical representations of various excited‐state processes, provide detailed insight into electronic structure, and are suitable for automated processing of large data sets. The analysis is based on reduced quantities, such as state and transition density matrices (DMs), and allows one to distill simple molecular orbital pictures of physical phenomena from intricate correlated wavefunctions. The implemented descriptors provide a rigorous link between many‐body wavefunctions and intuitive physical and chemical models, for example, exciton binding, double excitations, orbital relaxation, and polyradical character. A broad range of quantum‐chemical methods is interfaced with libwfa via a uniform interface layer in the form of DMs. This contribution reviews the structure of libwfa and highlights its capabilities by several representative use cases. This article is categorized under: Software > Quantum Chemistry Theoretical and Physical Chemistry > Spectroscopy

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Crystal structure of vismodegib, C 19 H 14 Cl 2 N 2 O 3 S

The crystal structure of vismodegib has been solved and refined using synchrotron X-ray powder diffraction data, and optimized using density functional theory techniques. Vismodegib crystallizes in space group P2 1 /a (#14) with a = 16.92070(20), b = 10.20235(4), c = 12.16161(10) Å, β = 108.6802(3)°, V = 1988.873(9) Å 3 , and Z = 4. The crystal structure consists of corrugated layers of molecules parallel to the bc-plane. There is only one classical hydrogen bond in the structure, between the amide nitrogen atom and the N atom of the pyridine ring. Pairs of these hydrogen bonds link the molecules into dimers, with a graph set R2,2(14) > a > a. The powder pattern has been submitted to ICDD for inclusion in the Powder Diffraction File™ (PDF®).

36 MATERIALS SCIENCE↗
DOE OSTI2026

Multiscale Characterization of Electrode-Induced Degradation in Perovskite Solar Cells

The stability of metal-halide-perovskite (MHP) solar cells must be understood and improved for the commercial viability of MHP technologies. Here, we apply multiscale characterization methods to study degradation modes, specifically electrode corrosion, for p-i-n MHP partial device stacks and full devices that are stored in the dark under an inert atmosphere. Our multiscale characterization approaches include full-device electro-optical performance using current-voltage (JV) curves and spatial imaging with electroluminescence (EL) and photoluminescence (PL). We further correlate interface properties using cross-sectional Kelvin probe force microscopy, which maps the nanoscale electric field properties, and electron microscopy, which demonstrates structural and chemical features. Devices stored as a full device stack degrade primarily by metal (Ag) electrode diffusion into the absorber, with formation of AgI byproducts and Ag accumulation near the indium tin oxide (ITO) contact. This causes decomposition of the perovskite absorber domains, loss of the potential drop at the electron transport layer (ETL)/perovskite interface near the metal contact, and increased equivalent resistance at the perovskite/hole transport layer (HTL) interface near the ITO contact. The devices stored without metal show a different degradation pathway dominated by corrosion of the ITO, creating voids at the ITO electrode surface with diffusion of In and Sn into the absorber. We conclude that metal electrode-induced degradation is the most severe degradation pathway under dark storage, but that ITO corrosion and absorber instability must also be mitigated. We further demonstrate mitigation of these degradation pathways by changes to the device stack, including a SnO x blocking layer at the ETL side and replacing ITO with FTO at the HTL side. These results provide a useful demonstration of specific dark degradation pathways at each electrode interface, as well as a unique multiscale example that links degradation of chemical, structural, and electrical interface properties to the full-device electro-optical characteristics.

14 SOLAR ENERGY↗
DOE OSTI2020

Roll-to-Roll Advanced Materials Manufacturing DOE Laboratory Collaboration (FY2019 Final Report)

R2R processing is used to manufacture a wide range of products for various applications which span many industrial business sectors. The overall R2R methodology has been in use for decades and this continuous technique traditionally involves deposition of material(s) onto moving webs, carriers or other continuous belt-fed or conveyor-based processes that enable successive steps to build a final version which serves to support the deposited materials. Established methods that typify R2R include tape casting, silk-screen printing, reel-to-reel vacuum deposition/coating and R2R lithography. Products supported by R2R manufacturing include micro-electronics, electro-chromic window films, PVs, fuel cells for energy conversion, battery electrodes for energy storage, and barrier and membrane materials. Due to innovation in materials and process equipment, high-quality yet very low-cost multilayer technologies have the potential to be manufactured on a very cost-competitive basis. To move energy-related products from high-cost niche applications to the commercial sector, a means must be available to enable manufacture of these products in a cost-competitive manner that is affordable. Fortunately, products such as fuel cells, thin- and mid-film PVs, batteries, electrochromic and piezoelectric films, water separation membranes, and other energy saving technologies readily lend themselves to manufacture using R2R approaches. However, more early-stage research is needed to solve the challenge of linking the materials (particles, polymers, solvents, additives) used in ink and slurry formulations, though the ink processing, coating and drying processes, to the ultimate performance of the final R2R product, especially for a process that uses multiple layers of deposition to achieve the end product.

42 ENGINEERING↗
DOE OSTI2023

TransformerG2G: Adaptive time-stepping for learning temporal graph embeddings using transformers

Dynamic graph embedding has emerged as a very effective technique for addressing diverse temporal graph analytic tasks (i.e., link prediction, node classification, recommender systems, anomaly detection, and graph generation) in various applications. Such temporal graphs exhibit heterogeneous transient dynamics, varying time intervals, and highly evolving node features throughout their evolution. Hence, incorporating long-range dependencies from the historical graph context plays a crucial role in accurately learning their temporal dynamics. In this paper, we develop a graph embedding model with uncertainty quantification, TransformerG2G, by exploiting the advanced transformer encoder to first learn intermediate node representations from its current state (t) and previous context (over timestamps [t–1,t–l], l is the length of context). Moreover, we employ two projection layers to generate lower-dimensional multivariate Gaussian distributions as each node's latent embedding at timestamp t. We consider diverse benchmarks with varying levels of "novelty" as measured by the TEA (Temporal Edge Appearance) plots. Here, our experiments demonstrate that the proposed TransformerG2G model outperforms conventional multi-step methods and our prior work (DynG2G) in terms of both link prediction accuracy and computational efficiency, especially for high degree of novelty. Furthermore, the learned time-dependent attention weights across multiple graph snapshots reveal the development of an automatic adaptive time stepping enabled by the transformer. Importantly, by examining the attention weights, we can uncover temporal dependencies, identify influential elements, and gain insights into the complex interactions within the graph structure. For example, we identified a strong correlation between attention weights and node degree at the various stages of the graph topology evolution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Electronic Coupling of Metal–to–Insulator Transitions in Nickelate–Based Heterostructures

In rare earth nickelates, the metal-to-insulator transition observed as a function of temperature can be described using an electronic and a structural order parameter. The electronic one is linked to the electronic disproportionation observed below the transition temperature and the structural one characterizes the breathing mode that develops in the low temperature phase. Here SmNiO 3 /NdNiO 3 superlattices are grown with insulating LaAlO 3 spacer layers to study the unusual coupling of metal-to- insulator transitions observed at SmNiO 3 /NdNiO 3 interfaces and determine the role of the two order parameters. Temperature-dependent transport measurements reveal that a single unit cell of LaAlO 3 inserted between SmNiO 3 and NdNiO 3 leads to a complete decoupling of the metal-to-insulator transitions suggesting that the order parameter controlling the coupling is the electronic one.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Time-Domain Extreme-Ultraviolet Diffuse Scattering Spectroscopy of Nanoscale Surface Phonons

Here, we report the observation of dynamic fringe patterns in the diffuse scattering of extreme ultraviolet light from surfaces, following femtosecond optical excitation. At each point on the detector, the diffuse scattering intensity exhibits oscillations at well-defined frequencies that correspond to surface phonons with wave vectors determined by the scattering geometry, indicating that the optical excitation generates coherent surface phonons propagating in all directions and spanning a wavelength range from 60 to 300 nm. This phenomenon is observed on a variety of samples, including single-layer and multilayer metal films, as well as bulk semiconductors. The measured surface phonon dispersions show good agreement with theoretical calculations. By comparing signal amplitudes from samples with different surface morphologies, we find that the excitation mechanism is linked to the natural surface roughness of the samples. However, the signal is still detectable on extremely smooth surfaces with subnanometer roughness. Our findings demonstrate a simple and effective method for optically exciting coherent surface phonons with nanoscale wavelengths on a wide range of solid samples and establish a foundation for surface phonon spectroscopy in a wave vector range well beyond the limit of conventional surface Brillouin scattering.

Capotondi, F. [Elettra-Sincrotrone Trieste (Italy)↗
DOE OSTI2021

Learning Sequential Distribution System Restoration via Graph-Reinforcement Learning

We report a distribution service restoration algorithm as a fundamental resilient paradigm for system operators provides an optimally coordinated, resilient solution to enhance the restoration performance. The restoration problem is formulated to coordinate distribution generators and controllable switches optimally. A model-based control scheme is usually designed to solve this problem, relying on a precise model and resulting in low scalability. To tackle these limitations, this work proposes a graph-reinforcement learning framework for the restoration problem. We link the power system topology with a graph convolutional network, which captures the complex mechanism of network restoration in power networks and understands the mutual interactions among controllable devices. Latent features over graphical power networks produced by graph convolutional layers are exploited to learn the control policy for network restoration using deep reinforcement learning. The solution scalability is guaranteed by modeling distributed generators as agents in a multi-agent environment and a proper pre-training paradigm. Comparative studies on IEEE 123-node and 8500-node test systems demonstrate the performance of the proposed solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Mitigation of Pitting on Nitrogen-Doped Niobium Surfaces through Two-Step Electropolishing

Surface processing of niobium superconducting RF cavities used in particle accelerators is crucial for determining their performance. The nitrogen (N)-doping method, developed at Fermilab, enhances the cavities’ quality factor by doping the cavity’s interior surface with N atoms at 800 °C. After N-doping, electropolishing (EP) is employed to remove the niobium nitride phases and attain the desired concentration of interstitial N atoms. This study explores the effects of EP conditions on N-doped niobium samples. The samples were electropolished at 5 to 40 °C and voltages between 3 and 22 V. Different EP voltage ranges produced two types of pits, classified based on their sizes. Larger pits, linked to higher voltages, are also affected by the reaction rate. Pitting could be reduced at a lower temperature and adequate EP voltage. However, to effectively minimize gas evolution forming large-sized pitting, peeling off the top nitride layer before EP might be beneficial. This was achieved through precise low-voltage etching, forming a two-step EP process. The process involves removing the top 100–200 nm layer at a low voltage, followed by standard EP to remove the required material. This two-step EP process effectively mitigated the pitting risk associated with gas evolution on N-doped surfaces.

43 PARTICLE ACCELERATORS↗