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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

HCOO - aq Degradation in Droplets by OH aq in an Atmospheric Pressure Glow Discharge

Plasmas in contact with liquids can degrade organic molecules in solution, as reactive oxygen and nitrogen species produced in the plasma solvate into the liquid. Immersing small droplets (tens of microns in diameter) in the plasma can more rapidly activate the liquid compared to treating a large volume of liquid with a smaller surface-to-volume ratio. The interactions between a radio frequency glow discharge sustained in He/H 2 O and a water droplet containing formate (HCOO - aq ) immersed in and flowing through the plasma were modeled using a 0-dimensional global plasma chemistry model to investigate these activation processes. HCOO - aq interacts with OH aq , produced from solvation of OH from the gas phase. HCOO - aq concentrations were benchmarked with previously reported experimental measurements. The diameter of the droplet, initial HCOO - aq concentration, and gas flow rate affect only the HCOO - aq concentration and OH aq density, leaving the OH density in the gas phase unaffected. Power deposition and gas mixture (e.g., percentage of H 2 O) change both the gas and liquid phase chemistry. A general trend was observed – during the first portion of droplet exposure to the plasma, OH aq primarily consumes HCOO - aq . However, O2 - aq , a byproduct of HCOO - aq consumption, consumes OH aq once O2 - aq reaches a critically large density. Using HCOO - aq as a surrogate for OH aq sensitive contaminants, combinations of residence time, droplet diameter, water vapor density, and power will determine the optimum remediation strategy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Deep learning insights into cosmological structure formation

The evolution of linear initial conditions present in the early Universe into extended halos of dark matter at late times can be computed using cosmological simulations. However, a theoretical understanding of this complex process remains elusive; in particular, the role of anisotropic information in the initial conditions in establishing the final mass of dark matter halos remains a long-standing puzzle. Here, we build a deep learning framework to investigate this question. We train a three-dimensional convolutional neural network to predict the mass of dark matter halos from the initial conditions, and quantify in full generality the amounts of information in the isotropic and anisotropic aspects of the initial density field about final halo masses. We find that anisotropies add a small, albeit statistically significant amount of information over that contained within spherical averages of the density field about final halo mass. However, the overall scatter in the final mass predictions does not change qualitatively with this additional information, only decreasing from 0.9 dex to 0.7 dex. Given such a small improvement, our results demonstrate that isotropic aspects of the initial density field essentially saturate the relevant information about final halo mass. Therefore, instead of searching for information directly encoded in initial conditions anisotropies, a more promising route to accurate, fast halo mass predictions is to add approximate dynamical information based e.g. on perturbation theory. More broadly, our results indicate that deep learning frameworks can provide a powerful tool for extracting physical insight into cosmological structure formation. Published by the American Physical Society 2024

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Reviews and syntheses: Variable inundation across Earth's terrestrial ecosystems

Abstract. The structure, function, and dynamics of Earth's terrestrial ecosystems are profoundly influenced by how often (frequency) and how long (duration) they are inundated with water. A diverse array of natural and human-engineered systems experience temporally variable inundation whereby they fluctuate between inundated and non-inundated states. Variable inundation spans extreme events to predictable sub-daily cycles. Variably inundated ecosystems (VIEs) include hillslopes, non-perennial streams, wetlands, floodplains, temporary ponds, tidal systems, storm-impacted coastal zones, and human-engineered systems. VIEs are diverse in terms of inundation regimes, water chemistry and flow velocity, soil and sediment properties, vegetation, and many other properties. The spatial and temporal scales of variable inundation are vast, ranging from sub-meter to whole landscapes and from sub-hourly to multi-decadal. The broad range of system types and scales makes it challenging to predict the hydrology, biogeochemistry, ecology, and physical evolution of VIEs. Despite all experiencing the loss and gain of an overlying water column, VIEs are rarely considered together in conceptual, theoretical, modeling, or measurement frameworks and approaches. Studying VIEs together has the potential to generate mechanistic understanding that is transferable across a much broader range of environmental conditions, relative to knowledge generated by studying any one VIE type. We postulate that enhanced transferability will be important for predicting changes in VIE function in response to global change. Here we aim to catalyze cross-VIE science that studies drivers and impacts of variable inundation across Earth's VIEs. To this end, we complement expert mini-reviews of eight major VIE systems with overviews of VIE-relevant methods and challenges associated with scale. We conclude with perspectives on how cross-VIE science can derive transferable understanding via unifying conceptual models in which the impacts of variable inundation are studied across multi-dimensional environmental space.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Remote Sensing-Informed Zonation for Understanding Snow, Plant and Soil Moisture Dynamics within a Mountain Ecosystem

In the headwater catchments of the Rocky Mountains, plant productivity and its dynamics are largely dependent upon water availability, which is influenced by changing snowmelt dynamics associated with climate change. Understanding and quantifying the interactions between snow, plants and soil moisture is challenging, since these interactions are highly heterogeneous in mountainous terrain, particularly as they are influenced by microtopography within a hillslope. Recent advances in satellite remote sensing have created an opportunity for monitoring snow and plant dynamics at high spatiotemporal resolutions that can capture microtopographic effects. In this study, we investigate the relationships among topography, snowmelt, soil moisture and plant dynamics in the East River watershed, Crested Butte, Colorado, based on a time series of 3-meter resolution PlanetScope normalized difference vegetation index (NDVI) images. To make use of a large volume of high-resolution time-lapse images (17 images total), we use unsupervised machine learning methods to reduce the dimensionality of the time lapse images by identifying spatial zones that have characteristic NDVI time series. We hypothesize that each zone represents a set of similar snowmelt and plant dynamics that differ from other identified zones and that these zones are associated with key topographic features, plant species and soil moisture. We compare different distance measures (Ward and complete linkage) to understand the effects of their influence on the zonation map. Results show that the identified zones are associated with particular microtopographic features; highly productive zones are associated with low slopes and high topographic wetness index, in contrast with zones of low productivity, which are associated with high slopes and low topographic wetness index. The zones also correspond to particular plant species distributions; higher forb coverage is associated with zones characterized by higher peak productivity combined with rapid senescence in low moisture conditions, while higher sagebrush coverage is associated with low productivity and similar senescence patterns between high and low moisture conditions. In addition, soil moisture probe and sensor data confirm that each zone has a unique soil moisture distribution. This cluster-based analysis can tractably analyze high-resolution time-lapse images to examine plant-soil-snow interactions, guide sampling and sensor placements and identify areas likely vulnerable to ecological change in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

An adaptive approach to machine learning for compact particle accelerators

Abstract Machine learning (ML) tools are able to learn relationships between the inputs and outputs of large complex systems directly from data. However, for time-varying systems, the predictive capabilities of ML tools degrade if the systems are no longer accurately represented by the data with which the ML models were trained. For complex systems, re-training is only possible if the changes are slow relative to the rate at which large numbers of new input-output training data can be non-invasively recorded. In this work, we present an approach to deep learning for time-varying systems that does not require re-training, but uses instead an adaptive feedback in the architecture of deep convolutional neural networks (CNN). The feedback is based only on available system output measurements and is applied in the encoded low-dimensional dense layers of the encoder-decoder CNNs. First, we develop an inverse model of a complex accelerator system to map output beam measurements to input beam distributions, while both the accelerator components and the unknown input beam distribution vary rapidly with time. We then demonstrate our method on experimental measurements of the input and output beam distributions of the HiRES ultra-fast electron diffraction (UED) beam line at Lawrence Berkeley National Laboratory, and showcase its ability for automatic tracking of the time varying photocathode quantum efficiency map. Our method can be successfully used to aid both physics and ML-based surrogate online models to provide non-invasive beam diagnostics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Experimental study of multiple-orientation muon tomography with image optimization in sparse data environments

Due to the high penetrating power of cosmic-ray muons, they can be used to probe very thick and dense objects. As muons are charged particles, they can be tracked by ionization detectors, determining the position and direction of the muons. With detectors on either side of an object to measure particle direction change, scattering information within the object can be found. This can be used to produce a scattering-intensity image within the object related to density and atomic number. Such imaging is typically performed with a single detector-object orientation, taking advantage of the more intense downward flux of muons, producing planar imaging with some depth-of-field information in the third dimension. Several simulation studies were published with multiorientation tomography, which can form a three-dimensional representation faster than a single-orientation view. In this study, experimental muon-scatter-based tomography was performed using a concrete filled steel drum with several different metal wedges inside, with the drum between detector planes. Data were collected from different detector-object orientations by rotating the steel drum. The data collected from each orientation were combined using two different tomographic methods. A traditional inverse Radon transform approach used for computed tomography and a combination of multiple depth-of-field reconstructions were applied to the data. As cosmic-ray muon flux imaging is rate limited, the imaging techniques were compared for sparse data. Using the combined depth-of-field reconstruction technique, fewer detector-object orientations were needed to reconstruct images that could be used to differentiate the metal wedges.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Three-dimensional fracture continuum characterization aided by surface time-domain electromagnetics and hydrogeophysical joint inversion—proof-of-concept

Efficient and safe production of hydraulically fractured reservoirs benefits from the prediction of their geometrical attributes. Geophysical methods have the potential to provide data that are sensitive to fracture geometries, alleviating the typically sparse nature of in situ reservoir observations. Moreover, surface-based methods can be logistically and economically attractive since they avoid operational interference with the injection well infrastructure. Here, we investigate the potential of the surface-based time-domain electromagnetic (EM) method. EM methods can play an important role owing to their sensitivity to injection-induced fluid property changes. Two other advantageous factors are the EM signal-enhancing effect of vertical steel-cased wells and the fact that injected proppants can be enhanced to produce a stronger electrical conductivity contrast with the reservoir’s connate fluid. Nevertheless, an optimal fracture characterization will no doubt require the integration of EM and reservoir injection and production data. We hence carry out our investigations within a hydrogeophysical parameter estimation framework where EM data and injection flow rates are combined in a fully coupled way. Given the interdisciplinary nature of coupled hydrogeophysical inverse modeling, we dedicate one section to laying out key aspects in a didactic manner.

58 GEOSCIENCES↗
DOE OSTI2023

Competing topological superconducting phases in FeSe 0.45 ⁢Te 0.55

We demonstrate that recent angle-resolved photoemission spectroscopy experiments provide strong evidence for the existence of two competing topological superconducting phases in FeSe 0.45⁢ Te 0.55 . The coupling of their underlying microscopic mechanisms—one based on a three-dimensional topological insulator, one based on two-dimensional superconductivity—stabilizes topological superconductivity over a wide range of parameters, and gives rise to two disjoint topological regions in the phase diagram of FeSe 0.45 ⁢Te 0.55 . Here, we show that the topological origin of these regions can be identified by considering the form of Majorana edge modes at domain walls.

Angle-resolved photoemission spectroscopy↗
DOE OSTI2020

Holographic map for cosmological horizons

Here, we propose a holographic map between Einstein gravity coupled to matter in a de Sitter background and large N quantum mechanics of a system of spins. Holography maps a spin model with a finite-dimensional Hilbert space defined on a version of the stretched horizon into bulk gravitational dynamics. The full Hamiltonian of the spin model contains a nonlocal piece which generates chaotic dynamics, widely conjectured to be a necessary part of quantum gravity, and a local piece which recovers the perturbative spectrum in the bulk.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Effects of unburnt reaction progress on stretch flame dynamics under elevated temperatures

Flames in practical combustors and engines are inevitably subject to the effects of upstream chemical reaction progress and stretch, induced by elevated thermodynamic conditions and flow non-uniformities, respectively. Recent shock tube experiments and simulation studies on flame propagation have shown that flame speed under engine-relevant conditions can be enhanced with non-negligible upstream chemical reaction progress, especially when low-temperature heat release is involved in the unburnt mixture. On the other hand, depending on the mixture equivalence ratio and diluents, nonequidiffusion (including the non-unity Lewis number effect and the preferential diffusion effect) can couple with the flame stretch to fundamentally affect the flame propagation, which can manifest as either facilitation or suppression. Depending on the transport property of a reacting mixture, there hence can be either inhibition or promotion from unburnt reaction progress and stretch effects on flame propagation. In the current work, through one-dimensional numerical simulations of transient planar and spherical flames of n-heptane/air under elevated thermodynamic conditions, the combined effects of upstream chemical reaction progress and stretch on flame propagation are investigated. Results show that for both lean and rich n-heptane/air mixtures, flame speed can be substantially promoted with reaction progress, while the rich mixtures can exhibit opposite stretch dependence after first-stage ignition. Different definitions of effective Lewis number are adopted to explain the change in Markstein length for spherical flame in lean and rich mixtures reformed by the low temperature chemistry. Further, this work fills an important gap in laminar premixed flame research relevant to practical combustion systems and can provide useful insight into local turbulent flame behaviors and phi-sensitivity in engine combustion.

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

Room-Temperature Pseudo-Solid-State Iron Fluoride Conversion Battery with High Ionic Conductivity

Li-metal batteries (LMBs) employing conversion cathode materials (e.g., FeF 3 ) are a promising way to prepare inexpensive, environmentally friendly batteries with high energy density. Pseudo-solid-state ionogel separators harness the energy density and safety advantages of solid-state LMBs, while alleviating key drawbacks (e.g., poor ionic conductivity and high interfacial resistance). In this work, a pseudo-solid-state conversion battery (Li-FeF 3 ) is presented that achieves stable, high rate (1.0 mA cm –2 ) cycling at room temperature. The batteries described herein contain gel-infiltrated FeF 3 cathodes prepared by exchanging the ionic liquid in a polymer ionogel with a localized high-concentration electrolyte (LHCE). The LHCE gel merges the benefits of a flexible separator (e.g., adaptation to conversion-related volume changes) with the excellent chemical stability and high ionic conductivity (~2 mS cm –1 at 25 °C) of an LHCE. The latter property is in contrast to previous solid-state iron fluoride batteries, where poor ionic conductivities necessitated elevated temperatures to realize practical power levels. Importantly, the stable, room-temperature Li-FeF 3 cycling performance obtained with the LHCE gel at high current densities paves the way for exploring a range of architectures including flexible, three-dimensional, and custom shape batteries.

25 ENERGY STORAGE↗
DOE OSTI2025

Three-dimensional core-collapse supernova models with phenomenological treatment of neutrino flavor conversions

Abstract We perform three-dimensional supernova simulations with a phenomenological treatment of neutrino flavor conversions. We show that the explosion energy can increase to as high as $\sim 10^{51}$ erg depending on the critical density for the onset of flavor conversions, due to a significant enhancement of the mean energy of electron antineutrinos. Our results confirm previous studies showing such energetic explosions, but for the first time in three-dimensional configurations. In addition, we predict neutrino and gravitational wave (GW) signals from a nearby supernova explosion aided by flavor conversions. We find that the neutrino event number decreases because of the reduced flux of heavy-lepton neutrinos. In order to detect GWs, next-generation GW telescopes such as Cosmic Explorer and the Einstein Telescope are needed even if the supernova event is located at the Galactic Center. These findings show that the neutrino flavor conversions can significantly change supernova dynamics and highlight the importance of further studies on the quantum kinetic equations to determine the conditions of the conversions and their asymptotic states.

Mori, Kanji↗
DOE OSTI2026

Closure models for the feedback of energetic particles on plasma turbulence

Energetic particles interact with the plasma surrounding them, resonating with certain types of plasma waves to stabilize them while destabilizing others, and changing the character of the background turbulence in ways that have not been fully quantified or understood. Interaction with the turbulent background plasma is key to the acceleration of many types of energetic particles including high-energy cosmic rays, solar energetic particles, and pick-up ions. The acceleration of particles is a process that would ideally be described by a kinetic model, a type of model that follows a probability distribution function (PDF) for all particles in 7-dimensional (x, y, z, v x , v y , v z , t) space. Because of the high dimensionality of a kinetic model, simulations that solve kinetic equations use the largest computational resources currently available, and are yet unable to simulate a realistic number of particles, reach the large scales necessary for astrophysical problems, and use high-precision numerical methods. Two available alternatives to kinetic plasma models have been explored for this problem, with limited success. One is a multi-fluid model produced by a cumulant discarding closure, which evolves coupled equations for the velocity, magnetic field, and internal energy for both the background plasma and the fluid of energetic particles. However, simulations that solve multi-fluid magnetohydrodynamic (MHD) equations are able to include the interaction with energetic particles only in crude ways, typically as an add-on pressure term. The second alternative is to use a hybrid method to couple a fluid description of the background plasma to a kinetic model or a Fokker–Planck model for the energetic particles. These methods are hampered by the physical modeling of the coupling. In this work, we develop a new model, which follows the PDF for all particles; this can be viewed as a step toward physical realism above a multi-fluid MHD model, while also being more computationally efficient than a kinetic model. The equations we develop model both the background plasma and the energetic particles self-consistently. Over the last decade, similar PDF methods have been developed to a high level of sophistication to model reactive flows and turbulent combustion for engineering applications. For treatment of the feedback of the energetic particles on a background plasma, a PDF closure approach should evaluate the mean characteristics, including the density, with better statistical quality than will particle-sampling procedures.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Semiconductor to Topological Insulator Transition Induced by Stress Propagation in Metal Dichalcogenides Core-Shell Lateral Heterostructures

Polymorphic phase transition is an important route for engineering the properties of two-dimensional materials. Heterostructure construction, on the other hand, not only allows the integration of different functionalities for device applications, but also enables the exploration of new physics arising from proximity coupling. Yet, implementing a design that incorporates the advantages of both remains underexplored. Here in this paper, based on comprehensive experimental and theoretical studies of WSe 2 /SnSe 2 core-shell lateral heterostructure, we demonstrate an unexpected H to T' phase transition in transition metal dichalcogenides (TMDs), correlating to a change of materials properties from semiconductor to topological insulator (TI), and propose a novel shell-to-core stress propagation mechanism. This finding offers new insights into TMD phase transition empowered by the rational design of heterostructures. Owing to the superconducting properties of SnSe 2 at low temperatures, the unique TI/superconductor core-shell template is expected to add more arsenals to the ongoing search of Majorana fermions in condensed matter systems.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Thermal Frequency Drift of 3D Printed Microwave Components

Fabrication of microwave slot array antennas and waveguide bandpass and notch filters using 3D printing has significant advantages in terms of speed and cost even for parts with high mechanical complexity. One disadvantage of Stereolithography (SLA) 3D printed, copper plated microwave components is that some SLA resins have a high Coefficient of Thermal Expansion (CTE), quoted in micrometers per meter per degree or 10 -6 per degree. Compared to typically used metals such as aluminum (CTE 24 × 10 -6 ·K -1 ) and copper (CTE 17 × 10 -6 ·K -1 ), SLA resin can have CTE above 100 × 10 -6 ·K -1 . Resonant structures experience significant frequency drift with temperature changes on the order of 10–50 °C. The issue of 3D printed microwave structures changing frequency characteristics significantly with temperature shift has not been addressed or reviewed in current literature. We measured and simulated the effect of temperature change on a slot array, cavity notch filters, and post loaded waveguide bandpass filters. We tested several types of SLA resin, different plating techniques, and also Direct Metal Laser Sintering (DMLS) and Binder Infusion metal 3D printing. Performance as a function of temperature is presented for these alternatives.

three-dimensional printing↗
DOE OSTI2025

Simulation of Binary-single Interactions in AGN Disk. I. Gas-enhanced Binary Orbital Hardening

Stellar-mass binary black hole (BBH) mergers within the accretion disks of active galactic nuclei may contribute to gravitational wave (GW) events detected by ground-based GW detectors. In particular, the interaction between a BBH and a single stellar-mass black hole (sBH), known as the binary-single interaction (BSI) process, can potentially lead to GW events with detectable nonzero eccentricity. Previous studies of the BSI process, which neglected the effects of gas, showed that BSIs contribute non-negligibly to GW events in a coplanar disk environment. In this work, we conduct a series of two-dimensional hydrodynamical and N-body simulations to explore the BSI in a gas environment by coupling REBOUND with Athena++. We perform 360 simulation runs, spanning parameters in disk surface density Σ 0 and impact parameter b. We find that the gas-induced energy dissipation within the three-body system becomes significant if the encounter velocity between the sBHs is sufficiently large (≫c s ). Our simulation results indicate that approximately half of the end states of the BSI are changed by gas. Furthermore, at higher gas density, the number of close encounters during the BSI process will increase, and the end-state BBHs tend to be more compact. Consequently, the presence of gas may shorten the GW merger timescale for end-state BBHs and increase the three-body merger rate.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Atomic-Scale Andreev Probe of Unconventional Superconductivity

Recent emergence of low-dimensional unconventional superconductors and their exotic interface properties calls for new approaches to probe the pairing symmetry, a fundamental and frequently elusive property of the superconducting condensate. Here, we introduce the unique capability of tunneling Andreev reflection (TAR) to probe unconventional pairing symmetry, utilizing the sensitivity of this technique to specific Andreev reflections. Specifically, suppression of the lowest-order Andreev reflection due to quantum interference but emergence of the higher-order Andreev processes provides direct evidence of the sign-changing order parameter in the paradigmatic FeSe superconductor. Furthermore, TAR spectroscopy also reveals two superconducting gaps, points to a possibility of a nodal gap structure, and directly confirms that superconductivity is locally suppressed along the nematic twin boundary, with preferential and near-complete suppression of the larger energy gap. Furthermore, our findings therefore enable new, atomic-scale insight into microscopic, inhomogeneous, and interfacial properties of emerging quantum materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Full-waveform tomography reveals iron spin crossover in Earth’s lower mantle

Abstract Three-dimensional models of Earth’s seismic structure can be used to identify temperature-dependent phenomena, including mineralogical phase and spin transformations, that are obscured in 1-D spherical averages. Full-waveform tomography maps seismic wave-speeds inside the Earth in three dimensions, at a higher resolution than classical methods. By providing absolute wave speeds (rather than perturbations) and simultaneously constraining bulk and shear wave speeds over the same frequency range, it becomes feasible to distinguish variations in temperature from changes in composition or spin state. We present a quantitative joint interpretation of bulk and shear wave speeds in the lower mantle, using a recently published full-waveform tomography model. At all depths the diversity of wave speeds cannot be explained by an isochemical mantle. Between 1000 and 2500 km depth, hypothetical mantle models containing an electronic spin crossover in ferropericlase provide a significantly better fit to the wave-speed distributions, as well as more realistic temperatures and silica contents, than models without a spin crossover. Below 2500 km, wave speed distributions are explained by an enrichment in silica towards the core-mantle boundary. This silica enrichment may represent the fractionated remains of an ancient basal magma ocean.

58 GEOSCIENCES↗