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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 1,171 records · Page 65

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DOE OSTI2023

Emergent topological quantum orbits in the charge density wave phase of kagome metal CsV 3 Sb 5

The recently discovered kagome materials AV 3 Sb 5 (A = K, Rb, Cs) attract intense research interest in intertwined topology, superconductivity, and charge density waves (CDW). Although the in-plane 2 × 2 CDW is well studied, its out-of-plane structural correlation with the Fermi surface properties is less understood. In this work, we advance the theoretical description of quantum oscillations and investigate the Fermi surface properties in the three-dimensional CDW phase of CsV 3 Sb 5 . We derived Fermi-energy-resolved and layer-resolved quantum orbits that agree quantitatively with recent experiments in the fundamental frequency, cyclotron mass, and topology. We reveal a complex Dirac nodal network that would lead to a π Berry phase of a quantum orbit in the spinless case. However, the phase shift of topological quantum orbits is contributed by the orbital moment and Zeeman effect besides the Berry phase in the presence of spin-orbital coupling (SOC). Therefore, we can observe topological quantum orbits with a π phase shift in otherwise trivial orbits without SOC, contrary to common perception. Our work reveals the rich topological nature of kagome materials and paves a path to resolve different topological origins of quantum orbits.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Studying the effect of phenyl group content on the physical properties of un-crosslinked PDMS (Progress Summary)

Over the last couple of years, the emphasis on our A&L efforts has been on developing a thermal-age-aware constitutive model for foam cushions. From our studies so far, it appears that an $N = 2$ Ogden hyperfoam model within the framework of a two-network Tobolsky scheme is appropriate to describe the age-aware stress-strain response of both stochastic and additively manufactured (AM) foams. The models have so far been fitted only to a limited number of silicone-based materials systems, i.e., M97 and M9763 stochastic foams and AM foams made of SE1700 rubber. As we explore new and different rubber formulations for improved structural as well as A&L properties, we find it important to develop a deeper understanding of the effect of functional groups on the physical, mechanical, and flow properties of the constituent elastomer. To this end, in Q2 FY19, we have begun a project on multiscale modeling of polymers that realistically incorporates from bond-level dynamics to terminal dynamics of whole chains (e.g., tube dynamics). In such mesoscale simulations the polymer tube dynamics is modeled through coarse-graining of monomers to mesoscale “beads”, with the bead-bead potential being systematically fitted to accurate atomic-level forcefields. The aim of this collaboration is to develop a fully physical constitutive model that predicts the mechanical response of polymers of our interest based on structure and modeled dynamics alone.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Embedding Neural Thermal Scattering (NeTS) Modules in SERPENT for Higher Fidelity Advanced Reactor Analysis

When a neutron born in fission thermalizes to the order of $k$ $B$ $T$, it’s de-Broglie wavelength and energy approach the order of inter-atomic spacing and elementary lattice oscillations, respectively. $S$($a,β,t$) or the scattering law, uuantify these temperature-dependent crystallographic contributions to total cross section (or reaction rate). In a Monte Carlo analysis, cumulative distribution functions (CDFs) of $S$($a,β,t$) are loaded to memory from “A Compact ENDF” (ACE) files for stochastically selecting thermal scattered neutron trajectories. In this work, novel neural thermal scattering (NeTS) modules for $S$($a,β,t$) CDFs are designed, trained, serialized and embedded within SERPENT using Python’s limited C-API for on-the-fly deployment of crystalline graphite $S$($a,β,t$) sampling. Torchscript tracing and Numba just-in-time (JIT) compilation streamline neural inference on NVIDIA GPUs with CUDA libraries. Demonstrations of bare sphere thermalization of fast and thermal sources show excellent agreement between embedded NeTS in SERPENT and MCNP. With an explicit model of the reactor, NeTS can predict on-the-fly changes in TREAT neutron spectra as a function of local temperature, which can serve to improve transient and accident predictions in a multiphysics analysis framework. This framework can be further extended to account on-the-fly for changes in local graphitic microstructure to scattering cross sections, and outlines a novel coupling of modern machine learning with state-of-the-art reactor physics methods.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Application of an Embedded Fracture and Borehole Modeling Approach to the Understanding of EGS Collab Experiment 1

EGS Collab is a series of meso-scale experiments and associated numerical simulation activities being funded by the United States Department of Energy, Geothermal Technologies Office (GTO) to investigate enhanced geothermal system processes under in-situ stress and slightly elevated temperature conditions. This project is designed to provide scientists and engineers with immediate access to impermeable rock at scales larger than possible in the laboratory, but generally smaller than those for commercial production. Immediate access to rock is provided via the existing drifts of the former Homestake Gold Mine, now operated as the Sanford Underground Research Facility in Lead, South Dakota. The objectives of the EGS Collab project are to develop well controlled fracture networks between injector and producer boreholes using normal and shear stimulation for permeability enhancement. The first experimental site was located off the West Access drift on the 4850 Level (4850 feet below ground surface) in phyllite of the Precambrian Poorman formation, and involved the creation of a fracture network comprising a combination of hydraulic and natural fractures. A second experimental site is now being considered near the battery alcove on the 4100 Level in amphibolite and rhyolite of the Yates Unit. Data generated during these experiments will be compared against predictions of a suite of computer codes specifically designed to solve problems involving coupled thermal, hydrological, geomechanical, and geochemical processes. Comparisons between experimental and numerical simulation results will provide code developers with direction for improvements and verification of process models, build confidence in the suite of available numerical tools, and ultimately identify critical future development needs for the geothermal modeling community. Moreover, conducting thorough comparisons of models, modelling approaches, measurement approaches and measured data, via the EGS Collab project, will serve to identify techniques that are most likely to succeed at the Frontier Observatory for Research in Geothermal Energy (FORGE), the GTO’s flagship EGS research effort. Experiment 1 has comprised a series of successful tests, including a long-term chilled-water circulation test, but the testbed has two atypical EGS elements. Active ventilation in the adjacent drift over a 50-year period cooled the testbed rock mass and hydraulic fracturing intersected monitoring boreholes making them conduits for fluid flow. Numerical simulations executed in support of the design of the EGS Collab Experiment 1, computed a radial temperature distribution and stress gradient orthogonal to the drift axis, resulting in the forecast of an oblong hydraulic fracture geometry, extended in the direction of the drift from the stimulation borehole. This paper describes the numerical simulation of long-term chilled-water circulation test with an embedded fracture and borehole modeling approach. The principal objective of the simulation work is show agreement between experimental observations in terms of production fluid temperatures, monitoring borehole temperatures, injection and production pressures, and tracer recoveries using a single conceptual model for the fracture network, using characterization and monitoring data generally available for EGS. A secondary objective is to improve the numerical simulation result comparisons with additional data available from the broader monitoring equipment within the testbed versus deeper, hotter, and more remote EGS. One complicating factor for comparisons between the numerical simulation results and experimental observations, is the Joule-Thomson heating associated with large pressure drops across the fracture network.

numerical simulation, embedded fractures and boreh↗

DOE OSTI2025

Coupled Lake‐Atmosphere‐Land Physics Uncertainties in a Great Lakes Regional Climate Model

Abstract This study develops a surrogate‐based method to assess the uncertainty within a convective permitting integrated modeling system of the Great Lakes region, arising from interacting physics parameterizations across the lake, atmosphere, and land surface. Perturbed physics ensembles of the model during the 2018 summer are used to train a neural network surrogate model to predict lake surface temperature (LST) and near‐surface air temperature (T2m). Average physics uncertainties are determined to be 1.5C for LST and T2m over land, and 1.9C for T2m over lake, but these have significant spatiotemporal variations. We find that atmospheric physics parameterizations alone are the dominant sources of uncertainty (45%–53%), while lake and land parameterizations account for 33% and 38% of the uncertainty of LST and T2m over land respectively. Interactions of atmosphere physics parameterizations with those of the land and lake contribute to an additional 13%–17% of the total variance. LST and T2m over the lake are more uncertain in the deeper northern lakes, particularly during the rapid warming phase that occurs in late spring/early summer. The LST uncertainty increases with sensitivity to the lake model's surface wind stress scheme. T2m over land is more uncertain over forested areas in the north, where it is most sensitive to the land surface model, than the more agricultural land in the south, where it is most sensitive to the atmospheric planetary boundary and surface layer scheme. Uncertainty also increases in the southwest during multiday temperature declines with higher sensitivity to the land surface model.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

High-Performance Near-Infrared Quantum Emission from Color Centers in hBN

Color centers hosted in hexagonal boron nitride (hBN) have emerged as a highly promising platform for single-photon emission and spin-photon technologies relevant to quantum communication and quantum networking. As a wide bandgap van der Waals material, hBN can host optically active quantum defects across a broad spectral range. Here, we demonstrate a simple and scalable oxygen-plasma process that reproducibly creates single quantum emitters in hBN with blinking-free zero-phonon lines (ZPLs) spanning near-infrared (NIR) from 700 up to 971 nm. These emitters combine MHz-level brightness, single-photon purity up to 99.9%, and ultranarrow cryogenic line widths down to 2.7 GHz under quasi-resonant excitation, placing them in a particularly attractive regime for quantum photonics. Photostability measurements further reveal resistance to photobleaching, subnanometer spectral stability over long time scales, and near-shot-noise-limited intensity fluctuations. Analysis of the phonon sidebands shows weak vibronic coupling and ZPL-dominated emission, with Debye–Waller factors approaching 50%. Control experiments together with elemental mapping support oxygen incorporation as a necessary ingredient in activating the NIR emitter population, while first-principles calculations identify O N V N and O N V N H as the leading defect candidates. These results establish a high-performance NIR quantum-emitter platform in hBN for free-space quantum networking and future integrated quantum-photonic architectures.

2D materials↗

DOE OSTI2024

Flexible Soft X-Ray Image Sensors based on Metal Halide Perovskites With High Quantum Efficiency

Soft X-ray imaging is a powerful tool to explore the structure of cells, probe material with nanometer resolution, and investigate the energetic phenomena in the universe. Conventional soft X-ray image sensors are by and large Si-based charge coupled devices that suffer from low frame rates, complex fabrication processes, mechanical inflexibility, and required cooling below -60 °C. Here, a soft X-ray photodiode is reported based on low-cost metal halide perovskite with comparable performance to commercial Si-based device. Nanothrough network electrode minimized the optical loss due to the shadowing of insensitive layers, while a multidimensional perovskite heterojunction is generated to reduce the photo-generated carrier loss. Further, this strategy promoted a record quantum efficiency of 8 × 10 3 % without cooling, several orders of magnitude greater than the previously achieved. Flexible and curved soft X-ray imaging arrays are fabricated based on this high-performance device structure, demonstrating stable soft X-ray response and sharp imaging capabilities. This work highlights the low-cost and efficient perovskite photodiode as a strong candidate for the next-generation soft X-ray image sensors.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Multiple Lattice Instabilities and Complex Ground State in Cs 2 Ag Bi Br 6

Metal-halide perovskites (MHPs) are attracting considerable interest for optoelectronic applications, with Cs 2 Ag Bi Br 6 one of the main contenders among lead-free systems. Cs 2 Ag Bi Br 6 crystallizes in a nominally double-perovskite structure, but exhibits a soft lattice with large atomic fluctuations characteristic of MHPs. While crucial to understand electron-phonon and phonon-phonon couplings, the spatiotemporal correlations of these fluctuations remain largely unknown. Here, we reveal these correlations using comprehensive neutron and x-ray scattering measurements on Cs 2 Ag Bi Br 6 single crystals, complemented with first-principles simulations augmented with machine-learned neural-network potentials. We report the discovery of an unexpected complex modulated ground-state structure containing several hundred atoms, arising from a soft-phonon instability of the low-temperature tetragonal phase. Further, our experiments and simulations both reveal extensive correlated two-dimensional fluctuations of Br octahedra at finite temperature, arising from soft optic phonons that are strongly broadened by anhamonicity, reflecting very shallow potential wells. These results provide new insights into the atomic structure and fluctuations in MHPs, critical to understand and control their thermal and optoelectronic properties. Published by the American Physical Society 2024

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Deep learning classification of lipid droplets in quantitative phase images

We report the application of supervised machine learning to the automated classification of lipid droplets in label-free, quantitative-phase images. By comparing various machine learning methods commonly used in biomedical imaging and remote sensing, we found convolutional neural networks to outperform others, both quantitatively and qualitatively. We describe our imaging approach, all implemented machine learning methods, and their performance with respect to computational efficiency, required training resources, and relative method performance measured across multiple metrics. Overall, our results indicate that quantitative-phase imaging coupled to machine learning enables accurate lipid droplet classification in single living cells. As such, the present paradigm presents an excellent alternative of the more common fluorescent and Raman imaging modalities by enabling label-free, ultra-low phototoxicity, and deeper insight into the thermodynamics of metabolism of single cells.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

One-Pot Aqueous and Template-Free Synthesis of Mesoporous Polymeric Resins

This report explores the novel one-pot aqueous phase synthesis of mesoporous phenolic-hyperbranched polyethyleneimine resins without the use of a template, and their utility as heterogeneous catalysts in batch reactors and continuous microreactors. Catalyst surface areas of up to 432 m 2 /g were achieved with a uniform Pd distribution and an interconnected, highly porous, network structure, confirmed through Brunauer–Emmett–Teller (BET) surface area measurements, scanning electron microscopes (SEM), X-Ray Photoelectron Spectroscopy (XPS), Transmission Electron Microscopy (TEM), and Energy-dispersive X-ray spectroscopy (EDS). The heterogeneous catalysts achieved a maximum 98.98 ± 1% conversion in batch Suzuki couplings, with conversions being dependent upon reaction conditions, reactant chemistries, Pd loading and catalyst surface area. The catalysts were shown to be recyclable with only a marginal loss in conversion achieved after five runs. Up to 62 ± 5% and 46.5 ± 8% conversions at 0.2 mL/s and 0.4 mL/s flow rates, respectively, were achieved in a continuous microreactor. Understanding the mechanism of action of this mesoporous resin is a future research area, which could help expand the application vistas for this catalyst platform.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1987

Design considerations for the beamwaveguide retrofit of a ground antenna station

A primary requirement of the NASA Deep Space Network (DSN) is to provide for optimal reception of very low signal levels. This requirement necessitates optimizing the antenna gain to the total system operating noise level quotient. Low overall system noise levels of 16 to 20 K are achieved by using cryogenically cooled preamplifiers closely coupled with an appropriately balanced antenna gain/spillover design. Additionally, high-power transmitters (up to 400 kW CW) are required for spacecraft emergency command and planetary radar experiments. The frequency bands allocated for deep space telemetry are narrow bands near 2.1 and 2.3 GHz (Ka-band), 7.1 and 8.4 GHz (X-band), and 32 and 34.5 GHz (Ka-band). In addition, planned operations for the Search for Extraterrestrial Intelligence (SETI) program require continuous low-noise receive coverage over the 1 to 10 GHz band. To summarize, DSN antennas must operate efficiently with low receive noise and high-power uplink over the 1 to 35 GHz band.

Veruttipong, T.↗

NASA NTRS2000

Neural Network and Response Surface Methodology for Rocket Engine Component Optimization

The goal of this work is to compare the performance of response surface methodology (RSM) and two types of neural networks (NN) to aid preliminary design of two rocket engine components. A data set of 45 training points and 20 test points obtained from a semi-empirical model based on three design variables is used for a shear coaxial injector element. Data for supersonic turbine design is based on six design variables, 76 training, data and 18 test data obtained from simplified aerodynamic analysis. Several RS and NN are first constructed using the training data. The test data are then employed to select the best RS or NN. Quadratic and cubic response surfaces. radial basis neural network (RBNN) and back-propagation neural network (BPNN) are compared. Two-layered RBNN are generated using two different training algorithms, namely solverbe and solverb. A two layered BPNN is generated with Tan-Sigmoid transfer function. Various issues related to the training of the neural networks are addressed including number of neurons, error goals, spread constants and the accuracy of different models in representing the design space. A search for the optimum design is carried out using a standard gradient-based optimization algorithm over the response surfaces represented by the polynomials and trained neural networks. Usually a cubic polynominal performs better than the quadratic polynomial but exceptions have been noticed. Among the NN choices, the RBNN designed using solverb yields more consistent performance for both engine components considered. The training of RBNN is easier as it requires linear regression. This coupled with the consistency in performance promise the possibility of it being used as an optimization strategy for engineering design problems.

Vaidyanathan, Rajkumar↗

NASA NTRS2003

Shuttle Payload Ground Command and Control: An Experiment Implementation Combustion Module-2 Software Development, STS-107

This presentation covers the design of a command and control architecture developed by the author for the Combustion Module-2 microgravity experiment, which flew aboard the STS-107 Shuttle mission, The design was implemented to satisfy a hybrid network that utilized TCP/IP for both the onboard segment and ground segment, with an intermediary unreliable transport for the space to ground segment. With the infusion of Internet networking technologies into Space Shuttle, Space Station, and spacecraft avionics systems, comes the need for robust methodologies for ground command and control. Considerations of high bit error links, and unreliable transport over intermittent links must be considered in such systems. Internet protocols applied to these systems, coupled with the appropriate application layer protections, can provide adequate communication architectures for command and control. However, there are inherent limitations and additional complexities added by the use of Internet protocols that must be considered during the design. This presentation will discuss the rationale for the: framework and protocol algorithms developed by the author. A summary of design considerations, implantation issues, and learned lessons will be will be presented. A summary of mission results using this communications architecture will be presented. Additionally, areas of further needed investigation will be identified.

Carek, David Andrew↗

NASA NTRS2019

Explicit IMF B(sub y)-Effect Maximizes at Subauroral Latitudes (Dedicated to the Memory of Eigil Friis-Christensen)

The most important parameter in the coupling between solar wind and geomagnetic activity is the B(sub z)‐component of the interplanetary magnetic field (IMF). However, recent studies have shown that IMF B(sub y) is an additional, independent driver of geomagnetic activity. We use here local geomagnetic indices from a large network of magnetic stations to study how IMF B(sub y) affects geomagnetic activity at different latitudes for all solar wind and, separately, during coronal mass ejections. We show that geomagnetic activity, for all solar wind, is 20% stronger for B(sub y) > 0 than for B(sub y) < 0 at subauroral latitudes of about 60° corrected geomagnetic latitude. During coronal mass ejections, the B(sub y)‐effect is larger, about 40%, at slightly lower latitudes of about 57° (corrected geomagnetic) latitude. These results highlight the importance of the IMF B(sub y)‐component for space weather at different latitudes and must be taken into account in space weather modeling

Holappa, L.↗

DOE OSTI2020

Coordinated net-load management

A management device includes at least one processor communicatively coupled to at least one energy resource controller controlling at least one energy resource and to at least one deferrable load controller controlling power to at least one deferrable load. The is configured to receive an indication, determined based on a frequency value of an electrical network and a nominal frequency value, that a frequency anomaly event has occurred. Responsive to receiving the indication that the frequency anomaly event has occurred, the processor is also configured to determine, for at least one of the energy resource and the deferrable load, based on the frequency value, the nominal frequency value, and a power value of the electrical network, a respective power command, and cause at least one of the at least one energy resource and the at least one deferrable load to modify operation based on the respective power command.

42 ENGINEERING↗

DOE OSTI2022

Coordinated net-load management

Lundstrom, Blake Richard↗

DOE OSTI2021

Synergistic Coupling of CO2 and H2O during Expansion of Clays in Supercritical CO2-CH4 Fluid Mixtures

A combination of in operando IR and XRD methods were used to investigate the interaction of variably hydrated supercritical CO2-CH4 fluids with Na/NH4/Cs substituted montmorillonites. Comparing the behavior of Na-clay exposed to CH4 versus CO2 dominant fluid phases demonstrated that CO2 disrupts the H-bond network of intercalated H2O. At relatively low potentials of H2O, CO2 facilitates H2O intercalation and expansion of the interlayer region of the Na-clay. In contrast, CO2 inhibited H2O intercalation but promoted expansion of the Cs-clay. The NH4-clay displayed intermediated behavior. Methane likely intercalated the clays but opportunistically, filling unoccupied space after CO2 and H2O actively expanded the interlayer region. By comparing and contrasting the behavior of the Cs and NH4 clays to the Na Clay we conclude that, whereas H2O is required for initial Na-clay expansion, CO2 synergistically facilitated expansion and hydration of Na-clay by mixing with H2O (the entropic contribution) and participating in the outer solvation sphere of Na (the enthalpic contribution). In contrast, CO2 can directly solvate interlayer Cs and NH4 and cause expansion in the absence of H2O; nonetheless, H2O and CO2 also act synergistically to facilitate expansion of the Cs and NH4 clays at low H2O concentrations.

Loring, John S.↗

DOE OSTI2020

Perfect quantum state transfer on diamond fractal graphs

In the quest for designing novel protocols for quantum information and quantum computation, an important goal is to achieve perfect quantum state transfer for systems beyond the well-known one- dimensional cases, such as 1D spin chains. Here, we use methods from fractal analysis and probability to find a new class of quantum spin chains on fractal-like graphs (known as diamond fractals) which support perfect quantum state transfer and which have a wide range of different Hausdorff and spectral dimensions. The resulting systems are spin networks combining Dyson hierarchical model structure with transverse permutation symmetries of varying order.

97 MATHEMATICS AND COMPUTING↗