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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Dynamic, hollow nanotubular networks with superadjustable pH-responsive and temperature resistant rheological characteristics

Recently, the interest in stimuli-responsive and adaptable materials has continuously grown in various fields and applications. For such responsive systems, different triggers, including pH, light, pressure, temperature, and electric field, have been utilized to control dynamics and assembly. Among these, pH is one of the most convenient, energy-efficient, and economic modalities. Besides, plenty of traditional materials have poor thermal and salt stability, limiting their applications. Herein, we report a new design of a pH-responsive viscoelastic supramolecular complex (VSC) based on commplexation of a new long-chain amino-amide and maleic acid. In this study, the system demonstrated a sol–gel-sol transition from pH 2 to 10, with the largest static viscosity occurring at pH 6 (~1000 Pa·s) and the smallest viscosity at pH 4 (~3.3 Pa·s), indicating ~ 300-fold control over the viscosity. For a given concentration, the static viscosity of VSC was about 15 times larger than that of CTAB/NaSal, a well-established dynamic viscoelastic system, and no pH-responsiveness was observed for the traditional system. In addition, the VSC demonstrated a superior temperature tolerance and lower temperature dependence. The potential of these intriguing dynamics viscoelastic systems was evaluated for hydraulic fracturing and enhanced oil recovery applications. Proppant settling velocity of DMAA/MA was 500 ~ 1000 times lower than that of CTAB/NaSal and common traditional polymers. Likewise, the oil recovery percentage could be significantly improved with the utilization of DMAA/MA compared to the CTAB/NaSal (86 % vs 52 %). Aside from applications in hydraulic fracturing and enhanced oil recovery, we anticipate that the intriguing rheological properties of this viscoelastic system can be beneficial for other chemical engineering applications including personal care products, cosmetics, lubricants, and biomedical gels.

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

Bridging microscale to macroscale mechanical property measurements of FeCrAl alloys by crystal plasticity modeling

FeCrAl alloys are candidates for accident tolerant fuel cladding of light water reactors. In this work, a microstructure- and temperature-dependent crystal plasticity model is employed to bridge microscale to macroscale mechanical property measurements of FeCrAl alloys. With the visco-plastic self-consistent (VPSC) polycrystal plasticity framework, a mechanism-based single crystal plasticity (MSCP) model adopts the Arrhenius type rate equation to describe the dependence of the critical resolved shear stress for dislocation slips on their temperature-dependent intrinsic frictional resistance and the microstructure-dependent irradiation hardening. The intrinsic frictional resistance associated with {110}<111> and {112}<111> slip systems were measured by in-situ micromechanical testing on unirradiated/irradiated samples at 25-500 °C. The irradiation hardening is estimated by the Bacon-Kocks-Scattergood (BKS) model with density and size of radiation-induced defects measured from microstructural characterization. Several features associated with thermo-mechanical behavior of unirradiated/irradiated polycrystalline FeCrAl alloys are captured. High density of deformation-induced dislocations and radiation-induced defects results in obvious hardening at room temperature, which is weakened at high temperature, and facilitates damage evolution during deformation. Moreover, both high temperature and radiation-induced defects, which facilitate dislocation multiplication, trigger large hardening rate. Finally, the proposed method together with application of accelerator-based ion irradiation technique is a surrogate approach to simulate neutron damage, improving the efficiency associated with evaluation of mechanical properties of FeCrAl alloys exposed to temperature, stress and radiation conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

DDxNet: a deep learning model for automatic interpretation of electronic health records, electrocardiograms and electroencephalograms

Effective patient care mandates rapid, yet accurate, diagnosis. With the abundance of non-invasive diagnostic measurements and electronic health records (EHR), manual interpretation for differential diagnosis has become time-consuming and challenging. This has led to wide-spread adoption of AI-powered tools, in pursuit of improving accuracy and efficiency of this process. While the unique challenges presented by each modality and clinical task demand customized tools, the cumbersome process of making problem-specific choices has triggered the critical need for a generic solution to enable rapid development of models in practice. In this spirit, we develop DDxNet, a deep architecture for time-varying clinical data, which we demonstrate to be well-suited for diagnostic tasks involving different modalities (ECG/EEG/EHR), required level of characterization (abnormality detection/phenotyping) and data fidelity (single-lead ECG/22-channel EEG). Using multiple benchmark problems, we show that DDxNet produces high-fidelity predictive models, and sometimes even provides significant performance gains over problem-specific solutions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Site-decorated model for unconventional frustrated magnets: Ultranarrow phase crossover and two-dimensional spin reversal transition

Here, the site-decorated Ising model is introduced to advance the understanding and experimental realization of the recently discovered one-dimensional (1D) finite-temperature ultranarrow phase crossover in an external magnetic field, while mitigating the geometric complexities of traditional bond-decorated models. The unconventional frustration and physics are clarified by exactly mapping the 1D site-decorated Ising model in a magnetic field onto a zero-field bond-decorated 𝐽 1 −𝐽 2 Ising model with conventional geometrical frustration. Furthermore, although higher-dimensional Ising models in an external field remain unsolved exactly, an exact solution for a spin-reversal transition—driven by an exotic, hidden half-ice, half-fire state induced by site decoration—is derived. This transition, triggered by a slight variation in temperature or magnetic field—without changing its direction—even in the weak-field limit, offers a promising route toward energy-efficient applications such as data storage and processing. The results suggest that site decoration offers an avenue for materials and device design, particularly in systems such as mixed 𝑑−𝑓 compounds, optical lattices, and neural networks, calling for further studies with site-decorated Heisenberg models. In addition, the site-decorated model offers a rigorous test ground for artificial intelligence (AI) in science, as the analytic derivation of the present results was not only validated but also improved by a general-purpose large language model, inspiring the use of AI as scientific discoverer.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Performance of the LHCb muon detector in Run 3

In Run 3 of the LHC, the instantaneous luminosity at the LHCb interaction point has been increased by a factor of five, from to $\mathscr{L}$ = 4 x 10 32 cm -2 s -2 to $\mathscr{L}$ = 2 x 10 33 cm -2 s -1 . Several hardware interventions, including a complete overhaul of the readout electronics, have been carried out on the muon detector. The muon identification algorithms in the software trigger were improved with the aim of ensuring Run 2 performance under a higher particle rate. The operation and calibration of the upgraded muon detector are presented. The muon detection efficiency and muon identification performance are evaluated on data calibration samples collected during the year 2024. A muon identification efficiency above 90% with sub-percent hadron misidentification probability is achieved by exploiting the pattern of hits in the muon detector.

Gaseous detectors↗
NASA NTRS1974

Two-position dc pulse voltage stabilizer

The advantages of the dc pulse voltage stabilizers over the continuous action stabilizers are described. These advantages include higher efficiency, low sensitivity to the ambient temperature and insignificant size and weight. A comparison is made between the schematics of the known two position pulse stabilizer with a Schmitt trigger and that developed by the author. A characteristic feature of the improved system is the increased stabilization coefficient and the possibility of smooth regulation of the output voltage. A practical schematic is presented for the improved two position pulse stabilizer along with its parameters.

Osadchiy, V. I.↗
DOE OSTI2020

Generating realistic building electrical load profiles through the Generative Adversarial Network (GAN)

Building electrical load profiles can improve understanding of building energy efficiency, demand flexibility, and building-grid interactions. Current approaches to generating load profiles are time-consuming and not capable of reflecting the dynamic and stochastic behaviors of real buildings; some approaches also trigger data privacy concerns. In this study, we proposed a novel approach for generating realistic electrical load profiles of buildings through the Generative Adversarial Network (GAN), a machine learning technique that is capable of revealing an unknown probability distribution purely from data. The proposed approach has three main steps: (1) normalizing the daily 24-hour load profiles, (2) clustering the daily load profiles with the k-means algorithm, and (3) using GAN to generate daily load profiles for each cluster. The approach was tested with an open-source database – the Building Data Genome Project. We validated the proposed method by comparing the mean, standard deviation, and distribution of key parameters of the generated load profiles with those of the real ones. The KL divergence of the generated and real load profiles are within 0.3 for majority of parameters and clusters. Additionally, results showed the load profiles generated by GAN can capture not only the general trend but also the random variations of the actual electrical loads in buildings. We report the proposed GAN approach can be used to generate building electrical load profiles, verify other load profile generation models, detect changes to load profiles, and more importantly, anonymize smart meter data for sharing, to support research and applications of grid-interactive efficient buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Structural evolution at the oxidative and reductive limits in the first electrochemical cycle of Li 1.2 Ni 0.13 Mn 0.54 Co 0.13 O 2

High-energy-density lithium-rich materials are of significant interest for advanced lithium-ion batteries, provided that several roadblocks, such as voltage fade and poor energy efficiency are removed. However, this remains challenging as their functioning mechanisms during first cycle are not fully understood. Here we enlarge the cycling potential window for Li 1.2 Ni 0.13 Mn 0.54 Co 0.13 O 2 electrode, identifying novel structural evolution mechanism involving a structurally-densified single-phase A’ formed under harsh oxidizing conditions throughout the crystallites and not only at the surface, in contrast to previous beliefs. We also recover a majority of first-cycle capacity loss by applying a constant-voltage step on discharge. Using highly reducing conditions we obtain additional capacity via a new low-potential P” phase, which is involved into triggering oxygen redox on charge. Altogether, these results provide deeper insights into the structural-composition evolution of Li 1.2 Ni 0.13 Mn 0.54 Co 0.13 O 2 and will help to find measures to cure voltage fade and improve energy efficiency in this class of material.

25 ENERGY STORAGE↗
DOE OSTI2019

Enabling real-time multi-messenger astrophysics discoveries with deep learning

Multi-messenger astrophysics is a fast-growing, interdisciplinary field that combines data, which vary in volume and speed of data processing, from many different instruments that probe the Universe using different cosmic messengers: electromagnetic waves, cosmic rays, gravitational waves and neutrinos. In this Expert Recommendation, we review the key challenges of real-time observations of gravitational wave sources and their electromagnetic and astroparticle counterparts, and make a number of recommendations to maximize their potential for scientific discovery. These recommendations refer to the design of scalable and computationally efficient machine learning algorithms; the cyber-infrastructure to numerically simulate astrophysical sources, and to process and interpret multi-messenger astrophysics data; the management of gravitational wave detections to trigger real-time alerts for electromagnetic and astroparticle follow-ups; a vision to harness future developments of machine learning and cyber-infrastructure resources to cope with the big-data requirements; and finally, the need to build a community of experts to realize the goals of multi-messenger astrophysics.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1980

Interplanetary shock waves and magnetospheric substorms

It is shown that substorm activity after a storm sudden commencement (SSC) depends on whether or not an interplanetary shock wave is accompanied by a large increase of the solar wind-magnetosphere energy coupling function. It has long been thought that substorm activity associated with an SSC results from sudden conversion of magnetic energy stored in the magnetotail, and that this conversion is triggered by the shock wave. However, the present result implies that the magnetospheric substorm is not a sudden conversion of stored magnetic energy, but is a direct consequence of increased efficiency of the solar wind-magnetosphere dynamo.

Akasofu, S.-I.↗
NASA NTRS2019

Enabling Real-time Multi-messenger Astrophysics Discoveries with Deep Learning

Multi-messenger astrophysics is a fast-growing, interdisciplinary field that combines data, which vary in volume and speed of data processing, from many different instruments that probe the Universe using different cosmic messengers: electromagnetic waves, cosmic rays, gravitational waves and neutrinos. In this Expert Recommendation, we review the key challenges of real-time observations of gravitational wave sources and their electromagnetic and astroparticle counterparts, and make a number of recommendations to maximize their potential for scientific discovery. These recommendations refer to the design of scalable and computationally efficient machine learning algorithms; the cyber-infrastructure to numerically simulate astrophysical sources, and to process and interpret multi-messenger astrophysics data; the management of gravitational wave detections to trigger real-time alerts for electromagnetic and astroparticle follow-ups; a vision to harness future developments of machine learning and cyber-infrastructure resources to cope with the big-data requirements; and the need to build a community of experts to realize the goals of multi-messenger astrophysics.

E A Huerta↗
DOE OSTI2023

RPC based tracking system at CERN GIF++ facility

With the HL-LHC upgrade of the LHC machine, an increase of the instantaneous luminosity by a factor of five is expected and the current detection systems need to be validated for such working conditions to ensure stable data taking. At the CERN Gamma Irradiation Facility (GIF++) many muon detectors undergo such studies, but the high gamma background can pose a challenge to the muon trigger system which is exposed to many fake hits from the gamma background. A tracking system using RPCs is implemented to clean the fake hits, taking profit of the high muon efficiency of these chambers. This work will present the tracking system configuration, used detector analysis algorithm and results.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Matched Guiding and Controlled Injection in Dark-Current-Free, 10-GeV-Class, Channel-Guided Laser-Plasma Accelerators

Here we measure the high-intensity laser propagation throughout meter-scale, channel-guided laser-plasma accelerators by adjusting the length of the plasma channel on a shot-by-shot basis, showing high-quality guiding of 500 TW laser pulses over 30 cm in a hydrogen plasma of density n 0 ≈ 1 X 10 17 cm -3 . We observed transverse energy transport of higher-order modes in the first ≈ 12 cm of the plasma channel, followed by quasimatched propagation, and the gradual, dark-current-free depletion of laser energy to the wake. We quantify the laser-to-wake transfer efficiency limitations of currently available petawatt-class lasers and demonstrate via simulation how control over the laser mode can significantly improve beam parameters. Using 21.3 J of laser energy, and triggering localized electron injection, we observed electron bunches with single, quasimonoenergetic peaks up to 9.2 GeV with charge extending beyond 10 GeV.

43 PARTICLE ACCELERATORS↗
NASA NTRS2017

Flight Crew Survey Responses from the Interval Management (IM) Avionics Phase 2 Flight Test

The Interval Management (IM) Avionics Phase 2 flight test used three aircraft over a nineteen day period to operationally evaluate a prototype IM avionics. Quantitative data were collected on aircraft state data and IM spacing algorithm performance, and qualitative data were collected through end-of-scenario and end-of-day flight crew surveys. The majority of the IM operations met the performance goals established for spacing accuracy at the Achieve-by Point and the Planned Termination Point, however there were operations that did not meet goals for a variety of reasons. While the positive spacing accuracy results demonstrate the prototype IM avionics can contribute to the overall air traffic goal, critical issues were also identified that need to be addressed to enhance IM performance. The first category was those issues that impacted the conduct and results of the flight test, but are not part of the IM concept or procedures. These included the design of arrival and approach procedures was not ideal to support speed as the primary control mechanism, the ground-side of the Air Traffic Management Technology Demonstration (ATD-1) integrated concept of operations was not part of the flight test, and the high workload to manually enter the information required to conduct an IM operation. The second category was issues associated with the IM spacing algorithm or flight crew procedures. These issues include the high frequency of IM speed changes and reversals (accelerations), a mismatch between the deceleration rate used by the spacing algorithm and the actual aircraft performance, and some spacing error calculations were sensitive to normal operational variations in aircraft airspeed or altitude which triggered additional IM speed changes. Once the issues in these two categories are addressed, the future IM avionics should have considerable promise supporting the goals of improving system throughput and aircraft efficiency.

Baxley, Brian T.↗
DOE OSTI2020

Guanidinium-Assisted Surface Matrix Engineering for Highly Efficient Perovskite Quantum Dot Photovoltaics

Metal halide perovskite quantum dots (Pe-QDs) are of great interest in new-generation photovoltaics (PVs). However, it remains challenging in the construction of conductive and intact Pe-QD films to maximize their functionality. Herein, a ligand-assisted surface matrix strategy to engineer the surface and packing states of Pe-QD solids is demonstrated by a mild thermal annealing treatment after ligand exchange processing (referred to as “LE-TA”) triggered by guanidinium thiocyanate. The “LE-TA” method induces the formation of surface matrix on CsPbI 3 QDs, which is dominated by the cationic guanidinium (GA+) rather than the SCN-, maintaining the intact cubic structure and facilitating interparticle electrical interaction of QD solids. Consequently, the GA-matrix-confined CsPbI 3 QDs exhibit remarkably enhanced charge mobility and carrier diffusion length compared to control ones, leading to a champion power conversion efficiency of 15.21% when assembled in PVs, which is one of the highest among all Pe-QD solar cells. Additionally, the “LE-TA” method shows similar effects when applied to other Pe-QD PV systems like CsPbBr 3 and FAPbI 3 (FA = formamidinium), indicating its versatility in regulating the surfaces of various Pe-QDs. This work may afford new guidelines to construct electrically conductive and structurally intact Pe-QD solids for efficient optoelectronic devices.

36 MATERIALS SCIENCE↗
NASA NTRS2017

Chemical Complexity Induced by Efficient Ice Evaporation in the Barnard 5 Molecular Cloud

Cold gas-phase water has recently been detected in a cold dark cloud, Barnard 5 located in the Perseus complex, by targeting methanol peaks as signposts for ice mantle evaporation. Observed morphology and abundances of methanol and water are consistent with a transient non-thermal evaporation process only affecting the outermost ice mantle layers, possibly triggering a more complex chemistry. Here we present the detection of the complex organic molecules (COMs) acetaldehyde (CH3CHO) and methyl formate (CH3OCHO), as well as formic acid (HCOOH) and ketene (CH2CO), and the tentative detection of di-methyl ether (CH3OCH3) towards the ''methanol hotspot'' of Barnard 5 located between two dense cores using the single dish OSO 20 m, IRAM 30 m, and NRO 45 m telescopes. The high energy cis-conformer of formic acid is detected, suggesting that formic acid is mostly formed at the surface of interstellar grains and then evaporated. The detection of multiple transitions for each species allows us to constrain their abundances through LTE and non-LTE methods. All the considered COMs show similar abundances between approx. 1 and approx. 10% relative to methanol depending on the assumed excitation temperature. The non-detection of glycolaldehyde, an isomer of methyl formate, with a [glycolaldehyde]/[methyl formate] abundance ratio lower than 6%, favours gas phase formation pathways triggered by methanol evaporation. According to their excitation temperatures derived in massive hot cores, formic acid, ketene, and acetaldehyde have been designated as ''lukewarm'' COMs whereas methyl formate and di-methyl ether were defined as ''warm'' species. Comparison with previous observations of other types of sources confirms that lukewarm and warm COMs show similar abundances in low-density cold gas whereas the warm COMs tend to be more abundant than the lukewarm species in warm protostellar cores. This abundance evolution suggests either that warm COMs are indeed mostly formed in protostellar environments and/or that lukewarm COMs are efficiently depleted by increased hydrogenation efficiency around protostars.

ISM: molecules↗
NASA NTRS2017

Chemical Complexity Induced by Efficient Ice Evaporation in the Barnard 5 Molecular Cloud

Cold gas-phase water has recently been detected in a cold dark cloud, Barnard 5 located in the Perseus complex, by targeting methanol peaks as signposts for ice mantle evaporation. Observed morphology and abundances of methanol and water are consistent with a transient non-thermal evaporation process only affecting the outermost ice mantle layers, possibly triggering a more complex chemistry. Here we present the detection of the complex organic molecules (COMs) acetaldehyde (CH3CHO) and methyl formate (CH3OCHO), as well as formic acid (HCOOH) and ketene (CH2CO), and the tentative detection of di-methyl ether (CH3OCH3) towards the ‘methanol hotspot’ of Barnard 5 located between two dense cores using the single dish OSO 20m, IRAM 30m, and NRO 45m telescopes. The high energy cis- conformer of formic acid is detected, suggesting that formic acid is mostly formed at the surface of interstellar grains and then evaporated. The detection of multiple transitions for each species allows us to constrain their abundances through LTE and non-LTE methods. All the considered COMs show similar abundances between ∼ 1 and ∼ 10 % relative to methanol depending on the assumed excitation temperature. The non-detection of glycolaldehyde, an isomer of methyl formate, with a [glycolaldehyde]/[methyl formate] abundance ratio lower than 6 %, favours gas phase formation pathways triggered by methanol evaporation. According to their excitation temperatures derived in massive hot cores, formic acid, ketene, and acetaldehyde have been designated as ‘lukewarm’ COMs whereas methyl formate and di-methyl ether were defined as ‘warm’ species. Comparison with previous observations of other types of sources confirms that lukewarm and warm COMs show similar abundances in low-density cold gas whereas the warm COMs tend to be more abundant than the lukewarm species in warm protostellar cores. This abundance evolution suggests either that warm COMs are indeed mostly formed in protostellar environments and/or that lukewarm COMs are efficiently depleted by increased hydrogenation efficiency around protostars.

astrochemistry – ISM: abundances – ISM: clouds – I↗
DOE OSTI2021

Entanglement and many-body effects in collective neutrino oscillations

Collective neutrino oscillations play a crucial role in transporting lepton flavor in astrophysical settings, such as supernovae, where the neutrino density is large. In this regime, neutrino-neutrino interactions are important and simulations in the mean-field approximation show evidence for collective oscillations occurring at timescales much shorter than those associated with vacuum oscillations. In this work, we study the out-of-equilibrium dynamics of a corresponding spin model using matrix product states and show how collective bipolar oscillations can be triggered by many-body correlations if appropriate initial conditions are present. We find entanglement entropies scaling at most logarithmically in the system size suggesting that classical tensor network methods could be efficient in describing collective neutrino dynamics more generally. These observation provide a clear path forward, not only to increase the accuracy of current simulations, but also to elucidate the mechanism behind collective flavor oscillations without resorting to the mean-field approximation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗