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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

cymyc: $\underline{C}$alabi-$\underline{Y}$au $\underline{M}$etrics, $\underline{Y}$ukawas, and $\underline{C}$urvature

We introduce cymyc, a high-performance Python library for numerical investigation of the geometry of a large class of string compactification manifolds and their associated moduli spaces. We develop a well-defined geometric ansatz to numerically model tensor fields of arbitrary degree on a large class of Calabi-Yau manifolds. cymyc includes a machine learning component which incorporates this ansatz to model tensor fields of interest on these spaces by finding an approximate solution to the system of partial differential equations they should satisfy.

differential and algebraic geometry↗
DOE OSTI2022

Higgs boson decay to charmonia via $\mathcal{c}$-quark fragmentation

We calculate the decay branching fractions of the Higgs boson to $J/ψ$ and $n_c$ via the charm-quark fragmentation mechanism for the color-singlet and color-octet states in the framework of non-relativistic QCD. The decay rates are governed by the charm-quark Yukawa coupling, unlike the decay H → $J/ψ$ +γ, which is dominated by the $γ^*- J/ψ$ mixing. We find that the decay branching fractions can be about 2 x 10 -5 for H →$c\bar c$ + $J/ψ$, and 6 x 10 -5 for H →$c\bar c$ + $n-c$. We comment on the perspective of searching for the Higgs boson to $J/ψ$ transition at the High-Luminosity LHC for testing the charm-quark Yukawa coupling.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

New Record Ocean Temperatures and Related Climate Indicators in 2023

The global physical and biogeochemical environment has been substantially altered in response to increased atmospheric greenhouse gases from human activities. In 2023, the sea surface temperature (SST) and upper 2000 m ocean heat content (OHC) reached record highs. The 0–2000 m OHC in 2023 exceeded that of 2022 by 15 ± 10 ZJ (1 Zetta Joules = 10 21 Joules) (updated IAP/CAS data); 9 ± 5 ZJ (NCEI/NOAA data). The Tropical Atlantic Ocean, the Mediterranean Sea, and southern oceans recorded their highest OHC observed since the 1950s. Associated with the onset of a strong El Niño, the global SST reached its record high in 2023 with an annual mean of ~0.23°C higher than 2022 and an astounding > 0.3°C above 2022 values for the second half of 2023. The density stratification and spatial temperature inhomogeneity indexes reached their highest values in 2023.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Detailing cloud property feedbacks with a regime-based decomposition

Here, we report diagnosing the root causes of cloud feedback in climate models and reasons for inter-model disagreement is a necessary first step in understanding their wide variation in climate sensitivities. Here we bring together two analysis techniques that illuminate complementary aspects of cloud feedback. The first quantifies feedbacks from changes in cloud amount, altitude, and optical depth, while the second separates feedbacks due to cloud property changes within specific cloud regimes from those due to regime occurrence frequency changes. We find that in the global mean, shortwave cloud feedback averaged across ten models comes solely from a positive within-regime cloud amount feedback countered slightly by a negative within-regime optical depth feedback. These within-regime feedbacks are highly uniform: In nearly all regimes, locations, and models, cloud amount decreases and cloud albedo increases with warming. In contrast, global-mean across-regime components vary widely across models but are very small on average. This component, however, is dominant in setting the geographic structure of the shortwave cloud feedback: Thicker, more extensive cloud types increase at the expense of thinner, less extensive cloud types in the extratropics, and vice versa at low latitudes. The prominent negative extratropical optical depth feedback has contributions from both within- and across-regime components, suggesting that thermodynamic processes affecting cloud properties as well as dynamical processes that favor thicker cloud regimes are important. The feedback breakdown presented herein may provide additional targets for observational constraints by isolating cloud property feedbacks within specific regimes without the obfuscating effects of changing dynamics that may differ across timescales.

58 GEOSCIENCES↗
DOE OSTI2020

Nanoparticle surfactants and structured liquids

Materials are usually classified as solids or liquids, based on their structural stability, dynamic response, and rheological properties. Structured liquid, a new state of matter, has attracted much attention in recent years. Different with either solid or liquid, structured liquid combines the desirable characteristics of fluids with the structural stability of a solid, showing a myriad of potential applications in encapsulation, biphasic reactors, and programmable liquid constructs. Here, a brief review is given, by introducing a new strategy to structure liquids based on the formation, assembly, and jamming of nanoparticle surfactants (NPSs) at liquid-liquid interfaces. Furthermore, the interfacial packing of the NPSs can be effectively manipulated using external triggers, endowing the structured liquids with adaptiveness and responsiveness to changes in their external environment.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Thermally activated structural transformations in manganese oxide nanoparticles under air and argon atmospheres

The properties of manganese oxide nanomaterials are dictated by the structure and morphology of the particular phases they can adopt. The effects of post-synthesis heat treatments on amorphous monodisperse manganese oxide nanoparticles at ≤1300° under lab. air and argon atmospheres were investigated using X-ray diffraction, thermal analysis and electron microscopy techniques. During heat treatments in air, the nanoparticles undergo three transformations, resulting in: crystallization to cubic Mn 2 O 3 at ~500°, followed by the transformation to tetragonal Mn 3 O 4 at ~1010°, and to cubic Mn 3 O 4 at ~1190°. The first two transformations are irreversible, are associated with oxygen loss, and involve reductions. of the Mn ions. The latter transformation is polymorphic and spontaneously reversible, and so, tetragonal Mn 3 O 4 is observed at ambient temperature in samples heat-treated at >1000°. The samples heat treated in argon firstly crystallize to a mixt. of monoclinic Mn 2 O 3 and tetragonal Mn 3 O 4 at ~475°, followed by complete transformation to tetragonal Mn 3 O 4 at ~820°, and then to mostly cubic MnO at ~1145°; here again, the residual tetragonal Mn 3 O 4 undergoes a reversible polymorphic transformation at ~1180°, whereas the other transformations are irreversible. In both atmospheres, the amorphous material exhibits short-range cryptomelane-type order with a mixture of Mn 3+ and Mn 4+ prior to crystallization. Furthermore, these data indicate that most of the stable manganese oxide phases can be obtained from initially amorphous nanoparticles by heat treatment under appropriate conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Efficient learning of power grid voltage control strategies via model-based deep reinforcement learning

Here this article proposes a model-based deep reinforcement learning (DRL) method to design emergency control strategies for short-term voltage stability problems in power systems. Recent advances show promising results for model-free DRL-based methods in power systems control problems. But in power systems applications, these model-free methods have certain issues related to training time (clock time) and sample efficiency; both are critical for making state-of-the-art DRL algorithms practically applicable. DRL-agent learns an optimal policy via a trial-and-error method while interacting with the real-world environment. It is also desirable to minimize the direct interaction of the DRL agent with the real-world power grid due to its safety-critical nature. Additionally, the state-of-the-art DRL-based policies are mostly trained using a physics-based grid simulator where dynamic simulation is computationally intensive, lowering the training efficiency. We propose a novel model-based DRL framework where a deep neural network (DNN)-based dynamic surrogate model (SM), instead of a real-world power grid or physics-based simulation, is utilized within the policy learning framework, making the process faster and more sample efficient. However, having stable training in model-based DRL is challenging because of the complex system dynamics of large-scale power systems. We addressed these issues by incorporating imitation learning to have a warm start in policy learning, reward-shaping, and multi-step loss in surrogate model training. Finally, we achieved 97.5% reduction in samples and 87.7% reduction in training time for an application to the IEEE 300-bus test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Some Problems in Density Functional Theory

Though calculations based on density functional theory (DFT) are used remarkably widely in chemistry, physics, materials science, and biomolecular research and though the modern form of DFT has been studied for almost 60 years, some mathematical problems remain. From a physical science perspective, it is far from clear whether those problems are of major import. For context, we provide an outline of the basic structure of DFT as it is presented and used conventionally in physical sciences, note some unresolved mathematical difficulties with those conventional demonstrations, then pose several questions regarding both the time-independent and time-dependent forms of DFT that could benefit from attention in applied mathematics. Furthermore, progress on any of these would aid in development of better approximate functionals and in interpretation of DFT.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Ion Acceleration in Fermi-LAT Behind-the-Limb Solar Flares: The Role of Coronal Shock Waves

Here, we investigate the relationship between the gamma-ray emission measured with Fermi-LAT and radio signatures of coronal shock waves in four behind-the-limb (BTL) solar flares. All events were associated with metric type II radio burst. Both start and end times of the radio bursts were synchronized with the gamma-ray emission. The type II bursts associated with the BTL gamma-ray flares had higher speeds and lower formation heights than those of an average sample. These findings support the notion that the highly relativistic ions that produce the gamma-rays in BTL flares are accelerated at CME-driven propagating coronal shock waves rather than in large-scale coronal loops.

Corona↗
DOE OSTI2023

Energetic Electron Precipitation Driven by Electromagnetic Ion Cyclotron Waves from ELFIN’s Low Altitude Perspective

We review comprehensive observations of electromagnetic ion cyclotron (EMIC) wave-driven energetic electron precipitation using data collected by the energetic electron detector on the Electron Losses and Fields InvestigatioN (ELFIN) mission, two polar-orbiting low-altitude spinning CubeSats, measuring 50-5000 keV electrons with good pitch-angle and energy resolution. EMIC wave-driven precipitation exhibits a distinct signature in energy-spectrograms of the precipitating-to-trapped flux ratio: peaks at >0.5 MeV which are abrupt (bursty) (lasting ~17 s, or ΔL ~ 0.56) with significant substructure (occasionally down to sub-second timescale). We attribute the bursty nature of the precipitation to the spatial extent and structuredness of the wave field at the equator. Multiple ELFIN passes over the same MLT sector allow us to study the spatial and temporal evolution of the EMIC wave - electron interaction region. Case studies employing conjugate ground-based or equatorial observations of the EMIC waves reveal that the energy of moderate and strong precipitation at ELFIN approximately agrees with theoretical expectations for cyclotron resonant interactions in a cold plasma. Using multiple years of ELFIN data uniformly distributed in local time, we assemble a statistical database of ~50 events of strong EMIC wave-driven precipitation. Most reside at L ~ 5 – 7 at dusk, while a smaller subset exists at L ~ 8 – 12 at post-midnight. The energies of the peak-precipitation ratio and of the half-peak precipitation ratio (our proxy for the minimum resonance energy) exhibit an L-shell dependence in good agreement with theoretical estimates based on prior statistical observations of EMIC wave power spectra. The precipitation ratio’s spectral shape for the most intense events has an exponential falloff away from the peak (i.e., on either side of ~ 1.45 MeV). It too agrees well with quasi-linear diffusion theory based on prior statistics of wave spectra. It should be noted though that this diffusive treatment likely includes effects from nonlinear resonant interactions (especially at high energies) and nonresonant effects from sharp wave packet edges (at low energies). Sub-MeV electron precipitation observed concurrently with strong EMIC wave-driven >1 MeV precipitation has a spectral shape that is consistent with efficient pitch-angle scattering down to ~ 200-300 keV by much less intense higher frequency EMIC waves at dusk (where such waves are most frequent). At ~100 keV, whistler-mode chorus may be implicated in concurrent precipitation. These results confirm the critical role of EMIC waves in driving relativistic electron losses. Nonlinear effects may abound and require further investigation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Constraining self-interacting dark matter with the full dataset of PandaX-II

Self-interacting dark matter (SIDM) is a leading candidate proposed to solve discrepancies between predictions of the prevailing cold dark matter theory and observations of galaxies. Many SIDM models predict the existence of a light force carrier that mediates strong dark matter self-interactions. If the mediator couples to the standard model particles, it could produce characteristic signals in dark matter direct detection experiments. We report searches for signals of SIDM models with a light mediator using the full dataset of the PandaX-II experiment, basing on a total exposure of 132 tonne-days. No significant excess over background is found, and our likelihood analysis leads to a strong upper limit on the dark matter-nucleon coupling strength. We further combine the PandaX-II constraints and those from observations of the light element abundances in the early universe, and show that direct detection and cosmological probes can provide complementary constraints on dark matter models with a light mediator.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Surface Integrity and Oxidation of a Powder Metallurgy Ni-Based Superalloy Treated by Laser Shock Peening

Laser shock peening is a mechanical surface treatment which can induce large compressive residual stresses and microstructural changes in the material by using repetitive shocks from laser pulses. In this work, the surface integrity (surface microstructure, topography, hardness and residual stress) of a laser shock peening treated powder metallurgy Ni-based superalloy was investigated. Laser shock peening treatment introduces large plastic deformation especially at a depth of about 100 μm from the surface, which increases the local hardness. The residual stress from the surface to the interior of the sample was investigated by synchrotron X-ray diffraction. The maximum compressive stress reaches 400 MPa at the surface, while the depth of the compressive stress is about 0.7 mm. Lastly, the oxidation behavior of the treated and untreated samples was evaluated by thermal exposure at 700°C for 312 h. The LSP treatment decreased the thickness of oxide layer, thereby showing improved oxidation resistance.

36 MATERIALS SCIENCE↗