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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

All-Electric Nonassociative Learning in Nickel Oxide

Habituation and sensitization represent nonassociative learning mechanisms in both non-neural and neural organisms. They are essential for a range of functions from survival to adaptation in dynamic environments. Design of hardware for neuroinspired computing strives to emulate such features driven by electric bias and can also be incorporated into neural network algorithms. Herein, cellular-like learning in oxygen-deficient NiO x devices is demonstrated. Both habituation learning and sensitization response can be achieved in a single device by simply controlling the magnitude of the electric field. Spontaneous memory relaxations and dynamic redistribution of oxygen vacancies under electric bias enable such learning behavior of NiO x under sequential training. These characteristics in simple device arrays are implemented to learn alphabets as well as demonstrate simulated algorithmic use cases in digit recognition. Transition metal oxides with carefully prepared defect concentrations can be highly sensitive to electronic structure perturbations under moderate electrical stimulus and serve as building blocks for next-generation neuroinspired computing hardware.

36 MATERIALS SCIENCE↗
DOE OSTI2026

The Zooplankton International Geospatial dataset: A global repository of spatiotemporal freshwater zooplankton community composition data from lakes and reservoirs to support ecological research

Zooplankton transfer substantial energy in aquatic food webs and are used as indicators of environmental change. Syntheses of zooplankton community dynamics globally require datasets that span a wide range of environmental gradients; however, these datasets are limited due to methodological differences across programs, taxonomic inconsistencies, and a lack of standardized metadata. To reconcile these challenges, we created the Zooplankton International Geospatial (ZIG) dataset, which includes original zooplankton, water physical and chemical variables, and lake morphometric data from 311 inland lakes and reservoirs. ZIG includes waterbodies ranging in size from 0.005 to 82,100 km2 and spanning broad latitudinal (−47.26 to 64.90) and longitudinal ranges (−165.04 to 176.53). Temporal coverage for individual waterbodies ranges between 1 and 60 yr with sampling frequency ranging from annually to weekly. With its extensive coverage and content, we consider ZIG to be a cornerstone for future investigations of global scale lake biodiversity change.

Figary, Stephanie [Cornell University, Ithaca, NY]↗
DOE OSTI2020

Potential annual daylighting performance of a high-efficiency daylight redirecting slat system

While the primary role of window attachments is often to moderate glare and solar heat gains, they are also able to provide additional daylight to interior spaces. For this purpose, a variety of daylight-redirecting window systems have been developed over the past 150 years. Fixed reflective systems (slats/light shelves) or prismatic systems that rely on total internal reflection work well under specific solar conditions, but generally sacrifice performance over a much wider range of incident solar angles and sky conditions. Dynamic systems - typically reflective slats - are more responsive to sun angles but have not been able to achieve optimal performance for glare and daylight redirection efficiency. A previous investigation into an adjustable, reflective blind concept first conceived of in the late 1970s showed promise but was not reduced to practice due to lack of adequate simulation and analysis tools. In this paper, this concept is further developed and its energy and visual comfort performance evaluated for four mid-latitude, temperate climates using ray-tracing simulation techniques. Overall, results indicate significant potential lighting energy savings when compared with conventional automated reflective blinds (2.1–4.9 kWh/(m 2 ·a), or 14%–42%, depending on climate and orientation) or, especially, manually-operated matte white venetian blinds (1.4–7.9 kWh/(m 2 ·a), or 9%–54%, depending on climate and orientation), while maintaining acceptable or better visual comfort conditions throughout the interior space.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Adaptation of virtual synchronous generators to dynamic conditions in power grids

Virtual synchronous generators (VSGs) are widely adopted as grid-forming controls for inverter-based resources. However, when grid conditions vary significantly as characterized by changes in short-circuit ratio (SCR) and the reactance-to-resistance (X/R) ratio, fixed-gain designs and the commonly used P–Q decoupling assumption can become inaccurate. Such conditions can degrade transient power performance, leading to oscillations, prolonged settling, and overshoot, particularly in stiff-grid operating points. This paper quantifies how grid strength and impedance-dependent coupling affect the active–reactive power dynamics of a conventional VSG over a broad range of SCR and X/R values. An adaptive VSG tuning framework is then developed by combining (i) a coupling-explicit, impedance-parameterized state-space model to enable systematic controller synthesis, (ii) a full-state-feedback law designed via pole placement to meet prescribed damping and settling-time specifications, and (iii) a physics-informed neural network (PINN)–based online grid-impedance estimator that updates controller gains in real time as grid conditions vary. Offline simulations in MATLAB/Simulink and real-time validation on an OPAL-RT platform show that the proposed method preserves consistent damping and settling behavior with reduced overshoot across wide SCR and X/R ranges, compared with fixed-gain VSG baselines.

Adaptive control↗
DOE OSTI2025

Ultra-high efficiency hydrogen production using a large-scale solid oxide electrolysis cell system

Efficient and cost-effective production of clean hydrogen is key to decarbonizing the production of hard-to-abate industries, such as chemicals, fuels, steel, cement and many other commodities that form the basis of modern societies. High-temperature steam electrolysis (HTSE) has recently become commercially available and offers opportunities for producing hydrogen at higher efficiency and lower cost than competing low temperature technologies. In this work, we report world record setting hydrogen production efficiency from large-scale prototype HTSE systems based on solid oxide electrolysis cell (SOEC) technology. Independent tests performed at Idaho National Laboratory (INL) employed a Bloom Energy 100 kW SOEC system to achieve a hydrogen production direct current specific electric energy consumption as low as 36.7 kWh per kilogram of hydrogen. Remarkably, similar high efficiencies in the range of 36–39 kW/kg-H2 were obtained over a wide range of hydrogen production rates and even during dynamic ramping as the hydrogen production and electric power consumption of the system were varied between 20 % and 100 % of nominal conditions. Furthermore, these test results validate previous projections that commercial SOEC systems can produce clean hydrogen at efficiencies approaching 100 % for less than 2 U S. dollars per kilogram when located near sources of inexpensive, low-grade heat and clean electricity.

08 HYDROGEN↗
DOE OSTI2024

SAXS of murine amelogenin identifies a persistent dimeric species from pH 5.0 to 8.0

Amelogenin is an intrinsically disordered protein essential to tooth enamel formation in mammals. Here, using advanced small angle X-ray scattering (SAXS) capabilities at synchrotrons and computational models, we revisited measuring the quaternary structure of murine amelogenin as a function of pH and phosphorylation at serine-16. The SAXS data shows that at the pH extremes, amelogenin exists as an extended monomer at pH 3.0 (R g = 38.4 Å) and nanospheres at pH 8.0 (R g = 84.0 Å), consistent with multiple previous observations. At pH 5.0 and above there was no evidence for a significant population of monomeric species. Instead, at pH 5.0 ~ 80% of the population is a heterogenous dimeric species that increases to ~ 100% at pH 5.5. The dimer population was observed at all pH > 5 conditions in dynamic equilibrium with a species in the pentamer range at pH < 6.5 and nanospheres at pH 8.0. At pH 8.0 ~ 40% of the amelogenin still remained in the dimeric state. In general, serine-16 phosphorylation of amelogenin appears to modestly stabilize the population of the dimeric species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

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

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

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

RBSP-ECT Combined Pitch Angle Resolved Electron Flux Data Product

We describe a new data product combining pitch angle resolved electron flux measurements from the Radiation Belt Storm Probes (RBSP) Energetic Particle Composition and Thermal Plasma (ECT) suite on the National Aeronautics and Space Administration’s Van Allen Probes. Here, we describe the methodology used to combine each of the data sets and produce a consistent set of pitch-angle-resolved spectra for the entire Van Allen Probes mission. Three-minute-averaged flux spectra are provided spanning energies from 15 eV up to 20 MeV. This new data product offers researchers a consistent cross calibrated data set to explore the particle dynamics of the inner magnetosphere across a wide range of energies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Hydrostatic and Non‐Hydrostatic Baroclinic Instability in the Dynamical Core of the DOE Global Climate Model

Abstract The dynamical core of the Department of Energy global climate model is used to understand the role of non‐hydrostatic dynamics in the simulation of dry and moist baroclinic waves. To reduce computational cost, the Diabatic Acceleration and REscaling approach is adopted. Scale analysis and numerical simulations suggest that the model solution is not distorted by the change of spherical metric terms due to the change of Earth radius, neither are the inter‐scale interactions strongly altered as indicated by the analysis of spectral flux. Compared with hydrostatic simulations, the onset of baroclinic instability is delayed under non‐hydrostatic dynamics as the associated weaker vertical motions tend to increase the critical wavelength and narrow the range of waves that can be baroclinically unstable. During the development of baroclinic waves, non‐hydrostatic dynamics tends to induce vertical motions in the upper troposphere, accelerating the eastward propagation of upper‐level ridges through their impact on local vorticity tendency. These processes reduce the westward tilt of the vertical ridge axes and suppress the conversion of mean flow available potential energy to eddy kinetic energy, leading to weaker baroclinic eddies than in hydrostatic simulations. The contrasts between hydrostatic and non‐hydrostatic settings hold in supplemental experiments that vary the background flow Rossby number, the amount of water vapor content and vertical resolution. We also find that mesoscale and smaller‐scale activities can be considerably under‐represented when the vertical resolution is limited to that typically used in global climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Tensor factorization for elucidating mechanisms of piezoresponse relaxation via dynamic Piezoresponse Force Spectroscopy

Spatially resolved time and voltage-dependent polarization dynamics in PbTiO 3 thin films is explored using dynamic piezoresponse force microscopy (D-PFM) in conjunction with interferometric displacement sensing. This approach gives rise to 4D data sets containing information on bias-dependent relaxation dynamics at each spatial location without long-range electrostatic artifacts. To interpret these data sets in the absence of defined physical models, we employ a non-negative tensor factorization method which clearly presents the data as a product of simple behaviors allowing for direct physics interpretation. Correspondingly, we perform phase-field modeling finding the existence of ‘hard’ and ‘soft’ domain wall edges. This approach can be extended to other multidimensional spectroscopies for which even exploratory data analysis leads to unsatisfactory results due to many components in the decomposition.

36 MATERIALS SCIENCE↗
DOE OSTI2020

X-ray spectral and flux variability of the microquasar GRS 1758-258 on timescales from weeks to years

We present the spectral and timing evolution of the persistent black hole X-ray binary GRS 1758-258 based on almost 12 years of observations using the Rossi X-ray Timing Explorer Proportional Counter Array. While the source was predominantly found in the hard state during this time, it entered the thermally dominated soft state seven times. In the soft state GRS 1758-258 shows a strong decline in flux above 3 keV rather than the pivoting flux around 10 keV more commonly shown by black hole transients. In its 3–20 keV hardness intensity diagram, GRS 1758-258 shows a hysteresis of hard and soft state fluxes typical for transient sources in outburst. The RXTE-PCA and RXTE-ASM long-term light curves do not show any orbital modulations in the range of 2–30 d. However, in the dynamic power spectra significant peaks drift between 18.47 and 18.04 d for the PCA data, while less significant signatures between 19 d and 20 d are seen for the ASM data as well as for the Swift/BAT data. We discuss different models for the hysteresis behavior during state transitions as well as possibilities for the origin of the long term variation in the context of a warped accretion disk.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Percolation and nanosecond fluctuators in V 2 O 3 films within the metal–insulator transition

Vanadium sesquioxide (V 2 O 3 ) exhibits a metal–insulator transition (MIT) at 160 K between a low temperature, monoclinic, antiferromagnetic Mott insulator and a high temperature, rhombohedral, paramagnetic, metallic phase. In thin films, a percolative transition takes place over a finite temperature range of phase coexistence. We study the fluctuating dynamics of this percolative MIT by measuring voltage noise spectra at both low frequencies (up to 100 kHz) and radio frequencies (between 10 MHz and 1 GHz). Noise intensity quadratic in bias is observed in the MIT region, as expected for resistive fluctuations probed nonperturbatively by the current. The low frequency noise resembles flicker-type 1/f β noise, often taking on the form of Lorentzian noise dominated by a small number of fluctuators as the volume fraction of the insulating phase dominates. Radio frequency noise intensity also quadratic in the bias current allows the identification of resistance fluctuations with lifetimes below 1 ns, approaching timescales seen in non-equilibrium pump–probe studies of the transition. We find quantitative consistency with a model for fluctuations in the percolative fraction. The thermodynamics of the MIT suggests that dominant fluctuations are ones that alter small volumes affecting the connectivity of domain boundaries. This noise serves as a sensitive and nonperturbative probe for the dynamics of switching phenomena in this system.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Terawatt attosecond x-ray source driven by a plasma accelerator

Plasma accelerators can generate ultra-high-brightness electron beams that open the door to light sources with a smaller physical footprint and properties un-achievable with conventional accelerator technology. In this paper, we show that electron beams from Plasma WakeField Accelerators can generate few-cycle coherent tunable soft x-ray pulses with TW peak power and a duration of tens of attoseconds, an order of magnitude more powerful, shorter, and with better stability than state-of-the-art X-ray Free Electron Lasers (XFELs). Such a light source would significantly enhance the ability to experimentally investigate electron dynamics on ultrafast timescales, having a broad-ranging impact across multiple scientific fields. Rather than starting from noise as in typical XFELs, the x-ray emission in this approach is driven by coherent radiation from a pre-bunched, high peak current electron beam of attosecond duration. This relaxes the restrictive tolerances that have hindered progress toward utilizing plasma accelerators as coherent x-ray drivers thus far, presenting a new paradigm for advanced accelerator light source applications.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Magneto-optical spectroscopy based on pump-probe strobe light

Here, we demonstrate a pump-probe strobe light spectroscopy for sensitive detection of magneto-optical dynamics in the context of hybrid magnonics. The technique uses a combinatorial microwave-optical pump-probe scheme, leveraging both the high-energy resolution of microwaves and high-efficiency detection using optical photons. In contrast with conventional stroboscopy using continuous-wave light, we apply microwave and optical pulses with varying pulse widths, and demonstrate magneto-optical detection of magnetization dynamics in Y 3 Fe 5 O 12 films. The detected magneto-optical signals depend strongly on the characteristics of both the microwave and the optical pulses, as well as their relative time delays. We show that good magneto-optical sensitivity and coherent stroboscopic character are maintained, even at a microwave pump pulse of 1.5 ns and an optical probe pulse of 80 ps, under a 7 MHz clock rate, corresponding to a pump-probe footprint of approximately 1% in one detection cycle. Our results show that time-dependent strobe light measurement of magnetization dynamics can be achieved in the gigahertz frequency range under a pump-probe detection scheme.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Ab Initio Multiplet-Plus-Cumulant Approach for Correlation Effects in X-Ray Photoelectron Spectroscopy

The treatment of electronic correlations in open-shell systems is among the most challenging problems of condensed matter theory. Current approximations are only partly successful. Ligand-field multiplet theory has been widely successful in describing intra-atomic correlation effects in x-ray spectra, but typically ignores itinerant states. The cumulant expansion for the one-electron Green’s function has been successful in describing shake-up effects but ignores atomic multiplets. More complete methods, such as dynamic mean-field theory can be computationally demanding. Here, we show that separating the dynamic Coulomb interactions into local and longer-range parts with ab initio parameters yields a combined multiplet-plus-cumulant approach that accounts for both local atomic multiplets and satellite excitations. The approach is illustrated in transition metal oxides and explains the multiplet peaks, charge-transfer satellites, and distributed background features observed in XPS experiment.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Microstructural Pattern Formation during Far-from-Equilibrium Alloy Solidification

We introduce a new phase-field formulation of rapid alloy solidification that quantitatively in- corporates non-equilibrium effects at the solid-liquid interface over a very wide range of interface velocities. Simulations identify a new dynamical instability of dendrite tip growth driven by solute trapping at velocities approaching the absolute stability limit. They also reproduce the formation of the widely observed banded microstructures, revealing how this instability triggers transitions between dendritic and microsegregation-free solidification. Predicted band spacings agree quantita- tively with observations in rapidly solidified Al-Cu thin films.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Generalized Aerosol/Chemistry Interface (GIANT): A Community Effort to Advance Collaborative Science across Weather and Climate Models

Atmospheric aerosol and chemistry modules are key elements in Earth system models (ESMs), as they predict air pollutant concentrations and properties that can impact human health, weather, and climate. The current uncertainty in climate projections is partly due to the inaccurate representation of aerosol direct and indirect forcing. Aerosol/chemistry parameterizations used within ESMs and other atmospheric models span large structural and parameter uncertainties that are difficult to assess independently of their host models. Moreover, there is a strong need for a standardized interface between aerosol/chemistry modules and the host model to facilitate portability of aerosol/chemistry parameterizations from one model to another, allowing not only a comparison between different parameterizations within the same modeling framework, but also quantifying the impact of different model frameworks on aerosol/chemistry predictions. To address this need, we have initiated a new community effort to coordinate the construction of a Generalized Aerosol/Chemistry Interface (GIANT) for use across weather and climate models. We aim to organize a series of community workshops and hackathons to design and build GIANT, which will serve as the interface between a range of aerosol/chemistry modules and the physics and dynamics components of atmospheric host models. GIANT will leverage ongoing efforts at the U.S. modeling centers focused on building next-generation ESMs and the international AeroCom initiative to implement this common aerosol/chemistry interface. GIANT will create transformative opportunities for scientists and students to conduct innovative research to better characterize structural and parametric uncertainties in aerosol/chemistry modules, and to develop a common set of aerosol/chemistry parameterizations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

GEFSv12 High- and Low-Skill Day-10 Tornado Forecasts

Abstract On average, modern numerical weather prediction forecasts for daily tornado frequency exhibit no skill beyond day 10. However, in this extended-range lead window, there are particular model cycles that have exceptionally high forecast skill for tornadoes because of their ability to correctly simulate the future synoptic pattern. Here, model initial conditions that produced a more skillful forecast for tornadoes over the United States were exploited while also highlighting potential causes for low-skill cycles within the Global Ensemble Forecasting System, version 12 (GEFSv12). There were 88 high-skill and 91 low-skill forecasts in which the verifying day-10 synoptic pattern for tornado conditions revealed a western U.S. thermal trough and an eastern U.S. thermal ridge, a favorable configuration for tornadic storm occurrence. Initial conditions for high skill forecasts tended to exhibit warmer sea surface temperatures throughout the tropical Pacific Ocean and Gulf of Mexico, an active Madden–Julian oscillation, and significant modulation of Earth-relative atmospheric angular momentum. Low-skill forecasts were often initialized during La Niña and negative Pacific decadal oscillation conditions. Significant atmospheric blocking over eastern Russia—in which the GEFSv12 overforecast the duration and characteristics of the downstream flow—was a common physical process associated with low-skill forecasts. This work helps to increase our understanding of the common causes of high- or low-skill extended-range tornado forecasts and could serve as a helpful tool for operational forecasters. Significance Statement This research provides a framework for the anticipation of a more (or less) skillful 10-day tornado forecast in an operational numerical weather prediction system. High-skill forecasts were associated with substantial tropical convection and warm sea surface temperature throughout the Pacific Ocean and Gulf of Mexico, whereas the underlying cause of low-skill forecasts were typically associated with a blocking anticyclone over eastern Russia. These findings are important because they permit increased or decreased confidence in a long-range forecast of tornado occurrence based on a dynamical prediction system.

Meteorology & Atmospheric Sciences↗