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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Nature Versus Nurture: A Bayesian Framework for Assessing Apparent Correlations between Planetary Orbital Properties and Stellar Ages

Many exoplanets have orbital characteristics quite different from those seen in our own solar system, including planets locked in orbital resonances and planets on orbits that are elliptical or highly inclined from their host star’s spin axis. It is debated whether the wide variety in system architecture is primarily due to differences in formation conditions (nature) or due to evolution over time (nurture). Identifying trends between planetary and stellar properties, including stellar age, can help distinguish between these competing theories and offer insights as to how planets form and evolve. However, it can be challenging to determine whether observed trends between planetary properties and stellar age are driven by the age of the system—pointing to evolution over time being an important factor—or other parameters to which the age may be related, such as stellar mass or stellar temperature. The situation is complicated further by the possibilities of selection biases, small number statistics, uncertainties in stellar age, and orbital evolution timescales that are typically much shorter than the range of observed ages. Here, we develop a Bayesian statistical framework to assess the robustness of such observed correlations and to determine whether they are indeed due to evolutionary processes, are more likely to reflect different formation scenarios, or are merely coincidental. We apply this framework to reported trends between stellar age and 2:1 orbital resonances, spin–orbit misalignments, and hot Jupiters’ orbital eccentricities. We find strong support for the nurture hypothesis only in the final case.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Real-time tracking of structural evolution in 2D MXenes using theory-enhanced machine learning

In situ Electron Energy Loss Spectroscopy (EELS) combined with Transmission Electron Microscopy (TEM) has traditionally been pivotal for understanding how material processing choices affect local structure and composition. However, the ability to monitor and respond to ultrafast transient changes, now achievable with EELS and TEM, necessitates innovative analytical frameworks. Here, we introduce a machine learning (ML) framework tailored for the real-time assessment and characterization of in operando EELS Spectrum Images (EELS-SI). We focus on 2D MXenes as the sample material system, specifically targeting the understanding and control of their atomic-scale structural transformations that critically influence their electronic and optical properties. This approach requires fewer labeled training data points than typical deep learning classification methods. By integrating computationally generated structures of MXenes and experimental datasets into a unified latent space using Variational Autoencoders (VAE) in a unique training method, our framework accurately predicts structural evolutions at latencies pertinent to closed-loop processing within the TEM. This study presents a critical advancement in enabling automated, on-the-fly synthesis and characterization, significantly enhancing capabilities for materials discovery and the precision engineering of functional materials at the atomic scale.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Modeling and Analysis of Wind Turbine Wake Vortex Evolution Due to Time-Constant Spatial Variations in Atmospheric Flow

Modern utility-scale wind turbines are evolving toward larger, lighter, and more flexible designs to meet the growing demand for renewable energy while minimizing logistical costs. However, these advancements in lightweight design result in heightened aeroelastic sensitivity, leading to complex interactions which affect the rotor’s capacity to withstand aerodynamic loading and the cascading effects that manifest in the wake’s vortex-structure evolution under variable atmospheric conditions. In this paper, we analyze the influence of stream-wise fluctuating atmospheric flow conditions on wind turbines with large, flexible rotors through simulations of the National Rotor Testbed (NRT) turbine, located at Sandia National Labs’ Scaled Wind Farm Technology (SWiFT) facility in Lubbock, Texas. The Common Ordinary Differential Equation Framework (CODEF) modeling suite is used to simulate wind turbine aeroelastic oscillatory behavior and wind farm vortex–wake interactions for a range of conditions with spatially variant atmospheric flow. CODEF solutions for turbine operation in wind conditions featuring only one parameter fluctuation are compared to wind conditions with several wind parameter variations in combination. By isolating individual inflow variations and comparing them to multi-parameter scenarios, we determine the contributions of each atmospheric factor to rotor dynamics, wake evolution, and downstream wind farm interactions. The purpose of this paper is to analyze the effects of spatial variations in atmospheric flow on the topological evolution of wind turbine vortex wakes, which constitutes a gap in the current understanding of wind turbine wake dynamics. The insights gained from this study are particularly valuable for the development of wind farm control strategies aimed at mitigating the adverse effects of wake interactions, enhancing energy capture, and improving the overall stability of wind farm operations. With these insights, we aim to contribute to the development of modeling and simulation tools to optimize utility-scale wind power plants operating in diverse atmospheric environments.

Farrell, Alayna (ORCID:000000023555720X)↗
DOE OSTI2024

Experimental trends and theoretical descriptors for electrochemical reduction of carbon dioxide to formate over Sn-based bimetallic catalysts

The electrochemical carbon dioxide reduction reaction (CO 2 RR) using renewable energy sources is a promising solution for mitigating CO 2 emissions. In particular, CO 2 RR to formate represents a commercially profitable target. However, a comprehensive understanding of the catalytic mechanisms of Sn-based catalysts under reaction conditions, including the real-time structural evolution of catalysts and the role of all key reaction intermediates in influencing the CO 2 RR selectivity, is still lacking. The current study reports a framework to study the selectivity preference of Sn-based bimetallic catalysts using a combination of electrochemical measurements, in situ characterization, and density functional theory (DFT) calculations. The addition of a second metal (Co, Ni, Ag, Zn, Ga, Bi) was found to play a vital role in affecting the CO 2 RR performance. In situ X-ray absorption near edge structure (XANES) measurements revealed a dynamic evolution in the Sn valence state induced by different secondary metals. A multidimensional descriptor involving all the key reaction intermediates was developed to assess formate selectivity using a 2-dimensional volcano plot. Finally, this research offers an effective framework for understanding CO 2 RR catalytic selectivity by considering both the real-time structural evolution of catalysts and all the key intermediates involved.

58 GEOSCIENCES↗
DOE OSTI2022

Algebraic compression of quantum circuits for Hamiltonian evolution

Here unitary evolution under a time-dependent Hamiltonian is a key component of simulation on quantum hardware. Synthesizing the corresponding quantum circuit is typically done by breaking the evolution into small time steps, also known as Trotterization, which leads to circuits the depth of which scales with the number of steps. When the circuit elements are limited to a subset of SU(4) - or equivalently, when the Hamiltonian may be mapped onto free fermionic models - several identities exist that combine and simplify the circuit. Based on this, we present an algorithm that compresses the Trotter steps into a single block of quantum gates using algebraic relations between adjacent circuit elements. This results in a fixed depth time evolution for certain classes of Hamiltonians. We explicitly show how this algorithm works for several spin models, and demonstrate its use for adiabatic state preparation of the transverse field Ising model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Real-Time Modulation of Hydrogen Evolution Activity of Graphene Electrodes Using Mechanical Strain

This paper reports the effect of mechanically applied elastic strain on the hydrogen evolution reaction (HER) activity of graphene under acidic conditions. Here, applied tensile strain of 0.2% on a graphene electrode is shown to lead to a 1–3% increase of HER current. Tensile strain increases HER activity while compressive strain decreases it. Density functional theory (DFT) calculations using a periodic graphene slab model show increasing in the adsorption energy of H atom with growing tensile strain, leading to a corresponding enhancement of current density in HER, similar to that observed experimentally.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Robust negativity in the quantum-to-classical transition of Kerr dynamics

Here, we quantify the quantum-to-classical transition of the single-mode Kerr nonlinear dynamics in the presence of loss. We establish three timescales that govern the dynamics, each with distinct characteristics. For times short compared with the Ehrenfest time, the evolution is classical, characterized by Gaussian dynamics. For sufficiently long times, as we increase the initial photon number, unitary Kerr evolution would generate macroscopic superpositions of coherent states (so-called kitten states). However, this is severely restricted in the presence of small photon loss, and the expectation values of observables coincide with their classical values. The intermediate timescale, however, shows resilient quantum behavior in the macroscopic limit. We show that in the mean-field non-Gaussian regime, the Kerr Hamiltonian (with small photon loss) generates a significant amount of Wigner-negativity, and classical flow is recovered only if the loss rate grows with system size. Our results broaden the usual understanding of quantum-to-classical transitions and demonstrate the potential for creating robust nonclassical resources for continuous-variable quantum information processing in the presence of loss.

Raza, Mohsin [University of New Mexico, Albuquerqu↗
DOE OSTI2022

Quenching time-scales in the IllustrisTNG simulation

ABSTRACT The time-scales for galaxy quenching offer clues to its underlying physical drivers. We investigate central galaxy quenching time-scales in the IllustrisTNG 100-1 simulation, their evolution over time, and the pre-quenching properties of galaxies that predict their quenching time-scales. Defining quenching duration τq as the time between crossing specific star formation rate (sSFR) thresholds, we find that ${\sim} 40{{\ \rm per\ cent}}$ of galaxies quench rapidly with τq < 1 Gyr, but a substantial tail of galaxies can take up to 10 Gyr to quench. Furthermore, 29 per cent of galaxies that left the star-forming main sequence (SFMS) more than 2 Gyr ago never fully quench by z = 0. While the median τq is fairly constant with epoch, the rate of galaxies leaving the SFMS increases steadily over cosmic time, with the rate of slow quenchers being dominant around z ∼ 2–0.7. Compared to fast quenchers (τq < 1 Gyr), slow-quenching galaxies (τq > 1 Gyr) were more massive, had more massive black holes, had larger stellar radii, and accreted gas with higher specific angular momentum (AM) prior to quenching. These properties evolve little by z = 0, except for the accreting gas AM for fast quenchers, which reaches the same high AM as the gas in slow quenchers. By z = 0, slow quenchers also have residual star formation in extended gas rings. Using the expected relationship between stellar age gradient and τq for inside-out quenching we find agreement with Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) integral field unit (IFU) observations. Our results suggest the accreting gas AM and potential well depth determine the quenching time-scale.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Causal explicit algorithm for heat conduction in a plasma

Hyperbolic heat conduction extends standard Spitzer-Harm heat conduction by including a term proportional to the time derivative of the heat flux. The new term arises from a kinetic derivation of the heat flux that includes higher order corrections. Here we present a causal explicit numerical algorithm for solving the nonlinear hyperbolic heat conduction equation in an unmagnetized plasma. The maximum stable timestep for the causal explicit algorithm scales linearly with the cell size, owing to the hyperbolic nature of the problem. This is in contrast to the quadratic scaling of the maximum stable timestep with the cell size for the parabolic forward time centered space algorithm. The favorable scaling of the timestep with the cell size enables a practical explicit implementation of heat conduction in high-performance massively parallel plasma codes. In particular, we have implemented the causal explicit algorithm in the laser plasma interaction code pF3D. We verify the CE algorithm and analyze its convergence rate by simulating a harmonic mode, which has an analytic solution within the context of the HHC model. We also compare simulations using the CE algorithm to those using the forward time centered space algorithm on a pair of test problems: evolution in time of a Gaussian temperature perturbation in a uniform plasma and heat transport in the presence of inverse bremsstrahlung heating by a Gaussian laser speckle.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Quark flavor equilibration of the quark-gluon plasma

The early stage of a heavy-ion collision is marked by rapid entropy production and the transition from a gluon saturated initial condition to a plasma of quarks and gluons that evolves hydrodynamically. However, during the early times of the hydrodynamic evolution, the chemical composition of the QCD medium is still largely unknown. We present a study of quark chemical equilibration in the (Q)GP using a novel model of viscous hydrodynamic evolution in partial chemical equilibrium. Motivated by the success of gluon saturated initial condition models, we initialize the QCD medium as a completely gluon dominated state. Local quark production during the hydrodynamic phase is then simulated through the evolution of time-dependent fugacities for each independent quark flavor, with the timescales set as free parameters to compare different rates of equilibration. We present the results of complete heavy-ion collision simulations using this partial chemical equilibrium model, and show the effects on hadronic and electromagnetic observables. In particular, we show that the development of flow is sensitive to the equilibration timescale, providing an empirical way to probe the chemical equilibration of the QCD medium.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Asymptotic errors in adiabatic evolution

The adiabatic theorem in quantum mechanics implies that if a system is in a discrete eigenstate of a Hamiltonian and the Hamiltonian evolves in time arbitrarily slowly, the system will remain in the corresponding eigenstate of the evolved Hamiltonian. Understanding corrections to the adiabatic result that arise when the evolution of the Hamiltonian is slow—but not arbitrarily slow—has become increasingly important, especially since adiabatic evolution has been proposed as a method of state preparation in quantum computing. Here, this paper identifies two regimes, an adiabatic regime in which corrections are generically small and can depend on details of the evolution throughout the path, and a hyperadiabatic regime in which the error is given by a form similar to an asymptotic expansion in the inverse of the evolution time with the coefficients depending principally on the behavior at the endpoints. However, the error in this hyperadiabatic regime is neither given by a true asymptotic series nor solely dependent on the endpoints: the coefficients combine the contributions from both endpoints, with relative phase factors that depend on the average spectral gaps along the trajectory, multiplied by the evolution time. The central result of this paper is to identify a quantity, referred to as the typical error, which is obtained by appropriately averaging the error over evolution times that are small compared to the evolution time itself. This typical error is characterized by an asymptotic series and depends solely on the endpoints of the evolution, remaining independent of the details of the intermediate evolution.

adiabatic approximation↗
DOE OSTI2020

Verification of an improved equation-free projective integration method for neoclassical plasma-profile evolution in tokamak geometry

A brute-force, long-time gyrokinetic simulation of plasma profile evolution in magnetic fusion devices is not desirable due to large computational resource requirements and a possible accumulation of numerical error. The equation-free projective integration method of Keverekidis et al. [Commun. Math. Sci. 1(4), 715–762 (2003)] is one of the outstanding candidates in projecting micro-scale simulations to a longer timescale. However, its application to tokamak plasma has not been fruitful due to the appearance of spurious transient oscillations in the lifting process, which are present when the kinetic simulations are initialized with a simplified model distribution function and which make the kinetic simulations to deviate from the desired paths. In this work, a kinetically informed lifting algorithm is added to the equation-free projective integration method, which is then verified in the electrostatic gyrokinetic particle-in-cell code XGCa [R. Hager and C. S. Chang, Phys. Plasmas 23, 042503 (2016)] for a neoclassical ion heat transport problem with adiabatic electrons. This new lifting operator is demonstrated to control spurious transients, enabling an over four-times reduction in the overall computing time in the time-evolution of the ion temperature profile in an axisymmetric toroidal plasma. Further reduction in the computing time is found to be limited due to the stability properties of the linear least squares projective integrator.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Universal progression of structure and dynamics in colloidal nanocrystal gels during salt-accelerated aging

Controlling the structure and function of colloidal gels requires a detailed understanding of how the various components govern network formation and aging. In particular, molecular additives like salts are widely used to tune interparticle interactions, yet their influence on gelation pathways in complex systems such as colloidal nanocrystal gels remains inadequately understood. Here, we investigate how noncoordinating salts modulate the evolution of gels formed using chemically linked tin-doped indium oxide nanocrystals. Through combined structural, dynamic, and kinetic analyses, we demonstrate that increasing salt concentration accelerates gelation. When rescaled by salt-dependent characteristic times, the evolution collapses onto universal trajectories, revealing a time-salt superposition principle. The universality extends across length scales, suggesting a consistent salt-dependent mechanism that controls both local structuring and macroscopic network formation. This observed salt modulation of structure and dynamics provides a predictive basis for controlling the kinetics of nonequilibrium nanocrystal gel assembly, enhancing the rational design of functional nanomaterials with tunable properties.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Neural-network learning of SPOD latent dynamics

Here, we aim to reconstruct the latent space dynamics of high dimensional, quasi-stationary systems using model order reduction via the spectral proper orthogonal decomposition (SPOD). The proposed method is based on three fundamental steps: in the first, once that the mean flow field has been subtracted from the realizations (also referred to as snapshots), we compress the data from a high-dimensional representation to a lower dimensional one by constructing the SPOD latent space; in the second, we build the time-dependent coefficients by projecting the snapshots containing the fluctuations onto the SPOD basis and we learn their evolution in time with the aid of recurrent neural networks; in the third, we reconstruct the high-dimensional data from the learnt lower -dimensional representation. The proposed method is demonstrated on two different test cases, namely, a compressible jet flow, and a geophysical problem known as the Madden-Julian Oscillation. An extensive comparison between SPOD and the equivalent POD-based counterpart is provided and differences between the two approaches are highlighted. The numerical results suggest that the proposed model is able to provide low rank predictions of complex statistically stationary data and to provide insights into the evolution of phenomena characterized by specific range of frequencies. The comparison between POD and SPOD surrogate strategies highlights the need for further work on the characterization of the interplay of error between data reduction techniques and neural network forecasts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Temporal evolution of scalar modes in Richtmyer–Meshkov instability of inclined interface using high-speed PIV and PLIF measurements at 60 kHz

Abstract The current work presents simultaneous, high-speed measurements at 60,000 fields per second of velocity and mole fraction using particle image velocimetry (PIV) and planar laser induced acetone-fluorescence in a Richtmyer–Meshkov instability of an inclined interface (Atwood number, At = 0.22). Specifically, around 2 ms of temporal evolution of the vortex structures and their associated scalar modes immediately following the interface-reshock interaction is presented. Two initial interface conditions are discussed—(a) a sharp, inclined ‘single mode’ interface and (b) a ‘multi-mode’ interface where small perturbations are imposed on the single mode case. A 2D wavelet decomposition of the scalar flow field shows a highly intermittent distribution of small-scale variance throughout the interface even at late times. These are correlated strongly with the vortex structures and local turbulence intensity, where each small-scale scalar mode is sandwiched between two co-rotating vortex structures. This indicates that the interstitial regions between the vortices are significant hotspots of entrainment, which is then dispersed by the induced, counter-flow velocity fields. The multimode case demonstrates similar organization at large scales, while the scalar field is much more homogeneous at smaller scales. These observations highlight the importance of capturing the early time vortex evolution to accurately estimate any late time intermittency, especially where deposition of intense vorticity on sharp interfaces is present.

Engineering↗
DOE OSTI2021

Development of a reduced model for energetic particle transport by sawteeth in tokamaks

We report that the sawtooth instability is known for inducing transport and loss of energetic particles (EPs), and for generating seed magnetic islands that can trigger tearing modes. Both effects degrade the overall plasma performance. Several theories and numerical models have been previously developed to quantify the expected EP transport caused by sawteeth, with various degrees of sophistication to differentiate the response of EPs at different energies and on different orbits (e.g. passing vs. trapped), although the analysis is frequently limited to a single time slice during a tokamak discharge. This work describes the development and initial benchmark of a framework that enables a reduced model for EP transport by sawteeth retaining the full EP phase-space information. The model, implemented in the ORBIT hamiltonian particle-following code, can be used either as a standalone post-processor taking input data from codes such as TRANSP, or as a pre-processor to compute transport coefficients that can be fed back to TRANSP for time-dependent simulations including the effects of sawteeth on EPs. The advantage of the latter approach is that the evolution of the EP distribution can be simulated quantitatively for sawtoothing discharges, thus enabling a more accurate modeling of sources, sinks and overall transport properties of EP and thermal plasma species for comprehensive physics studies that require detailed information of the fast-ion distribution function and its evolution over time.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗