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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Photoinduced anisotropic lattice dynamic response and domain formation in thermoelectric SnSe

Identifying and understanding the mechanisms behind strong phonon–phonon scattering in condensed matter systems is critical to maximizing the efficiency of thermoelectric devices. To date, the leading method to address this has been to meticulously survey the full phonon dispersion of the material in order to isolate modes with anomalously large linewidth and temperature-dependence. Here we combine quantitative MeV ultrafast electron diffraction (UED) analysis with Monte Carlo based dynamic diffraction simulation and first-principles calculations to directly unveil the soft, anharmonic lattice distortions of model thermoelectric material SnSe. A small single-crystal sample is photoexcited with ultrafast optical pulses and the soft, anharmonic lattice distortions are isolated using MeV-UED as those associated with long relaxation time and large displacements. We reveal that these modes have interlayer shear strain character, induced mainly by c -axis atomic displacements, resulting in domain formation in the transient state. These findings provide an innovative approach to identify mechanisms for ultralow and anisotropic thermal conductivity and a promising route to optimizing thermoelectric devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Probing nuclear structure of heavy ions at energies available at the CERN Large Hadron Collider

We perform high-statistics simulations to study the impacts of nuclear structure on the ratios of anisotropic flow observables in 208 Pb + 208 Pb and 129 Xe + 129 Xe collisions at the Large Hadron Collider. Even with 40% difference in atomic numbers between 208 Pb and 129 Xe nuclei, the ratios of anisotropic flow in the same centrality class between the two collision systems are strongly affected by the nuclear structure inputs in the initial state. The ratios of v 2 ⁡{4}/v 2 ⁡{2} in these collisions are sensitive to the nuclear skin thickness of the colliding nuclei, providing indirect constraints on the nuclei's neutron skin. In conclusion, our model predictions serve as a benchmark to compare with experimental measurements.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Driving Next-Generation Workflows from the Data Plane

We observe the emergence of a new generation of scientific workflows that process data produced at a sustained rate by scientific instruments and large scale numerical simulations. This data is consumed by multiple analysis, visualization, or Machine Learning components not only to enable inference and justify the scientific program, but also to monitor and steer the evolution of these experiments. In such workflows, moving intermediate data efficiently is key to performance, more than efficiently scheduling computational tasks. However, most traditional workflow management systems focus on optimizing task scheduling and then deal with data management, assuming a “move little, compute for long” model, which makes them unfit to the efficient management of this new generation of workflows. Therefore, we advocate for a new way to manage scientific workflows. We propose to consider an efficiently and independently managed data plane that can store and stream data. Workflows compute components, in the application plane can then interact with the data plane, abstracted from complexities of data management. Then, the role of a workflow management system would become that of a control plane that allows users to connect services together to execute the workflow and manages connections between the application and data planes. In this position paper, we characterize several next-generation workflow motifs and describe how their interaction with the data plane is a challenge to traditional workflow management systems. Then, we express a set of requirements that a workflow management system should meet to efficiently manage next-generation workflows at different scales. Based on these requirements, we expose our vision of driving next-generation workflows from the data plane and list remaining open challenges.

Suter, Fred↗
DOE OSTI2024

The inviscid incompressible limit of Kelvin–Helmholtz instability for plasmas

The Kelvin–Helmholtz Instability (KHI) is an interface instability that develops between two fluids or plasmas flowing with a common shear layer. KHI occurs in astrophysical jets, solar atmosphere, solar flows, cometary tails, planetary magnetospheres. Two applications of interest, encompassing both space and fusion applications, drive this study: KHI formation at the outer flanks of the Earth’s magnetosphere and KHI growth from non-uniform laser heating in magnetized direct-drive implosion experiments. Here, we study 2D KHI with or without a magnetic field parallel to the flow. We use both the GAMERA code, which solves the compressible Euler equations, and the STRATOSPEC code, which solves the Navier-Stokes equations under the Boussinesq approximation, coupled with the magnetic field dynamics. GAMERA is a global three-dimensional MHD code with high-order reconstruction in arbitrary nonorthogonal curvilinear coordinates, which is developed for a large range of astrophysical applications. STRATOSPEC is a three-dimensional pseudo-spectral code with an accuracy of infinite order (no numerical diffusion). Magnetized KHI is a canonical case for benchmarking hydrocode simulations with extended MHD options. An objective is to assess whether or not, and under which conditions, the incompressibility hypothesis allows to describe a dynamic compressible system. For comparing both codes, we reach the inviscid incompressible regime, by decreasing the Mach number in GAMERA, and viscosity and diffusion in STRATOSPEC. Here, we specifically investigate both single-mode and multi-mode initial perturbations, either with or without magnetic field parallel to the flow. The method relies on comparisons of the density fields, 1D profiles of physical quantities averaged along the flow direction, and scale-by-scale spectral densities. We also address the triggering, formation and damping of filamentary structures under varying Mach number or Atwood number, with or without a parallel magnetic field. Comparisons show very satisfactory results between the two codes. The vortices dynamics is well reproduced, along with the breaking or damping of small-scale structures. We end with the extraction of growth rates of magnetized KHI from the compressible regime to the incompressible limit in the linear regime assessing the effects of compressibility under increasing magnetic field. The observed differences between the two codes are explained either from diffusion or non-Boussinesq effects.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Representative-cell-based Modeling of HTTF in SAM

Although the current nuclear power market is primarily occupied by the light water reactors (LWRs), the TRISO-fueled helium-cooled graphite-moderated high temperature gas reactors (HTGRs) are drawing growing attention as the nuclear power industry marches towards more advanced systems. Compared to that of conventional LWRs, the thermal hydraulics of HTGR cores show extra complexity from their multi-scale heat transfer mechanisms with varying importance during different operation modes or transient stages. The modeling of HTGR cores for the system analysis purpose therefore faces the challenge of reaching reasonable fidelity and accuracy while maintaining sufficient simplicity. Previous development and validation efforts have demonstrated that a “2-D ring model” with reasonable performance can be implemented in the System Analysis Module (SAM) for prismatic HTGR cores. In the current project, an alternative modeling methodology based on “representative cells” is proposed for the typical prismatic core of HTGRs. Different from the previous ring model approach, the proposed methodology first separately models and then combines the small- and large-scale thermal conductions, by connecting representative local heat transfer units (cells) with effective core- wise thermal resistance. A modeling practice for an integral high-temperature test facility (HTTF) elaborates the modeling details. Steady-state validation of the resultant candidate model is performed against a higher-resolution benchmark from a 3D-1D coupled simulation, which shows satisfactory prediction with reasonably captured global parameters and well-represented temperature fields. A postulated pressurized conduction cooldown (PCC) is also simulated and analyzed, demonstrating the model’s capability of transient prediction with physically captured phenomena resolved in both small and large temporal and spatial scales. In general, the current work achieves a preliminary success in proposing a methodology using representative cells to model prismatic HTGR cores in SAM. Future efforts are envisioned with more validation activities and with potential modeling improvements to eventually achieve the high confidence on a high-fidelity robust modeling methodology with reasonable accuracy.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Dirty bosons on the Cayley tree: Bose-Einstein condensation versus ergodicity breaking

Building on large-scale quantum Monte Carlo simulations, we investigate the zero-temperature phase diagram of hard-core bosons in a random potential on site-centered Cayley trees with branching number K=2. In order to follow how the Bose-Einstein condensate (BEC) is affected by the disorder, we focus on both the zero-momentum density, probing the quantum coherence, and the one-body density matrix (1BDM) whose largest eigenvalue monitors the off-diagonal long-range order. We further study its associated eigenstate which brings useful information about the real-space properties of this leading eigenmode. Upon increasing randomness, we find that the system undergoes a quantum phase transition at finite disorder strength between a long-range ordered BEC state, fully ergodic at large scale, and a new disordered Bose glass regime showing conventional localization for the coherence fraction while the 1BDM displays a nontrivial algebraic vanishing BEC density together with a nonergodic occupation in real space. These peculiar properties can be analytically captured by a simple phenomenological description on the Cayley tree which provides a physical picture of the Bose glass regime.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Decoding the Desorption Mechanism of 2LiH:1Mg(NH2)2 Using Metal Borohydrides

The complex metal hydride 2LiH:1Mg­(NH2)2 has emerged as a promising material for stationary hydrogen storage applications, such as seasonal storage or energy backup systems, due to its high volumetric and gravimetric capacities and robust reversibility. However, its widespread adoption is hindered by sluggish reaction rates, performance degradation upon cycling, and improper end-use cases. To address these problems and better understand the desorption pathway, we used metal borohydrides (MBH4; M = Li–Cs) as chemical probes. A thorough analysis of the bulk behavior of all six materials, including hydrogen cycling experiments, X-ray absorption spectroscopy, FTIR, pXRD, solid-state NMR, and ab initio DFT simulations, shows that the borohydride additives decrease the activation energy of hydrogen release by about 20 kJ/mol for MBH4@2:1 materials versus pristine. Furthermore, more surface-sensitive studies show that the amide-to-imide desorption pathway in these materials, while essentially complete in the bulk, is incomplete in the near-surface region, suggesting an “inverse core–shell” desorption mechanism for amide dehydrogenation to imide. The kinetic enhancements produced by MBH4 additives (M = K, Rb, and Cs) are attributed to the destabilization of the amide N–H bond and interaction with the LiH/Mg­(NH2)2 interface to promote H–H bond formation. An inverse core-shell mechanism is also operative in the hydrogen desorption for the 2LiH:1LiNH2 system, suggesting this may be a general feature of amides. Given the fast dehydrogenation rate and large gravimetric capacity, these materials satisfy these requirements for telecom backups and seasonal microgrid storage applications.

Absorption↗
DOE OSTI2025

Machine-learning-informed scattering correlation analysis of sheared colloids

We have carried out theoretical analysis, Monte Carlo simulations and machine-learning analysis to quantify microscopic rearrangements of dilute dispersions of spherical colloidal particles from coherent scattering intensity. Both monodisperse and polydisperse dispersions of colloids were created and underwent a rearrangement consisting of an affine simple shear and non-affine rearrangement using the Monte Carlo method. We calculated the coherent scattering intensity of the dispersions and the correlation function of intensity before and after the rearrangement and generated a large data set of angular correlation functions for varying system parameters, including number density, polydispersity, shear strain and non-affine rearrangement. Singular value decomposition of the data set shows the feasibility of machine-learning inversion from the correlation function for the polydispersity, shear strain and non-affine rearrangement using only three parameters. A Gaussian process regressor is then trained on the data set and can retrieve the affine shear strain, non-affine rearrangement and polydispersity with relative errors of 3%, 1% and 6%, respectively. Altogether, our model provides a framework for quantitative studies of both steady and non-steady microscopic dynamics of colloidal dispersions using coherent scattering methods.

Gaussian process regression↗
DOE OSTI2024

Milky Way-est: Cosmological Zoom-in Simulations with Large Magellanic Cloud and Gaia–Sausage–Enceladus Analogs

Abstract We present Milky Way-est, a suite of 20 cosmological cold-dark-matter-only zoom-in simulations of Milky Way (MW)-like host halos. Milky Way-est hosts are selected such that they (i) are consistent with the MW’s measured halo mass and concentration, (ii) accrete a Large Magellanic Cloud (LMC)-like (≈10 11 M ⊙ ) subhalo within the last 2 Gyr on a realistic orbit, placing them near 50 kpc from the host center at z ≈ 0, and (iii) undergo a >1:5 sub-to-host halo mass ratio merger with a Gaia–Sausage–Enceladus (GSE)-like system at early times (0.67 < z < 3). Hosts satisfying these LMC and GSE constraints constitute <1% of all halos in the MW’s mass range, and their total masses grow rapidly at late times due to LMC analog accretion. Compared to hosts of a similar final halo mass that are not selected to include LMC and GSE analogs, Milky Way-est hosts contain 22% more subhalos with present-day virial masses above 10 8 M ⊙ throughout the virial radius, on average. This enhancement reaches ≈80% in the inner 100 kpc and is largely, if not entirely, due to LMC-associated subhalos. These systems also induce spatial anisotropy in Milky Way-est subhalo populations, with ≈60% of the total subhalo population within 100 kpc found in the current direction of the LMC. Meanwhile, we find that GSE-associated subhalos do not significantly contribute to present-day Milky Way-est subhalo populations. These results provide context for our Galaxy’s dark matter structure and subhalo population and will help interpret a range of measurements that are currently only possible in the MW.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Predicting nonequilibrium Green’s function dynamics and photoemission spectra via nonlinear integral operator learning

Understanding the dynamics of nonequilibrium quantum many-body systems is an important research topic in a wide range of fields across condensed matter physics, quantum optics, and high-energy physics. However, numerical studies of large-scale nonequilibrium phenomena in realistic materials face serious challenges due to intrinsic high-dimensionality of quantum many-body problems and the absence of time-invariance. The nonequilibrium properties of many-body systems can be described by the dynamics of the correlator, or the Green's function of the system, whose time evolution is given by a high-dimensional system of integro-differential equations, known as the Kadanoff–Baym equations (KBEs). The time-convolution term in KBEs, which needs to be recalculated at each time step, makes it difficult to perform long-time numerical simulation. In this paper, we develop an operator-learning framework based on recurrent neural networks (RNNs) to address this challenge. We utilize RNNs to learn the nonlinear mapping between Green's functions and convolution integrals in KBEs. By using the learned operators as a surrogate model in the KBE solver, we obtain a general machine-learning scheme for predicting the dynamics of nonequilibrium Green's functions. Besides significant savings per each time step, the new methodology reduces the temporal computational complexity from $O(N_t^3)$ to $O(N_t)$ where N t is the number of steps taken in a simulation, thereby making it possible to study large many-body problems which are currently infeasible with conventional KBE solvers. Through various numerical examples, we demonstrate the effectiveness of the operator-learning based approach in providing accurate predictions of physical observables such as the reduced density matrix and time-resolved photoemission spectra. Moreover, our framework exhibits clear numerical convergence and can be easily parallelized, thereby facilitating many possible further developments and applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Non -degenerate marginal-likelihood calibration with application to quantum characterization

Here, we propose a marginal likelihood strategy within the Kennedy-O’Hagan (KOH) Bayesian framework, where a Gaussian process (GP) models the discrepancy between a physical system and its simulator. Our approach introduces a novel marginalized likelihood by integrating out the degenerate eigenspace of the covariance matrix, rather than approximating the original likelihood. Unlike approximation methods that compromise accuracy for computational efficiency, our method defines an exact likelihood—distinct from the original but preserving all relevant information. This formulation achieves computational efficiency and stability, even for large datasets where the covariance matrix nears degeneracy. Applied to the characterization of a superconducting quantum device at Lawrence Livermore National Laboratory, the approach enhances the predictive accuracy of the Lindblad master equations for modeling Ramsey measurement data by effectively quantifying uncertainties consistent with the quantum data.

general physics↗
DOE OSTI2021

Precambrian Crystalline Basement Properties From Pressure History Matching and Implications for Induced Seismicity in the US Midcontinent

Injection-induced seismicity across the US midcontinent has almost exclusively occurred in the crystalline basement that underlies the Arbuckle Group aquifer and its equivalents, the primary wastewater disposal zone in this region. However, the properties of the basement are not well known. Newly compiled data, from Class I wells in Kansas, provide a unique record of pressures in the Arbuckle and an opportunity to constrain the reservoir-scale properties of the basement such as permeability, diffusivity, and specific storage. Constraints on these parameters are critical for modeling fluid flow and pressures across the entire Arbuckle-basement system, and are necessary for accurate evaluation and prediction of injection-induced earthquakes. Here, we present a detailed, three-dimensional geological and pressure history-matched numerical model for the Arbuckle and basement, based on data from >400 wells covering a large region in south-central Kansas, where injection-induced seismicity has been concentrated since 2014. Simulations of dynamic data from 319 wells indicate that Arbuckle pressures have increased by 1.1 MPa in high injection rate areas and an overpressure of <0.1 MPa may be the cause of seismicity in the basement. Pressure-history matching also yields the likely range in porosity (0.3%–7%), permeability (0.1–0.7 mD), and diffusivity (0.004–0.07 m2 /s) for the basement. The resulting estimates suggest reservoir-scale properties of the basement are enhanced by faults and fractures. Importantly, the diffusivities determined in this study are lower than estimates derived from Kansas earthquake triggering fronts, and suggest that such seismicity-based techniques may have limitations, particularly where spacetime patterns between injection and seismicity are complex.

58 GEOSCIENCES↗
DOE OSTI2025

Continuous operation of a coherent 3,000-qubit system

Neutral atoms are a promising platform for quantum science, enabling advances in areas ranging from quantum simulations and computation to metrology, atomic clocks and quantum networking. Although atom losses typically limit these systems to a pulsed mode, continuous operation could substantially enhance cycle rates, remove bottlenecks in metrology and enable deep-circuit quantum evolution through quantum error correction. Here we demonstrate an experimental architecture for high-rate reloading and continuous operation of a large-scale atom-array system while realizing coherent storage and manipulation of quantum information. Our approach utilizes a series of two optical lattice conveyor belts to transport atom reservoirs into the science region, where atoms are repeatedly extracted into optical tweezers without affecting the coherence of qubits stored nearby. Using a reloading rate of 300,000 atoms in tweezers per second, we create over 30,000 initialized qubits per second, which we leverage to assemble and maintain an array of over 3,000 atoms for more than 2 hours. Furthermore, we demonstrate persistent refilling of the array with atomic qubits in either a spin-polarized or a coherent superposition state while preserving the quantum state of stored qubits. Our results pave the way for the realization of large-scale continuously operated atomic clocks, sensors and fault-tolerant quantum computers.

atomic and molecular physics↗
DOE OSTI2019

Stochastic self-tuning hybrid algorithm for reaction-diffusion systems

Many biochemical phenomena involve reactants with vastly different concentrations, some of which are amenable to continuum-level descriptions, while the others are not. We present a hybrid self-tuning algorithm to model such systems. The method combines microscopic (Brownian) dynamics for diffusion with mesoscopic (Gillespie-type) methods for reactions and remains efficient in a wide range of regimes and scenarios with large variations of concentrations. Furthermore, its accuracy, robustness, and versatility are balanced by redefining propensities and optimizing the mesh size and time step. We use a bimolecular reaction to demonstrate the potential of our method in a broad spectrum of scenarios: from almost completely reaction-dominated systems to cases where reactions rarely occur or take place very slowly. The simulation results show that the number of particles present in the system does not degrade the performance of our method. This makes it an accurate and computationally efficient tool to model complex multireaction systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Three-dimensional plasmoid-mediated reconnection and turbulence in Hall magnetohydrodynamics

Plasmoid instability accelerates reconnection in collisional plasmas by transforming a laminar reconnection layer into numerous plasmoids connected by secondary current sheets in two dimensions (2D) and by fostering self-generated turbulent reconnection in three dimensions (3D). In large-scale astrophysical and space systems, plasmoid instability likely initiates in the collisional regime but may transition into the collisionless regime as the fragmentation of the current sheet progresses toward kinetic scales. Hall magnetohydrodynamics (MHD) models are widely regarded as a simplified yet effective representation of the transition from collisional to collisionless reconnection. However, plasmoid instability in 2D Hall MHD simulations often leads to a single-X-line reconnection configuration, which significantly differs from fully kinetic particle-in-cell simulation results. This study shows that single-X-line reconnection is less likely to occur in 3D compared to 2D. Moreover, depending on the Lundquist number and the ratio between the system size and the kinetic scale, Hall MHD can also realize 3D self-generated turbulent reconnection. We analyze the features of the self-generated turbulent state, including the energy power spectra and the scale dependence of turbulent eddy anisotropy.

Physics↗
DOE OSTI2021

Sensitivity of organized convective storms to model grid spacing in current and future climates

Mesoscale convective systems (MCSs) are complexes of thunderstorms that become organized and cover hundreds of kilometres over several hours. MCSs are prolific rain producers in the tropics and mid-latitudes and are the major cause of warm-season flooding. Traditionally, climate models have difficulties in simulating MCSs partly due to the misrepresentation of complex process interactions that operate across a large range of scales. Significant improvements in simulating MCSs have been found in kilometre-scale models that explicitly simulate deep convection. However, these models operate in the grey zone of turbulent motion and have known deficiencies in simulating small-scale processes (e.g. entrainment, vertical mass transport). Here, we perform mid-latitude idealized ensemble MCS simulations under current and future climate conditions in three atmospheric regimes: hydrostatic (12 km horizontal grid spacing; Δx), non-hydrostatic (Δx = 4, 2 and 1 km) and large eddy scale (Δx = 500 m and 250 m). Our results show a dramatic improvement in simulating MCS precipitation, movement, cold pools, and cloud properties when transitioning from 12 km to 4 km Δx. Decreasing Δx beyond 4 km results in modest improvements except for up- and downdraft sizes, average vertical mass fluxes, and cloud top height and temperature, which continue to change. Most important for climate modelling is that Δx = 4 km simulations reliably capture most MCS climate change signals compared to those of the Δx = 250 m runs. Significantly different climate change signals are found in Δx = 12 km runs that overestimate extreme precipitation changes by up to 100%.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Carrier Localization and Spontaneous Formation of Two-Dimensional Polarization Domain in Halide Perovskites

Halide perovskites are known for their rich phase diagram and superior performance in diverse optoelectronics applications. The latter property is often attributed to the long electron-hole recombination time, whose underlying physical mechanism has been a long-standing controversy. In this Letter, we investigate the transport and localization properties of electron and hole carriers in a prototypical halide perovskite (CsPbBr 3 ), through ab initio tight-binding nonadiabatic dynamics approach for large-scale (tens of nm size) supercell calculations, to simulate electron and ion dynamics on the same footing. Here, we found distinct structural, lattice polarization, and electron-phonon coupling properties at low (below 100 K) and high temperatures, consistent with experimental observations. In particular, at low temperature we find spontaneous formation of polar grain boundaries in the nonpolar bulk systems, which result in two-dimensional polarization patterns that serve to localize and separate electrons and holes. We reveal phonon-assisted variable-range hopping mostly responsible for low-temperature transport, and their characteristic frequency correlates with temperature-dependent phonon power spectrum and energy oscillation frequency in nonadiabatic dynamics. We answer the critical questions of long electron-hole recombination lifetime at low temperature and offer the correlation among polarization domains, electron-phonon couplings, and photocarrier dynamics.

Carrier generation & recombination↗
DOE OSTI2025

Collective neutrino oscillations in three flavors on qubit and qutrit processors

Collective neutrino flavor oscillations are of primary importance in understanding the dynamic evolution of core-collapse supernovae and subsequent terrestrial detection, but also among the most challenging aspects of numerical simulations. This situation is complicated by the quantum many-body nature of the problem due to neutrino-neutrino interactions, which demands a quantum treatment. An additional complication is the presence of three flavors, which often is approximated by the electron flavor and a heavy lepton flavor. In this work, we provide both qubit and qutrit encodings for all three flavors, and develop optimized quantum circuits for the time evolution and analyze the Trotter error. We conclude our study with a hardware experiment of a system of two neutrinos with superconducting hardware: the IBM Torino device for qubits and Advanced Quantum Testbed device at the Lawrence Berkeley National Laboratory for qutrits. We find that error mitigation greatly helps in obtaining a signal consistent with simulations. Finally, while hardware results are comparable at this stage, we expect the qutrit setup to be more convenient for large-scale simulations since it does not suffer from probability leakage into nonphysical qubit space, unlike the qubit setup.

Neutrino oscillations↗