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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 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Majorana zero modes in impurity-assisted vortex of LiFeAs superconductor

The iron-based superconductor is emerging as a promising platform for Majorana zero mode, which can be used to implement topological quantum computation. One of the most significant advances of this platform is the appearance of large vortex level spacing that strongly protects Majorana zero mode from other low-lying quasiparticles. Despite the advantages in the context of physics research, the inhomogeneity of various aspects hampers the practical construction of topological qubits in the compounds studied so far. Here we show that the stoichiometric superconductor LiFeAs is a good candidate to overcome this obstacle. By using scanning tunneling microscopy, we discover that the Majorana zero modes, which are absent on the natural clean surface, can appear in vortices influenced by native impurities. Our detailed analysis reveals a new mechanism for the emergence of those Majorana zero modes, i.e. native tuning of bulk Dirac fermions. The discovery of Majorana zero modes in this homogeneous material, with a promise of tunability, offers an ideal material platform for manipulating and braiding Majorana zero modes, pushing one step forward towards topological quantum computation.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Finite-difference time-domain methods

The finite-difference time-domain (FDTD) method is a widespread numerical tool for full-wave analysis of electromagnetic fields in complex media and for detailed geometries. Applications of the FDTD method cover a range of time and spatial scales, extending from subatomic to galactic lengths and from classical to quantum physics. Technology areas that benefit from the FDTD method include biomedicine — bioimaging, biophotonics, bioelectronics and biosensors; geophysics — remote sensing, communications, space weather hazards and geolocation; metamaterials — sub-wavelength focusing lenses, electromagnetic cloaks and continuously scanning leaky-wave antennas; optics — diffractive optical elements, photonic bandgap structures, photonic crystal waveguides and ring-resonator devices; plasmonics — plasmonic waveguides and antennas; and quantum applications — quantum devices and quantum radar. This Primer summarizes the main features of the FDTD method, along with key extensions that enable accurate solutions to be obtained for different research questions. Additionally, hardware considerations are discussed, plus examples of how to extract magnitude and phase data, Brillouin diagrams and scattering parameters from the output of an FDTD model. Furthermore, the Primer ends with a discussion of ongoing challenges and opportunities to further enhance the FDTD method for current and future applications.

42 ENGINEERING↗
DOE OSTI2022

Particle-in-cell modeling of plasma jet merging in the large-Hall-parameter regime

The merging process of magnetized plasma jets with parameters relevant to the plasma-jet-driven magneto-inertial fusion (PJMIF) design and the plasma liner experiment (PLX) is modeled by fully kinetic particle-in-cell (PIC) simulations in one and two spatial dimensions. Here, the modified two-stream instability is identified to be the main mechanism responsible for stopping the plasma jets and preventing species interpenetration. The electron and ion Hall parameters of the merged plasma are greater than unity, and the plasma β is close to unity, which is the desired characteristic of planned experiments at PLX. Our 2D PIC simulations validate the results of the radiation magneto-hydrodynamics code FLASH, which will be the primary tool for modeling various stages of future PJMIF experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Electron kinetics in a positive column of AC discharges in a dynamic regime

Abstract We have performed hybrid kinetic-fluid simulations of a positive column in alternating current (AC) argon discharges over a range of driving frequencies f and gas pressure p for the conditions when the spatial nonlocality of the electron energy distribution function (EEDF) is substantial. Our simulations confirmed that the most efficient conditions of plasma maintenance are observed in the dynamic regime when time modulations of mean electron energy (temperature) are substantial. The minimal values of the root mean square electric field and the electron temperature have been observed at f/p values of about 3 kHz Torr −1 in a tube of radius R = 1 cm. The ionization rate and plasma density reached maximal values under these conditions. The numerical solution of a kinetic equation allowed accounting for the kinetic effects associated with spatial and temporal nonlocality of the EEDF. Using the kinetic energy of electrons as an independent variable, we solved an anisotropic tensor diffusion equation in phase space. We clarified the role of different flux components during electron diffusion in phase space over surfaces of constant total energy. We have shown that the kinetic theory uncovers a more exciting and rich physics than the classical ambipolar diffusion (Schottky) model. Non-monotonic radial distributions of excitation rates, metastable densities, and plasma density have been observed in our simulations at pR > 6 Torr cm. The predicted off-axis plasma density peak in the dynamic regime has never been observed in experiments so far. We hope our results stimulate further experimental studies of the AC positive column. The kinetic analysis could help uncover new physics even for such a well-known plasma object as a positive column in noble gases.

Physics↗
DOE OSTI2020

Earth's water reservoirs in a changing climate

Progress towards achieving a quantitative understanding of the exchanges of water between Earth's main water reservoirs is reviewed with emphasis on advances accrued from the latest advances in Earth Observation from space. These exchanges of water between the reservoirs are a result of processes that are at the core of important physical Earth-system feedbacks, which fundamentally control the response of Earth's climate to the greenhouse gas forcing it is now experiencing, and are therefore vital to understanding the future evolution of Earth's climate. The changing nature of global mean sea level (GMSL) is the context for discussion of these exchanges. Different sources of satellite observations that are used to quantify ice mass loss and water storage over continents, how water can be tracked to its source using water isotope information and how the waters in different reservoirs influence the fluxes of water between reservoirs are described. The profound influence of Earth's hydrological cycle, including human influences on it, on the rate of GMSL rise is emphasized. The many intricate ways water cycle processes influence water exchanges between reservoirs and thus sea-level rise, including disproportionate influences by the tiniest water reservoirs, are emphasized.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Assessing the difficulty of capturing the distribution function of neutrinos in neutron star merger simulations

The collision of two neutron stars is a rich source of information about nuclear physics. In particular, the kilonova signal following a merger can help us elucidate the role of neutron stars in nucleosynthesis, and informs us about the properties of matter above nuclear saturation. Approximate modeling of neutrinos remains an important limitation to our ability to make predictions for these observables. Part of the problem is the fermionic nature of neutrinos. By the exclusion principle, the expected value 𝑓 𝜈 for the number of neutrinos in a quantum state is at most 1. Any process producing neutrinos is suppressed by a blocking factor (1 −𝑓 𝜈 ). Recent simulations focused on neutrino physics mostly use a gray two-moment scheme to evolve neutrinos. This evolves integrals of 𝑓 𝜈 over momentum space, preventing direct calculations of blocking factors. Monte Carlo methods may be an attractive alternative, providing access to the full distribution of neutrinos. Their current implementation is, however, inadequate to estimate 𝑓 𝜈 : in our most recent simulations, a single Monte Carlo packet causes, in the worst cases, estimates of 𝑓 𝜈 to jump from 𝑓 𝜈 =0 to 𝑓 𝜈 ∼10 5 . While this is concerning, this brazen violation of the fermionic nature of neutrinos has been largely inconsequential, as the interactions used in simulations avoid direct calculations of 𝑓 𝜈 . We are, however, reaching a level of modeling at which this problem can no longer be ignored. Here, we discuss the relatively simple origin of this issue. We then show that very rough estimates of 𝑓 𝜈 can in theory be obtained in merger simulations, but that they will require a combination of unintuitive weighting schemes for Monte Carlo packets and smoothing of the neutrino distribution at coarser resolution than what the merger simulation uses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Topological states on fractal lattices

Here, we investigate the fate of topological states on fractal lattices. Focusing on a spinless chiral p-wave paired superconductor, we find that this model supports two qualitatively distinct phases when defined on a Sierpinski gasket.While the trivial phase is characterized by a self-similar spectrum with infinitely many gaps and extended eigenstates, the “topological” phase has a gapless spectrum and hosts chiral states propagating along edges of the graph. Besides employing theoretical probes such as the real-space Chern number, inverse participation ratio, and energy-level statistics in the presence of disorder, we develop a simple physical picture capturing the essential features of the model on the gasket. Extending this picture to other fractal lattices and topological states, we show that the p + ip state admits a gapped topological phase on the Sierpinski carpet and that a higher-order topological insulator placed on this lattice hosts gapless modes localized on corners.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
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 OSTI2020

𝐹 𝐾 ⁡/𝐹 𝜋 from Möbius domain-wall fermions solved on gradient-flowed HISQ ensembles

We report the results of a lattice quantum chromodynamics calculation of 𝐹 𝐾 ⁡/𝐹 𝜋 using Möbius domain-wall fermions computed on gradient-flowed 𝑁 𝑓 =2 +1 +1 highly improved staggered quark (HISQ) ensembles. The calculation is performed with five values of the pion mass ranging from 130 ≲ 𝑚 𝜋 ≲ 400 MeV , four lattice spacings of 𝑎 ∼ 0.15, 0.12, 0.09 and 0.06 fm and multiple values of the lattice volume. The interpolation/extrapolation to the physical pion and kaon mass point, the continuum, and infinite volume limits are performed with a variety of different extrapolation functions utilizing both the relevant mixed-action effective field theory expressions as well as discretization-enhanced continuum chiral perturbation theory formulas. We find that the 𝑎 ∼ 0.06 fm ensemble is helpful, but not necessary to achieve a subpercent determination of 𝐹 𝐾 ⁡/𝐹 𝜋 . We also include an estimate of the strong isospin breaking corrections and arrive at a final result of 𝐹 $\hat{K}$ + ⁡ /𝐹 $\hat{𝜋}$ + = 1.1942⁢(45) with all sources of statistical and systematic uncertainty included. This is consistent with the Flavour Lattice Averaging Group average value, providing an important benchmark for our lattice action. Combining our result with experimental measurements of the pion and kaon leptonic decays leads to a determination of |𝑉 𝑢⁢𝑠 |/|𝑉 𝑢⁢𝑑 | = 0.2311⁢(10).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Natural anomaly mediation from the landscape with implications for LHC SUSY searches

Supersymmetric models with the anomaly-mediated supersymmetry (SUSY) breaking (AMSB) form for soft SUSY breaking terms arise in two different settings: (1) extra-dimensional models where SUSY breaking occurs in a sequestered sector, and (2) 4 − d models with dynamical SUSY breaking in a hidden sector where scalars gain masses of order the gravitino mass m 3 / 2 , but gaugino masses and trilinear soft terms are assumed to be of the AMSB form. Both models run into serious conflicts with (1) LHC sparticle and Higgs mass constraints, (2) constraints from winolike weakly interacting massive particle dark matter searches, and (3) bounds from naturalness. These conflicts may be avoided by introducing minor changes to the underlying phenomenological models consisting of nonuniversal bulk scalar Higgs masses and A terms, providing a setting for natural anomaly mediation (nAMSB). In nAMSB, the wino is still expected to be the lightest of the gauginos, but the Higgsinos are expected to be the lightest electroweakinos (EWinos) in accord with naturalness. We examine what sorts of spectra are expected to emerge when nAMSB arises from a string landscape setting: While model 2 can only be natural for a Higgs mass m h ≲ 123 GeV , model 1 can accommodate naturalness along with m h ∼ 125 GeV while still respecting LHC bounds on sparticle masses. We explore the LHC phenomenology of nAMSB models where we find that for Higgsino pair production, typically larger dilepton mass gaps arise from the soft dilepton-plus-jets signature than in models with gaugino mass unification. For wino-pair production, the higher m 3 / 2 portion of nAMSB parameter space is excluded by recent LHC bounds from gaugino pair production searches. We characterize the dominant LHC signatures arising from the remaining lower m 3 / 2 ∼ 90 – 200 TeV range of parameter space, which should be fully testable at high-luminosity LHC via EWino pair production searches. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2024

Gravitationally misaligned ultralight dark matter and implications for neutron stars

We examine the possibility that dark matter (DM) may be an ultralight scalar that was misaligned via nonminimal coupling to gravity, in the early Universe. For a certain regime of scalar masses, gravitational effects in neutron stars could place interesting bounds on the viable parameter space of the model, even in the absence of nongravitational interactions between DM and ordinary matter. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Operator origin of anomalous dimensions in de Sitter space

The late-time limit of the power spectrum for heavy (principal series) fields in de Sitter (dS) space yields a series of polynomial terms with complex scaling dimensions. Such scaling behavior is expected to result from an associated operator with a complex dimension. In a free theory, these complex dimensions are known to match the constraints imposed by unitarity on the space of states. Yet, perturbative corrections to the scaling behavior of operators are naively inconsistent with unitary evolution of the quantum fields in dS space. This paper demonstrates how to compute one-loop corrections to the scaling dimensions that appear in the two-point function from the field theory description in terms of local operators. We first show how to evaluate these anomalous dimensions using Mellin space, which has the feature that it naturally accommodates a scaleless regulator. We then explore the consequences for the soft de Sitter effective theory (SdSET) description that emerges in the long wavelength limit. Carefully matching between the UV and SdSET descriptions requires the introduction of novel nondynamical “operators” in the effective theory. This is not only necessary to reproduce results extracted from the Källén-Lehmann representation (that use the space of unitary states directly), but it is also required by general arguments that invoke positivity. Published by the American Physical Society 2025

Cohen, Timothy↗
DOE OSTI2023

Uncertainty quantification for equations of state: copper as an example

Equations of state are essential for providing a fundamental description of materials properties in thermodynamic equilibrium and are used to provide closure relations for hydrodynamics simulations. Generally, equations of state rely on simple physics-based parameterized materials models to inform on the free energy of a material through out a given thermodynamic state space. Historically the parameters of these models have been tuned by hand to fit various experimental data. However, modern optimization and uncertainty quantification techniques allow us to quickly test thousands of parameter combinations and obtain meaningful uncertainty estimates on the parameters, opening opportunities for assessing systematic uncertainties in experiments, assessing model adequacy, and more. In this report, we use Bayesian inference to fit the solid (fcc) equation of state of copper. We focus on fitting five different experimental datasets, including the isobaric density, isobaric heat capacity, room temperature isotherm, principal isentrope, and principal Hugoniot. We fit all five data types simultaneously, and then explore the extent to which combinations of 2 subsets of the 5 datasets can constrain the EOS parameters, as compared to the fit to all 5. This information is useful for investigating the extent to which different datasets can con strain EOS models and thereby help guide experimental investigations in order to best constrain the EOS. We also discuss ways that the methodologies can be used to investigate systematic discrepancies between experiments, as well as how the methods can be used to assess model uncertainty. The framework we develop is general, in that it can be used with a variety of optimization or uncertainty quantification techniques and with a variety of data sources, including both experimental and ab-inito data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Using Gravitational Lensing to Probe for Candidate Quintessential Galaxies in the Epoch of Reionization

Abstract Understanding the properties of the first generation of galaxies is an ongoing challenge in observational astrophysics. James Webb Space Telescope deep-field observations have led to the identification of large numbers of galaxies within the Epoch of Reionization (EoR); however, it remains observationally challenging to study the detailed properties of the most numerous, faint high- z galaxies without strong gravitational lensing. To this end, we present five m AB ≃ 24 galaxies, all projected behind the cores of massive clusters where high lensing magnifications significantly (≳1.5 mag) boost their observed brightness. These galaxies are each characterized by a drop-off in their spectra between the near-IR and optical wavelengths, suggesting the presence of a Lyman break at z > 6. The bright sources enable precise dropout color constraints. We combine the dropout data with follow-up imaging to constrain continuum slopes redward of their breaks. Using the open-source spectral energy distribution modeling software Prospector , we characterize two of these galaxies as probable high- z ( z ∼ 6.5–7) and three as probable low- z ( z ∼ 2) sources, demonstrating that for very bright ( m AB < 24) dropout candidates even limited photometric data have good power to distinguish between high- z galaxies and red or dusty low- z galaxies. The two candidate high- z dropouts are comparably bright to the brightest galaxies identified at such redshifts in deep fields, but due to lensing magnifications are intrinsically fainter by at least 1.5 mag. If confirmed, these galaxies represent exciting laboratories for performing detailed follow-up studies of galaxy properties within the EoR.

Roberson, Joshua [University of Cincinnati] (ORCID↗
DOE OSTI2021

A deep learning hybrid predictive modeling (HPM) approach for estimating evapotranspiration and ecosystem respiration

Climate change is reshaping vulnerable ecosystems, leading to uncertain effects on ecosystem dynamics, including evapotranspiration (ET) and ecosystem respiration (R eco ). However, accurate estimation of ET and R eco still remains challenging at sparsely monitored watersheds, where data and field instrumentation are limited. In this study, we developed a hybrid predictive modeling approach (HPM) that integrates eddy covariance measurements, physically based model simulation results, meteorological forcings, and remote-sensing datasets to estimate ET and R eco in high space–time resolution. HPM relies on a deep learning algorithm and long short-term memory (LSTM) and requires only air temperature, precipitation, radiation, normalized difference vegetation index (NDVI), and soil temperature (when available) as input variables. We tested and validated HPM estimation results in different climate regions and developed four use cases to demonstrate the applicability and variability of HPM at various FLUXNET sites and Rocky Mountain SNOTEL sites in Western North America. To test the limitations and performance of the HPM approach in mountainous watersheds, an expanded use case focused on the East River Watershed, Colorado, USA. The results indicate HPM is capable of identifying complicated interactions among meteorological forcings, ET, and R eco variables, as well as providing reliable estimation of ET and R eco across relevant spatiotemporal scales, even in challenging mountainous systems. The study documents that HPM increases our capability to estimate ET and R eco and enhances process understanding at sparsely monitored watersheds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Scalable Deep-Learning-Accelerated Topology Optimization for Additively Manufactured Materials

Topology optimization (TO) is a popular and powerful computational approach for designing novel structures, materials, and devices. Two computational challenges have limited the applicability of TO to a variety of industrial applications. First, a TO problem often involves a large number of design variables to guarantee sufficient expressive power. Second, many TO problems require a large number of expensive physical model simulations, and those simulations cannot be parallelized. To address these issues, we propose a general scalable deep-learning (DL) based TO framework, referred to as SDL-TO, which utilizes parallel schemes in high performance computing (HPC) to accelerate the TO process for designing additively manufactured (AM) materials. Unlike the existing studies of DL for TO, our framework accelerates TO by learning the iterative history data and simultaneously training on the mapping between the given design and its gradient. The surrogate gradient is learned by utilizing parallel computing on multiple CPUs incorporated with a distributed DL training on multiple GPUs. The learned TO gradient enables a fast online update scheme instead of an expensive update based on the physical simulator or solver. Using a local sampling strategy, we achieve to reduce the intrinsic high dimensionality of the design space and improve the training accuracy and the scalability of the SDL-TO framework. The method is demonstrated by benchmark examples and AM materials design for heat conduction. The proposed SDL-TO framework shows competitive performance compared to the baseline methods but significantly reduces the computational cost by a speed up of around 8.6x over the standard TO implementation.

Bi, Sirui↗
DOE OSTI2023

NETL Plastic Pipes Project (Final Report)

Plastic or composite pipelines have been the bane of the utility locating industry because they are neither conductive nor magnetic which are the properties traditionally used to locate buried utilities. Ground penetrating radar (GPR) is an effective geophysical tool for locating plastic/composite pipelines where resistive cover allows for adequate penetration of radar energy. However, GPR has limited applicability in areas where the soil cover is conductive due to significant clay and/or salt content. This study examines complementary near-surface geophysical methods that are potentially useful for locating buried plastic/composite pipelines, either singly or in combination. Specifically, this modeling study used computational numerical methods to forward model the response of GPR, resistivity, seismic, gravity gradiometry, and photoacoustic/thermoacoustic imaging methods to plastic/composite pipelines for various scenarios including: (1) pipe diameters ranging between 2 in. to 12 in.; (2) burial depths ranging between 3 ft. to 4 ft.; (3) various degrees in contrast in physical properties (i.e., electrical permittivity, elasticity, resistivity, density); and (4) various experimental acquisition choices (e.g., GPR radar and seismic source frequencies, electrode spacing). Numerical modeling performed herein reconfirmed that GPR is the preferred method for detecting/locating plastic pipelines. A caveat for GPR detection is that the material covering the plastic pipe (trench fill material and adjacent soil) must be sufficiently resistive to allow the two-way propagation to the required depth of investigation and back to the surface. GPR was the only method modeled in this study that can be used to directly detect plastic pipelines of 2-in.-diameter and larger when buried 3-ft-deep. GPR data processing and imaging also can determine pipe depth, pipe diameter, trench dimensions, and moisture conditions. Seismic modeling results suggest that direct detection of a 12-in.-diameter plastic pipe at 3-ft.-depth may be possible under favorable conditions; however, the associated signature would be weak (e.g., surface- to S-wave, backscattered surface-waves, and/or forward scattered surface-waves to S-wave). Direct pipe detection under field conditions with noise and strong lateral geologic heterogeneity is doubtful. Numerical modeling also suggests that plastic pipelines can be indirectly located by detecting the trench in which they are buried. GPR, direct current (DC) resistivity, and seismic methods have the potential to locate the pipeline trench if there is sufficient contrast between the trench-wall and trench-fill materials for the physical property being measured by each method (i.e., electrical permittivity for GPR; resistivity for DC resistivity; or density, compressional velocity, or shear velocity for seismic). Modeling also indicated that currently available (commercial) gravity gradiometers would be unable to directly detect/locate plastic pipelines ≤ 8-in.-diameter when buried 3-ft.-deep given the typical instrument noise floor for field surveying as well as the expected density variations due to geologic heterogeneity. The numerical modeling performed in this project did not identify a universal geophysical technology that can locate buried plastic pipelines in all parts of the United States (although GPR is suggested for all areas with resistive cover). However, the project results suggest that a towed land streamer simultaneously acquiring multiple geophysical data types including multi-offset GPR, multi-channel DC resistivity, seismic geophone- and/or distributed acoustic sensing (DAS), and potentially photoacoustic/thermoacoustic data would be an appropriate platform for locating buried plastic pipeline. Moreover, the complementary multiphysics data acquired by a towed land streamer would permit the use of joint and/or cooperative inversion frameworks for a more rigorous and consistent data interpretation.

42 ENGINEERING↗