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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 1,729 records · Page 96
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Hydrodynamic generators in relativistic kinetic theory

Here, we resum the nonequilibrium gradient corrections to a single-particle distribution function evolved by the Boltzmann equation in the relaxation time approximation (RTA). We first study a system undergoing Bjorken expansion and show that, for a constant relaxation time, the exact solution of the RTA Boltzmann equation at late times (i.e., after the decay of nonhydrodynamic modes) generates the Borel resummed Chapman-Enskog series. Extending this correspondence to systems without Bjorken symmetry, we construct a ( 3 + 1 )-dimensional hydrodynamic generator for RTA kinetic theory, which is an integral representation of the Chapman-Enskog series in the limit of vanishing nonhydrodynamic modes. Relaxing this limit, we discover at earlier times a set of nonhydrodynamic modes coupled to the RTA Chapman-Enskog expansion. Including the dynamics of these nonhydrodynamic modes is shown to control the emergence of hydrodynamics as an effective field theory description of nonequilibrium fluids, which works well even for far-off-equilibrium situations where the Knudsen number is initially large.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Path description of coordinate-space amplitudes

We develop a coordinate version of light-cone-ordered perturbation theory, for general time-ordered products of fields, by carrying out integrals over one light-cone coordinate for each interaction vertex. The resulting expressions depend on the lengths of paths, measured in the same light-cone coordinate. Each path is associated with a denominator equal to a “light-cone deficit,” analogous to the “energy deficits” of momentum-space time- or light-cone-ordered perturbation theory. In effect, the role played by intermediate states in momentum space is played by paths between external fields in coordinate space. We derive a class of identities satisfied by coordinate diagrams, from which their imaginary parts can be derived. Using scalar QED as an example, we show how the eikonal approximation arises naturally when the external points in a Green function approach the light cone, and we give applications to products of Wilson lines. Although much of our discussion is directed at massless fields in four dimensions, we extend the formalism to massive fields and dimensional regularization.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Evaluating transition metal oxides within DFT-SCAN and SCAN + U frameworks for solar thermochemical applications

Using the strongly constrained and appropriately normed (SCAN) and SCAN+U approximations for describing electron exchange-correlation (XC) within density functional theory, we investigate the oxidation energetics, lattice constants, and electronic structure of binary Ce-, Mn-, and Fe-oxides, which are crucial ingredients for generating renewable fuels using two-step, oxide-based, solar thermochemical reactors. Unlike other common XC functionals, we find that SCAN does not over-bind the O 2 molecule, based on direct calculations of its bond energy and robust agreement between calculated formation enthalpies of main group oxides versus experiments. However, in the case of transition-metal oxides (TMOs), SCAN systematically overestimates (i.e., yields too negative) oxidation enthalpies due to remaining self-interaction errors in the description of their ground-state electronic structure. Adding a Hubbard U term to the transition-metal centers, where the magnitude of U is determined from experimental oxidation enthalpies, significantly improves the qualitative agreement and marginally improves the quantitative agreement of SCAN+U-calculated electronic structure and lattice parameters, respectively, with experiments. Importantly, SCAN predicts the wrong ground-state structure for a few oxides, namely, Ce 2 O 3 , Mn 2 O 3 , and Fe 3 O 4 , while SCAN+U predicts the right polymorph for all systems considered in this work. Furthermore, the SCAN+U framework, with an appropriately determined U, will be required to accurately describe ground-state properties and yield qualitatively consistent electronic properties for most transition-metal and rare earth oxides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Calibrating the Classical Hardness of the Quantum Approximate Optimization Algorithm

The trading of fidelity for scale enables approximate classical simulators such as matrix product states (MPSs) to run quantum circuits beyond exact methods. A control parameter, the so-called bond dimension $\mathcal{χ}$ for MPSs, governs the allocated computational resources and the output fidelity. Here, we characterize the fidelity for the quantum approximate optimization algorithm by the expectation value of the cost function that it seeks to minimize and find that it follows a scaling law $\mathscr{F}$(ln $\mathcal{χ}$/N), where N is the number of qubits. With ln $\mathcal{χ}$ amounting to the entanglement that a MPS can encode, we show that the relevant variable for investigating the fidelity is the entanglement per qubit. Importantly, our results calibrate the classical computational power required to achieve the desired fidelity and benchmark the performance of quantum hardware in a realistic setup. For instance, we quantify the hardness of performing better classically than a noisy superconducting quantum processor by readily matching its output to the scaling function. Moreover, we relate the global fidelity to that of individual operations and establish its relationship with $\mathcal{χ}$ and N. We sharpen the requirements for noisy quantum computers to outperform classical techniques at running a quantum optimization algorithm in speed, size, and fidelity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

NeuralCubes: Deep Representations for Visual Data Exploration

Visual exploration of large multi-dimensional datasets has seen tremendous progress in recent years, allowing users to express rich data queries that produce informative visual summaries, all in real time. Techniques based on data cubes are some of the most promising approaches. However, these techniques usually require a large memory footprint for large datasets. To tackle this problem, we present NeuralCubes: neural networks that predict results for aggregate queries, similar to data cubes. NeuralCubes learns a function that takes as input a given query, for instance, a geographic region and temporal interval, and outputs the result of the query. The learned function serves as a real-time, low-memory approximator for aggregation queries. Our models are small enough to be sent to the client side (e.g. the web browser for a web-based application) for evaluation, enabling data exploration of large datasets without database/network connection. Here, we demonstrate the effectiveness of NeuralCubes through extensive experiments on a variety of datasets and discuss how NeuralCubes opens up opportunities for new types of visualization and interaction.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Ergodic Lagrangian dynamics in a superhero universe

We present a fictional scenario that, while undeniably whimsical, provides the foundation for a unique exercise in extended problem solving, physics analysis, and quantitative model development. Starting with the foundational premise of the Wild Cards shared-world superhero universe, we demonstrate how a variety of concepts appropriate to the advanced undergraduate level—ergodicity, functional analysis, Lagrangian mechanics, and the ever-important simplifying approximation—can be combined into a rich, coherent mathematical model. The goal of this case study is to develop a useful pedagogical exercise in exploring an open-ended research question that presents, at first glance, no clear path forward. Being both eclectic and lengthy, this exercise offers a unique way for students to apply their core physics and mathematics education. It is perhaps best used within a senior honors seminar or within a brief (e.g., January term) elective class.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Calculation of Energy States of Excitons in Square Quantum Wells

The ground and excited energy states of excitons in single square GaAs-based quantum wells are found by the numerical solution of the three-dimensional Schrödinger equation. This equation is obtained within the envelope-function formalism from the exciton energy operator using the spherical approximation of the Luttinger Hamiltonian. Precise results for the exciton states are achieved by the finite-difference method. The radiative decay rates of the calculated states are also determined.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Contribution of Iron Clusters to the Magnetic Properties of Pb{sub 1– y}Fe{sub y}Te Alloys

The field dependences of the magnetization (temperatures T = 2.0–70 K, magnetic fields B ≤ 7.5 T) of the samples from a single-crystalline Pb{sub 1– y}Fe{sub y}Te ingot (y = 0.02) grown by the Bridgman method are studied. It is established that the sample magnetization contains several major contributions such as the paramagnetism of iron ions, diamagnetism of the crystal lattice, and the contributions of charge carriers and clusters of iron atoms. The field dependences of the paramagnetic contribution of iron ions and the contribution of clusters of iron atoms are approximated by theoretical dependences based on the Brillouin and Langevin functions, respectively. The average concentrations and magnetic moment of clusters as well as the total magnetic momentum of clusters in the volume unit in the samples upon increasing the impurity concentration along the ingot are determined.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Genome description of Phlebia radiata 79 with comparative genomics analysis on lignocellulose decomposition machinery of phlebioid fungi

Background: The white rot fungus Phlebia radiata, a type species of the genus Phlebia, is an efficient decomposer of plant cell wall polysaccharides, modifier of softwood and hardwood lignin, and is able to produce ethanol from various waste lignocellulose substrates. Thus, P. radiata is a promising organism for biotechnological applications aiming at sustainable utilization of plant biomass. Here we report the genome sequence of P. radiata isolate 79 originally isolated from decayed alder wood in South Finland. To better understand the evolution of wood decay mechanisms in this fungus and the Polyporales phlebioid clade, gene content and clustering of genes encoding specific carbohydrate-active enzymes (CAZymes) in seven closely related fungal species was investigated. In addition, other genes encoding proteins reflecting the fungal lifestyle including peptidases, transporters, small secreted proteins and genes involved in secondary metabolism were identified in the genome assembly of P. radiata. Results: The PACBio sequenced nuclear genome of P. radiata was assembled to 93 contigs with 72X sequencing coverage and annotated, revealing a dense genome of 40.4 Mbp with approximately 14 082 predicted protein-coding genes. According to functional annotation, the genome harbors 209 glycoside hydrolase, 27 carbohydrate esterase, 8 polysaccharide lyase, and over 70 auxiliary redox enzyme-encoding genes. Comparisons with the genomes of other phlebioid fungi revealed shared and specific properties among the species with seemingly similar saprobic wood-decay lifestyles. Clustering of especially GH10 and AA9 enzyme-encoding genes according to genomic localization was discovered to be conserved among the phlebioid species. In P. radiata genome, a rich repertoire of genes involved in the production of secondary metabolites was recognized. In addition, 49 genes encoding predicted ABC proteins were identified in P. radiata genome together with 336 genes encoding peptidases, and 430 genes encoding small secreted proteins. Conclusions: The genome assembly of P. radiata contains wide array of carbohydrate polymer attacking CAZyme and oxidoreductase genes in a composition identifiable for phlebioid white rot lifestyle in wood decomposition, and may thus serve as reference for further studies. Comparative genomics also contributed to enlightening fungal decay mechanisms in conversion and cycling of recalcitrant organic carbon in the forest ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Uncertainty about the Uncertainty [Slides]

A golden standard in science is to repeat an experiment a statistically significant number of times, recording data using the same set of detectors and the same data analysis methodology. In such case experimental error includes both the range of true values generated by repetitions of the experiment, and measurement uncertainty caused by the detector. They are independent. It is a huge and too frequently used simplification, to assume that one can measure multiple repetitions of an identical experiment, resulting in identical true experimental value. Repetitions, as similar is it is experimentally achievable result in a range of the true values rather than in a single value. When modern, very sensitive and well calibrated measurement systems are used, this range is not negligible, and sometimes dominates, in comparison to the measurement uncertainty. Range of true values depends on the physics of the experiment, while measurement uncertainty depends on the measurement method (properties of the detector not of the experiment). When data from one–of–a kind experiment are analyzed, only the measurement uncertainty is reported. It gives no information about the range, in which the true values of experiment would spread if the experiment was repeated. A frequently used approximation, that if a physical quantity is measured as a function of time, only measurement of this quantity, produces uncertainty is also in some real experiments fare to strong. Example: In reaction history time measurement uncertainty propagated to alpha dominated under certain conditions over the flux measurement uncertainty propagated to alpha. Reliability of a data point is in general independent from its measurement uncertainty. However, in practice reliable measurement methods frequently have high measurement uncertainty, while low reliability methods are applied to limit measurement uncertainty. Comparison of reliable data with high measurement uncertainty to not so reliable data measured with low uncertainty is discussed – in different scenarios different data analysis methods are applicable.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Synthesis of observed and simulated rain microphysics to inform a new Bayesian statistical framework for microphysical parameterization in climate models (Final Scientific Report)

This project aimed to investigate a new approach to bulk microphysics schemes. We identified the need to move beyond the fixed structural assumptions and approximation of existing schemes. For example, most schemes assume some functional form for the rain drop size distribution (e.g. a gamma or exponential distribution). Most schemes then evolve some number of statistical moments of that distribution via various processes, such as evaporation, sedimentation, collision-coalescence, and collisional breakup. These microphysical processes, in turn, are typically some fixed functional form derived from either some other (more detailed) model, or using some single-particle rates that are then integrated over the size distribution. While these process rate functions may have some free parameters to adjust, in other cases doing so is impossible (e.g. when the process rates are analytical or piecewise solutions to some target function). Our goal was to build and test a scheme that assumed no size distribution form, and used a series of power laws as the basis for the process rates. Moments of the size distribution would be predicted, but no underlying size distribution would be specified. Any number or choice of size distribution moments could be used, and any number of power laws could be employed to model the process rates. Thus, our approach is flexible, and can seamlessly scale across levels of complexity, as demanded by the data. Bayesian inference then would provide the formalism to estimate the model parameters and structure, allowing for robust uncertainty quantification. We proposed testing this framework in idealized simulations using bin microphysical schemes as a data source. We also proposed using real data to inform our microphysics scheme, and also that we would integrate our scheme into WRF.

58 GEOSCIENCES↗
DOE OSTI2022

A physics-based model of cladding wastage layer formation rate

In this report, lower length scale simulations to inform an engineering-scale model of fuel-cladding chemical interaction (FCCI) conducted under the auspices of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program in FY22 are described. An overall strategy for the implementation of the BISON model is described, and the past and current lower length scale work on FCCI formation is put into the context of this overall strategy. Density functional theory and kinetic Monte Carlo simulations are used to determine the diffusion coefficient of neodymium in iron. Density functional theory calculations are also used to parameterize a parabolic approximation for the dependence of free energy on composition for the intermetallic compound Fe 17 Nd 2 . A phase-field model of the Fe-Nd system was developed that includes the random solid solution body-centered cubic phase and the intermetallic Fe 17 Nd 2 . The model was used to simulate growth of the intermetallic layer in a diffusion couple and the results were compared to experiment. The model’s prediction of the parabolic growth constant is within 40 % of the experimental value. The model is also used to simulate the formation of a grain boundary attack layer that is observed in experiment. The simulations show enhanced Nd concentration along the grain boundaries, but do not clearly show formation of a Fe 17 Nd 2 layer

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Full-physics 3D heterogeneous simulations of electromagnetic induction fields on level and deformed sea ice

In this article we explore simulated responses of electromagnetic (EM) signals relative to in situ field surveys and quantify the effects that different values of conductivity in sea ice have on the EM fields. We compute EM responses of ice types with a three-dimensional (3-D) finite-volume discretization of Maxwell's equations and present 2-D sliced visualizations of their associated EM fields at discrete frequencies. Several interesting observations result: First, since the simulator computes the fields everywhere, each gridcell acts as a receiver within the model volume, and captures the complete, coupled interactions between air, snow, sea ice and sea water as a function of their conductivity; second, visualizations demonstrate how 1-D approximations near deformed ice features are violated. But the most important new finding is that changes in conductivity affect EM field response by modifying the magnitude and spatial patterns (i.e. footprint size and shape) of current density and magnetic fields. These effects are demonstrated through a visual feature we define as 'null lines'. Null line shape is affected by changes in conductivity near material boundaries as well as transmitter location. Our results encourage the use of null lines as a planning tool for better ground-truth field measurements near deformed ice types.

58 GEOSCIENCES↗
DOE OSTI2025

Galaxy Clustering with LSST: Effects of Number Count Bias from Blending

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will survey the southern sky to create the largest galaxy catalog to date, and its statistical power demands an improved understanding of systematic effects such as source overlaps, also known as blending. In this work we study how blending introduces a bias in the number counts of galaxies (instead of the flux and colors), and how it propagates into galaxy clustering statistics. We use the 300 deg 2 DC2 image simulation and its resulting galaxy catalog (LSST Dark Energy Science Collaboration et al. 2021) to carry out this study. We find that, for a LSST Year 1 (Y1)-like cosmological analyses, the number count bias due to blending leads to small but statistically significant differences in mean redshift measurements when comparing an observed sample to an unblended calibration sample. In the two-point correlation function, blending causes differences greater than 3σ on scales below approximately 10', but large scales are unaffected. We fit Ω m and linear galaxy bias in a Bayesian cosmological analysis and find that the recovered parameters from this limited area sample, with the LSST Y1 scale cuts, are largely unaffected by blending. Our main results hold when considering photometric redshift and a LSST Year 5 (Y5)-like sample.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Dicarbon Formation in Collisions of Two Carbon Atoms

Abstract Radiative association cross sections and rates are computed, using a quantum approach, for the formation of C 2 molecules (dicarbon) during the collision of two ground-state C( 3 P ) atoms. We find that transitions originating in the C 1 Π g , d 3 Π g , and 1 5 Π u states are the main contributors to the process. The results are compared and contrasted with previous results obtained from a semiclassical approximation. New ab initio potential curves and transition dipole moment functions have been obtained for the present work using the multi-reference configuration interaction approach with the Davidson correction (MRCI+Q) and aug-cc-pCV5Z basis sets, substantially increasing the available molecular data on dicarbon. Applications of the current computations to various astrophysical environments and laboratory studies are briefly discussed, focusing on these rates.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

The algebraic structure of gravitational scrambling

We introduce a new algebraic framework to describe gravitational scrambling, including the semiclassical limit of any out-of-time-order correlation function that is built out of operator insertions separated by approximately the scrambling time. In two dimensions, the scrambling algebra, which we call a modular-twisted product, is defined in terms of two copies of the Leutheusser-Liu half-sided modular inclusion of von Neumann algebras; these describe early- and late-time operators respectively. In limits where the separation between insertions is taken to be either significantly greater or smaller than the scrambling time, the modular-twisted product reduces, respectively, to free- and tensor-product algebras that were previously studied in [arXiv:2209.10454]. In a sense, the modular-twisted product interpolates between these two products. Including the Hamiltonian in the scrambling algebra leads to a Type II$_\infty$ von Neumann algebra with finite renormalized entropies that interpolate between single-QES and multi-QES phases. We also describe how to generalize the modular-twisted product algebra to higher dimensions, including spatially localized boundary excitations.

FOS: Physical sciences↗
DOE OSTI2021

Hollow nanoparticles with hybrid double layers

The present invention discloses the morphology of hollow, double-shelled submicrometer particles generated through a rapid aerosol-based process. The inner shell is an essentially hydrophobic carbon layer of nanoscale dimension (5-20 nm), and the outer shell is a hydrophilic silica layer of approximately 5-40 nm, with the shell thickness being a function of the particle size. The particles are synthesized by exploiting concepts of salt bridging to lock in a surfactant (CTAB) and carbon precursors together with iron species in the interior of a droplet. This deliberate negation of surfactant templating allows a silica shell to form extremely rapidly, sealing in the organic species in the particle interior. Subsequent pyrolysis results in a buildup of internal pressure, forcing carbonaceous species against the silica wall to form an inner shell of carbon. The incorporation of magnetic iron oxide into the shells opens up applications in external stimuli-responsive nanomaterials.

John, Vijay T.↗
DOE OSTI2025

Cosmic Reionization on Computers: Statistical Properties of the Distributions of Mean Opacities

Quasar absorption lines provide a unique window to the relationship between galaxies and the intergalactic medium during the Epoch of Reionization. In particular, high redshift quasars enable measurements of the neutral hydrogen content of the universe. However, the limited sample size of observed quasar spectra, particularly at the highest redshifts, hampers our ability to fully characterize the intergalactic medium during this epoch from observations alone. In this work, we characterize the distributions of mean opacities of the intergalactic medium in simulations from the Cosmic Reionization on Computers (CROC) project. We find that the distribution of mean opacities along sightlines follows a non-trivial distribution that cannot be easily approximated by a known distribution. When comparing the cumulative distribution function of mean opacities measurements in subsamples of sample sizes similar to observational measurements from the literature, we find consistency between CROC and observations at redshifts $z\lesssim 5.7$. However, at higher redshifts ($z\gtrsim5.7$), the cumulative distribution function of mean opacities from CROC is notably narrower than those from observed quasar sightlines implying that observations probe a systematically more opaque intergalactic medium at higher redshifts than the intergalactic medium in CROC boxes at these same redshifts. This is consistent with previous analyses that indicate that the universe is reionized too early in CROC simulations.

79 ASTRONOMY AND ASTROPHYSICS↗