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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Systematic uncertainties from higher-twist corrections in DIS at large x

We investigate the systematic uncertainties and potential biases arising from the inclusion of large- x corrections to proton and deuteron deep inelastic scattering (DIS) data in global quantum chromodynamics (QCD) analyses. Using the CTEQ-JLab framework, we examine various approaches to implementing higher-twist corrections in nucleon structure functions and off-shell PDF modifications in deuteron targets. We analyze how these components interact and influence the determination of the d -quark PDF and the neutron structure function at large x . We find that it is very important to consider isospin-dependent higher-twist corrections in order to minimize implementation biases in the extracted quantities. Published by the American Physical Society 2025

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Ultraviolet to far-infrared dielectric function of n -doped cadmium oxide thin films

Spectroscopic ellipsometry and Fourier transform infrared spectroscopy were applied to extract the ultraviolet to far-infrared (150 – 33333 cm -1 ) complex dielectric functions of high-quality, sputtered indium-doped cadmium oxide (In:CdO) thin crystalline films on MgO substrates possessing carrier densities (N d ) ranging from 1.1 x 10 19 cm -1 to 4.1 x 10 20 cm -1 . A multiple oscillator fit model was used to identify and analyze the three major contributors to the dielectric function and their dependence on doping density: interband transitions in the visible, free-carrier excitations (Drude response) in the near- to far-infrared, and IR-active optic phonons in the far-infrared. More specifically, values pertinent to the complex dielectric function such as the optical band gap (E g ), are shown here to be dependent upon carrier density, increasing from approximately 2.5–3 eV, while the high-frequency permittivity (ε ∞ ) decreases from 5.6 to 5.1 with increasing carrier density. The plasma frequency (ω p ) scales as $\sqrt{N_d}$, resulting in ω p values occurring within the mid- to near-IR, and the effective mass (m *) was also observed to exhibit doping density-dependent changes, reaching a minimum of 0.11 m o in unintentionally doped films (1.1 x 10 19 cm -1 ). Good quantitative agreement with prior work on polycrystalline, higher-doped CdO films is also demonstrated, illustrating the generality of the results. The analysis presented here in this paper will aid in predictive calculations for CdO-based next-generation nanophotonic and optoelectronic devices, while also providing an underlying physical description of the key properties dictating the dielectric response in this atypical semiconductor system.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Electronic Properties of Aluminum Doped Carbon Nanotubes with Stone Wales Defects: Density Functional Theory

Al-doped single wall carbon nanotube with Stone Wales defect was theoretically analyzed, two different orientations of chiral (8, 4) carbon nanotubes was doped among the joints of defective carbon rings. Density functional theory was implemented to study structural and electronic properties of Al-doped chiral carbon nanotubes. Doping bond lengths as well as their geometrical structure were determined at the different orientations. The electronic properties were also illustrated by evaluation band of the gap energies at each possible doping site. Our results indicated that not only Al-doping tune the band structure, but also dopant site played a crucial rule on manipulating physical properties of chiral carbon nanotubes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Effective hopping in holographic Bose and Fermi-Hubbard models

In this paper, we analyze a proposed gravity dual to a SU(N) Bose-Hubbard model, as well as construct a holographic dual of a SU(N) Fermi-Hubbard model from D-branes in string theory. In both cases, the SU(N) is dynamical, i.e. the hopping degrees of freedom are strongly coupled to SU(N) gauge bosons which themselves are strongly interacting. The vacuum expectation value (VEV) of the hopping term (i.e. the hopping energy) is analyzed in the gravity dual as a function of the bulk mass of the field dual to the hopping term, as well as of the coupling constants of the model. The bulk mass controls the anomalous dimension (i.e. the critical exponent) of the hopping term in the SU(N) Bose-Hubbard model. We compare the hopping energy to the corresponding result in a numerical simulation of the ungauged SU(N) Bose-Hubbard model. We find agreement when the hopping parameter is smaller than the other couplings. Our analysis shows that the kinetic energy increases as the bulk mass increases, due to increased contributions from the IR. The holographic Bose-Hubbard model is then compared with the string theory construction of a SU(N) Fermi-Hubbard model. The string theory construction makes it possible to describe fluctuations around a half-filled state in the supergravity limit, which map to O(1) occupation number fluctuations in the Fermi-Hubbard model at half filling. Finally, the VEV of the Bose-Hubbard model is shown to agree with the one of the fermionic Hubbard model with the help of a two-site version of the Jordan-Wigner transformation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Residence time distribution in a structured packing unit for monitoring aerosol emissions

Solvent absorption in a structured packed column has been demonstrated as a viable option for post-combustion carbon capture. Amine emissions in the form of aerosol particles pose a major challenge that severely impacts the separation efficiency of the packed column. The aerosol particles quickly achieve the motion of the gas flow. In this context, residence time distribution (RTD) of the gaseous phase will provide insights for managing aerosol particles, thereby controlling amine loss in the packed column. Computational fluid dynamics (CFD) modeling of such columns is a multiscale problem because of a wide range of disparity in length scales. Accordingly, three-dimensional CFD simulations in the representative elementary unit of a structured packing are conducted using OpenFOAM. The RTD is analyzed in terms of residence time distribution function, mean residence time, and variance. Effects of the diffusivity and flow rates on RTD are extensively studied, and the dispersion coefficient is calculated using a one-dimensional axial dispersion model. Furthermore, RTDs computed in a smaller domain are extrapolated to a larger domain using a convolution integral. The computed and corresponding CFD models derived from the convolution integral match well at different flow rates and domain sizes. A comparison of RTD among different packing designs also is presented at a fixed number of repeating units and different flow rates.

structured packings, residence time distribution↗
DOE OSTI2023

The impact of feedstock size and composition on the hydrothermal growth of (U,Th)O 2

Bulk crystal growth of refractory oxides requires unique approaches, and the U x Th 1-x O 2 solid solution is no exception. Hydrothermal transport reactions of U 0.1 Th 0.9 O 2 onto ThO 2 seeds with feedstocks comprised of U 0.1 Th 0.9 O 2 or mixtures of UO 2 and ThO 2 with a nominal composition of U 0.1 Th 0.9 O 2 are investigated with µ-Raman spectroscopy and X-ray fluorescence. In each case, the trends in stoichiometry as a function of distance from the seed are analyzed and the deviations from the nominal stoichiometry discussed. When the feedstock is composed of mixed oxides, the particle surface area’s influence on the feedstock dissolution rate is the dominant factor and can produce U-rich stoichiometries as high as U 0.75 Th 0.25 O 2 . When composed solely of U 0.1 Th 0.9 O 2 , the total growth amount depends on the particle size, but the obtained stoichiometry is the product of differing solubilities. Although the U0.1Th0.9O 2 feedstock produces the most homogeneous growth, the ending growth of the smallest particle UO 2 /ThO 2 mixture yields the stoichiometry closest to U 0.1 Th 0.9 O 2 . How to obtain desired stoichiometries from mixtures by matching the particle size and solubilities is briefly discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Ethylene oxidation on unpromoted silver catalysts: Reaction pathway and selectivity analysis using DFT calculations

Chemical conversions in catalytic partial oxidation processes of light hydrocarbons are responsible for the production of numerous industrial chemicals, plastics, and intermediates. These processes are relatively expensive to perform, and are typically operated at high thermodynamic inefficiency, so the development of novel, highly efficient catalysts would prove to be very cost effective. Herein, our study focused on surface catalytic mechanisms of the ethylene oxide (EO) formation process. Periodic plane-wave Density Functional Theory (DFT) methods were used to analyze related reaction mechanisms on the Ag(111) surface facet with low coverage. Energetic changes of related species and pathways were calculated. Key surface species are identified to suggest the factors for the observed selectivity during EO formation. Our results are consistent with previous kinetic modeling efforts in the literature which did not employ DFT analysis. Lastly, our study demonstrates how fundamental theoretical investigations and multi-scale modeling techniques are currently impacting the advancement of rational catalyst design and microkinetic modeling techniques in the light hydrocarbon processing industry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Chemical Modifications of Ag Catalyst Surfaces with Imidazolium Ionomers Modulate H 2 Evolution Rates during Electrochemical CO 2 Reduction

Bridging polymer design with catalyst surface science is a promising direction for tuning and optimizing electrochemical reactors that could impact long-term goals in energy and sustainability. Particularly, the interaction between inorganic catalyst surfaces and organic-based ionomers provides an avenue to both steer reaction selectivity and promote activity. In this work, we studied the role of imidazolium-based ionomers for electrocatalytic CO 2 reduction to CO (CO 2 R) on Ag surfaces and found that they produce no effect on CO 2 R activity yet strongly promote the competing hydrogen evolution reaction (HER). By examining the dependence of HER and CO 2 R rates on concentrations of CO 2 and HCO 3 –, we developed a kinetic model that attributes HER promotion to intrinsic promotion of HCO 3 – reduction by imidazolium ionomers. We also show that varying the ionomer structure by changing substituents on the imidazolium ring modulates the HER promotion. This ionomer-structure dependence was analyzed via Taft steric parameters and density functional theory calculations, which suggest that steric bulk from functionalities on the imidazolium ring reduces access of the ionomer to both HCO 3 – and the Ag surface, thus limiting the promotional effect. Our results help develop design rules for ionomer–catalyst interactions in CO 2 R and motivate further work into precisely uncovering the interplay between primary and secondary coordination in determining electrocatalytic behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Prognostic Power of Extreme Rainfall Scaling Formulas Across Space and Time Scales

Some studies documenting changes in extreme precipitation use scaling formulas to approximate the large percentiles of the rainfall distribution from average dynamical and thermodynamical variables, called predictors. Here we instead assess the performance of these formulas as approximations to the rain rates in individual events. We evaluate the accuracies of the scaling relationships as functions of spatial and temporal scales by analyzing tropical rainfall in a superparameterized model. Relationships using full vertical profiles of the predictors are more accurate than those using their values at specific vertical levels because they better characterize the specific dynamics of each event. Both types of scaling relationships perform well over a range of length scales from 200 to 2,000 km and time scales from an hour to a week, and their precision is higher in the case of simulations with superparameterization than with parameterized convection. Uncertainties emerging from the local use of the scaling relationships suggest that they may only characterize the intensification of individual extremes for a warming of 4–5 K or larger. Finally, we argue that these formulas can be used to reconstruct the tail of the rainfall distribution directly from its predictors without prior information on P. While scalings have been used as diagnostic equations conditioned on the occurrence of extreme rainfall, they are actually able to mimic the prognostic behavior of climate model parameterizations on a variety of scales when estimating the intensity, frequency, and spatial patterns of extremes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Scalable fabrication of an array-type fixed-target device for automated room temperature X-ray protein crystallography

X-ray crystallography is one of the leading tools to analyze the 3-D structure, and therefore, function of proteins and other biological macromolecules. Traditional methods of mounting individual crystals for X-ray diffraction analysis can be tedious and result in damage to fragile protein crystals. Furthermore, the advent of multi-crystal and serial crystallography methods explicitly require the mounting of larger numbers of crystals. To address this need, we have developed a device that facilitates the straightforward mounting of protein crystals for diffraction analysis, and that can be easily manufactured at scale. Inspired by grid-style devices that have been reported in the literature, we have developed an X-ray compatible microfluidic device that can be used to trap protein crystals in an array configuration, while also providing excellent optical transparency, a low X-ray background, and compatibility with the robotic sample handling and environmental controls used at synchrotron macromolecular crystallography beamlines. At the Stanford Synchrotron Radiation Lightsource (SSRL), these capabilities allow for fully remote-access data collection at controlled humidity conditions. Furthermore, we have demonstrated continuous manufacturing of these devices via roll-to-roll fabrication to enable cost-effective and efficient large-scale production.

chemical engineering↗
DOE OSTI2020

Femtosecond stimulated Raman spectro-microscopy for probing chemical reaction dynamics in solid-state materials

Femtosecond stimulated Raman spectroscopy (FSRS) is a chemically specific vibrational technique that has the ability to follow structural dynamics during photoinduced processes such as charge transfer on the ultrafast timescale. FSRS has a strong background in following structural dynamics and elucidating chemical mechanisms; however, its use with solid-state materials has been limited. As photovoltaic and electronic devices rely on solid-state materials, having the ability to track the evolving dynamics during their charge transfer and transport processes is crucial. Following the structural dynamics in these solid-state materials will lead to the identification of specific chemical structures responsible for various photoinduced charge transfer reactions, leading to a greater understanding of the structure–function relationships needed to improve upon current technologies. Furthermore, isolating the specific nuclear motions and molecular structures that drive a desired physical process will provide a chemical blueprint, leading to the rational design and fabrication of efficient electronic and photovoltaic devices. In this perspective, we discuss technical challenges and experimental developments that have facilitated the use of FSRS with solid-state samples, explore previous studies that have identified structure–function relationships in charge transfer reactions, and analyze the future developments that will broaden and advance the field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

How to select distracted driving countermeasures evaluation metrics: A systematic review

While there are numerous performance metrics that have been developed for the evaluation of distracted driving prevention programs, there is little information on how to select them depending on the requirements and/or objectives of the study. Here, this paper describes a systematic literature review that was conducted on the metrics for evaluating distracted driving countermeasures in order to bridge this research gap. A summary of the evaluation metrics used for the existing distracted driving countermeasures was provided. Guidance for choosing an evaluation measure was provided by analyzing the metrics from the perspectives of functionality, spatial-temporal dimension, and equity. Three examples of distracted driving countermeasure evaluation processes were thoroughly reviewed in order to offer insight into metric selection and measurement. This paper contributes to the body of knowledge by discussing the implications for policy on how to enhance the thoroughness and accuracy of the evaluation of distracted driving countermeasures. Analysis from multiple angles, the development of data collection tools and direct behavior indicators, taking into account temporal dimensions, and equity considerations, are proposed.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2018

Experimental realization of Feynman’s ratchet

Feynman's ratchet is a microscopic machine in contact with two heat reservoirs, at temperatures T A and T B , that was proposed by Richard Feynman to illustrate the second law of thermodynamics. In equilibrium (T A = T B ), thermal fluctuations prevent the ratchet from generating directed motion. When the ratchet is maintained away from equilibrium by a temperature difference (T A ≠T B ), it can operate as a heat engine, rectifying thermal fluctuations to perform work. While it has attracted much interest, the operation of Feynman's ratchet as a heat engine has not been realized experimentally, due to technical challenges. In this work, we realize Feynman's ratchet with a colloidal particle in a one dimensional optical trap in contact with two heat reservoirs: one is the surrounding water, while the effect of the other reservoir is generated by a novel feedback mechanism, using the Metropolis algorithm to impose detailed balance. We verify that the system does not produce work when T A = T B , and that it becomes a microscopic heat engine when T A ≠T B . We analyze work, heat and entropy production as functions of the temperature difference and external load. As a result, our experimental realization of Feynman's ratchet and the Metropolis algorithm can also be used to study the thermodynamics of feedback control and information processing, the working mechanism of molecular motors, and controllable particle transportation.

42 ENGINEERING↗
DOE OSTI2022

Investigating the impact of atmospheric conditions on wake-steering performance at a commercial wind plant

Wake steering is a wind farm control strategy in which upstream wind turbines are misaligned with the wind to deflect their wakes away from downstream turbines, thereby increasing net energy production. But research suggests that the effectiveness of wake steering strongly depends on atmospheric conditions such as stability. In this paper, we investigate results from a two-turbine wake-steering experiment at a commercial wind plant to assess the impact of stability and five other atmospheric variables on wake-steering performance. Specifically, for different atmospheric condition bins we compare the ability of the controller to achieve the intended yaw offsets, the power gain from wake steering, and the reduction in wake losses. Further, we analyze wake-steering performance as a function of wind speed to eliminate the confounding impact of different wind speed distributions in different atmospheric conditions. Overall, we find that wind direction standard deviation is the best predictor of wake-steering performance, followed by turbulence intensity and turbulent kinetic energy. The results suggest the importance of adapting wake-steering control strategies to different atmospheric conditions.

17 WIND ENERGY↗
DOE OSTI2020

Fermi-liquid theory and divergences of the two-particle irreducible vertex in the periodic Anderson lattice

Here we analyze the divergences of the irreducible vertex function in dynamical mean field theory, which may indicate either a nonphysical breakdown of the perturbation theory or a response to some physical phenomenon. To investigate this question, we construct a quasiparticle vertex from the diverging irreducible vertex functions. This vertex describes the scattering between quasiparticles and quasiholes in a Fermi liquid. We show that the quasparticle vertex does not diverge in the charge channel, wherein the irreducible vertex does diverge; and we show that the quasiparticle vertex does diverge in the spin channel, wherein the irreducible vertex does not diverge. This divergence occurs at the Mott transition, wherein the Fermi-liquid theory breaks down. Both the half filled Hubbard and Anderson lattices are investigated. In general, our results support that the divergences of the irreducible vertex function do not indicate a nonphysical failure of the perturbation theory. Instead, the divergences are the mathematical consequence of inverting a matrix (the local charge susceptibility) which accumulates increasingly negative diagonal elements as the Hubbard interaction suppresses charge fluctuations. Indeed, we find that the first divergences of the irreducible vertex in both Hubbard and Anderson lattices occurs near the maximum magnitude of the (negative) vertex-connected part of the charge susceptibility.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Specific heat and gap structure of a nematic superconductor: Application to FeSe

We report the results of our in-depth analysis of spectroscopic and thermodynamic properties of a multiorbital metal, like FeSe, which first develops a nematic order and then undergoes a transition into a superconducting state, which coexists with nematicity. We analyze the angular dependence of the gap function and specific heat C v (T) of such a nematic superconductor. We specifically address three issues: (i) the angular dependence of the gap in light of the competition between the nematicity-induced s - d mixture and the orbital transmutation of low-energy excitations in the nematic state, (ii) the effect of nematicity on the magnitude of the jump of the specific heat C v (T) at T c and the temperature dependence of C v (T) below T c , and (iii) a potential transition at T c1 < T c from an s + d state to an s + e iη d state that breaks time-reversal symmetry. We consider two scenarios for a nematic order: scenario A, in which this order develops between d xz and d yz orbitals on hole and electron pockets, and scenario B, in which there is an additional component of the nematic order for d xy fermions on the two electron pockets.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Universal Compiling and (No-)Free-Lunch Theorems for Continuous-Variable Quantum Learning

Quantum compiling, where a parameterized quantum circuit is trained to learn a target unitary, is an important primitive for quantum computing that can be used as a subroutine to obtain optimal circuits or as a tomographic tool to study the dynamics of an experimental system. While much attention has been paid to quantum compiling on discrete-variable hardware, less has been paid to compiling in the continuous-variable paradigm. Here we motivate several, closely related, short-depth continuous-variable algorithms for quantum compilation. We analyze the trainability of our proposed cost functions and numerically demonstrate our algorithms by learning arbitrary Gaussian operations and Kerr nonlinearities. We further make connections between this framework and quantum learning theory in the continuous-variable setting by deriving no-free-lunch theorems. These generalization bounds demonstrate a linear resource reduction for learning Gaussian unitaries using entangled coherent-Fock states and an exponential resource reduction for learning arbitrary unitaries using two-mode-squeezed states.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Artifact identification in X-ray diffraction data using machine learning methods

In situ synchrotron high-energy X-ray powder diffraction (XRD) is highly utilized by researchers to analyze the crystallographic structures of materials in functional devices ( e.g. battery materials) or in complex sample environments ( e.g. diamond anvil cells or syntheses reactors). An atomic structure of a material can be identified by its diffraction pattern along with a detailed analysis of the Rietveld refinement which yields rich information on the structure and the material, such as crystallite size, microstrain and defects. For in situ experiments, a series of XRD images is usually collected on the same sample under different conditions ( e.g. adiabatic conditions) yielding different states of matter, or is simply collected continuously as a function of time to track the change of a sample during a chemical or physical process. In situ experiments are usually performed with area detectors and collect images composed of diffraction patterns. For an ideal powder, the diffraction pattern should be a series of concentric Debye–Scherrer rings with evenly distributed intensities in each ring. For a realistic sample, one may observe different characteristics other than the typical ring pattern, such as textures or preferred orientations and single-crystal diffraction spots. Textures or preferred orientations usually have several parts of a ring that are more intense than the rest, whereas single-crystal diffraction spots are localized intense spots owing to diffraction of large crystals, typically >10 µm. In this work, an investigation of machine learning methods is presented for fast and reliable identification and separation of the single-crystal diffraction spots in XRD images. The exclusion of artifacts during an XRD image integration process allows a precise analysis of the powder diffraction rings of interest. When it is trained with small subsets of highly diverse datasets, the gradient boosting method can consistently produce high-accuracy results. The method dramatically decreases the amount of time spent identifying and separating single-crystal diffraction spots in comparison with the conventional method.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗