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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Enhancing Electrocatalysis for Hydrogen Production over CoP Catalyst by Strain: A Density Functional Theory Study

The facet-dependent strain effects on the hydrogen evolution reaction catalyzed by CoP were studied using density functional theory methods. We show that both atomic and electronic effects need to be taken into consideration to understand the strain effects. For the (111) surface, tensile strain promotes hydrogen evolution at all the levels of hydrogen coverage. For the (101) surface, a moderate tensile strain of ~3% endows this facet with optimum performance.

Liu, Fanghan↗
DOE OSTI2021

Estimate of pre-thermal quench non-thermal electron density profile during Ar pellet shutdowns of low-density target plasmas in DIII-D

The radial density profile of pre-thermal quench (pre-TQ) early-time runaway electrons (REs) is estimated by combining electron cyclotron emission (ECE) and soft x-ray (SXR) data during rapid shutdown of low-density (n e ≲ 10 13 cm -3 ) DIII-D target plasmas with cryogenic argon pellet injection. This technique is limited in these experiments to the pre-TQ phase and quickly loses validity during the TQ. Two different cases are studied: a high (10 keV) temperature target and a lower (4 keV) temperature target. The results indicate that early-time, low-energy (~10 keV) REs form ahead of the argon pellet as it enters the plasma, affecting the pellet ablation rate; it is hypothesized that this may be caused by rapid cross-field transport of argon ions ahead of the pellet. Fokker-Planck modeling of the two shots suggests that the RE current is quite significant during the pre-TQ phase (up to 50% of the total current). Comparison between modeled pre-TQ RE current and post-TQ RE current inferred from avalanche theory suggests that RE current increases during the high temperature target TQ but decreases during the low temperature target TQ. Here, the uncertainties in this estimate are large; but, if true, this suggests that TQ loss of REs can be larger than previously estimated in DIII-D.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Estimates of Ta strength at ultrahigh pressures and strain rates using thin-film graded-density impactors

In this paper, we present results from an experimental technique used to estimate the strength of Ta at extreme pressures (150 GPa) and strain rates (10 7 s -1 ). A graded-density impactor (GDI) was fabricated using sputter deposition to produce an approximately 40-μm-thick film containing alternating layers of Al and Cu. The thicknesses of the respective layers are adjusted to give an effective density gradient through the film. The GDIs were launched with a 2-stage light gas gun, and shock-ramp-release velocity profiles were measured over timescales of ~10 ns. Results are presented for the direct impact of the film onto LiF windows, which allows for a dynamic characterization of the GDI, as well as from impact onto thin (~40μm) sputtered Ta samples backed by a LiF window. The measurements were coupled with mesoscale numerical simulations to infer the strength of Ta, and the results agree well with other high-pressure platforms, particularly when strain-rate, microstructural, and thermodynamic-path differences are considered.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Density response from kinetic theory and time-dependent density-functional theory for matter under extreme conditions

The density linear response function for an inhomogeneous system of electrons in equilibrium with an array of fixed ions is considered. Two routes to its evaluation for extreme conditions (e.g., warm dense matter) are considered. The first is from a recently developed short-time kinetic equation; the second is from time-dependent density functional theory. The result from the latter approach agrees with that from kinetic theory in the “adiabatic approximation,” providing support and contextual clarity for each. Both provide a connection to the phenomenological Kubo-Greenwood method for calculating transport properties.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Colossal Density-Driven Resistance Response in the Negative Charge Transfer Insulator MnS 2

A reversible density driven insulator to metal to insulator transition in high-spin MnS 2 is experimentally observed, leading with a colossal electrical resistance drop of $10^8$ Omega by 12 GPa. Density functional theory simulations reveal the metallization to be unexpectedly driven by previously unoccupied $S_{2}^{-2}$ $\sigma^{*}_{3p}$ antibonding states crossing the Fermi level. This is a unique variant of the charge transfer insulator to metal transition for negative charge transfer insulators having anions with an unsaturated valence. By 36 GPa the emergence of the low-spin insulating arsenopyrite ($P2_1/c$) is confirmed, and the bulk metallicity is broken with the system returning to an insulative electronic state.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Data-driven predictive probability density function control of fiber length stochastic distribution shaping in refining process

Pulp is the most important raw material in paper in paper industries, whose Fiber Length Stochastic Distribution (FLSD) shaping directly determines the energy consumption and paper quality of the subsequent papermaking processes. However, the mean and variance are insufficient to describe the output FLSD shaping, which display non-Gaussian distribution properties. Therefore, the traditional control, method based on the mean and variance of fiber length is difficult to control the FLSD shaping effectively. In this paper, a novel data-driven predictive probability density function (PDF) control method is proposed for output FLSD shaping in refining process. Primarily, in order to improve the approximation accuracy of the PDF employing RBF neural network, the parameters (center value and width) of each RBF basis functions are tuned via utilizing iterative learning control (ILC) law, and the corresponding estimations of weights law can be obtained. Secondly, considering that the conventional linear model of weights vector has drawbacks of low accuracy and weak generalization ability, random vector functional link networks (RVFLNs) based data driven nonlinear modelling method is employed to characterize the prediction model between the input variables and weights vector. Finally, in order to reduce the randomness of the output FLSD, a minimum entropy control method under mean constraint is employed to design the predictive PDF controller for the output FLSD shaping with the help of the established nonlinear stochastic distribution model. Both simulations and experiments are given to illustrate the effectiveness and practicability of the proposed method.

Probability debsity function, Fiber length distrib↗
DOE OSTI2018

Metal Amorphous Nanocomposite Soft Magnetic Material-Enabled High Power Density, Rare Earth Free Rotational Machines [Metal Amorphous Nanocomposite (MANC) Soft Magnetic Material (SMM) Enabled High Power Density, Rare Earth Free Rotational Machines]

Metal amorphous nanocomposites (MANCs) are promising soft magnetic materials (SMMs) for power electronic applications offering low power loss at high frequency and maintaining a relatively high flux density. While applications in certain motor designs have been recently modeled, their widespread application awaits scaled manufacturing of MANC materials and proliferation of new higher speed motor designs. A hybrid motor design based on permanent magnets and doubly salient stator and rotor is reported here to develop a compact (a factor of 10 smaller than currently possible in Si steels), high-speed (>1 kHz, electrical), high-power (>2.5 kW) motor by incorporating low loss (<10 W/kg at 1 kHz) MANCs such as recently reported Fe-Ni-based alloys. A feature of this motor design is flux focusing from the permanent magnet allowing use of lower energy permanent magnet chosen from among non-rare earth containing compositions and attractive due to constraints posed by rare earth criticality. A 2-D finite element analysis model reported here indicates that a 2.5 kW hybrid motor may be built with a permanent magnet with a 0.4 T remanence at a rotor speed of 6000 rpm. At a magnetic switching frequency of 1.4 kHz, the core loss may be limited to <3 W by selecting an appropriate MANC SMM. The projected efficiency exceeds 96% not including power loss in the controller. Under full load conditions, the flux density distributions for the SMM stay predominantly <1.3 T, the saturation magnetization of optimized FeNi-based MANC alloys. As a result, the maximum demagnetizing field in the permanent magnet is less than 2.2 × 10 5 A/m sustainable, for example, with a high-grade hard ferrite magnet.

42 ENGINEERING↗
DOE OSTI2021

High-Current Density Durability of Pt/C and PtCo/C Catalysts at Similar Particle Sizes in PEMFCs

The durability of carbon supported PtCo-alloy based nanoparticle catalysts play a key role in the longevity of proton-exchange membrane fuel cells (PEMFC) in electric vehicle applications. To improve its durability, it is important to understand and mitigate the various factors that cause PtCo-based cathode catalyst layers (CCL) to lose performance over time. These factors include i) electrochemical surface area (ECSA) loss, ii) specific activity loss, iii) H + /O 2 -transport changes and iv) Co 2+ contamination effects. We use a catalyst-specific accelerated stress test (AST) voltage cycling protocol to compare the durability of Pt and PtCo catalysts at similar average nanoparticle size and distribution. Our studies indicate that while Pt and PtCo nanoparticle catalysts suffer from similar magnitudes of electrochemical surface area (ECSA) losses, PtCo catalyst shows a significantly larger cell voltage loss at high current densities upon durability testing. The distinctive factor causing the large cell voltage loss of PtCo catalyst appears to be the secondary effects of the leached Co 2+ cations that contaminate the electrode ionomer. A 1D performance model has been used to quantify the cell voltage losses arising from various factors causing degradation of the membrane electrode assembly (MEA).

08 HYDROGEN↗
DOE OSTI2021

Bulk Diffusion of Cl through O Vacancies in α-Cr 2 O 3 : A Density Functional Theory Study

Many metals form passive oxides which are broken or weakened by anionic-induced degradation leading to material failure and anionic diffusion is an important step of this degradation process. The diffusion of anionic species through oxides involves a combination of diffusion along grain boundaries, cracks, and channels, as well as bulk diffusion via point defects which is the focus of this study. Using density functional theory, we study bulk diffusion of Cl through O vacancies in α -Cr 2 O 3 as a model system for passive metal oxides. Little is known about Cl diffusion and bonding characteristics, so we benchmark our work through comparison to numerous studies on O diffusion in α -Cr 2 O 3 to analyze similarities and differences between the O and Cl diffusion in the passivation and degradation process of α -Cr 2 O 3 respectively. Unlike O diffusion, the lowest diffusion barrier for Cl is cross-plane diffusion between two (0001) planes through a vacant cation site but the much shorter in-plane diffusion path within the same coordination polyhedron has 35% higher barrier. This work provides the basis for considering the contributions of Cl bulk-diffusion in the overall diffusion kinetics of Cl through α -Cr 2 O 3 .

Oware Sarfo, Kofi↗
DOE OSTI2022

The Influence of Current Density on Transport of Vanadium Acetylacetonate through a Cation-Exchange Membrane

Fluxes of negatively charged, neutral, and positively charged vanadium acetylacetonates through the cation-exchange membrane Nafion® 211 were measured as functions of current density. Fluxes increase in order V(C 5 H 7 O 2 ) 3 – < V(C 5 H 7 O 2 ) 3 0 < V(C 5 H 7 O 2 ) 3 + as expected for a membrane with fixed negative charges. Furthermore, the dependence of these fluxes on current density is quantitatively consistent with predictions made using independently measured conductivities in Nernst-Planck-Einstein transport equations. However, differences between the three fluxes are smaller than predicted by Donnan equilibrium calculations for Nafion 211 immersed in V(C 5 H 7 O 2 ) 3 solutions. Furthermore, specific interactions between sorbed species appear to be responsible for the relatively rapid transport of V(C 5 H 7 O 2 ) 3 – compared to V(C 5 H 7 O 2 ) 3 + .

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

Data for Spatial Analysis of Cell Patterning to Aid Genetic and Phenotypic Understanding of Grass Stomatal Density: A Case Study in Maize

Biological processes involve complex hierarchies where composite traits result from multiple component traits. However, holistically understanding of how sets of component traits interact to underpin genotype-to-phenotype relationships is generally lacking. Stomatal density (SD) is a tractable model system for exploring how high-throughput phenotyping (HTP) data could be exploited by a new spatial analysis approach to better understand a developmentally and functionally important trait. SD is a composite trait, resulting from various components related to cell identity and size, which are themselves governed by a series of spatio-developmental processes. Data from 192 recombinant inbred lines of maize [Zea mays (L.)] were analyzed by a new stomatal patterning phenotype (SPP) to (1) describe the average spatial probability distribution of the nearest neighboring stomata; (2) derive a core set of component traits related to cell size, cell packing, and positional probabilities; (3) build a structural equation model of component traits underlying SD; and (4) identify stomatal patterning quantitative trait loci (QTL). The core set of SPP-derived traits explained 74% of the variation in SD. Analyzing SPP component traits allowed some loci previously identified as generic SD QTL to be recognized as specific to lateral versus longitudinal elements of stomatal patterning. Therefore, this study highlights how novel insights can be gained by decomposing a composite trait (e.g., SD) into a set of component traits that were present in HTP data but not previously exploited.

AI/ML↗