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Results for “effective diffusivity”

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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Effect of Commercial Gas Diffusion Layers on Catalyst Durability of Polymer Electrolyte Fuel Cells in Varied Cathode Gas Environment

Gas diffusion layers (GDLs) play a crucial role in heat transfer and water management of cathode catalyst layers in polymer electrolyte fuel cells (PEFCs). Thermal and water gradients can accelerate electrocatalyst degradation and therefore the selection of GDLs can have a major influence on PEFC durability. Currently, the role of GDLs in electrocatalyst degradation is poorly studied. Here, we perform electrocatalyst accelerated stress test studies on membrane electrode assemblies (MEAs) prepared using three most commonly used GDLs. The effect of GDLs on electrocatalyst degradation is evaluated in both nitrogen (non-reactive) and air (reactive) gas environments at 100% relative humidity. In situ electrochemical characterization and extensive physical characterization is performed to understand the subtle differences in electrocatalyst degradation and correlated to the use of different GDLs. Overall, no difference is observed in the electrocatalyst degradation due to GDLs based on polarization curves at the end of life. But interestingly, MEA with a cracked microporous layer (MPL) in the GDL exhibited a higher electrocatalyst loading loss, which resulted in a lower and more heterogeneous increase in the average electrocatalyst nanoparticle size.

25 ENERGY STORAGE↗
DOE OSTI2022

Characteristics and mathematical modeling of apple slice drying in an electrohydrodynamic system with a needle‐plate electrode

Abstract The drying of apple slices in an electrohydrodynamic (EHD) system with a needle‐plate electrode was characterized and mathematically modeled at voltages of 30, 40, and 50 kV and with distances between needles of 5, 6, and 7 cm. The results showed that the drying rate, effective water diffusion coefficient, and rehydration ratio of the apple slices, and specific energy consumption of drying, all increased with increasing voltage. Initially, there was a period when the drying rate was approximately constant in the low‐voltage EHD, but not in the high voltage conditions. At the same voltage, the drying rate was highest when the distance between needles was 6 cm. The voltage and distance between needles had a significant ( p < .05) interactive effect on the effective water diffusion coefficient and specific energy consumption, but not on the rehydration ratio. General mathematical models for drying can be used to represent the drying behavior of apple slices. The Midilli and Kucuk model and the Logarithmic model had the best fits, with correlation coefficients of 0.998803 and 0.998267, respectively. Predictive functions for the moisture ratio of apple slices based on voltage and distance between needles were established and verified. The results indicated that the Logarithmic model could more accurately predict the moisture ratio of apple slices dried using the EHD method. Practical Applications As a new drying technology, electrohydrodynamic (EHD) drying has unequaled advantages. According to the results, using the appropriate voltage and distance between needles improves not only drying efficiency, but also the rehydration ratio of apple slices, which reflects the quality of dried products. The Logarithmic model can accurately predict the EHD drying behavior of apple slices, which is of great significance in optimizing actual production.

Li, Bowen↗
DOE OSTI2022

Leaching Model of Radionuclides in Metal-Organic Framework Particles

Metal-organic frameworks (MOFs) have been used to sequester radionuclides and seal them inside of porous scaffolds using postsynthetic modification procedures. Experiments show that certain Zr-MOF with different capping linkers significantly affects the radionuclide release kinetics. In this work, we developed a leaching model of radionuclides in Zr-MOF particles. The model assumes that uranyl species occupy two energetically favored sites: the metal node and the MOF pores. For a given overall concentration of uranyl species, the partitions of uranyl species at the metal nodes and within the pores are determined by their chemical potentials. The model also considers the effect of particle surface and concentration on chemical potentials and diffusivity. The effects of spatial and structural dependent chemical potentials and diffusivity as well as particle sizes on leaching kinetics are investigated with the model. Predicted and measured uranyl leaching kinetics in Zr-MOF particles under batch experiments are compared. The results demonstrate the model’s capability for exploring the mechanisms of leaching and provide guidance for material design.

Metal-Organic Framework, Diffusion, uranyl, Leachi↗
DOE OSTI2024

Effect of different grain boundary diffusion alloys on magnetic properties of Dy-free sintered NdFeB magnet

Dy-free sintered magnets were fabricated by blending Neo powder with different grain boundary diffusion alloy powders. Cu, CeAl and CeAlCu have a negative effect on H cj of magnets, while PrAlCu and AlCuGa have a positive effect. The PrAlCu-added magnet achieves the best magnetic properties among all magnets with the additions of different diffusion alloys. With increasing PrAlCu from 0-10 wt.%, H cj of the magnets gradually increases from the original 14.5 kOe to 19.2 kOe. The magnet with 7.5 wt.% PrAlCu obtains a H cj of 18 kOe and (BH) max of 39.1 MGOe. It is found that Pr and Cu in PrAlCu alloy is mainly distributed at grain boundary and triple junctions, leading to a reduced coupling among grains, thus an enhanced H cj . Here, the grain boundary engineering by adding an appropriate alloy is an effective method to improve H cj of Dy-free NdFeB magnets.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Effective field theory of stochastic diffusion from gravity

Planar black holes in AdS have long-lived quasinormal modes which capture the physics of charge and momentum diffusion in the dual field theory. How should we characterize the effective dynamics of a probe system coupled to the conserved currents of the dual field theory? Specifically, how would such a probe record the long-lived memory of the black hole and its Hawking fluctuations? We address this question by exhibiting a universal gauge invariant framework which captures the physics of stochastic diffusion in holography: a designer scalar with a gravitational coupling governed by a single parameter, the Markovianity index. We argue that the physics of gauge and gravitational perturbations of a planar Schwarzschild-AdS black hole can be efficiently captured by such designer scalars. We demonstrate that this framework allows one to decouple, at the quadratic order, the long-lived quasinormal and Hawking modes from the short-lived ones. It furthermore provides a template for analyzing fluctuating open quantum field theories with memory. In particular, we use this set-up to analyze the diffusive Hawking photons and gravitons about a planar Schwarzschild-AdS black hole and derive the quadratic effective action that governs fluctuating hydrodynamics of the dual CFT. Along the way we also derive results relevant for probes of hyperscaling violating backgrounds at finite temperature.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Bulk and surface diffusion of neodymium in alpha-uranium: Ab initio calculations and kinetic Monte Carlo simulations

A fundamental understanding of lanthanide transport in metallic fuels is critical for high fidelity modeling of the fuel-cladding chemical interaction (FCCI) phenomenon, which can lead to the formation of brittle intermetallic compounds and premature failure of the cladding. Here we report a combined ab initio density functional theory (DFT) and kinetic Monte Carlo (KMC) study of the bulk diffusivity of Nd in α-U, fully taking into account the effect of radiation enhanced diffusion. In this work, the vacancy mechanism is considered to be the dominant mechanism for the bulk diffusion of Nd since a Nd interstitial is found to be intrinsically unstable in α-U. The surface diffusivity of a Nd adatom on α-U (001) surface has been further predicted using KMC simulations parameterized by DFT calculations. The present study suggests that Nd transport via the surface diffusion mechanism can be many orders of magnitude faster than bulk diffusion. Furthermore, the results from the present lower length scale study can be used to inform mesoscale phase-field simulations to determine the effective diffusion coefficient of Nd through α-U with a porous microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Remarks on the thesis of Aitor Bengoechea Fernández: Generalization of Doppler effect processing using S(α,β) thermal diffusion laws

The thesis titled “Generalization of Doppler effect processing using S(α,β) thermal diffusion laws” addresses a critical gap in the modeling of neutron scattering phenomena in nuclear materials, particularly where crystal lattice effects intersect with low-energy resonances. Conducted within the Doctoral School ED 352 at Aix-Marseille Université and hosted at CEA Cadarache, the research presents a theoretical and numerical framework for extending the applicability of Thermal Scattering Laws (TSLs) using higher-order correlation functions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Development of physics-consistent conditional diffusion model to overcome data scarcity in critical heat flux

Deep generative modeling provides a powerful pathway to overcome data scarcity in energy-related applications where experimental data are often limited. By learning the underlying probability distribution of the training dataset, deep generative models, such as the diffusion model, can generate high-fidelity synthetic samples that statistically resemble the training data. Such synthetic data generation can significantly enrich the size and diversity of the available training data, and more importantly, improve the robustness of downstream machine learning models in predictive tasks. The objective of this paper is to investigate the effectiveness of diffusion models for overcoming data scarcity in nuclear energy applications. By leveraging a public dataset on critical heat flux which covers a wide range of commercial nuclear reactor operational conditions, we developed a diffusion model that can generate an arbitrary amount of synthetic samples. Since a vanilla diffusion model can only generate samples randomly, we also developed a conditional diffusion model capable of generating targeted critical heat flux data under user-specified thermal-hydraulic conditions. The performance of the diffusion model was evaluated based on its ability to capture empirical feature distributions and pair-wise correlations, as well as to maintain physical consistency. The results showed that both the diffusion model and conditional diffusion model can successfully generate realistic and physics-consistent critical heat flux data. Furthermore, uncertainty quantification results demonstrate that the conditional diffusion model is highly effective in augmenting critical heat flux data while maintaining acceptable levels of uncertainty.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Improving Gas Selectivity in Membranes Using Polymer-Grafted Silica Nanoparticles

Herein, we demonstrate that tuning of structural parameters and material chemistry enables control of the permeability and selectivity of gases (CO 2 , He, and CH 4 ) in membranes based on poly(butyl methacrylate)-grafted nanoparticles (PGNs). Our data show that the presence of nanoparticles and the overall dense packing of grafted chains noticeable in PGNs with low grafting density have an adverse effect on the diffusivity of gases. This effect is compensated by an improvement in the solubility of CO 2 gas promoted by the silica nanoparticle surface, yielding a substantial improvement in the permeability of CO 2 versus CH 4 . Furthermore, in membranes with high grafting density, changes in the structural arrangements and alterations in the membrane porosity, evident from small-angle X-ray scattering and positron annihilation lifetime spectroscopy, positively influence the permeability of He and CO 2 gases. In contrast, CH 4 permeability in the same membranes is significantly suppressed, suggesting the formation of a unique, highly selective environment for gas separation. As a result, an improvement of up to 50% in selectivity for gas pairs containing large CH 4 molecules is observed. Our studies provide fundamental insights into the role that structural parameters play in gas transport through polymer membranes, laying a foundation for the rational design of membranes with improved permeability and selectivity.

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

Molecular dynamics study of grain boundary and radiation effects on tritium population and diffusion in zirconium

Tritium population thermodynamics and transport kinetics critically define the tritium storage performance of zirconium tritides that can be used for a variety of nuclear applications including tritium-producing burnable absorber rods. Both thermodynamic and kinetic properties can be sensitive to grain sizes of materials and can be significantly altered by irradiated defects during operation under the reactor environments. A thorough experimental characterization of how these properties evolve under different reactor conditions and different initial grain structures is extremely challenging. Here molecular dynamics simulations are used to investigate tritium population and diffusion in zirconium with and without different planar symmetric and asymmetric tilt grain boundaries and irradiated defects. Here, we found that in addition to trapping tritium, the most significant effect of planar grain boundaries is to increase tritium diffusivity on the boundary plane. Furthermore, fine grain structures are found to mitigate the change of tritium diffusivity due to irradiated point defects as these point defects are likely to migrate to and sink at grain boundaries.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Analysis of thermal grooving effects on vortex penetration in vapor-diffused Nb 3 Sn

While Nb 3 Sn theoretically offers better superconducting radio-frequency (RF) cavity performance (Q 0 and E acc ) to Nb at any given temperature, peak RF magnetic fields consistently fall short of the ~400 mT prediction. The relatively rough topography of vapor-diffused Nb 3 Sn is widely conjectured to be one of the factors that limit the attainable performance of Nb 3 Sn-coated Nb cavities prepared via Sn vapor diffusion. Here we investigate the effect of coating duration on the topography of vapor-diffused Nb 3 Sn on Nb and calculate the associated magnetic field enhancement and superheating field suppression factors using atomic force microscopy topographies. It is shown that the thermally grooved grain boundaries are major defects which may contribute to a substantial decrease in the achievable accelerating field. Further, the severity of these grooves increases with total coating duration due to the deepening of thermal grooves during the coating process.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Hydrogen and deuterium permeation in Hastelloy N

Hastelloy N was chosen as the fluoride salt-contacting structural material for the Molten Salt Reactor Experiment due to its excellent compatibility with the fuel salt FLiBe. FLiBe is currently investigated for several advanced fusion and fission reactor concepts where tritium generation in the FLiBe is anticipated. Knowledge of hydrogen transport properties through Hastelloy N is important to understand how tritium would permeate through this material and result in an unintentional release. In this study, the hydrogen and deuterium permeability, diffusivity, and solubility were measured from 500 to 700 °C at a primary-side pressure of 10 kPa in a well-characterized sample of Hastelloy N. The prepared polycrystalline Hastelloy N had C and O impurities present on the surface. These impurities were investigated using Auger Emission Spectroscopy and Ar depth profiling. Here, the adventitious C was removed upon the first Ar sputter cycle whereas O persisted deeper into the sample. For permeation experiments, applied deuterium pressures ranged from 13 Pa to 100 kPa and deuterium transport remained in the diffusion-limited regime (J ∝ P 0.5 ) throughout the pressure range examined. Two methods are employed to measure the effective hydrogen and deuterium diffusivity: rise and decline. The decline method produced improved statistical model fits for calculating the effective diffusion coefficient compared to the rise method. The resultant transport properties compared well to published values for other nickel alloys.

08 HYDROGEN↗
DOE OSTI2021

Charge balance functions for heavy-ion collisions at energies available at the CERN Large Hadron Collider

Heavy-ion collisions at the Large Hadron Collider provide the conditions to investigate regions of quark-gluon plasma that reach higher temperatures and that persist for longer periods of time compared with collisions at the Relativistic Heavy Ion Collider. This extended duration allows correlations from charge conservation to better separate during the quark-gluon plasma phase, and thus be better distinguished from correlations that develop during the hadron phase or during hadronization. Here, charge balance functions binned by relative rapidity and azimuthal angle and indexed by species are considered. A detailed theoretical model that evolves charge correlations throughout the entirety of an event is compared with preliminary results from the ALICE Collaboration. The comparison with experiment provides insight into the evolution of the chemistry and diffusivity during the collision. A ratio of balance functions is proposed to better isolate the effects of diffusion and thus better constrain the diffusivity.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Towards universal unfolding of detector effects in high-energy physics using denoising diffusion probabilistic models

Correcting for detector effects in experimental data, particularly through unfolding, is critical for enabling precision measurements in high-energy physics. However, traditional unfolding methods face challenges in scalability, flexibility, and dependence on simulations. We introduce a novel approach to multidimensional object-wise unfolding using conditional Denoising Diffusion Probabilistic Models (cDDPM). Our method utilizes the cDDPM for a non-iterative, flexible posterior sampling approach, incorporating distribution moments as conditioning information, which exhibits a strong inductive bias that allows it to generalize to unseen physics processes without explicitly assuming the underlying distribution. Our results highlight the potential of this method as a step towards a "universal" unfolding tool that reduces dependence on truth-level assumptions, while enabling the unfolding of a wide range of measured distributions with improved adaptability and accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗