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DOE OSTI2025

First-Principles Studies of Tritium Species Diffusivity Across the Interfaces of Ni-NiZr Alloy-Zircaloy-4

A tritium producing assembly, also known as tritium producing burnable absorber rods (TPBARs), consists of a metal getter tube located between the cladding and γ-LiAlO2 pellets. The metal getter tube is composed of a nickel (Ni) layer coated on Zircaloy-4. The getter assembly is used to capture tritium (3H) species (mainly 3H2 and 3H2O) generated from γ-LiAlO2 pellets during irradiation. Exploring 3H species (3H2, 3H2O) dissociation on the Ni surface and diffusion in the Ni layer and across the interface of Ni-plated Zircaloy-4 getters can provide insights on tritium transport and retention in the pellets and the getter materials. . In FY25, based on the ideal interface model of Ni-Zircaloy-4 generated in FY24, we will further explore the diffusion pathways of 3H across such Ni-ZrNi-alloy layer-Zircalory-4 interfaces under different conditions, including with oxide/hydroxide clusters on the Ni layer, and impurities located in ZrNi-alloy and Zircalory-4 layers. Due to the size limitation of DFT simulation, we will separate the 3-layer system into 3 sub-systems: Ni-ZrNi interface, ZrNi alloy layer, ZrNi-alloy-Zircaloy-4 interface, and simulate the diffusion barriers for tritium.

diffusion barrier↗

DOE OSTI2023

Mechanistic FCCI model for BISON

In this report, multi-scale simulations to develop a mechanistic model of fuel-cladding chemical interaction (FCCI) conducted under the auspices of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program in FY23 are described. The model assumes that cladding wastage is dominated by the intermetallic phase (Fe,Cr)$_{17}$Nd$_2$, and calculates production and diffusion of Nd in the fuel, diffusion into the cladding, and formation and growth of the intermetallic wastage layer. Atomistic simulations are used to calculate diffusivity of Nd in the (Fe,Cr) system. Mesoscale simulations, informed by previous atomistic calculations, are used to determine the effective diffusivity of Nd through the fuel, accounting for empty and sodium-filled porosity within the fuel. The BISON model incorporates this data and calculates the wastage layer thickness as a function of time, assuming parabolic growth kinetics based on the best available data. The results of the new mechanistic BISON model are compared to existing assessment cases for the X447 experiment in EBR-II, and show good agreement with experimental data and the existing BISON empirical model. To improve predictions of kinetics for future work, a phase-field model that includes fuel, wastage, and cladding phases is developed. Preliminary testing indicates that the kinetics may differ significantly from the assumed parabolic growth law, suggesting direction for future improvement of the model that will allow it to be applied to other fuel designs with greater confidence.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

An implicit-explicit time splitting strategy for the far SOL plasma fluid model with DG-FEM discretization

We consider a far scrape-off layer (SOL) plasma fluid model of ions that is governed by a Braginskiitype model: a one-dimensional, nonlinear system of advection-diffusion equations coupled with a diffusion equation for neutral particles. Our motivation for studying this system arises from the coupling between the edge plasma and radio-frequency (RF) heating, where solving a far SOL plasma fluid model provides critical insights into edge plasma dynamics. Numerical simulations of plasma fluid models require advanced computational techniques to achieve both efficiency and accuracy, especially when resolving the boundary layer in magnetically confined plasmas. In this work, we propose an implicit-explicit time operator splitting strategy that allows for an efficient solution algorithm, where the diffusive terms are treated semi-implicitly requiring only a linear solve, while the advection part is handled explicitly using a strong-stability-preserving Runge-Kutta (SSP-RK3) scheme. This leads to a fully decoupled system in which the diffusion and advection sub-problems can be solved separately, simplifying the overall solution procedure and allowing for efficient parallelization, which is particularly relevant for exploring the impact of RF heating on the SOL plasma. The main challenge of the discretization is due to the strong coupling between diffusion and advection, particularly through the boundary conditions. This makes implementation of such a scheme in an accurate and stable manner nontrivial. We discuss in detail how to split the equations and manage boundary conditions to maintain stability and well-posedness for each subsystem. We also describe a spatial discretization approach, based on the discontinuous Galerkin finite element method (DG-FEM) and present numerical results for a one-dimensional system.

Burkovska, Olena [ORNL] (ORCID:0000000163101130)↗

DOE OSTI2020

Comparison of plug flow and multi-node stratified tank modeling approaches regarding computational efficiency and accuracy

Residential water heaters contain water stratified by temperature-driven density differences. This implies that a water tank can reach a state in which the top and bottom sections have different temperatures, unless mixing happens. A high degree of thermal stratification can improve the efficiency of some water heaters, by saving the amount of energy required for the heat-up process. Studies of stratification became popular in the 1970s and it remains an active research topic today. The research has led to the development of different models and techniques to better predict and define a stratified tanks behavior. By comparing these models and techniques used previously to describe thermal stratification, the phenomenon could be better understood, exploited, and used to increase efficiency and thermal energy capacity in modern water tanks. From the existing models, we found the one-dimensional standard plug-flow and a multi node model to be appropriate for analyzing the processes of the heat up and cool-down in a water tank. These two models are based on energy balances. This work involved comparing the accuracy and computational effort needed to implement these models. To assess accuracy, we compared both types of existing models to experimental data (also collected in this work) which included a heat up process using an external heat pump. This external process included a layering process that has an eddy diffusivity at five times the rate of thermal diffusion. For this project, we implemented the models in MATLAB, the multi-paradigm numerical computing environment. We quantified model accuracy using the root mean squared error between modeled data and experimental data for six measured tank temperatures. Comparing the accuracy and the computational time taken to run the simulation provides a method to contrast the performance of each model and a way to rate it. The multi node model was run using from 6 to 96 spatial nodes; the plug flow model was run using 1 to 0.001 º C temperature bin sizes. Additionally, timesteps were varied from 4 to 236 s. The results quantify the tradeoff between accuracy and computational time, providing guidance for simulations to intelligently select the best model type and simulation parameters. This research can be used to validate the pre-existing models and possibly improve the modern water tank.

Bulnes, Fernando Karg↗

DOE OSTI2023

Optical information transfer through random unknown diffusers using electronic encoding and diffractive decoding

Free-space optical information transfer through diffusive media is critical in many applications, such as biomedical devices and optical communication, but remains challenging due to random, unknown perturbations in the optical path. We demonstrate an optical diffractive decoder with electronic encoding to accurately transfer the optical information of interest, corresponding to, e.g., any arbitrary input object or message, through unknown random phase diffusers along the optical path. This hybrid electronic-optical model, trained using supervised learning, comprises a convolutional neural network-based electronic encoder and successive passive diffractive layers that are jointly optimized. After their joint training using deep learning, our hybrid model can transfer optical information through unknown phase diffusers, demonstrating generalization to new random diffusers never seen before. The resulting electronic-encoder and optical-decoder model was experimentally validated using a 3D-printed diffractive network that axially spans <70λ, where λ = 0.75 mm is the illumination wavelength in the terahertz spectrum, carrying the desired optical information through random unknown diffusers. The presented framework can be physically scaled to operate at different parts of the electromagnetic spectrum, without retraining its components, and would offer low-power and compact solutions for optical information transfer in free space through unknown random diffusive media.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Unified Entrainment and Detrainment Closures for Extended Eddy-Diffusivity Mass-Flux Schemes

The extended Eddy Diffusivity Mass Flux (EDMF) scheme is used as a unied parameterization that simulates subgrid-scale dynamics across a range of regimes.This work presents unied entrainment and detrainment closures that allow this scheme to simulate the dry convective boundary layer, shallow convection and deep convection , while adjacent works present other necessary closures for this unied scheme and test its performance for stable, stratocumulus topped and convective boundary layers. Entrainment and detrainment are modeled as a combination of turbulent and dynamical processes. The turbulent component is taken as downgradient diffusion between subdomains. The dynamical component is based on a ratio of buoyancy and vertical velocity that ensures consistent treatment of the ratio of mass-flux at vanishing area fraction. Dynamical detrainment is controlled by the difference in relative humidity between subdomains when liquid water is present. These closures are rst evaluated with entrainment and detrainment diagnosed from Large Eddy Simulations where decaying tracers are used to identify the different subdomains and mass exchanges between them. When implemented in a single column model (SCM), these closures are tested in simulations of several observationally motivated cases of dry convective boundary layer, shallow convection and deep convection. Results show good agreement between the SCM and Large Eddy Simulations in key properties for climate models and profiles of first, second and third moments. The development of diurnal cycles and the onset of and precipitation (with simplified microphysics) are well predicted by the SCM.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Multi-arrival infrasound from meteoroids: Fragmentation signatures versus propagation effects in a fine-scale layered atmosphere

Infrasonic signatures of meteoroid fragmentation are frequently ambiguous: do multiple arrivals signify a complex breakup or merely the distorting effects of a layered atmosphere? Resolving this ambiguity is critical for accurate energy estimates and source reconstruction. In this study, we address this challenge by analyzing a unique regional dataset of well-constrained meteoroid events observed by the Southern Ontario Meteor Network and the co-located Elginfield Infrasound Array. We employ pseudo-differential parabolic equation (PPE) simulations to quantify how fine-scale gravity-wave structures in the stratosphere and lower thermosphere modify acoustic waveforms at ranges <300 km. Our modeling reveals that while fine-scale layering can stretch signals and generate diffuse oscillatory tails, it does not produce discrete, high-amplitude pulse splitting at ranges below ∼140 km. By applying these results to the rare multi-arrival event 20060305, we demonstrate that its distinct double arrival at 100 km range is inconsistent with atmospheric multipathing and provides definitive evidence of separate fragmentation episodes. These findings establish new diagnostic criteria for separating source physics from propagation artifacts, improving the reliability of infrasound as a monitoring tool for natural bolides, space debris re-entries, and catastrophic launch failures.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Temperature Coefficients of Perovskite Photovoltaics for Energy Yield Calculations

Temperature coefficients for maximum power (TPCE), open circuit voltage (VOC), and short circuit current (JSC) are standard specifications included in data sheets for any commercially available photovoltaic module. To date, there has been little work on determining the TPCE for perovskite photovoltaics (PV). We fabricate perovskite solar cells with a TPCE of -0.08 rel %/°C and then disentangle the temperature-dependent effects of the perovskite absorber, contact layers, and interfaces by comparing different device architectures and using drift-diffusion modeling. A main factor contributing to the small TPCE of perovskites is their low intrinsic carrier concentrations with respect to Si and GaAs, which can be explained by its wider band gap. In this work, we demonstrate that the unique increase in Eg with increasing temperatures seen for perovskites results in a reduction in JSC but positively influences VOC. The current limiting factors for the TPCE in perovskite PV are identified to originate from interfacial effects.

14 SOLAR ENERGY↗

DOE OSTI2022

Heat conduction in an irregular magnetic field. Part 2. Heat transport as a measure of the effective non-integrable volume

Given the large anisotropy of transport processes in magnetized plasmas, the magnetic field structure can strongly impact heat diffusion: magnetic surfaces and cantori form barriers to transport while chaotic layers and island structures can degrade confinement. When a small but non-zero amount of perpendicular diffusion is included, the structure of the magnetic field becomes less important, allowing pressure gradients to be supported across chaotic regions and island chains. We introduce a metric for the effective volume over which the local parallel diffusion dominates based on the solution to the anisotropic heat diffusion equation. To validate this metric, we consider model fields with a single island chain and a strongly chaotic layer for which analytic predictions of the relative parallel and perpendicular transport can be made. We also analyse critically chaotic fields produced from different sets of perturbations, highlighting the impact of the mode number spectrum on the heat transport. Our results indicate that this metric coincides with the effective volume of non-integrability in the limit $\kappa _{\perp } \rightarrow 0$ , where $\kappa_{\perp}$ is the perpendicular diffusion coefficient. We propose that this metric be used to assess the impact of non-integrability on the heat transport in stellarator equilibria.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Model for Humidity-Mediated Diffusion on Aluminum Surfaces and Its Role in Accelerating Atmospheric Aluminum Corrosion

Bare aluminum metal surfaces are highly reactive, which leads to the spontaneous formation of a protective oxide surface layer. Because many subsequent corrosive processes are mediated by water, the structure and dynamics of water at the oxide interface are anticipated to influence corrosion kinetics. Here, using molecular dynamics simulations with a reactive force field, we model the behavior of aqueous aluminum metal ions in water adsorbed onto aluminum oxide surfaces across a range of ion concentrations and water film thicknesses corresponding to increasing relative humidity. We find that the structure and diffusivity of both the water and the metal ions depend strongly on the humidity of the environment and the relative height within the adsorbed water film. Aqueous aluminum ion diffusion rates in water films corresponding to a typical indoor relative humidity of 30% are found to be more than 2 orders of magnitude slower than self-diffusion of water in the bulk limit. Connections between metal ion diffusivity and corrosion reaction kinetics are assessed parametrically with a reductionist model based on a 1D continuum reaction–diffusion equation. Our results highlight the importance of incorporating the properties specific to interfacial water in predictive models of aluminum corrosion.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Direct numerical simulation of a turbulent methane/air flame impinged by a sub-breakdown electric field

Here, the effects of an external electric field on a turbulent methane/air diffusion flame are analyzed in this work using direct numerical simulations. The analyzed configuration consists of a temporally evolving mixing layer of air and a mixture of methane and nitrogen at 1 atm that is impinged by an electric field in the direction normal to the mean mixing plane. The combustion and chemi-ionization reactions involved in the flow are modeled using finite-rate chemistry and a reduced reaction scheme consisting of 26 species and 134 reactions. The mass diffusion and ion-wind effects are modeled using a detailed description of the diffusion coefficients and electric mobilities based on kinetic theory. The presented calculations show that the turbulence generated within the mixing layer is mostly unaffected by the applied electric field for the configuration under exam. In fact, the electric body force is developed away from the mixing region where the flow is uniform. Conversely, the turbulence is able to introduce very high intermittency in the electrically charged species concentration and, consequently, in the electric body force. Such intermittency will constitute a challenge in the future formulation of combustion models that take into account ion-wind effects.

09 BIOMASS FUELS↗

DOE OSTI2021

A vortex sheet based analytical model of the curled wake behind yawed wind turbines

Motivated by the need for compact descriptions of the evolution of non-classical wakes behind yawed wind turbines, we develop an analytical model to predict the shape of curled wakes. Interest in such modelling arises due to the potential of wake steering as a strategy for mitigating power reduction and unsteady loading of downstream turbines in wind farms. We first estimate the distribution of the shed vorticity at the wake edge due to both yaw offset and rotating blades. By considering the wake edge as an ideally thin vortex sheet, we describe its evolution in time moving with the flow. Vortex sheet equations are solved using a power series expansion method, and an approximate solution for the wake shape is obtained. The vortex sheet time evolution is then mapped into a spatial evolution by using a convection velocity. Apart from the wake shape, the lateral deflection of the wake including ground effects is modelled. Our results show that there exists a universal solution for the shape of curled wakes if suitable dimensionless variables are employed. For the case of turbulent boundary layer inflow, the decay of vortex sheet circulation due to turbulent diffusion is included. Finally, we modify the Gaussian wake model by incorporating the predicted shape and deflection of the curled wake, so that we can calculate the wake profiles behind yawed turbines. Model predictions are validated against large-eddy simulations and laboratory experiments for turbines with various operating conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Resolving experimental biases in the interpretation of diffusion experiments with a user-friendly numerical reactive transport approach

The reactive transport code CrunchClay was used to derive effective diffusion coefficients (D e ), clay porosities (ε), and adsorption distribution coefficients (K D ) from through-diffusion data while considering accurately the influence of unavoidable experimental biases on the estimation of these diffusion parameters. These effects include the presence of filters holding the solid sample in place, the variations in concentration gradients across the diffusion cell due to sampling events, the impact of tubing/dead volumes on the estimation of diffusive fluxes and sample porosity, and the effects of O-ring-filter setups on the delivery of solutions to the clay packing. Doing so, the direct modeling of the measurements of (radio)tracer concentrations in reservoirs is more accurate than that of data converted directly into diffusive fluxes. While the above-mentioned effects have already been described individually in the literature, a consistent modeling approach addressing all these issues at the same time has never been described nor made easily available to the community. A graphical user interface, CrunchEase, was created, which supports the user by automating the creation of input files, the running of simulations, and the extraction and comparison of data and simulation results. While a classical model considering an effective diffusion coefficient, a porosity and a solid/solution distribution coefficient (D e –ε–K D ) may be implemented in any reactive transport code, the development of CrunchEase makes it easy to apply by experimentalists without a background in reactive transport modeling. CrunchEase makes it also possible to transition more easily from a D e –ε–K D modeling approach to a state-of-the-art process-based understanding modeling approach using the full capabilities of CrunchClay, which include surface complexation modeling and a multi-porosity description of the clay packing with charged diffuse layers.

58 GEOSCIENCES↗

DOE OSTI2022

Thermal model for time-domain thermoreflectance experiments in a laser-flash geometry

Time-domain thermoreflectance (TDTR) is a well-established pump–probe method for measuring thermal conductivity and interface conductance of multilayers. Interpreting signals in a TDTR experiment requires a thermal model. In standard front/front TDTR experiments, both pump and probe beams typically irradiate the surface of a multilayer. As a result, existing thermal models for interpreting thermoreflectance experiments assume that the pump and probe beams both interact with the surface layer. Here, we present a frequency-domain solution to the heat-diffusion equation of a multilayer in response to nonhomogeneous laser heating. This model allows analysis of experiments where the pump and probe beams irradiate opposite sides of a multilayer. We call such a geometry a front/back experiment to differentiate such experiments from standard TDTR experiments. As an example, we consider a 60nm amorphous Si film. We consider how signals differ in a front/front vs front/back geometry and compare thermal model predictions to experimental data.

Peng, Wanyue↗

DOE OSTI2022

The Importance of a Moving Boundary Approach for Modeling the SEI Layer Growth to Predict Capacity Fade

One of the contributing factors to the aging of lithium-ion batteries is the growth of the solid-electrolyte interphase (SEI) layer. The growth of the SEI layer leads to the irreversible loss of lithium available for cycling and increases the resistance of the battery. Physics-based models in literature model the kinetically limited or solvent diffusion-limited growth. In such models, the interface resistance is a constant, and the contribution to the overpotential of the intercalation reaction from the SEI layer is considered to be ohmic. In this study, we propose a model that describes the growth of the SEI layer on the electrode surface as a moving interface. The transport of lithium ions and the solvent in the electrolyte are affected by this moving interface. The equations that govern the species transport and the potential drop across the SEI layer are derived from dilute solution theory and solved by transforming the coordinates of the moving boundary. The ion transport induces changes in the conductivity across the SEI layer, which affects the potential drop that arises due to its growth. The effects of this potential on capacity fade are studied over cycling the battery.

25 ENERGY STORAGE↗

DOE OSTI2022

MODELLING FIBER ORIENTATION DURING ADDITIVE MANUFACTURING COMPRESSION MOLDING PROCESSES

The production of high-performance thermoplastic composites reinforced with short carbon fibers can be achieved by a novel “additive manufacturing-compression molding” technique. An advantage of such combination is two-fold: controlled fiber orientation in additive manufacturing and less void content by compression molding. In this study, a computational fluid dynamics model has been developed to predict the behavior of printed layers during fiber-reinforced thermoplastic extrusion and subsequent compression molding. The fiber orientation was modelled with a simple quadratic closure model. The interaction between the fibers is included using a rotary diffusion coefficient which becomes significant in concentrated regimes. Finally, the second order orientation tensor is coupled with the momentum equation as an anisotropic part of the stress term. The effect of processing parameters on the behavior of printed layers was investigated to determine the favorable printing scenarios. The developed numerical model enables design of high-performance composites with tunable mechanical properties.

Seta, Berin↗

DOE OSTI2022

How the Hydrophobic Interface between a Perfluorosulfonic Acid Polymer and Water Vapor Controls Membrane Hydration

Stable hydration in perfluorinated polyelectrolyte membranes such as Nafion is essential to maintain good ion conductivity and manage permeation, especially in vapor-fed devices where water content depends on relative humidity in a gas stream. Extensive studies in the literature have shown that Nafion hydration in water vapor is controlled by its interfacial transport resistance. Nafion forms a fluorine-rich layer at the polymer-gas interface, and it has been proposed that this layer blocks water transport due to its hydrophobicity. To develop a molecular-level description of the physics underlying transport resistance in this system, we have performed a computational reaction-diffusion kinetics study of water evaporation from Nafion. Two distinct models are examined, one mimicking the blocking function proposed in the literature and the other assuming that there is no blocking, treating instead water evaporation as a dynamic balance between uptake from the gas and desorption from the polymer surface. Simulation results are compared to time-dependent infrared data over a range of 100-0% relative humidity from the literature. Only the dynamic model successfully reproduces experimental observations. This indicates that the physical nature of interfacial transport resistance is not slow diffusion across an interfacial layer; rather, it is due to the competition between dehydration and rehydration. The simulation data provide details on the accompanying water distributions throughout the membrane and on interfacial kinetics, showing that they are characterized by strong fluctuations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Insights into the Li Diffusion Mechanism in Si/C Composite Anodes for Lithium-Ion Batteries

Recently, Si/C composite materials have attracted enormous research interest as the most promising candidates for the anodes of next-generation lithium-ion batteries, owing to their high energy density and mechanical buffering property. However, the fundamental mechanism of Li diffusion behavior in various Si/C composite materials remains unclear, with our understanding limited by experimental techniques and continuum modeling methodologies. Herein, the atomic behavior of Li diffusion in the Si/C composite material is studied within the framework of density functional theory. Two representative structural mixing formats, that is, simple mixture mode and core-shell mode, are modeled and compared. We discover that the carbon material increases Li diffusion in silicon from 7.75 x 10 -5 to 2.097 x 10 -4 cm 2 /s. The boost is about 50% more obvious in the mixture mode, while the core-shell structure shows more dependence on the atomic structures of the carbon layer. These results offer new insights into Li diffusion behavior in Si/C composites and unlock the enhancing mechanism for Li diffusion in Si/C. Furthermore, this understanding facilitates the modeling of batteries with composite anodes and will guide the corresponding structure designs for robust and high-energy-density batteries.

25 ENERGY STORAGE↗