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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Molecular dynamics based study on the effects of cation size on the local structure and diffusion in polymerized ionic liquids

We have used coarse-grained molecular dynamics simulations to understand the effect of cation size on ion diffusion in polymerized ionic liquids at temperatures well above the glass transition temperature of the polymers. We investigated dependencies of the diffusion constant on the cation radius and static dielectric constant and interpreted these results in terms of underlying structural changes, and decoupling phenomenon. We have found non-monotonic effects of the cation radius on the diffusion constant, with a maximum at an intermediate radius resulting from two different size dependent effects. Changes in the radial distribution functions characterizing spatial distribution of cations with respect to anions result in a monotonic increase in the coordination number. This yields an increase in the effective interaction energy as a function of cation radius, which can explain the decrease in the diffusion constant. This increase is counteracted at small cation radii by a corresponding increase in decoupling of cation and anion dynamics. In addition, the diffusion constant is found to increase on increasing the static dielectric constant for all radii of the cations. These results highlight the significant role of decoupling in designing polymerized ionic liquids with an enhanced diffusion constant of cations.

Gillespie, Colin [ORNL] (ORCID:0000000320287080)↗
DOE OSTI2024

Simulating hindered grain boundary diffusion using the smoothed boundary method

Abstract Grain boundaries can greatly affect the transport properties of polycrystalline materials, particularly when the grain size approaches the nanoscale. While grain boundaries often enhance diffusion by providing a fast pathway for chemical transport, some material systems, such as those of solid oxide fuel cells and battery cathode particles, exhibit the opposite behavior, where grain boundaries act to hinder diffusion. To facilitate the study of systems with hindered grain boundary diffusion, we propose a model that utilizes the smoothed boundary method to simulate the dynamic concentration evolution in polycrystalline systems. The model employs domain parameters with diffuse interfaces to describe the grains, thereby enabling solutions with explicit consideration of their complex geometries. The intrinsic error arising from the diffuse interface approach employed in our proposed model is explored by comparing the results against a sharp interface model for a variety of parameter sets. Finally, two case studies are considered to demonstrate potential applications of the model. First, a nanocrystalline yttria-stabilized zirconia solid oxide fuel cell system is investigated, and the effective diffusivities are extracted from the simulation results and are compared to the values obtained through mean-field approximations. Second, the concentration evolution during lithiation of a polycrystalline battery cathode particle is simulated to demonstrate the method’s capability.

Materials Science↗
DOE OSTI2022

Eddy diffusivity operator in homogeneous isotropic turbulence

Here, we use the recently developed macroscopic forcing method to compute the scale-dependent eddy diffusivity characterizing ensemble-averaged scalar and momentum transport in incompressible homogeneous isotropic turbulence. For scales larger than the energy containing eddies, eddy diffusivity is found to be constant and consistent with the Boussinesq approximation. However, for small scales eddy diffusivity is found to vanish inversely proportional to the wave number. Behavior at all scales is reasonably captured by a nonlocal eddy diffusivity operator modeled as D/$\sqrt{I - l^2∇^2}$, where D is the eddy diffusivity in the Boussinesq limit, and l is a constant on the order of the large-eddy length. These results present a direct measurement of eddy diffusivity in turbulence with implications in turbulence modeling.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

In situ counter-diffusion crystallization and long-term crystal preservation in microfluidic fixed targets for serial crystallography

Compared with batch and vapor diffusion methods, counter diffusion can generate larger and higher-quality protein crystals yielding improved diffraction data and higher-resolution structures. Typically, counter-diffusion experiments are conducted in elongated chambers, such as glass capillaries, and the crystals are either directly measured in the capillary or extracted and mounted at the X-ray beamline. Despite the advantages of counter-diffusion protein crystallization, there are few fixed-target devices that utilize counter diffusion for crystallization. In this article, different designs of user-friendly counter-diffusion chambers are presented which can be used to grow large protein crystals in a 2D polymer microfluidic fixed-target chip. Methods for rapid chip fabrication using commercially available thin-film materials such as Mylar, propylene and Kapton are also detailed. Rules of thumb are provided to tune the nucleation and crystal growth to meet users' needs while minimizing sample consumption. These designs provide a reliable approach to forming large crystals and maintaining their hydration for weeks and even months. This allows ample time to grow, select and preserve the best crystal batches before X-ray beam time. Importantly, the fixed-target microfluidic chip has a low background scatter and can be directly used at beamlines without any crystal handling, enabling crystal quality to be preserved. The approach is demonstrated with serial diffraction of photoactive yellow protein, yielding 1.32 Å resolution at room temperature. Fabrication of this standard microfluidic chip with commercially available thin films greatly simplifies fabrication and provides enhanced stability under vacuum. These advances will further broaden microfluidic fixed-target utilization by crystallographers.

Liu, Zhongrui↗
DOE OSTI2024

Constrained Local Approximate Ideal Restriction for Advection-Diffusion Problems

Herein this paper focuses on developing a reduction-based algebraic multigrid (AMG) method that is suitable for solving general (non)symmetric linear systems and is naturally robust from pure advection to pure diffusion. Initial motivation comes from a new reduction-based AMG approach, $\ell \text{AIR}$ (local approximate ideal restriction), that was developed for solving advection-dominated problems. Though this new solver is very effective in the advection-dominated regime, its performance degrades in cases where diffusion becomes dominant. This is consistent with the fact that in general, reduction-based AMG methods tend to suffer from growth in complexity and/or convergence rates as the problem size is increased, especially for diffusion-dominated problems in two or three dimensions. Motivated by the success of $\ell \text{AIR}$ in the advective regime, our aim in this paper is to generalize the AIR framework with the goal of improving the performance of the solver in diffusion-dominated regimes. To do so, we propose a novel way to combine mode constraints as used commonly in energy-minimization AMG methods with the local approximation of ideal operators used in $\ell \text{AIR}$. The resulting constrained $\ell \text{AIR}$ algorithm is able to achieve fast scalable convergence on advective and diffusive problems. In addition, it is able to achieve standard low complexity hierarchies in the diffusive regime through aggressive coarsening, something that was previously difficult for reduction-based methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Calibration of the Diffusivity Predictions of Centipede Using Approximate Bayesian Computation and Applications in Nyx (Engineering Scale) and Xolotl-MARMOT (Meso-Scale) Simulations

Fission gas evolution and release in UO 2 nuclear fuel are important fuel performance metrics and occur in several distinct stages: 1) nucleation, growth and resolution of intra-granular bubbles, 2) diffusion to grain boundaries and 3) nucleation and growth of bubbles at grain boundaries, which eventually form a connected network (percolation) enabling release of gas from grain boundaries through connections to triple junctions, grain edges or free surfaces. The NE-SciDAC project is developing several computational tools to model this problem, which are connected in a hierarchical multi-scale framework. The information transfer in the multi-scale framework is a critical step that, in addition to best-estimates, should include uncertainty quantification. Despite taking a first-principles multi-scale approach, there is a need to perform parameter calibration to ensure consistency with available experimental data. In the present study, uncertainty quantification (UQ) and parameter calibration is demonstrated for one of the lower length scale codes in the multi-scale framework (Centipede) and then the results, including instances of the propagated uncertainties, are used in other codes within the framework, specifically Nyx and Xolotl-MARMOT. We calibrated the model parameters in Centipede, a computer code used to predict diffusivities of uranium (U) and xenon (Xe) in the context of the simulation of fission gas in uranium oxide (UO 2 ) nuclear fuel. The Centipede code depends on 183 parameters, all of which are subject to uncertainty. The three data sets used in our calibration effort are taken from the literature. This data is available as a set of measurements, including measurement errors. Our goal is to calibrate a statistical model that predicts both the value of the measurement and the uncertainty associated with the measurement. We perform a Bayesian calibration of the model parameters using a dedicated approximate Bayesian computation (ABC) likelihood function. To avoid excessive computational costs, we replace the expensive Centipede simulation code by a higher-order surrogate model, constructed using only the 9 most important parameters. These important parameters are identified by a preliminary global sensitivity analysis (GSA) study. Among the important parameters are T0 (the temperature at which UO 2 is perfectly stoichiometric) and Hf_pO2 (the temperature dependence of the oxygen (O) partial pressure) that should be considered as operating conditions to be estimated along with the other parameters. We consider two different cases: one where we define one set of these operating conditions for all data sets, and one where we define distinct operating condition parameters for each data set. The Xe diffusivities predicted by the latter case show distinct features that could not be observed in the former. Next, we use the diffusivity predictions by Centipede as input to Nyx, a reduced order fuel performance code focused on gas behavior alone, in order to estimate quantities associated with inter-granular bubble formation at conditions specified by the experiments. Finally, the diffusivities obtained from the calibrated Centipede runs were used in coupled Xolotl-MARMOT simulations of intra- and inter-granular gas evolution. The results are compared to simulations using the baseline diffusivities from Turnbull et al.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Molecular dynamics simulations of fission gas xenon (Xe) diffusion at UO 2 grain-boundaries (Rev.1)

The diffusivity of fission gas xenon (Xe) at UO 2 grain-boundaries is one of the most important parameters in mechanistic modeling of fission gas diffusion in UO 2 based nuclear fuels. In this report, we use molecular dynamics simulations to investigate the Xe diffusivity in UO 2 grain-boundaries, employing the many-body potential developed by Cooper, Rushton and Grimes for UO 2 . Three different types of grain-boundaries are investigated, twist Σ5, tilt Σ5, and a random grain-boundary. Diffusion activation energies in the range of 0.39 – 1.46 eV are obtained for the Xe diffusivity. Comparison to results for the uranium vacancy diffusivity from MD simulations employing the same methodology suggests a weak to moderate attractive Xe-uranium vacancy binding energy depending on the grain-boundary type.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Solar-Tracker Diffuse-Response Algorithm for Balancing Energy Gain and Mechanical Wear in Photovoltaic Systems

Single-axis solar tracking maximizes photovoltaic energy production under clear-sky conditions; however, its effectiveness decreases under cloudy and overcast skies, where diffuse irradiance dominates and the optimal module orientation changes. Conventional tracking algorithms either neglect sky conditions or rely on simplified diffuse-response strategies that may trigger frequent tracker repositioning under variable cloud cover, leading to increased mechanical wear with marginal energy gains. This work proposes an enhanced diffuse-response tracking algorithm that explicitly accounts for both the intensity and temporal persistence of cloudiness. By requiring overcast conditions to persist for a minimum duration before reorienting the tracker to a diffuse-stow position, the proposed approach reduces unnecessary movements while preserving the benefits of diffuse-response operation. The algorithm is evaluated through numerical simulations based on historical meteorological data and validated using field measurements on monofacial and bifacial photovoltaic strings. The results show that the proposed strategy reduces excess tracker movement from 114% to 0.16% while maintaining nearly the same energy yield. Compared to a conventional diffuse-response algorithm, the associated energy reduction is minimal (≈0.17%) relative to the ≈0.37% yield gain observed at the studied location. These findings demonstrate that incorporating cloudiness duration enables a practical compromise between energy performance and tracker durability, particularly for monofacial photovoltaic systems.

14 SOLAR ENERGY↗
DOE OSTI2020

Dirichlet absorbing boundary conditions for classical and peridynamic diffusion-type models

Diffusion-type problems in (nearly) unbounded domains play important roles in various fields of fluid dynamics, biology, and materials science. The aim of this paper is to construct accurate absorbing boundary conditions (ABCs) suitable for classical (local) as well as nonlocal peridynamic (PD) diffusion models. The main focus of the present study is on the PD diffusion formulation. The majority of the PD diffusion models proposed so far are applied to bounded domains only. In this study, we propose an effective way to handle unbounded domains both with PD and classical diffusion models. For the former, we employ a meshfree discretization, whereas for the latter the finite element method (FEM) is employed. The proposed ABCs are time-dependent and Dirichlet-type, making the approach easy to implement in the available models. The performance of the approach, in terms of accuracy and stability, is illustrated by numerical examples in 1D, 2D, and 3D.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Nonadiabatic Effects on Defect Diffusion in Silicon-Doped Nanographenes

Single atom impurities in graphene, substitutional silicon defects in particular, have been observed to diffuse under electron beam irradiation. However, the relative importance of elastic and inelastic scattering in facilitating their mobility remains unclear. Here, we employ excited-state electronic structure calculations to explore potential inelastic effects, and find an electronically nonadiabatic excited-state silicon diffusion pathway involving “softened” Si–C bonding that presents an ~2 eV lower diffusion barrier than the ground-state pathway. Beam-induced transition rates to this state indicate that the excited-state pathway is accessible through irradiation of the defect site. However, even in the limit of fully elastic scattering, upward nonadiabatic transitions are also possible along the diffusion coordinate, increasing the diffusion barrier and further demonstrating the potential for electronic nonadiabaticity to influence beam-induced atomic transformations in materials. Additionally, we also propose some experimentally testable signatures of such excited-state pathways.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
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↗
DOE OSTI2021

Analysis of Anisotropic Nonlocal Diffusion Models: Well-posedness of Fractional Problems for Anomalous Transport

We analyze the well-posedness of an anisotropic, nonlocal diffusion equation. Establishing an equivalence between weighted and unweighted anisotropic nonlocal diffusion operators in the vein of unified nonlocal vector calculus, we apply our analysis to a class of fractional-order operators and present rigorous estimates for the solution of the corresponding anisotropic anomalous diffusion equation. Furthermore, we extend our analysis to the anisotropic diffusion-advection equation and prove well-posedness for fractional orders s ∊ [0.5, 1). We also present an application of the advection-diffusion equation to anomalous transport of solutes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Bulk and Short-Circuit Anion Diffusion in Epitaxial Fe 2 O 3 Films Quantified Using Buried Isotopic Tracer Layers

Self-diffusion is a fundamental physical process that, in solid materials, is intimately correlated with both microstructure and functional properties. In this work, a universal approach is presented to precisely characterize self-diffusion in ionic solids by isotopically enriching anions and/or cations at specific locations within an epitaxial film stack, and characterize their redistribution at high spatial resolution with atom probe tomography. Nanoscale anion diffusivity is quantified in epitaxial α-Fe 2 O 3 thin films deposited by molecular beam epitaxy with a thin (10 nm) buried layer highly enriched in 18 O. The isotopic sensitivity of the atom probe allows precise measurement of 18 O distribution across the sharp interfaces between this layer and the surrounding Fe 2 O 3 after annealing. Short-circuit anion diffusion through 1D and 2D structural defects in Fe 2 O 3 are also directly visualized in 3D. This versatile approach to study precisely tailored thin film samples at high spatial and mass fidelity will facilitate a deeper understanding of atomic-scale diffusion phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2020

An Experimental Method to Measure Gaseous Diffusivity in Tight and Partially Saturated Porous Media via Continuously Monitored Mass Spectrometry

Detection of radioxenon and radioargon produced by underground nuclear explosions is one of the primary methods by which the Comprehensive Nuclear-Test–Ban Treaty (CTBT) monitors for nuclear activities. However, transport of these noble gases to the surface via barometric pumping is a complex process relying on advective and diffusive processes in a fractured porous medium to bring detectable levels to the surface. To better understand this process, experimental measurements of noble gas and chemical surrogate diffusivity in relevant lithologies are necessary. However, measurement of noble gas diffusivity in tight or partially saturated porous media is challenging due to the transparent nature of noble gases, the lengthy diffusion times, and difficulty maintaining consistent water saturation. Here, the quasi-steady-state Ney–Armistead method is modified to accommodate continuous gas sampling via effusive flow to a mass spectrometer. An analytical solution accounting for the cumulative sampling losses and induced advective flow is then derived. Experimental results appear in good agreement with the proposed theory, suggesting the presence of retained groundwater reduces the effective diffusivity of the gas tracers by 10–1000 times. Finally, by using a mass spectrometer, the method described herein is applicable to a broad range of gas species and porous media.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Structural and chemical disorder enhance point defect diffusion and atomic transport in Ni 3 Al-based γ' phase

The ordered L1 2 γ' Ni 3 Al intermetallic inclusions are routinely used as strengthening constituents in Ni-based superalloys and recent high-entropy alloys. As there are different metallic elements relative to the alloy matrix, the composition of γ' phase inclusions usually suffers some variations. In this work, we studied the elemental partition and its influence on atomic transport properties in a model (NiCo) 3 Al γ' phase with chemical and structural disorder. Combining the Monte Carlo and molecular static techniques, we first determined the elemental distribution in such compositionally-complexed γ' phase. The results suggest that Co tends to segregate, which profoundly influences defect energetics and diffusion properties. By modeling thermally activated diffusion by molecular dynamics, we found that chemical disorder induced by Co can enhance vacancy diffusion while significantly suppress diffusion via interstitial atom migration, as compared to the stoichiometric γ' Ni 3 Al. We further reveal that these observations are closely related to the defect energetics in these systems. Furthermore, our results explain the effects of disorder, long- and short-range orders on the diffusion properties in multicomponent intermetallic alloys, which helps to understand the stability and, thus, γ'-phase-assisted strengthening at different conditions including annealing and irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Atomistic modeling of metal–nonmetal interphase boundary diffusion

Atomistic computer simulations are applied to investigate the atomic structure, thermal stability, and diffusion processes in Al–Si interphase boundaries as a prototype of metal–ceramic interfaces in composite materials. Some of the most stable orientation relationships between the phases found in this work were previously observed in epitaxy experiments. Here, a non-equilibrium interface can transform to a more stable state by a mechanism that we call interface-induced recrystallization. Diffusion of both Al and Si atoms in stable Al–Si interfaces is surprisingly slow compared with diffusion of both elements in Al grain boundaries but can be accelerated in the presence of interface disconnections. A qualitative explanation of the sluggish interphase boundary diffusion is proposed. Atomic mechanisms of interphase boundary diffusion are similar to those in metallic grain boundaries and are dominated by correlated atomic rearrangements in the form of strings and rings of collectively moving atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A finite difference informed random walker (FDiRW) solver for strongly inhomogeneous diffusion problems

In nature, many complex multi-physics coupling problems exhibit strong diffusivity inhomogeneity. For instance, in the context of radionuclide absorption by porous wasteform materials within a flowing waste stream, the difference of species’ diffusivity in solid and liquid phases spans by 3~8 orders of magnitude. To solve the diffusion equations with strongly inhomogeneous diffusivity, traditional discretization-based methods, such as the Finite Difference Method (FDM), require infinitesimally small time steps (<10 -10 ) as high spatial resolutions are employed in most microstructure evolution processes, leading to prohibitively high computational costs. Here, this work developed an integrated numerical approach (FDiRW: Finite Difference informed Random Walk) to tackle this challenge. The idea is that utilizing the Random Walk concept, the fast diffusion is modeled as a superposition of point source’s solution for a concentration distribution while FDM is used to obtain the point source’s solution at each node. A mesh-coarsening algorithm is developed to generate an exclusive coarse mesh for FDiRW approach to maximize its efficiency. The effectiveness of the coarse mesh-based FDiRW approach is validated by benchmarking Finite Difference solutions. Numerical results demonstrated that FDiRW achieves a remarkable 1000x computational efficiency improvement over FDM while preserving desired accuracy for a medium-sized model of 192 × 192 × 192 grids. Finally, as models scale up, a floating-point operations (PLOPs) analysis of the FDiRW algorithm reveals that its computational complexity grows quadratically in terms of the number of nodes employed in computation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A provably stable numerical method for the anisotropic diffusion equation in confined magnetic fields

We present a novel numerical method for solving the anisotropic diffusion equation in magnetic fields confined to a periodic box which is accurate and provably stable. We derive energy estimates of the solution of the continuous initial boundary value problem. A discrete formulation is presented using operator splitting in time with the summation by parts finite difference approximation of spatial derivatives for the perpendicular diffusion operator. Weak penalty procedures are derived for implementing both boundary conditions and parallel diffusion operator obtained by field line tracing. We prove that the fully-discrete approximation is unconditionally stable. Discrete energy estimates are shown to match the continuous energy estimate given the correct choice of penalty parameters. A nonlinear penalty parameter is shown to provide an effective method for tuning the parallel diffusion penalty and significantly minimises rounding errors. Several numerical experiments, using manufactured solutions, the “NIMROD benchmark” problem and a single island problem, are presented to verify numerical accuracy, convergence, and asymptotic preserving properties of the method. Finally, we present a magnetic field with chaotic regions and islands and show the contours of the anisotropic diffusion equation reproduce key features in the field.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗