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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Kinetic lattice Monte Carlo model for oxygen vacancy diffusion in praseodymium doped ceria: Applications to materials design

Kinetic lattice Monte Carlo (KLMC) model is developed for investigating oxygen vacancy diffusion in praseodymium-doped ceria. The current approach uses a database of activation energies for oxygen vacancy migration, calculated using first-principles, for various migration pathways in praseodymium-doped ceria. Since the first-principles calculations revealed significant vacancy-vacancy repulsion, we investigate the importance of that effect by conducting simulations with and without a repulsive interaction. Initially, as dopant concentrations increase, vacancy concentration and thus conductivity increases. However, at higher concentrations, vacancies interfere and repel one another, and dopants trap vacancies, creating a 'traffic jam' that decreases conductivity, which is consistent with the experimental findings. The modeled effective activation energy for vacancy migration slightly increased with increasing dopant concentration in qualitative agreement with the experiment. The current methodology comprising a blend of first-principle calculations and KLMC model provides a very powerful fundamental tool for predicting the optimal dopant concentration in ceria related materials. -- graphical abstract: Ionic conductivity in praseodymium doped ceria as a function of dopant concentration calculated using the kinetic lattice Monte Carlo vacancy-repelling model, which predicts the optimal composition for achieving maximum conductivity. Display Omitted Research highlights: {yields} KLMC method calculates the accurate time-dependent diffusion of oxygen vacancies. {yields} KLMC-VR model predicts a dopant concentration of {approx}15-20% to be optimal in PDC. {yields} At higher dopant concentration, vacancies interfere and repel one another, and dopants trap vacancies. {yields} Activation energy for vacancy migration increases as a function of dopant content

36 MATERIALS SCIENCE↗
DOE OSTI2011

Multinomial diffusion equation

We describe a new, microscopic model for diffusion that captures diffusion induced uctuations at scales where the concept of concentration gives way to discrete par- ticles. We show that in the limit as the number of particles N ! 1, our model is equivalent to the classical stochastic diffusion equation (SDE). We test our new model and the SDE against Langevin dynamics in numerical simulations, and show that our model successfully reproduces the correct ensemble statistics, while the classical model fails.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2010

ISDD: A Computational Model of Particle Sedimentation, Diffusion and Target Cell Dosimetry for In Vitro Toxicity Studies

Background: The difficulty of directly measuring cellular dose is a significant obstacle to application of target tissue dosimetry for nanoparticle and microparticle toxicity assessment. As a consequence, the target tissue paradigm for dosimetry and hazard assessment of nanoparticles has largely been ignored in favor of using metrics of exposure (e.g. μg particle/mL culture medium, particle surface area/mL, particle number/mL). We have developed a computational model of solution particokinetics (sedimentation, diffusion) and dosimetry for non-interacting spherical particles and their agglomerates in monolayer cell culture systems. Particle transport to cells is calculated by simultaneous solution of Stokes Law (sedimentation) and the Stokes-Einstein equation (diffusion). Results: The In vitro Sedimentation, Diffusion and Dosimetry model (ISDD) was tested against measured transport rates or cellular doses for multiple sizes of polystyrene spheres (20-1100 nm), 35 nm amorphous silica, and large agglomerates of 30 nm iron oxide particles. Overall, without adjusting any parameters, model predicted doses were in close agreement with the experimental data, differing from as little as 5% to as much as three-fold, but in most cases approximately two-fold, within the limits of the accuracy of the measurement systems. Applying the model, we generalize the effects of particle size, particle density, agglomeration state and agglomerate characteristics on target cell dosimetry in vitro. Conclusions: Our results confirm our hypothesis that the dose-rates for all particles are not equal, but can vary significantly, in direct contrast to the assumption of dose-equivalency implicit in the use of mass-based media concentrations as metrics of exposure for dose-response assessment. The difference between equivalent nominal media concentration exposures on a μg/mL basis and target cell doses on a particle surface area or number basis can be as high as three to six orders of magnitude. As a consequence, in vitro hazard assessments utilizing mass-based exposure metrics have inherently high errors where particle number or surface areas target cells doses are believed to drive response. The gold standard for particle dosimetry for in vitro nanotoxicology studies should be direct experimental measurement of the cellular content of the studied particle. However, where such measurements are impractical, unfeasible, and before such measurements become common, particle dosimetry models such as ISDD provide a valuable, immediately useful alternative, and eventually an adjunct to such measurements.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Reshaping and sintering of 3D fcc metal nanoclusters: Stochastic atomistic modeling with realistic surface diffusion kinetics

Far-from-equilibrium evolution of metallic nanocluster shapes is highly sensitive to the atomistic-level details of surface diffusion for diverse local surface configurations. A stochastic model was developed incorporating realistic values for the multiple diffusion barriers (contrasting previous unrealistic generic prescriptions) based upon insights from homoepitaxial film growth. Kinetic Monte Carlo simulation then elucidates the conversion of Ag nanocubes to Wulff polyhedra mediated by nucleation of new {100} facets, the pinch-off of sufficiently elongated Ag nanorods, and key aspects of sintering for orientationally aligned Ag and Au nanoclusters. In conclusion, the time scale for sintering of Au nanoclusters observed in high-resolution transmission electron microscopy studies was also recovered.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Unified Analytical Model for Pressure Solution With Fully Coupled Diffusion and Reaction

Abstract Geophysical models for pressure solution are typically developed for diffusion‐controlled or reaction‐controlled scenarios. We present a unified analytical model that considers fully coupled diffusion and reaction during pressure solution. The model recovers the diffusion‐controlled and reaction‐controlled models in the literature as specific limiting cases. When diffusion and reaction exhibit comparable influences, we validate the proposed model against independent numerical simulations. The proposed model is then employed in interpreting experimental measurements, demonstrating a better agreement compared to previous interpretations.

Wang, Ziyan [Energy Geosciences Division Lawrence ↗
DOE OSTI2025

Scalar flux transport models for self-similar turbulent mixing

A common approach to closing turbulent species flux in multicomponent Reynolds-averaged Navier-Stokes models is to use the standard gradient diffusion approximation. While such an approach has been shown to work well when applied to many canonical turbulent mixing configurations, a gradient diffusion approach is fundamentally limited in its ability to capture complex phenomena such as countergradient transport. For this reason, complicated mixing applications may benefit by treating the turbulent diffusivity with a model transport equation in a manner analogous to second-moment momentum closure in Reynolds-stress transport models. Here, the present work explores the development and application of two different scalar flux transport (SFT) models. Self-similarity constraints are derived for these models, and they are evaluated against gradient-diffusion-based models in several one- and two-dimensional problems of turbulent mixing. It is found that the new SFT models out-perform gradient diffusion models in problems involving rapid acceleration reversal and in problems involving anisotropic transport of materials. In addition, it is found that even a hybrid-SFT approach, in which an SFT equation is utilized along with a gradient diffusion closure, provides some measure of improvement over models that transport the mass flux rather than the scalar flux.

Reynolds-averaged Navier Stokes↗
DOE OSTI2022

Atomistic and cluster dynamics modeling of fission gas (Xe) diffusivity in TRISO fuel kernels

TRISO fuel particles are candidates for use in next generation reactors including gas reactors, fluoride salt-cooled high temperature reactors, and micro-reactors. The UCO fuel kernel consists of a uranium dioxide (UO) and uranium carbide mixture. The addition of UC helps suppress the formation of carbon monoxide gas, which led to failures during initial TRISO development. The addition of uranium carbide alters the chemistry of the UO kernel, which is known to influence performance parameters such as fission gas diffusivity, although the impact has not been quantified and no models exist that take the change in chemistry into account. Therefore, better understanding and more accurate models of the impact of chemistry on fuel performance are of high priority. In this paper, a first-principles density functional theory (DFT) and empirical potential based multi-scale study has been carried out to model the diffusivity of fission gas xenon (Xe) in UCO TRISO fuel kernels. The focus is on the UO component in the UCO fuel kernels, as that represents the largest volume fraction of the fuel kernels. The study relies on DFT and empirical potential calculations to determine Xe and point defect properties, which are then used in thermodynamic and kinetic models to predict diffusion for intrinsic conditions. In addition, the information is utilized in cluster dynamics simulations using the Centipede code to estimate the impact of irradiation on defect transport. Additionally, the presence of UC or UC in the UCO fuel kernels is shown to have a substantial impact on the UO non-stoichiometry by inducing oxygen vacancies and driving UO sub-stoichiometric, which causes much slower Xe diffusion in UCO compared to light water reactor UO fuel. The application of this model in fuel performance simulations using the Bison code is also demonstrated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Sagittarius A* as an origin of the Galactic PeV cosmic rays?

Supernova remnants (SNRs) have commonly been considered as a source of the observed PeV cosmic rays (CRs) or a Galactic PeV particle accelerator ('Pevatron'). In this work, we study Sagittarius A* (Sgr A*), which is the low-luminosity active galactic nucleus of the Milky Way Galaxy, as another possible canditate of the Pevatron, because it sometimes became very active in the past. We assume that a large number of PeV CRs were injected by Sgr A* at the outburst about 10{sup 7} yr ago when the Fermi bubbles were created. We constrain the diffusion coefficient for the CRs in the Galactic halo on the condition that the CRs have arrived on the Earth by now, while a fairly large fraction of them have escaped from the halo. Based on a diffusion-halo model, we solve a diffusion equation for the CRs and compare the results with the CR spectrum on the Earth. The observed small anisotropy of the arrival directions of CRs may be explained if the diffusion coefficient in the Galactic disk is smaller than that in the halo. Our model predicts that a boron-to-carbon ratio should be energy-independent around the knee, where the CRs from Sgr A* become dominant. It is unlikely that the spectrum of the CRs accelerated at the outburst is represented by a power-law similar to the one for those responsible for the gamma-ray emission from the central molecular zone (CMZ) around the Galactic center.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Layers Can Be Deceiving: A Hopping Model for Small Molecule Diffusion in TATB Crystal

Sorption of small molecule gases in materials can play a significant role in their long‐term stability and compatibility within multi‐material assemblies. While many material properties of the insensitive high explosive TATB (1,3,5‐triamino‐2,4,6‐trinitrobenzene) are well understood, very little is known regarding its permeability to gases. TATB crystal exhibits a graphitic‐like layered packing structure that evokes a mental schema in which the layers form nanoscopic channels, but it is unclear whether this structure promotes gas transport. Here, we use molecular dynamics (MD) simulations to predict transport of small molecules through TATB single crystal. An approach to fit classical force fields is developed to model TATB interactions with H 2 O, He, Ne, and Ar, which is then combined with steered MD to probe gas transport along selected directions in the crystal. We find that small molecule transport occurs via a hopping mechanism that exhibits distinct jumps between interstitial sites and is substantially faster normal to the layers as compared to through them. This result stems from the finding that intralayer junctions between adjacent TATB molecules are the most stable interstitial sites and that energetic barriers are lower for hopping between adjacent layers. An empirical model for diffusion rate based on the MD data shows that the rate decays exponentially with increasing molecular radius and is negligibly small for all molecules larger than He, including common atmospheric gases. These findings have implications for the interpretation of experiments that measure surface area, material response to extreme conditions, and are expected to help constrain models for material aging.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Kinetic model describing self-limiting CO 2 diffusion in supported amine adsorbents

A reaction–diffusion shrinking core model describing the decay in diffusivity of supported amine sorbents upon CO 2 sorption under both simulated direct air capture and point source capture conditions is described. The decay in CO 2 diffusivity is associated with crosslinking in the aminopolymer samples and general pore blockage in the amino-silane derived samples, which occurs as CO 2 is adsorbed. The model is used to extract four kinetic parameters that govern the CO 2 uptake kinetics and working capacity: an apparent reaction rate constant, an initial effective diffusivity, and two dimensionless decay parameters. Ideally, an initially reaction limited system would allow for direct determination of the intrinsic reaction rate constant; however, sorption experiments suggest mass transfer resistances related to gas mixing, external boundary layers and intraparticle diffusion are present. Reaction rate constants are determined and agree well with theoretical values predicted with the Eyring equation parameterized using density functional theory energies from literature sources. The kinetic performance is expressed as the average effective diffusivity as a function of average conversion, which can be correlated to the dispersion of sorption sites on the support and the morphology of the active sorbent phase. Four supports are impregnated or grafted with amines, SBA-15, single-walled zeolite nanotubes (ZNT), Syloid SiO 2 , and γ-Al 2 O 3 . Due to its pore structure, γ-Al 2 O 3 supported amines can be modeled at the μm scale or at the nm scale, where the shell balance is on the μm-sized macroporous particle aggregate or on the nm-sized amine film on the surface of the Al 2 O 3 nanoparticles, which comprise the spherical particle aggregates. Faster diffusion rates are maintained under 400 ppm rather than 10% CO 2 due to a slower reaction rate giving a slower decay in diffusivity. In conclusion, this work provides a first principles kinetic analysis of CO 2 sorption where previous models are semi-empirical and use arbitrary kinetic parameters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Thermal flux limited electron Kapitza conductance in copper-niobium multilayers

The interplay between the contributions of electron thermal flux and interface scattering to the Kapitza conductance across metal-metal interfaces through measurements of thermal conductivity of copper-niobium multilayers was studied. Thermal conductivities of copper-niobium multilayer films of period thicknesses ranging from 5.4 to 96.2 nm and sample thicknesses ranging from 962 to 2677 nm are measured by time-domain thermoreflectance over a range of temperatures from 78 to 500 K. The Kapitza conductances between the Cu and Nb interfaces in multilayer films are determined from the thermal conductivities using a series resistor model and are in good agreement with the electron diffuse mismatch model. The results for the thermal boundary conductance between Cu and Nb are compared to literature values for the thermal boundary conductance across Al-Cu and Pd-Ir interfaces, and demonstrate that the interface conductance in metallic systems is dictated by the temperature derivative of the electron energy flux in the metallic layers, rather than electron mean free path or scattering processes at the interface.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2010

Transport Corrections in Nodal Diffusion Codes for HTR Modeling

The cores and reflectors of High Temperature Reactors (HTRs) of the Next Generation Nuclear Plant (NGNP) type are dominantly diffusive media from the point of view of behavior of the neutrons and their migration between the various structures of the reactor. This means that neutron diffusion theory is sufficient for modeling most features of such reactors and transport theory may not be needed for most applications. Of course, the above statement assumes the availability of homogenized diffusion theory data. The statement is true for most situations but not all. Two features of NGNP-type HTRs require that the diffusion theory-based solution be corrected for local transport effects. These two cases are the treatment of burnable poisons (BP) in the case of the prismatic block reactors and, for both pebble bed reactor (PBR) and prismatic block reactor (PMR) designs, that of control rods (CR) embedded in non-multiplying regions near the interface between fueled zones and said non-multiplying zones. The need for transport correction arises because diffusion theory-based solutions appear not to provide sufficient fidelity in these situations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Temperature-dependent ordering phenomena in single crystals of germanium antimony tellurides

The temperature-dependent behavior of quenched single-crystalline (GeTe){sub n}Sb{sub 2}Te{sub 3} (n~2.8, n~5 and n~11) was investigated by semiquantitative modeling of diffuse X-ray scattering. The structure at room temperature exhibits trigonal twin domains, each comprising a stacking-disordered sequence of distorted rocksalt-type slabs with variable thicknesses. Ge and Sb share the cation position and vacancies are partially ordered in defect layers (van der Waals gaps) between the slabs. The average structure determined with resonant diffraction data corresponds to a rocksalt-type structure whose cation position is split along the stacking direction. Upon heating, cation ordering leads to a metastable superstructure of the rocksalt type at ~400 °C, which transforms to a rocksalt-type high-temperature phase with randomly distributed cations and vacancies at ~500 °C; this structure was also refined using resonant diffraction. Cooling at high or intermediate rates does not yield the long-range ordered phase, but directly leads to the twinned disordered phase. - Graphical abstract: Development of the diffraction patterns of (GeTe){sub ~11}Sb{sub 2}Te{sub 3} upon heating; the insets symbolically sketch the real structure at the corresponding temperatures. - Highlights: • The structure of disordered (GeTe){sub n}Sb{sub 2}Te{sub 3} is described as a function of temperature. • Structural changes are tracked by modeling diffuse X-ray scattering. • Quenched crystals exhibit distorted NaCl-type slabs with different thicknesses. • Vacancy ordering upon heating leads to a metastable superstructure of the NaCl type. • Further heating leads to an undistorted disordered NaCl-type high-temperature phase.

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

Denoising diffusion algorithm for inverse design of microstructures with fine-tuned nonlinear material properties

Here we introduce a denoising diffusion algorithm to discover microstructures with nonlinear fine-tuned properties. Denoising diffusion probabilistic models are generative models that use diffusion-based dynamics to gradually denoise images and generate realistic synthetic samples. By learning the reverse of a Markov diffusion process, we design an artificial intelligence to efficiently manipulate the topology of microstructures to generate a massive number of prototypes that exhibit constitutive responses sufficiently close to designated nonlinear constitutive behaviors. To identify the subset of microcstructures with sufficiently precise fine-tuned properties, a convolutional neural network surrogate is trained to replace high-fidelity finite element simulations to filter out prototypes outside the admissible range. Results of this study indicate that the denoising diffusion process is capable of creating microstructures of fine-tuned nonlinear material properties within the latent space of the training data. More importantly, this denoising diffusion algorithm can be easily extended to incorporate additional topological and geometric modifications by introducing high-dimensional structures embedded in the latent space. Numerical experiments are conducted on the open-source mechanical MNIST data set (Lejeune, 2020). Consequently, this algorithm is not only capable of performing inverse design of nonlinear effective media, but also learns the nonlinear structure–property map to quantitatively understand the multiscale interplay among the geometry, topology, and their effective macroscopic properties.

42 ENGINEERING↗
DOE OSTI2024

Steady-state fuel performance analyses for the preliminary fuel concept of general atomics fast modular reactor

Here this manuscript presents the fuel performance analysis results of the General Atomics Fast Modular Reactor (FMR) based on an axi-symmetric (2D-RZ) geometry. Three fuel performance model sets that fit the FMR fuel specifications best, i.e., a BISON baseline model set, a BISON diffusion enhancement model set, and a BISON-FASTGRASS model set, were identified and evaluated against a series of relevant experimental cases featuring high burnup and low irradiation temperature conditions. The three BISON-based model sets were then utilized to conduct a comprehensive fuel performance analysis of the FMR fuel under normal operation including the shutdown/restarting periods for refueling. The evaluation of the fuel performance parameters, represented by temperature, internal pressure, stress, and strain, shows that the FMR fuel maintains its thermal and mechanical integrity during normal operation. Technology gaps and limitations are also discussed to guide future efforts for extending the performance analysis to transient scenarios as well as improving the fuel performance evaluation through experiments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2013

MULTI-WAVELENGTH OBSERVATIONS OF THE SPATIO-TEMPORAL EVOLUTION OF SOLAR FLARES WITH AIA/SDO. I. UNIVERSAL SCALING LAWS OF SPACE AND TIME PARAMETERS

We extend a previous statistical solar flare study of 155 GOES M- and X-class flares observed with AIA/SDO to all seven coronal wavelengths (94, 131, 171, 193, 211, 304, and 335 Å) to test the wavelength dependence of scaling laws and statistical distributions. Except for the 171 and 193 Å wavelengths, which are affected by EUV dimming caused by coronal mass ejections (CMEs), we find near-identical size distributions of geometric (lengths L, flare areas A, volumes V, and fractal dimension D{sub 2}), temporal (flare durations T), and spatio-temporal parameters (diffusion coefficient κ, spreading exponent β, and maximum expansion velocities v{sub max}) in different wavelengths, which are consistent with the universal predictions of the fractal-diffusive avalanche model of a slowly driven, self-organized criticality (FD-SOC) system, i.e., N(L)∝L {sup –3}, N(A)∝A {sup –2}, N(V)∝V {sup –5/3}, N(T)∝T {sup –2}, and D{sub 2} = 3/2, for a Euclidean dimension d = 3. Empirically, we find also a new strong correlation κ∝L {sup 0.94±0.01} and the three-parameter scaling law L∝κ T {sup 0.1}, which is more consistent with the logistic-growth model than with classical diffusion. The findings suggest long-range correlation lengths in the FD-SOC system that operate in the vicinity of a critical state, which could be used for predictions of individual extreme events. We find also that eruptive flares (with accompanying CMEs) have larger volumes V, longer flare durations T, higher EUV and soft X-ray fluxes, and somewhat larger diffusion coefficients κ than confined flares (without CMEs)

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2011

Diffusion dynamics of small molecules from mesoporous silicon films by real-time optical interferometry

Time-dependent laser reflectometry measurements are presented as a means to rigorously characterize analyte diffusion dynamics of small molecules from mesoporous silicon (PSi) films for drug delivery and membrane physics applications. Calculations based on inclusion of a spatially and temporally dependent solute concentration profile in a one-dimensional Fickian diffusion flow model are performed to determine the diffusion coefficients for the selected prototypical polar species, sucrose (340 Da), exiting from PSi films. The diffusion properties of the molecules depend on both PSi pore size and film thickness. For films with average pore diameters between 10-30 nm and film thicknesses between 300-900 nm, the sucrose diffusion coefficient can be tuned between approximately 100 and 550 {mu}m{sup 2}/s. Extensions of the real-time measurement and modeling approach for determining the diffusivity of small molecules that strongly interact with and corrode the internal surfaces of PSi films are also discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Dependence of radiation belt simulations to assumed radial diffusion rates tested for two empirical models of radial transport

Radial diffusion is one of the dominant physical mechanisms that drives acceleration and loss of the radiation belt electrons, which makes it very important for nowcasting and forecasting space weather models. In this paper, we investigate the sensitivity of the two parameterizations of the radial diffusion of Brautigam and Albert (2000) and Ozeke et al. (2014) on long-term radiation belt modeling using the Versatile Electron Radiation Belt (VERB). Following Brautigam and Albert (2000) and Ozeke et al. (2014), we first perform 1-D radial diffusion simulations. Comparison of the simulation results with observations shows that the difference between simulations with either radial diffusion parameterization is small. To take into account effects of local acceleration and loss, we perform 3-D simulations, including pitch angle, energy, and mixed diffusion. We found that the results of 3-D simulations are even less sensitive to the choice of parameterization of radial diffusion rates than the results of 1-D simulations at various energies (from 0.59 to 1.80 MeV). This result demonstrates that the inclusion of local acceleration and pitch angle diffusion can provide a negative feedback effect, such that the result is largely indistinguishable simulations conducted with different radial diffusion parameterizations. Finally, we also perform a number of sensitivity tests by multiplying radial diffusion rates by constant factors and show that such an approach leads to unrealistic predictions of radiation belt dynamics.

54 ENVIRONMENTAL SCIENCES↗