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At least 955 records · Page 53

Evidence for superionic H 2 O and diffusive He–H 2 O at high temperature and high pressure

In this work, we present the evidence of superionic phase formed in H 2 O and, for the first time, diffusive H 2 O–He phase, based on time-resolved x-ray diffraction experiments performed on ramp-laser-heated samples in diamond anvil cells. The diffraction results signify a similar bcc-like structure of superionic H 2 O and diffusive He–H 2 O, while following different transition dynamics. Based on time and temperature evolution of the lattice parameter, the superionic H 2 O phase forms gradually in pure H 2 O over the temperature range of 1350–1400 K at 23 GPa, but the diffusive He–H 2 O phase forms abruptly at 1300 K at 26 GPa. We suggest that the faster dynamics and lower transition temperature in He–H 2 O are due to a larger diffusion coefficient of interstitial-filled He than that of more strongly bound H atoms. This conjecture is then consistent with He disordered diffusive phase predicted at lower temperatures, rather than H-disordered superionic phase in He–H 2 O.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Investigations on a fuzzy process: effect of diffusion on calibration and particle identification in Liquid Argon Time Projection Chambers

Ionization electron diffusion in Liquid Argon Time Projection Chambers (LArTPCs) has typically been considered at the detector design stage, but little attention has been given to its effects on calibration and particle identification. We use a GEANT4-based simulation to study how diffusion impacts these techniques, and give consideration to how this effect is simulated. We find that diffusion can cause a drift-dependent bias to both the median and Most Probable Value (MPV) of dQ/dx distributions. The bias is estimated to be ~2.5% (median) and ~5.0% (MPV) for typical maximum drift times in currently running LArTPCs before adding detector specific considerations such as electric field non-uniformities. This information indicates that these metrics should not be used for calibration without care, contrary to the conventional wisdom. The impact of diffusion on the ability of LArTPCs to separate muons and protons is small, and not expected to pose any problems in future detectors. Diffusion may however be a significant source of systematic uncertainty when separating particles of more similar masses (muons and pions, kaons and protons). Separation of such populations may be improved by implementation of a drift-time dependent particle identification.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Escape and finite-size scaling in diffusion-controlled annihilation

In this paper, we study diffusion-controlled single-species annihilation with a finite number of particles. In this reaction-diffusion process, each particle undergoes ordinary diffusion, and when two particles meet, they annihilate. We focus on spatial dimensions d>2 where a finite number of particles typically survive the annihilation process. Using scaling techniques we investigate the average number of surviving particles, M, as a function of the initial number of particles, N. In three dimensions, for instance, we find the scaling law M ~ N 1/3 in the asymptotic regime N»1. We show that two time scales govern the reaction kinetics: the diffusion time scale, T ~ N 2/3 , and the escape time scale, τ ~ N 4/3 . The vast majority of annihilation events occur on the diffusion time scale, while no annihilation events occur beyond the escape time scale.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Superresolution Diffuse Optical Imaging by Localization of Fluorescence

The multiple scattering of light presents major challenges in realizing useful in vivo imaging at tissue depths of more than about one millimeter, where many answers to health questions lie. Visible through near-infrared photons can be readily and safely detected through centimeters of tissue; however, limited information is available for image formation. One strategy for obtaining images is to model the photon transport and a simple incoherent model is the diffusion equation approximation to the Boltzmann transport equation. Such an approach provides a prediction of the mean intensity of heavily scattered light and hence provides a forward model for optimization-based computational imaging. While diffuse optical imaging methods have received substantial attention, they remain restricted in terms of resolution because of the loss of high-spatial-frequency information that is associated with the multiple scattering of photons. Consequently, only relatively large inhomogeneities, such as tumors or organs in small animals, can be effectively resolved. We introduce a superresolution imaging approach based on point localization in a diffusion framework that enables over two orders of magnitude improvement in the spatial resolution of diffuse optical imaging. The method is demonstrated experimentally by localizing a fluorescent inhomogeneity in a highly scattering slab and characterizing the localization uncertainty. The approach allows imaging through centimeters of tissue with a resolution of tens of microns, thereby enabling cells or cell clusters to be resolved. More generally, this high-resolution imaging approach could be applied with any physical transport or wave model and hence to a broad class of physical problems. Finally, paired with a suitable optical contrast mechanism, as can be realized with targeted fluorescent molecules or genetically modified animals, superresolution diffuse imaging should open alternative dimensions for in vivo applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Multicomponent mutual diffusion in the warm, dense matter regime

In this work, we present the formulation, simulations, and results for multicomponent mutual diffusion coefficients in the warm, dense matter regime. While binary mixtures have received considerable attention for mass transport, far fewer studies have addressed ternary and more complex systems. We therefore explicitly examine ternary systems utilizing the Maxwell-Stefan formulation that relates diffusion to gradients in the chemical potential. Onsager coefficients then connect the macroscopic diffusion to microscopic particle motions, evinced in trajectories characterized by positions and velocities, through various autocorrelation functions (ACFs). These trajectories are generated by molecular dynamics (MD) simulations either through the Born-Oppenheimer approximation, which treats the ions classically and the electrons quantum-mechanically by an orbital-free density-functional theory, or through a classical MD approach with Yukawa pair-potentials, whose effective ionizations and electron screening length derive from quantal considerations. We employ the reference-mean form of the ACFs and determine the center-of-mass coefficients through a simple reference-frame-dependent similarity transformation. The Onsager terms in turn determine the mutual diffusion coefficients. We examine a representative sample of ternary mixtures as a function of density and temperature from those with only light elements (D-Li-C, D-Li-Al) to those with highly asymmetric mass components (D-Li-Cu, D-Li-Ag, H-C-Ag). We also follow trends in the diffusion as a function of number concentration and evaluated the efficacy of various approximations such as the Darken approximation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Protein drift-diffusion dynamics and phase separation in curved cell membranes and dendritic spines: Hybrid discrete-continuum methods

We develop methods for investigating protein drift-diffusion dynamics in heterogeneous cell membranes and the roles played by geometry, diffusion, chemical kinetics, and phase separation. Our hybrid stochastic numerical methods combine discrete particle descriptions with continuum-level models for tracking the individual protein drift-diffusion dynamics when coupled to continuum fields. We show how our approaches can be used to investigate phenomena motivated by protein kinetics within dendritic spines. The spine geometry is hypothesized to play an important biological role regulating synaptic strength, protein kinetics, and self-assembly of clusters. We perform simulation studies for model spine geometries varying the neck size to investigate how phase-separation and protein organization is influenced by different shapes. We also show how our methods can be used to study the roles of geometry in reaction-diffusion systems including Turing instabilities. Furthermore, our methods provide general approaches for investigating protein kinetics and drift-diffusion dynamics within curved membrane structures.

97 MATHEMATICS AND COMPUTING↗

Techniques for improved statistical convergence in quantification of eddy diffusivity moments

While recent approaches, such as the macroscopic forcing method (MFM) or Green's function-based approaches, can be used to compute Reynolds-averaged Navier-Stokes closure operators using forced direct numerical simulations, MFM can also be used to directly compute moments of the effective nonlocal and anisotropic eddy diffusivities. The low-order spatial and temporal moments contain limited information about the eddy diffusivity but are often sufficient for quantification and modeling of nonlocal and anisotropic effects. However, when using MFM to compute eddy diffusivity moments, the statistical convergence can be slow for higher-order moments. In this work, we demonstrate that using the same direct numerical simulation (DNS) for all forced MFM simulations improves statistical convergence of the eddy diffusivity moments. We present its implementation in conjunction with a decomposition method that handles the MFM forcing semianalytically and allows for consistent boundary condition treatment, which we develop for both scalar and momentum transport. We demonstrate that for a two-dimensional Rayleigh-Taylor instability case study, using the same DNS for all forced MFM simulations results in convergence with 𝒪⁡(100) simulations rather than 𝒪⁡(1000) simulations. In conclusion, we then demonstrate the impacts of improved convergence on the quantification of the eddy diffusivity.

general physics↗

Random Walks With Tweedie: A Unified View of Score-Based Diffusion Models [In the Spotlight]

We present a concise derivation for several influential score-based diffusion models that relies on only a few textbook results. Diffusion models have recently emerged as powerful tools for generating realistic, synthetic signals—particularly natural images—and often play a role in state-of-the-art algorithms for inverse problems in image processing. While these algorithms are often surprisingly simple, the theory behind them is not, and multiple complex theoretical justifications exist in the literature. Here, in this study, we provide a simple and largely self-contained theoretical justification for score-based diffusion models that is targeted towards the signal processing community. This approach leads to generic algorithmic templates for training and generating samples with diffusion models. We show that several influential diffusion models correspond to particular choices within these templates and demonstrate that alternative, more straightforward algorithmic choices can provide comparable results. This approach has the added benefit of enabling conditional sampling without any likelihood approximation.

97 MATHEMATICS AND COMPUTING↗

Matrix Diffusion Controls Mountain Hillslope Groundwater Ages and Inferred Storage Dynamics

Groundwater age distributions provide fundamental insights on coupled water and biogeochemical processes in mountain watersheds. Field-based studies have found mixtures of young and old-aged groundwater in mountain catchments underlain by bedrock; yet, the processes that dictate these groundwater age distributions are poorly understood. In this work, we use the coupled ParFlow-CLM integrated hydrologic and EcoSLIM particle tracking models to simulate groundwater age distributions on a lower montane hillslope in the East River Watershed, Colorado (USA). We develop a convolution-based approach to propagate fracture-matrix diffusion processes to the EcoSLIM advection-dominated age distributions. We compare observed 3 H and 4 He concentrations from two groundwater wells against model predictions that have varying advective transport times and matrix diffusion magnitudes. Based on a Monte Carlo analysis that considers uncertain matrix and fracture parameters, we find that matrix diffusion is needed to jointly predict 3 H and 4 He observations at both wells. The advection-dominated age distributions lack adequate mixing of young and old-aged water to capture the observed co-occurrence of 3 H and 4 He. The model scenario that best matches the 3 H, 4 He, and water level observations when considering both advective flowpath and matrix diffusion mixing processes has a dynamic bedrock groundwater reservoir that is susceptible to considerable storage losses during low-snow periods. This dynamic groundwater system amplifies the need to assimilate deeper bedrock groundwater into watershed hydro-biogeochemical predictions. This work further highlights the importance of considering matrix diffusion when interpreting environmental tracers in bedrock groundwater systems.

54 ENVIRONMENTAL SCIENCES↗

SU-E-T-196: Heat Diffusion Modeling for Digital Holographic Interferometry Dosimetry

Purpose: We have previously demonstrated that with Digital Holographic Interferometry (DHI) 2D spatial calorimetric measurements of high dose rate radiation sources can be obtained. The impact of heat transfer must be considered when undertaking any form of calorimetric measurement, as the radiation induced temperature distributions are subject to degradation due to heat diffusion. Unaccounted for, this limits the accuracy of the approach especially for long delivery times. Methods: 3D modelling of the heat diffusion in water was undertaken, and two different approaches developed to account for this effect. The mathematical framework to describe heat diffusion in 3D was applied, with the differential equations solved numerically using an implicit method. The first approach involved the comparison of the DHI measurements to an independent dose model of the source. The model was forward modeled to account for the heat diffusion during irradiation, allowing a direct comparison to validate the measured results. The second approach involved the correction of the measured data directly, by comparing the temperature distribution of two instances and subtracting the effects of heat diffusion of the first distribution from the second instance. This required the use of the Abel transform to approximate the 3D dose distribution from the 2D DHI results, thus limiting the approach to radiation applications possessing cylindrical symmetry. Results: The first approach resulted in higher accuracy and was more straightforward, but has a major limitation in that the measured results are only able to be utilized in comparison with an independent dose model. The applicability of the second approach is affected by noise in the measurement data and introduces higher uncertainties, but results in higher usability of the final data. Conclusion: Both approaches were implemented, and if used in conjunction would provide the most utility for the interpretation and use of DHI measurements.

07 ISOTOPE AND RADIATION SOURCES↗

Anisotropic diffusion in media with absorbing traps (application to the Keller–Dykhne theorem)

Anisotropic diffusion in multidimensional media with absorbing traps is investigated. It is shown that the diffusion asymptotic forms of the survival probability over long time intervals are determined by a new effective diffusion coefficient. Exact expressions derived for the effective diffusion coefficient generalize the well-known Dykhne–Keller 2D results to the 3D case. In other words, the dynamic diffusion approach is used for obtaining a generalization of the Dykhne–Keller theorem to the 3D case.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Study of Ferrocene Diffusion in Toluene/Tween 20/1-Butanol/Water Microemulsions for Redox Flow Battery Applications

Redox flow batteries (RFBs) possess multiple advantages as a flexible energy storage solution. However, RFB researchers are still facing many challenges in finding an appropriate electrolyte. Microemulsions have recently been proposed as a promising alternative RFB electrolyte because of their ability to accommodate organic redox species with fast electron transfer rates that are not soluble in aqueous phase, while still offering the high conductivity of an aqueous salt electrolyte. In this work, we focused on understanding the transport of ferrocene (Fc) in a toluene/Tween 20/1-butanol/water model microemulsion and studied the compositional influence on Fc diffusion. The results show that Fc redistributes among the oil, surfactant, and water microenvironments, and the corresponding diffusion and partition coefficients are quantified. Thus, a tortuous path diffusion model is proposed to describe the mass transport of Fc to an electrode surface. Diffusion coefficients are also obtained by pulsed-field gradient nuclear magnetic resonance (PFG NMR), while the values for Fc diffusion are substantially higher than those from electrochemical measurements, suggesting that they measure samples in different ways. The current contributions from each microenvironment indicate that the Fc permeability is much higher in the oil, even though the electron transfer reaction is likely occurring in the surfactant.

25 ENERGY STORAGE↗

Ab Initio Insights to Metal Passivation: Diffusion and Defect Formation in Amorphous Zirconia and Alumina

Metal passivation refers to the formation of protective oxide films on metals, which shield them from further corrosion and oxidation, playing a crucial role in maintaining their stability. The mesoscopic Point Defect Model has successfully predicted passivity as a steady state process where oxide growth from oxygen vacancies at the metal/film interface competes with oxide dissolution at the film/environment interface. In this work, informed by the Point Defect Model parameters, we use first-principles calculations to calculate defect formation and atomic diffusion in amorphous materials and correlate these descriptors with the behavior and growth of the oxide film. Focusing on amorphous zirconia and alumina, we demonstrate that defect formation energies exhibit significant variability in amorphous systems. In alumina, vacancies dominate, with cation and anion vacancies occurring at comparable concentrations. Diffusion calculations for stoichiometric amorphous alumina and zirconia, as well as oxygen-deficient zirconia, reveal faster diffusion in the oxygen-deficient case, highlighting the impact of defects on transport. Comparison of calculated self-diffusion coefficients for the dominant defect species with experimentally measured oxide thicknesses shows a clear correlation, suggesting that first-principles-derived diffusivity information can serve as a key descriptor for surface passivation film growth.

Farnell, Mackinzie S. [University of California, B↗

Efficient Reformulation of Solid Phase Diffusion in Electrochemical-Mechanical Coupled Models for Lithium-Ion Batteries: Effect of Intercalation Induced Stresses

Lithium-ion batteries are typically modeled using porous electrode theory coupled with various transport and reaction mechanisms with an appropriate discretization or approximation for the solid phase diffusion within the electrode particle. One of the major difficulties in simulating Li-ion battery models is the need for simulating solid-phase diffusion in the second radial dimension r within the particle. It increases the complexity of the model as well as the computation time/cost to a great extent. This is Particularly true for the inclusion of pressure induced diffusion inside particles experiencing volume change. A computationally efficient representation for solid-phase diffusion is discussed in this paper. The operating condition has a significant effect on the validity, accuracy, and efficiency of various approximations for the solid-phase transport governed by pressure induced diffusion. This paper introduces efficient methods for solid phase reformulation - (1) parabolic profile approach and (2) a mixed order finite difference method for approximating/representing solid-phase concentration variations within the active materials of porous electrodes for macroscopic models for lithium-ion batteries. (C) 2013 The Electrochemical Society. All rights reserved.

De, S↗

A Process for Modelling Diffuse Scattering from Disordered Molecular Crystals, Illustrated by Application to Monoclinic 9-Chloro-10-methylanthracene

Diffuse scattering from a crystal contains valuable information about the two-body correlations (related to the nanoscale order) in the material. Despite years of development, the detailed analysis of single crystal diffuse scattering (SCDS) has yet to become part of the everyday toolbox of the structural scientist. Recent decades have seen the pair distribution function approach to diffuse scattering (in fact, total scattering) from powders become a relatively routine tool. However, analysing the detailed, complex, and often highly anisotropic three-dimensional distribution of SCDS remains valuable yet rare because there is no routine method for undertaking the analysis. At present, analysis requires significant investment of time to develop specialist expertise, which means that the analysis of diffuse scattering, which has much to offer, is not incorporated thorough studies of many compounds even though it has the potential to be a very useful adjunct to existing techniques. This article endeavours to outline in some detail how the diffuse scattering from a molecular crystal can be modelled relatively quickly and largely using existing software tools. It is hoped this will provide a template for other studies. To enable this, the entire simulation is included as deposited material.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Isopycnal Eddy Diffusivities and Critical Layers in the Kuroshio Extension from an Eddying Ocean Model

High spatial resolution isopycnal diffusivities are estimated in the Kuroshio Extension (KE) region (28°–40°N, 120°–190°E) from a global 1/10° Parallel Ocean Program (POP) simulation. The numerical float tracks are binned using a clustering approach. The number of tracks in each bin is thus roughly the same leading to diffusivity estimates that converge better than those in bins defined by a regular geographic grid. Cross-stream diffusivities are elevated in the southern recirculation gyre region, near topographic obstacles and downstream in the KE jet, where the flow has weakened. Along-stream diffusivities, which are much larger than cross-stream diffusivities, correlate well with the magnitudes of eddy velocity. The KE jet suppresses cross-stream mixing only in some longitude ranges. This study estimates the critical layer depth both from linear local baroclinic instability analysis and from eddy phase speeds in the POP model using the Radon transform. The latter is a better predictor of large mixing length in the cross-stream direction. Critical layer theory is most applicable in the intense jet regions away from topography.

54 ENVIRONMENTAL SCIENCES↗

Diffuse Reflectance Spectroscopy and Principal Component Analysis to Retrospectively Determine Production History of Plutonium Dioxide

Diffuse reflectance spectroscopy measurements in the shortwave infrared (930–1600 nm) spectral region were acquired for Pu 2 (C 2 O 4 ) 3 •9H 2 O and its thermal decomposition product, PuO 2 . We analyzed a total of eight PuO 2 samples that were produced at different calcination temperatures (300, 350, 450, 525, 600, 675, 750, and 900 °C). Our goal was to identify spectroscopic fingerprints that could be used to gain retrospective information regarding the production parameters of these important nuclear compounds. The diffuse reflectance spectrum of Pu 2 (C 2 O 4 ) 3 •9H 2 O features several broad bands that currently preclude detailed analysis. However, all PuO 2 samples produced relatively sharp spectral features that got sharper and more intense for samples that were produced at higher calcination temperatures. The electronic band observed at 1433 nm in the diffuse reflectance spectra of PuO 2 was found to be a sensitive indicator of crystallinity; a result that is corroborated by ancillary Raman spectroscopy measurements. Principal component analysis of diffuse reflectance spectra was able to clearly rank and categorize PuO 2 samples based on the calcination temperature that was employed during their production. Thus, we show herein that important retrospective information pertaining to the process history of PuO 2 can be gained through the relatively simplistic combination of diffuse reflectance spectroscopy and principal component analysis. This discovery presents a new method for determining the provenance and process history of PuO 2 and should have an impact in the fields of nuclear forensics and nuclear nonproliferation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Understanding irradiation growth through atomistic simulations: Defect diffusion and clustering in α-zirconium and the influence of alloying elements - 2016-0093

Irradiation-induced structural changes of α-zirconium alloys and in particular the effect of iron were investigated by molecular dynamics simulations using embedded atom potentials derived from first-principles calculations. The simulations revealed that at temperatures between 500 and 600 K self-interstitial atoms (SIAs) diffuse rapidly in a cooperative movement, preferably parallel to basal planes (a directions; ), forming nano-clusters with an extension in and . Vacancies diffuse more slowly than SIAs and remain isolated for a longer period of time. Nano-clusters associated with SIAs cause a pronounced overall expansion in a directions, as well as local strains. Under compressive strain in the c direction, vacancy diffusivity increases in the c direction. In contrast, the diffusivity of SIAs increases in the c direction under a tensile strain in the c direction. SIA nano-clusters are highly mobile within basal planes. Vacancy clusters grow by merging, leading to a contraction in the a direction, compensating for the expansion caused by SIA nano-clusters and possibly contributing to the plateau in growth after the initial rapid expansion. At the onset of breakaway growth, possibly due to stress buildup, the vacancy nano-clusters can condense into c loops, thereby diminishing the compensation effect. The alloying elements iron, nickel, chromium, and niobium liberated from secondary phase particles under irradiation or already in solution are attracted to vacancies and SIAs and are found inside vacancy and SIA loops. The interaction of alloying elements with defect clusters is discussed, with a particular focus on iron. Iron has been found to promote cluster formation in zirconium, and the structures of zirconium-iron clusters have been analyzed. Tin is repelled by SIA clusters and only weakly attracted by vacancies. Niobium impedes the diffusion of SIAs (and therefore may increase annihilation rates with nearby vacancies) and does not destabilize vacancy or SIA clusters. Ab initio calculations of the dimensional and elastic coefficients of the intermetallic phases occurring in secondary phase particles, such as Zr{sub 2}Fe and Zr{sub 3}Fe, are presented, allowing an assessment of local strains in a zirconium matrix. Thus, novel results from extended molecular dynamics simulations provide new insights and contribute to a deeper understanding of the complex mechanisms causing irradiation-induced dimensional changes and the breakaway growth of zirconium alloys. (authors)

36 MATERIALS SCIENCE↗