Simulation Of Diffusive Transport Research Articles

Universal material trends in extraordinary magnetoresistive devices

Extraordinary magnetoresistance (EMR) is a geometric magnetoresistance emerging in hybrid systems typically comprising a high-mobility material and a metal. Due to a field-dependent redistribution of electrical currents in these devices, the electrical resistance at room temperature can increase by 107% when applying a magnetic field of 5 T. Although EMR holds considerable potential for realizing sensitive, all-electronic magnetometers, this potential is largely unmet. A key challenge is that the performance of EMR devices depends very sensitively on variations in a vast parameter space where changes in the device geometry and material properties produce widely different EMR performances. The challenge of navigating in the large parameter space is further amplified by the poor understanding of the interplay between the device geometry and material properties. By systematically varying the material parameters in four key EMR geometries using diffusive transport simulations, we here elucidate this interplay with the aim of finding universal guidelines for designing EMR devices. Common to all geometries, we find that the sensitivity scales inversely with the carrier density, while the MR reaches saturation at low carrier densities. Increasing the mobility beyond 20 000 cm2 Vs−1 is required to observe strong EMR effects at 1 T with the optimal magnetoresistance observed for mobilities between 100 000–500 000 cm2 Vs−1. An interface resistance below cm2 between the constituent materials in the hybrid devices was also found to be a prerequisite for very high magnetoresistances in all geometries. By further simulating several high-mobility materials at room and cryogenic temperatures, we conclude that encapsulated graphene and InSb are amongst the most promising candidates for EMR devices showing high magnetoresistance exceeding 107% below 1 T at room temperature. This study paves the way for understanding how to realize EMR devices with record-high magnetoresistance and high sensitivity for detecting magnetic fields.

Empirically modeled global distribution of magnetospheric chorus amplitude using an artificial neural network

AbstractAccurate knowledge of the global distribution of magnetospheric chorus waves is essential for radiation belt modeling because it provides a direct link to understanding radiation belt losses and acceleration processes. In this paper, we report on newly developed models of the global distribution of chorus amplitudes based on in situ measurements of interplanetary magnetic field (IMF) and solar wind parameters as well as geomagnetic indices using an artificial neural network technique. We find that solar wind speed and IMFBZare the most influential parameters that affect the evolution of the magnetospheric chorus. The variations of chorus amplitudes in the outer (L≥ 7) and in the inner (5 ≤L< 7) regions, respectively, are well correlated with the variations of solar wind speed and IMFBZ. In addition, the solar wind parameter‐based chorus model generally results in a slightly higher correlation between measured and modeled chorus amplitudes than any other models including geomagnetic indices AE,Kp, andDst. The developed model shows that the chorus is amplified near the prenoon sector during the geomagnetically disturbed conditions. With increasing southward IMFBZthe location of peak chorus amplitude moves from the prenoon sector to the midnight sector, which is due to the enhanced electron injection near midnight. We also present a comparison of diffusive transport simulations for radiation belt electrons interacting with two newly developed chorus models, solar wind parameter‐based and geomagnetic index‐based chorus models. The comparison between two models shows that the modeling outside the plasmapause can affect the dynamic even inside the plasmasphere because the populations outside the plasmapause can act as seed population to radiation belt particles inside the plasmapause. One weakness of our chorus modeling is that it is trained during the early phase of solar cycle 24 where very few strong storms occurred. Therefore, our model might not be valid in reproducing the chorus activity under extremely disturbed conditions, which should be updated in the future once chorus measurements for such conditions become available.

Equivalent diffusion coefficient of clay-rich geological formations: comparison between numerical and analytical estimates

Laboratory experiments in rock samples collected from clay-rich formations indicate that the effective molecular diffusion coefficient (D) is a heterogeneous and anisotropic property. Since laboratory measurements of D are representative of a very small volume, upscaling is necessary in order to incorporate these data in large-scale numerical models of diffusive transport. In this work we address the problem of the estimating the equivalent diffusion coefficient (D eq ), in terms of total diffusive flux, in a three-dimensional domain characterized by a heterogeneous and anisotropic spatial distribution of D. D eq was estimated from the results of steady-state diffusive transport simulations through several realizations of the D field. The ensemble averages of D eq from fields with different degrees of heterogeneity and anisotropy were then compared with estimates from analytical upscaling expressions based on stochastic as well as power-averaging approaches. These expressions are largely based on similar expressions developed for calculating the effective hydraulic conductivity in heterogeneous and anisotropic domains. Comparisons showed that stochastic expressions provide accurate estimates of D eq only for fields characterized by low heterogeneity. Within the range of heterogeneity and anisotropy considered, our results showed that a power-averaging expression is very accurate in predicting D eq especially when the parameter p i is estimated through fitting of the numerical results. Nonetheless, the relationship between this parameter and the anisotropy ratio is linear.

A continuum hard-sphere model of protein adsorption

Protein adsorption plays a significant role in biological phenomena such as cell-surface interactions and the coagulation of blood. Two-dimensional random sequential adsorption (RSA) models are widely used to model the adsorption of proteins on solid surfaces. Continuum equations have been developed so that the results of RSA simulations can be used to predict the kinetics of adsorption. Recently, Brownian dynamics simulations have become popular for modeling protein adsorption. In this work a continuum model was developed to allow the results from a Brownian dynamics simulation to be used as the boundary condition in a computational fluid dynamics (CFD) simulation. Brownian dynamics simulations were used to model the diffusive transport of hard-sphere particles in a liquid and the adsorption of the particles onto a solid surface. The configuration of the adsorbed particles was analyzed to quantify the chemical potential near the surface, which was found to be a function of the distance from the surface and the fractional surface coverage. The near-surface chemical potential was used to derive a continuum model of adsorption that incorporates the results from the Brownian dynamics simulations. The equations of the continuum model were discretized and coupled to a CFD simulation of diffusive transport to the surface. The kinetics of adsorption predicted by the continuum model closely matched the results from the Brownian dynamics simulation. This new model allows the results from mesoscale simulations to be incorporated into micro- or macro-scale CFD transport simulations of protein adsorption in practical devices.

Simulation of Diffusive Transport of Radionuclides in the Soil of a Radioactive Waste Disposal Site

The diffusive transport of 137Cs, 90Sr, and 60Co in the clay of a radioactive waste disposal site at PINSTECH was studied to assess the safety of the underlying permeable zone against the release of these radionuclides from buried waste containers in the clay. Diffusion coefficients of these radionuclides were estimated by reservoir to sediment diffusion method via their stable counterparts in a laboratory experiment. A curve-fitting procedure was applied on the measured concentration-time profiles of the reservoir using the one-dimensional solute transport equation with a nonlinear least squares technique. Distribution coefficients were determined in laboratory batch experiments. Diffusive transport simulations were performed with the estimated values of diffusion coefficients and distribution coefficients using the one-dimensional solute transport equation describing Fickian diffusion, equilibrium adsorption, and radioactive decay. The transport simulation results showed that 137Cs, 90Sr, and 60Co will transport distances of 4.33, 3.77, and 1.51 meters, respectively, in the clay before their activity concentrations will drop to clearance levels set by the International Atomic Energy Agency (IAEA), below which the waste is treated as non-radioactive. This showed that concentrations more than clearance levels will not be able to transport to the permeable zone at a minimum depth of seven meters from the ground surface if the waste containers are disposed in a trench below which a clay layer with a thickness of 4.33 meters or more exists.

The diffusive finite state projection algorithm for efficient simulation of the stochastic reaction-diffusion master equation.

We have developed a computational framework for accurate and efficient simulation of stochastic spatially inhomogeneous biochemical systems. The new computational method employs a fractional step hybrid strategy. A novel formulation of the finite state projection (FSP) method, called the diffusive FSP method, is introduced for the efficient and accurate simulation of diffusive transport. Reactions are handled by the stochastic simulation algorithm.

A hierarchical multi-scale method to simulate reactive–diffusive transport in porous media

A time-dependent, hierarchical multi-scale model to simulate reactive–diffusive transport in a 3-dimensional, porous structure, using a combination of molecular dynamics (MD), kinetic Monte-Carlo (KMC) and Monte-Carlo diffusion (MCD) methods has been developed. The parameters that are passed from the models at the lower spatial and temporal scales (MD, KMC) to those at the higher scales (KMC, MCD respectively) are identified. The advantages and disadvantages of the different methods are discussed with respect to reactive–diffusive transport simulations of atoms in porous 3D structures. The model is illustrated by simulating hydrogen transport, reactions, inventory and re-emission from a porous hydrocarbon layer.

MODELING DIFFUSION AND REACTION IN SOILS: VIII. GAS DIFFUSION PREDICTED FROM SINGLE-POTENTIAL DIFFUSIVITY OR PERMEABILTY MEASUREMENTS

Variations of gas diffusivity (ratio of gas diffusion coefficients in soil and free air, DS/D0) with air-filled porosity (ε) influence the transport, degradation, and volatilization of reactive gasses in soil systems. We show that the prediction accuracy of the Penman-Millington-Quirk (PMQ) diffusivity model (introduced in Part VII of this series) is often improved significantly by including as a reference point a measured value of the gas diffusion coefficient (Dfc) at a single soil-water potential, ψ, between −100 and −500 cm H20. As a result, the root mean square error of prediction was reduced by 45% (based on individual DS/D0 measurements) and by ≥ 65% (based on mean values of 6 to 9 closely-spaced DS/D0 measurements) for undisturbed soil samples from six differently textured surface soils. Gas permeability is measured more easily and more rapidly than gas diffusivity, and we suggest that a measured value of gas permeability (kfc) at a single soil-water potential, combined with a tortuous tube permeability model and the PMQ diffusivity model, can also be used to improve DS/D0 predictions. For practical use, a relation between the equivalent tube radius (rfc) at ψ = −100 cm H20 and clay content, taken to represent the soil structure-forming ability, is proposed for surface soils. Gas diffusive transport simulations using the DARC numerical model (Part I of this series) verified that the inclusion of a single (Dfc or kfc) measurement in the DS/D0(ε) predictions can improve simulation accuracy significantly. Dfc- and kfc-based diffusivity models require limited measurement effort and seem promising for site-specific simulations of gas diffusion and reaction.

Short Communication: A numerical method for diffusive transport with moving boundaries and discontinuous material properties

A method for the numerical simulation of diffusive transport with moving boundaries is developed and tested. The variable domain is mapped onto a fixed region, which introduces a term of convective form to the transformed governing equation. The resulting convection/diffusion equation is solved by a finite-difference method. An 'Immersed Interface' Method (IIM) is introduced in order to retain second-order accuracy near discontinuities in material properties, where the solution is not smooth. The method performs well in benchmark calculations against an analytical solution. The IIM scheme is capable of treating a strong discontinuity in the gradient, and it is readily extended to two or three dimensions. The methods are illustrated through a calculation for the temperature profile in a growing continental ice sheet, in which the thermal properties are discontinuous at the rock/ice interface.

Short Communication: A numerical method for diffusive transport with moving boundaries and discontinuous material properties

A method for the numerical simulation of diffusive transport with moving boundaries is developed and tested. The variable domain is mapped onto a fixed region, which introduces a term of convective form to the transformed governing equation. The resulting convection/diffusion equation is solved by a finite-difference method. An ‘Immersed Interface’ Method (IIM) is introduced in order to retain second-order accuracy near discontinuities in material properties, where the solution is not smooth. The method performs well in benchmark calculations against an analytical solution. The IIM scheme is capable of treating a strong discontinuity in the gradient, and it is readily extended to two or three dimensions. The methods are illustrated through a calculation for the temperature profile in a growing continental ice sheet, in which the thermal properties are discontinuous at the rock/ice interface. © 1997 by John Wiley & Sons, Ltd.