Simulation Of Diffusion Research Articles

Simulation and prediction of sulfamethazine migration, transformation and risk diffusion during cross-media infiltration from surface water to groundwater driven by dynamic water level: Machine learning coupled HYDRUS-GMS model

Seasonal water level fluctuations in rivers significantly influenced the cross-media migration, transformation, and risk diffusion of antibiotics from the vadose zone into groundwater. This study developed a coupled model integrating machine learning (ML) with HYDRUS-3D and GMS to accurately predict sulfamethazine migration under dynamic water levels. The predictive accuracy (E≥0.98) of this ML-HYDRUS-GMS model was enhanced by accounting for seasonal water level fluctuations and biogeochemical variability. Significant seasonal differences presented with sulfamethazine diffusion in the vadose zone with the migration rate decreased from 0.06 m/d to 0.02 m/d with the transition from wet to dry seasons. After 6 years of infiltration, it reached groundwater, where lateral migration rates, influenced by seasonal flow variations, were 0.12 m/d in the wet season and decreased to 0.07 m/d in the dry season, with a diffusion range extending to 217 m over 100 years. This discrepant continuous filtration of sulfamethazine and the succession of metabolic pathways induced toxicity range to expand by 65.6 m and the risk to increase to warning level. Sulfamethazine underwent oxidative breakdown in aerobic vadose zone conditions, while anaerobic groundwater conditions led to hydrogenation and reduction, increasing its migration distance.

Calculation and application research on real-time source term diffusion in NPP auxiliary building under accident circumstances

Abstract In the light of radioactive material leakage (due to containment bypass or failure) to the auxiliary building and its service compartments under severe accident circumstances, key techniques related to accident source terms in the nuclear emergency building were researched. During the research, the source-term diffusion and migration patterns were simulated in the building compartments, including the simulation of the gradual diffusion and decay process (driven by circulating air) of fission-derived gases and aerosol toward each compartment. Besides that, by taking a M310 unit at Fangjiashan NPP as the application object, the scenarios of initial accidents of LB/MB/SB-LOCA, MSLB and SGTR were chosen to establish a real-time diffusion calculation model for in-building radioactive source terms under nuclear accident circumstances. While considering the circumstances before and after being intervened by accident mitigation measures, the concentration distribution of radionuclides in the auxiliary building and personnel total-exposure radiation dose rate were quickly assessed online, and a basis was provided for the visualization of radiation dosage and the assessment of received radiation dosage and injury & death hazards during personnel activities outside the main control room.

Particle-Laden Fluid on Flow Maps

We propose a novel framework for simulating ink as a particle-laden flow using particle flow maps. Our method addresses the limitations of existing flow-map techniques, which struggle with dissipative forces like viscosity and drag, thereby extending the application scope from solving the Euler equations to solving the Navier-Stokes equations with accurate viscosity and laden-particle treatment. Our key contribution lies in a coupling mechanism for two particle systems, coupling physical sediment particles and virtual flow-map particles on a background grid by solving a Poisson system. We implemented a novel path integral formula to incorporate viscosity and drag forces into the particle flow map process. Our approach enables state-of-the-art simulation of various particle-laden flow phenomena, exemplified by the bulging and breakup of suspension drop tails, torus formation, torus disintegration, and the coalescence of sedimenting drops. In particular, our method delivered high-fidelity ink diffusion simulations by accurately capturing vortex bulbs, viscous tails, fractal branching, and hierarchical structures.

Simulation of hydrogen leakage and diffusion in an enclosed garage of mixed parking of fuel-cell vehicles

The numerical simulation is used to investigate the spread and diffusion behaviors of hydrogen leaks during mixed parking of two different models of fuel cell vehicle in a closed garage. Simultaneously, the impact of different adjacent vehicle models on hydrogen diffusion behaviors is also investigated. It is shown that for vehicles with a higher chassis, hydrogen diffuses rapidly along the ground after striking it. Conversely, vehicle with a lower chassis exhibit slower diffusion of hydrogen along the ground, owing to the limitations imposed by the chassis height. The development of the flammable zones caused by hydrogen leakage can be clearly distinguished into three stages. Each stage is influenced by distinct factors, including the model of leaking vehicle, the model of adjacent vehicles, and the presence of larger vehicles nearby. Notably, the chassis height has a significant impact on the volume of flammable zones, with vehicles possessing lower chassis exhibiting larger volumes. For a given vehicle model, parking near a fuel cell vehicle of the same model facilitates hydrogen diffusion more effectively than parking near a vehicle of a different model.

Geometric tortuosity at invaginating rod synapses slows glutamate diffusion and shapes synaptic responses: insights from anatomically realistic Monte Carlo simulations.

At the first synapse in the vertebrate retina, rod photoreceptor terminals form deep invaginations occupied by multiple second-order rod bipolar and horizontal cell (RBP and HC) dendrites. Synaptic vesicles are released into this invagination at multiple sites beneath an elongated presynaptic ribbon. We investigated the impact of this complex architecture on the diffusion of synaptic glutamate and activity of postsynaptic receptors. We obtained serial electron micrographs of mouse retina and reconstructed four rod terminals along with their postsynaptic RBP and HC dendrites. We incorporated these structures into an anatomically realistic Monte Carlo simulation of neurotransmitter diffusion and receptor activation. We compared passive diffusion of glutamate in these realistic structures to existing, geometrically simplified models of the synapse and found that glutamate exits anatomically realistic synapses ten times more slowly than previously predicted. By comparing simulations with electrophysiological recordings, we modeled synaptic activation of EAAT5 glutamate transporters in rods, AMPA receptors on HC dendrites, and metabotropic glutamate receptors (mGluR6) on RRBP dendrites. Our simulations suggested that ~3,000 EAAT5 transporters populate the rod presynaptic membrane and that, while uptake by surrounding glial Müller cells retrieves much of the glutamate released by rods, binding and uptake by EAAT5 influences RBP response kinetics. The relatively long lifetime of glutamate within the cleft allows mGluR6 on RBP dendrites to temporally integrate the steady stream of vesicles released at this synapse in darkness. Glutamate's tortuous diffusional path through realistic synaptic geometry confers quantal variability, as release from nearby ribbon sites exerts larger effects on RBP and HC receptors than release from more distant sites. While greater integration may allow slower sustained release rates, added quantal variability complicates the challenging task of detecting brief decreases in release produced by rod light responses at scotopic threshold.

Revealing membrane integrity and cell size from diffusion kurtosis time dependence.

The nonmonotonic dependence of diffusion kurtosis on diffusion time has been observed in biological tissues, yet its relation to membrane integrity and cellular geometry remains to be clarified. Here we establish and explain the characteristic asymmetric shape of the kurtosis peak. We also derive the relation between the peak time , when kurtosis reaches its maximum, and tissue parameters. The peak shape and its position qualitatively follow from the adiabatic extension of the Kärger model onto the case of intra-cellular diffusivity time-dependence. This intuition is corroborated by the effective medium theory-based calculation, as well as by Monte Carlo simulations of diffusion and exchange in randomly and densely packed spheres for various values of permeability, cell fractions and sizes, and intrinsic diffusivity. We establish that is proportional to the geometric mean of two characteristic time scales: extra-cellular correlation time (determined by cell size) and intra-cellular residence time (determined by membrane permeability). When exchange is barrier-limited, the peak shape approaches a universal scaling form determined by the ratio . Numerical simulations and theory provide an interpretation of a specific feature of kurtosis time-dependence, offering a potential biomarker for in vivo evaluation of pathology by disentangling the functional (permeability) and structural (cell size) integrity in tissues. This is relevant as the time-dependent diffusion cumulants are sensitive to pathological changes in membrane integrity and cellular structure in diseases, such as ischemic stroke, tumors, and Alzheimer's disease.

Multiscale simulation of liquid chromatography: Effective diffusion in macro–mesoporous beds and the B-term of the plate height equation

We performed multiscale simulations of analyte sorption and diffusion in hierarchical porosity models of monolithic silica columns for reversed-phase liquid chromatography to investigate how the mean mesopore size of the chromatographic bed and the analyte-specific interaction with the chromatographic interface influence the analyte diffusivity at various length scales. The reproduced experimental conditions comprised the retention of six analyte compounds of low to moderate solute polarity on a silica-based, endcapped, C18 stationary phase with water‒acetonitrile and water–methanol mobile phases whose elution strength was varied via the volumetric solvent ratio. Detailed information about the analyte-specific interfacial dynamics received from molecular dynamics simulations was incorporated through appropriate linker schemes into Brownian dynamics diffusion simulations in three hierarchical porosity models received from physical reconstructions of silica monoliths with a mean macropore size of 1.23 µm and mean mesopore sizes of 12.3, 21.3, or 25.7 nm. The mean mesopore size was found to have a similar influence on the effective mesopore diffusivity as the analyte polarity and the mobile-phase elution strength, which together determine the analyte residence time on a column. A smaller mesopore size attenuated the increase of the effective mesopore diffusivity with increasing mobile-phase elution strength significantly. The effective bed diffusivity was limited by the analyte residence time rather than by morphological details of the mesopore space. The stronger an analyte was retained by the chromatographic interface inside the mesopores, the slower became the mass transfer between the pore space hierarchies and the lower was the effective bed diffusivity. The B-terms of the plate height equation were finally generated with the bed diffusivities and phase-based retention factors derived from the hierarchical porosity models using additional information about the stationary-phase limit obtained from the analysis of analyte–bonded phase contacts. The B-terms highlight analyte- and mobile phase-specific behavior relevant to isocratic and gradient elution conditions in chromatographic practice. In particular, U-shaped B-term curves are observed due to the dominating contribution of the retention factor and the bed diffusivity to the B-term at low and high elution strength of the mobile phase, respectively.

The impact of fuel cell vehicle exhaust grille shape under natural ventilation on hydrogen leakage and diffusion

The rapid progression of hydrogen fuel cell vehicles has brought forth various challenges, primarily the frequent occurrence of hazardous incidents stemming from hydrogen leakage and diffusion. Consequently, there is a growing emphasis on hydrogen safety, leading to the development of stricter standards and regulations to mitigate the associated safety risks. Research on the design of exhaust port structures to facilitate the safe diffusion of hydrogen after leakage in diverse scenarios has become increasingly significant. This study examines the impact of exhaust grille shapes on hydrogen leakage and diffusion phenomena within the hydrogen storage compartment of fuel cell vehicles under natural ventilation conditions. Five distinct porous grille shapes were examined: rectangular, circular, square, rhombic, and hexagonal grilles. Numerical simulations of hydrogen leakage and diffusion within the compartment were conducted using Cradle scFLOW software. The effectiveness of the different grille shapes was assessed using several criteria, including average hydrogen molar fraction, pressure drop (indicative of negative pressure regions), density, and Richardson number. Overall, the rectangular grille exhibited superior performance in facilitating hydrogen venting.

A Two-Step Dry Etching Model for Non-Uniform Etching Profile in Gate-All-Around Field-Effect Transistor Manufacturing.

The Gate-All-Around Field-Effect Transistor (GAAFET) is proposed as a successor to Fin Field-Effect Transistor (FinFET) technology to increase channel length and improve the device performance. The GAAFET features a complex multilayer structure, which complicates the manufacturing process. One of the most critical steps in GAAFET fabrication is the selective lateral etching of the SiGe layers, essential for forming the inner-spacer. Industry commonly encounters a non-uniform etching profile during this step. In this paper, a continuous two-step dry etching model is proposed to investigate the mechanism behind the formation of the non-uniform profiles. The model consists of four modules: anisotropic etching simulation, Ge atom diffusion simulation, Si/SiGe etch selectivity calculation and SiGe selective etching simulation. By calibrating and verifying this model with experimental data, the edge rounding and gradient etching rates along the sidewall surface are successfully simulated. Based on further examination of the influence of chamber pressure on the profile using this model, the inner-spacer shape is improved experimentally by appropriately reducing the chamber pressure. This work aims to provide valuable insights for etching process recipes in advanced GAAFETs manufacturing.

Modeling and simulation of technological innovation diffusion of high-performance construction materials in transportation engineering

This study focuses on the diffusion process of technological innovations in high-performance construction materials (HPCMs) within the field of transportation engineering. The aim is to explore the impact of various factors on this process through modeling and simulation. The research employs a multi-agent modeling approach to construct a simulation model of the diffusion of technological innovations of HPCMs among firms and owners. It analyzes the impact of firms’ strategy choices, knowledge sharing, and government policies on the diffusion of technological innovations of HPCMs. Through simulation experiments, this study reveals the impact of the proportion of firms choosing followership or innovation strategies on the efficiency of technology diffusion within complex networks, as well as the double-edged effect of knowledge sharing. Additionally, the findings indicate that adjustments of government policies at different stages of diffusion have a significant impact on market dynamics. This study provides theoretical foundations and practical recommendations for promoting the research and application of high-performance construction materials, thereby advancing green and sustainable development in transportation engineering.

Diffusion of Ge Donors in β‐Ga2O3

Diffusion of Ge donors in β‐Ga2O3 is studied using a combination of secondary‐ion mass spectrometry, diffusion simulations, and first‐principles calculations, and compared to previous studies on Sn diffusion. Ge is implanted into (01)‐oriented samples and annealed at temperatures from 900 to 1050 °C for a total of 8 h. From previous first‐principles calculations, Sn is predicted to diffuse via the formation of a mobile complex with VGa that migrates through a sequence of exchange and rotation jumps. Herein, it is similarly predicted that Ge diffusion is mediated by VGa. However, the microscopic mechanism differs, as Ge can diffuse more easily through exchange combined with complex dissociation, rather than rotational jumps. This is explained by the difference in Ga‐site preference of Ge compared to Sn, and the three‐split mechanism that enables low migration barriers for VGa. The dissociation mechanism leads to a considerably faster transport for Ge as compared to Sn. The experimentally obtained Ge diffusion profiles are successfully fitted using a reaction–diffusion model based on the predicted diffusion mechanism, yielding a migration barrier of 2.5 ± 0.2 eV for the complex. The 2.72 eV obtained from first‐principles calculations is in good agreement with this value.

The not-so-forbidden triad: Evaluating the assumptions of the Strength of Weak Ties

Abstract The Strength of Weak Ties is among the most influential social theories of the past 50 years. However, its prediction that weak ties are especially useful for obtaining novel information is sometimes not supported. To understand why, I investigate whether social networks typically satisfy the theory’s assumptions, and whether the theory’s prediction is robust to violations of its assumptions. First, examining a diverse corpus of 56 empirical social networks, I show that empirical social networks (nearly) satisfy some but not all of the theory’s assumptions. Second, using a simulation of information diffusion, I show that the predicted utility of weak ties is not robust to violations of these assumptions. When the assumptions of the theory are violated, as is common in social networks, access to novel information depends on bridging ties, regardless of their strength. Moreover, when they exist, strong bridges (i.e., bridges with high bandwidth) are more useful than weak bridges (i.e., bridges with low bandwidth). I conclude by recommending that research applying this theory should first consider whether its assumptions are satisfied, and that a tie’s strength and bridgeness should be measured and modeled independently.

The Impact of the 8–10 March 2012 Geomagnetic Storm on Inner Zone Protons as Measured by Van Allen Probes

AbstractThe Relativistic Electron Proton Telescope (REPT) instrument on the Van Allen Probes observed a double‐peaked inner zone proton population throughout the 7 year lifetime of the mission. M. Hudson et al. (2023) showed that a strong SEP event accompanied by a CME‐shock in early March 2012 provided the Solar Energetic Proton (SEP) source for the higher L trapped proton population, which then diffused radially inward to be observed by REPT at . The study followed trajectories of SEP protons launched isotropically from a sphere at 7 Re for 2.5 hr in fields calculated by the LFM‐RCM global MHD model, which includes electric fields needed to model the transport and trapping of the protons by the shock, and then a radial diffusion simulation was run for 2 years using the result from the test‐particle simulation as the initial condition. The simulation result was compared with REPT measurement in November 2013 and showed reasonable agreement. However, the simulation overestimated the Phase Space Density by a factor of four due to lack of field line curvature scattering during the storm in the model. In this study, a test‐particle simulation is performed for 2 days following the injection and trapping of protons in March 2012 using TS05 fields to simulate the field line curvature scattering of the trapped SEP due to the buildup of the ring current during the geomagnetic storm. The resulting sample distribution was then weighted using the flux at the end of the two‐hour MHD‐test particle simulation. A radial diffusion simulation is then run using the initial profile that included the loss effect, with improved comparison with REPT measurements after 2 years.

A quick parameter configuration tool for SCHISM’s ocean transport simulation of radioactive materials

Abstract A quick tool capable of processing output files generated by the SCHISM particle tracking module has been developed to handle complex data processing procedures and conduct parameter sensitivity testing. This tool performs calculations, considering the influence of half-lives and partition coefficients, for the conversion of activity concentrations, plots particle diffusion trajectories, conducts statistical analyses of regional particle amounts, and presents activity concentration within the defined area. Using the IAEA MODARIA program as an example, this study investigates the transport of radioactive 137Cs in the ocean following the Fukushima accident on March 11, 2011. A three-year diffusion simulation was conducted by incorporating data such as ocean currents, wind fields, and tides. The calculated results demonstrate a high level of consistency with measurements, and the calculated results in the low activity concentration fall within the variability range reported in the literature.

Overcoming the Energy vs Power Dilemma in Commercial Li-Ion Batteries via Sparse Channel Engineering.

Improvements in both the power and energy density of lithium-ion batteries (LIBs) will enable longer driving distances and shorter charging times for electric vehicles (EVs). The use of thicker and denser electrodes reduces LIB manufacturing costs and increases energy density characteristics at the expense of much slower Li-ion diffusion, higher ionic resistance, reduced charging rate, and lower stability. Contrary to common intuition, we unexpectedly discovered that removing a tiny amount of material (<0.4 vol %) from the commercial electrodes in the form of sparsely patterned conical pores greatly improves LIB rate performance. Our research revealed that upon commercial production of high areal capacity electrodes, a very dense layer forms on the electrode surface, which serves as a bottleneck for Li-ion transport. The formation of sparse conical pore channels overcomes such a limitation, and the facilitated ion transport delivers much higher power without reduction in the practically attainable energy. Diffusion and finite element method-based simulations provide deep insights into the fundamentals of ion transport in such electrode designs and corroborate the experimental findings. The reported insights provide a major thrust to redesigning automotive LIB electrodes to produce cheaper, longer driving range EVs that retain fast charging capability.

Multi‐Scale Simulation of Reverse‐Bias Breakdown in All‐Perovskite Tandem Photovoltaic Modules under Partial Shading Conditions

Herein, a multi‐scale simulation approach to quantify the impact of nonuniformities in cell‐level performance on the photovoltaic characteristics of monolithically interconnected large‐area all‐perovskite tandem modules under partial shading conditions is presented, addressing a crucial aspect of the up‐scaling challenge for this promising photovoltaic technology. To this end, current–voltage characteristics of small‐area all‐perovskite tandem solar cells are obtained for dark and illuminated cases from a calibrated optoelectronic device model using drift–diffusion simulation coupled to a quantum transport formalism for the band‐to‐band tunneling underlying the Zener breakdown. These current–voltage curves are computed for varying density of mobile ions and subsequently used as local 1D coupling laws connecting the 2D electrodes in a quasi‐3D large‐area finite‐element simulation approach that then provides the module characteristics under consideration of spatial variation in active area quality related to mobile ion density. The simulation reveals the appearance of localized current hot spots for the case where the shaded cell is strongly reverse biased.

Isotopic fractionation of methane on Mars via diffusive separation in the subsurface

Many processes have been identified in the Martian subsurface which may produce or release methane that eventually can be emitted into the atmosphere. Given the wide range of isotopic values for source carbon reported on Mars and the importance of atmospheric methane isotopologues as a tracer for subsurface processes, it is critical to quantify the level of isotopic fractionation that can occur during subsurface transport. On Earth, isotopic fractionation occurs when methane transport is dominated by Knudsen diffusion through small pores. However, unlike the Earth, on Mars the low atmospheric pressure and commensurate longer mean free path suggest that most subsurface transport of methane occurs in the Knudsen regime, amplifying this effect. Here, we report on simulations of diffusion through the martian subsurface and report on the level of fractionation that would be expected under two end-member scenarios. For Interplanetary Dust Particles (IDPs) incorporated in near-surface sediments in which methane is released quickly upon generation, atmospheric emissions of methane are expected to be representative of the reservoir isotopic ratio. However, for deeper sources in which methane accumulates as trapped gas, subsurface transport will result in depletions of 13CH4 compared to reservoir concentrations by approximately −31‰. Over time, both the reservoir and the emitted gas will evolve to become isotopically enriched in 13CH4 compared to a standard of constant isotopic ratio. This necessitates temporal measurements of emitted methane to understand the δ13C of the reservoir and depth of the release, preferably with hourly or better frequency. Finally, a seasonal cycle in δ13C with an amplitude of 5.3‰ is expected with adsorption acting to create small temporary reservoirs that are filled and emptied over the year by the subsurface thermal wave. This effect may provide a way to probe near-surface thermophysical properties.

3D Bioprinting of Engineered Living Materials with Extracellular Electron Transfer Capability for Water Purification.

Attention is widely drawn to the extracellular electron transfer (EET) process of electroactive bacteria (EAB) for water purification, but its efficacy is often hindered in complex environmental matrices. In this study, the engineered living materials with EET capability (e-ELMs) were for the first time created with customized geometric configurations for pollutant removal using three-dimensional (3D) bioprinting platform. By combining EAB and tailored viscoelastic matrix, a biocompatible and tunable electroactive bioink for 3D bioprinting was initially developed with tuned rheological properties, enabling meticulous manipulation of microbial spatial arrangement and density. e-ELMs with different spatial microstructures were then designed and constructed by adjusting the filament diameter and orientation during the 3D printing process. Simulations of diffusion and fluid dynamics collectively showcase internal mass transfer rates and EET efficiency of e-ELMs with different spatial microstructures, contributing to the outstanding decontamination performances. Our research propels 3D bioprinting technology into the environmental realm, enabling the creation of intricately designed e-ELMs and providing promising routes to address the emerging water pollution concerns.

Data-driven wall modeling for LES involving non-equilibrium boundary layer effects

PurposeWall-modeled large eddy simulation (LES) is a practical tool for solving wall-bounded flows with less computational cost by avoiding the explicit resolution of the near-wall region. However, its use is limited in flows that have high non-equilibrium effects like separation or transition. This study aims to present a novel methodology of using high-fidelity data and machine learning (ML) techniques to capture these non-equilibrium effects.Design/methodology/approachA precursor to this methodology has already been tested in Radhakrishnan et al. (2021) for equilibrium flows using LES of channel flow data. In the current methodology, the high-fidelity data chosen for training includes direct numerical simulation of a double diffuser that has strong non-equilibrium flow regions, and LES of a channel flow. The ultimate purpose of the model is to distinguish between equilibrium and non-equilibrium regions, and to provide the appropriate wall shear stress. The ML system used for this study is gradient-boosted regression trees.FindingsThe authors show that the model can be trained to make accurate predictions for both equilibrium and non-equilibrium boundary layers. In example, the authors find that the model is very effective for corner flows and flows that involve relaminarization, while performing rather ineffectively at recirculation regions.Originality/valueData from relaminarization regions help the model to better understand such phenomenon and to provide an appropriate boundary condition based on that. This motivates the authors to continue the research in this direction by adding more non-equilibrium phenomena to the training data to capture recirculation as well.

Experimental investigation and numerical simulation of chloride diffusion in rubber concrete under dry-wet cycles

Chloride erosion caused by the dry-wet cycles is one of the most significant factors leading to durability problems in concrete structures. In this paper, the diffusion behavior of chloride in rubber concrete with varying rubber content is studied by experimental investigation and numerical simulation based on setting up artificial dry-wet cycles exposure conditions. The determination of chloride concentration in rubber concrete is achieved through chloride concentration titration, and as a result, the surface chloride concentration and the apparent chloride diffusion coefficient are expressed as a function of time, thus providing a theoretical guide for Comsol Multiphysics to perform numerical simulations. The findings indicate that the chloride diffusion behavior in rubber concrete complies with Fick's second law and that rubber can effectively reduce the diffusion rate of chloride in rubber concrete. Furthermore, the surface chloride concentration and apparent chloride diffusion coefficient are fitted with high accuracy according to the experimental data, which ensures the precision of the numerical simulation. In addition, numerical simulation results indicate that the diffusion of chloride in rubber concrete is impeded by the aggregate, that is, chloride diffusion is faster in areas where the local aggregate volume fraction is small. Also, it is evident that the presence of interfacial transition zone (ITZ) negatively affects the resistance of rubber concrete to chloride diffusion.