Stochastic Pore Research Articles

Asymmetry in three-site relaxation exchange NMR.

The asymmetry of peak integrals in 2D relaxation maps of exchange between three sites indicates circular flow between the relaxation sites. This disagrees with the detailed balance according to which the exchange between any pair of sites must be balanced in terms of thermodynamic equilibrium. Confined diffusion of particles jumping randomly on a 2D checkerboard grid to any of their eight neighbor positions and confined gas diffusion were modeled in Monte Carlo simulations to explore the impact of topological constraints on particle exchange between three pools. Both models produce density variations across the pore and reveal that up to 1 % of the molecules move in circular paths between the relaxation pools. This motion is driven by different features of either algorithm. It is silent in terms of thermodynamic equilibrium, confirming that multi-site exchange maps are symmetric in this case. The coherent flux is argued to result from stochastic pore resonance related to diffusion eigenmodes. If it can be driven experimentally by external time-varying electric, magnetic, or ultrasonic fields, this may be a way to enhance heterogeneous catalysis.

The Effects of Stochastic Circular Pores on Splitting Tensile Behavior of Concrete Based on the Multifractal Theory

Concrete naturally contains a large number of circular-like stochastic pores which weaken the tensile strength of concrete and change the crack propagation path. This study investigates the influences of the size distribution and the spatial distribution of stochastic pores on the fracture behavior of concrete based on the splitting tensile test. The mesoscale model of concrete containing coarse aggregate, mortar, interface transition zone (ITZ), and circular pores is established to simulate the crack initiation, propagation, and coalescence of concrete. Concrete samples with a single hole are prepared to verify the effectiveness of the numerical simulation method. Numerical tests are conducted on numerous mesoscale concrete samples with various porosities, pore size distributions, and pore spatial distributions. The numerical simulation results indicate that the tensile strength decreases with the increase of pore size at the same porosity. Based on multifractal theory, a quantitative indicator to describe the spatial distribution uniformity of concrete stochastic pores is proposed. There is a positive correlation between the spatial distribution uniformity of stochastic pores and the tensile strength. The stochastic circular pores can have a profound effect on the concrete’s fracture pattern, which results in three typical macro-crack patterns in the numerical simulation of the splitting tensile test. The presented results deepen the understanding of the influence of stochastic circular pores on the tensile mechanical properties of concrete and provide a reference for the design of concrete structures.

Multiscale pore-fracture hybrid pore network modeling for drainage in tight carbonate

Tight carbonate possesses both fractures and multiscale pores. Flow through tight carbonate rocks involves several length scales and the complicated flow physics. Capturing and modeling the entire void space into a single pore network model for drainage is challenging. Here, we present a novel method for modeling of a multiscale pore-fracture hybrid pore network, which enables various void spaces at multiple length scales and the flow characteristics in them to be included. Pores and fractures in a low-resolution CT image are extracted by medial axis-maximal ball algorithm and medial surface algorithm, respectively, to generate a pore-fracture hybrid pore network. Then, a statistics-based small-scale stochastic pore network is established in the CT image solid domains to represent the micropores unresolved by the image. The two pore networks are organically integrated into a multiscale hybrid pore network by cross-scale connections. The statistics of small-scale pore network are determined by experimental permeability. We study the effects of the small-scale pore network density on connectivity, single- and two-phase flow properties of the model to obtain the robust parameter. The influence of fractures on two-phase flow properties is analyzed. Results show the significance of incorporating fractures and micropores in the model. The model is validated via comparison between simulation result and experimental data. This method can accurately, efficiently, conveniently construct multiscale pore-fracture hybrid pore network of tight carbonate rock for evaluating the drainage characteristics.

Two Detection Modes of Nanoslit Sensing Based on Planar Heterostructure of Graphene/Hexagonal Boron Nitride

Solid-state nanopore sequencing is now confronted with problems of stochastic pore clogging and too fast speed during the DNA permeation through a nanopore, although this technique is revolutionary with long readability and high efficiency. These two problems are related to controlling molecular transportation during sequencing. To control the DNA motion and identify the four bases, we propose nanoslit sensing based on the planar heterostructure of two-dimensional graphene and hexagonal boron nitride. Molecular dynamics simulations are performed on investigating the motion of DNA molecules on the heterostructure with a nanoslit sensor. Results show that the DNA molecules are confined within the hexagonal boron nitride (HBN) domain of the heterostructure. And the confinement effects of the heterostructure can be optimized by tailoring the stripe length. Besides, there are two ways of DNA permeation through nanoslits: the DNA can cross or translocate the nanoslit under applied voltages along the y and z directions. The two detection modes are named cross-slit and trans-slit, respectively. In both modes, the ionic current drops can be observed when the nanoslit is occupied by the DNA. And the ionic currents and dwell times can be simultaneously detected to identify the four different DNA bases. This study can shed light on the sensing mechanism based on the nanoslit sensor of a planar heterostructure and provide theoretical guidance on designing devices controlling molecular transportation during nanopore sequencing.

Statistical effects of pore features on mechanical properties and fracture behaviors of heterogeneous random porous materials by phase-field modeling

Heterogeneous materials with randomly distributed pores are ubiquitous, such as sintered silver nanoparticles, concrete materials, 3D printed polymers, and natural bones. Recent experimental investigations have revealed that porosity and also pore-related geometries (size, number, shape, distribution and alignment) have significant impacts on the mechanical behavior of random porous materials. However, existing studies focus on the porosity effect while ignoring other pore features such as pore size and pore shape. Our research is dedicated to a computational framework for generating isotropic/anisotropic random porous materials using Gaussian random fields with stochastic pore size and shape factor and addressing the mechanical properties and behavior of brittle fractures using a fracture phase-field model with a preferred degradation function. Sintered silver nanoparticles with typical randomly distributed pores, as representative porous materials, are chosen for their promising applications in emerging fields such as power electronics and wearable devices. In order to emphasize the effect of pore size and shape, 420 random samples with a fixed porosity were generated to discuss the stress–strain response during fracture and to establish statistical relationships between pore feature distributions and mechanical properties such as Young's modulus, UTS, and average historical energy. Our findings suggest that the statical attributes of the pore sizes and shape factors significantly affect the material performance related to the mechanical properties and fracture behavior, which could give a better understanding of the random porous materials and guide reliability-based material design optimization.

Concurrent multiscale topology optimisation towards design and additive manufacturing of bio-mimicking porous structures

ABSTRACT This paper presents a novel multiscale explicit topology optimisation approach for concurrently optimizing the structure at the macro level and the bio-mimicking porous infillings at the micro level. Solid bar components with cross-section control at the macro level and sphere components at the micro level are constructed as the minimal control units to replace the manipulation of material distribution at each grid. The overlapping, moving and morphing of bar components provide the ability to generate flexible structural shapes at the macro level. Using the inspiration of the turtle shell (carapace), the sphere components are designed to move, overlap, and resize inside the bar to sufficiently mimic both the regular and irregular porous features. Classical beam designs, lattice structure designs and unit cell designs are illustrated as numerical examples to demonstrate the functionalities and correctness of the proposed method. As a result, the stochastic pores distribution and porosity control can be validated. The abilities of optimising lattice structure at truss-level and single unit cell level are demonstrated. Moreover, the samples are fabricated by selective laser melting (SLM) technology and then scanned with the X-ray micro-computed tomography (micro-CT) technique to further examine the manufacturability.

Stochastic microstructure delineation and flow simulation in asymmetric block copolymer ultrafiltration membranes

Asymmetric block copolymer ultrafiltration membranes have a wide range of applications from water purification and virus filtration all the way to drug delivery. Although optimizing flow is critical to the performance of such ultrafiltration membranes, their numerical flow characterization has remained challenging. The main problems include hierarchical pore structure delineation and lack of an efficient, image-based pore-scale modeling approach. In this study, we use 2D scanning electron microscopy (SEM) images with a variety of resolutions to delineate the hierarchical asymmetric pore structure. To simulate flow, a novel stochastic pore network model is proposed. The absolute permeabilities of two asymmetric block copolymer ultrafiltration membranes are computed and compared with experimental results showing good agreement.

Statistical and neural network analysis of the relationship between the stochastic nature of pore connectivity and flow properties of heterogeneous rocks

We used a stochastic 3D pore-scale simulation approach to statistically elucidate the effect of stochastic pore connectivity on permeability and hydraulic tortuosity of highly heterogeneous porous media such as carbonate rocks. The novel nature of our workflow lies in the generation of multiple 3D pore microstructures of the same effective porosity, pore size distribution, number of pores, but different stochastic pore connectivity where the only pore microstructural feature changing is pore connectivity. This workflow allows the explicit study of the role pore connectivity plays in permeability and hydraulic tortuosity without the interference of other pore microstructural factors or noise. Permeability and hydraulic tortuosity of the 3D pore microstructures of the aforementioned characteristics was obtained from direct pore-scale simulations using STAR CCM+. Our approach suppresses the necessity of conducting hundreds of experimental measurements and allows the training of neural network models to predict permeability and hydraulic tortuosity. We show that an approximate twofold increase in heterogeneity (pore size standard deviation), results in a two orders of magnitude reduction in permeability, and that an increase in heterogeneity results in a systematic shift of permeability from normal distribution to lognormal distribution. While the stochastic connectivity of pores has a significant impact on permeability, it has only minimal effect on hydraulic tortuosity. Furthermore, the predictability of permeability from hydraulic tortuosity decreases with an increasing heterogeneity. The high coefficient of determination obtained in permeability prediction with a feedforward neural network (NN) model trained with of PTSD data along with pore surface area parameters indicates that NN algorithms can capture the effect of stochastic pore connectivity on permeability. Since PTSD data and surface parameters can be obtained from mercury injection capillary pressure (MICP) measurements, our findings have large implication toward the prediction of permeability and hydraulic tortuosity in highly heterogeneous porous media.

Machine learning modeling of permeability in 3D heterogeneous porous media using a novel stochastic pore-scale simulation approach

Accurate predictions of rock permeability is critical for resource exploration and environmental management. To improve on existing approaches to permeability prediction, this study employed a stochastic pore-scale simulation approach. The petrophysical properties needed for the implementation of this approach are porosity and pore size distribution (PSD) of rock samples which can be obtained easily from mercury injection capillary pressure measurements. The approach was tested on four carbonate and five siliciclastic rock cores. To consider a wide range of possible pore connectivity scenarios that can be associated to the same PSD and porosity, the employed stochastic pore-scale simulation approach involves the generation of hundreds of 3D pore microstructures of the same PSD and porosity but different stochastic pore connectivity. Permeability is calculated by averaging the permeability distribution obtained from pore-scale flow simulations through the generated 3D pore microstructures. Permeability estimations were closer to measured permeability with this approach than with five deterministic empirical model equations. Machine learning was used to reduce the required number of pore-scale simulations by 157 times and reproduced permeability estimated from pore-scale flow simulations with a mean absolute percentage error of 10%.

The Impacts of Surface Microchannels on the Transport Properties of Porous Fibrous Media Using Stochastic Pore Network Modeling.

A stochastic pore network modeling method with tailored structures is proposed to investigate the impacts of surface microchannels on the transport properties of porous fibrous media. Firstly, we simplify the original pore network extracted from the 3D images. Secondly, a repeat sampling strategy is applied during the stochastic modeling of the porous structure at the macroscale while honoring the structural property of the original network. Thirdly, the microchannel is added as a spherical chain and replaces the overlapped elements of the original network. Finally, we verify our model via a comparison of the structure and flow properties. The results show that the microchannel increases the permeability of flow both in the directions parallel and vertical to the microchannel direction. The microchannel plays as the highway for the pass of reactants while the rest of the smaller pore size provides higher resistance for better catalyst support, and the propagation path in the network with microchannels is more even and predictable. This work indicates that our modeling framework is a promising methodology for the design optimization of cross-scale porous structures.

Impact of Surface Roughness on Evaporation in 2D Micromodels

AbstractEvaporation—a key process for water exchange between soil and atmosphere—is controlled by internal water fluxes and surface vapor fluxes. Recent studies demonstrated that the dynamics of the water flow in pore corners and thick‐film flow on the rough pore‐solid interface determine the time behavior of the evaporation rate. A comprehensive experimental study of the combined effect of corner flow (CF) and thick‐film flow (TFF) on evaporation is lacking. Herein, we present a comparative micromodel study of the evaporation process using 2D‐porous media, which exhibit the same stochastic pore structure, but different degree of surface roughness (silicon micromodels with smooth surface and glass‐ceramic micromodels with rough surface). Our study proves both experimentally and theoretically that surface roughness and wettability play a key role for the time and temperature behaviors of the evaporation process. We found a similar behavior up to 42°C regarding the mass loss as a function of time in stage‐2 and a transition to linear t behavior for higher temperatures (61°C) with a high statistical significance (regression coefficients near 1) for both micromodels. Our experimental results elucidate the strong temporal correlation between mass loss and geometric pattern of the unsaturated CF and TFF region. Partial wetting in silicon micromodels causes a weak driving force for CF, whereas complete wetting in glass‐ceramic micromodels causes a strong driving force for TFF. For a consistent description of the time‐dependent mass loss and geometry of the CF/TFF region, the fractality of the evaporation front must be considered. Based on our data, we estimate the film thickness and discover some interesting film‐thinning effect with increasing temperature.

Magnitude Estimation of Overpressure Generation Mechanisms Using Quantitative Stochastic 2D Basin Models: A Case Study from the Danube-Tisza Interfluve Area in Hungary

The overpressure formation in the Pannonian basin, Hungary, was investigated but has not been properly understood for the last 40 years because at least two different explanations were delineated. The first explanation considers the hydrocarbon generation as the main overpressure generation mechanism with some undercompaction contribution. On the contrary, another explanation assumes tectonic stress as the main trigger of abnormal pressure. The following research delivers a suitable workflow to understand which generation mechanisms were active in the study area and estimate the quantitative contribution of the mechanisms. The developed workflow relies on the basin modeling principles that were designed to simulate subsurface processes on a geological timeframe. Moreover, the uncertainty of input parameters was considered, and the joint application of a heuristic Monte Carlo simulation scheme and improved basin modeling resulted in stochastic pore pressure models. The most frequent value (MFV) method was applied on the simulated values to test a robust statistical method in pore pressure prediction. The study has identified not only the four main overpressure generation mechanisms, but it could calculate the individual contribution to the subsurface pressure. Finally, two independent and stochastic pore pressure prediction methods have been developed that could be used in the pre-drill well planning phase and the real-time prediction during drilling.

Kinetics of irreversible pore formation under constant electrical tension in giant unilamellar vesicles.

Stretching in the plasma membranes of cells and lipid membranes of vesicles plays important roles in various physiological and physicochemical phenomena. Irreversible electroporation (IRE) is a minimally invasive non-thermal tumor ablation technique where a series of short electrical energy pulses with high frequency is applied to destabilize the cell membranes. IRE also induces lateral tension due to stretching in the membranes of giant unilamellar vesicles (GUVs). Here, the kinetics of irreversible pore formation under constant electrical tension in GUVs has been investigated. The GUVs are prepared by a mixture of dioleoylphosphatidylglycerol and dioleoylphosphatidylcholine using the natural swelling method. An IRE signal of frequency 1.1kHz is applied to the GUVs through a gold-coated electrode system. Stochastic pore formation is observed for several 'single GUVs' at a particular constant tension. The time course of the fraction of intact GUVs among all the examined GUVs is fitted with a single-exponential decay function from which the rate constant of pore formation in the vesicle, kp, is calculated. The value of kp increases with an increase of membrane tension. An increase in the proportion of negatively charged lipids in a membrane gives a higher kp. Theoretical equations are fitted to the tension-dependent kp and to the probability of pore formation, which allows us to obtain the line tension of the membranes. The decrease in the energy barrier for formation of the nano-size nascent or prepore state, due to the increase in electrical tension, is the main factor explaining the increase of kp.

Deformation and poration of giant unilamellar vesicles induced by anionic nanoparticles

The interaction of anionic magnetite nanoparticles (MNPs) of size 18 nm with negatively charged giant unilamellar vesicles (GUVs) formed from a mixture of neutral dioleoylphosphatidylcholine (DOPC) and negatively charged dioleoylphosphatidylglycerol (DOPG) lipids has been investigated. It has been obtained that NPs induces the deformation of spherical GUVs. The reaction of other GUVs on NPs consists in the appearance of pores in their membranes. We focused the effect of electrostatics on the interaction of charged membranes with MNPs. To study the influence of the surface charge of GUVs on the processes under consideration, we varied the fraction of DOPG in the vesicles from 0 to 100%. We examined the influence of salt concentration in the range of 50−300 mM NaCl concentration. To describe the degree of deformation, a special parameter compactness was introduced. The pore formation in the membranes of GUVs was investigated by the leakage of sucrose. The compactness increases with time and also NPs concentration. The fraction of deformed GUVs increases with the increase of surface charge density of membranes as well as the decrease of salt concentration in buffer. The value of compactness for neutral membrane is 1.25 times higher than that of charged ones. The fraction of deformed GUVs become constant after 20 min, however it increases with NPs concentration. The time taken for stochastic pore formation is less for charged membrane than neutral one. The physical mechanism explaining the experimental results obtained in these investigations.

GPU-based Real-time Porous Medium Dynamic Network Simulation

Porous medium network simulation is to accurately describe the seepage law of multiphase fluids in porous media. Researchers have studied the relationship between various macroscopic physical properties of multiphase fluids (e.g. relative permeability, capillary pressure and fluid saturation) from theoretical, experimental, and computer simulation. This research introduces the construction method of stochastic pore network model and describes the calculation steps of pore network pressure field. In this research, the computational efficiency of the GPU-based pore network was compared with CPU. The calculation speed and simulation model scale of the pressure domain of the random pore network were improved.

Balancing Reactant Transport and PTL-CL Contact in PEM Electrolyzers by Optimizing PTL Design Parameters via Stochastic Pore Network Modeling

Optimizing the porous transport layer (PTL) structure is crucial for high current density operation of polymer electrolyte membrane (PEM) electrolyzers. Previous studies from the literature demonstrated that PTL structures, mainly porosity and titanium powder diameter, can be strategically chosen to improve the performance (1-3). However, transport mechanisms in the PTL can be further explained from the perspective of mass transport. In this work, we employed modelling approaches to investigate the effect of porosity and titanium particle size of the sintered titanium powder based PTL on mass transport. PTLs were numerically generated using a stochastic model (Figure 1) with three titanium powder diameters, 25 µm, 50 µm, and 75 µm, and three porosities, 26.5%, 40.5%, and 63.5%. Pore network modelling was used to calculate the gas saturation and the permeability of liquid water in the presence of oxygen gas. We observed that all simulated PTLs exhibited similar gas saturation profiles and relative permeabilities, yet the PTLs with higher porosities had significantly higher liquid water permeabilities. For a constant powder diameter of 25 μm, increasing the porosity from 26.5% to 63.5% led to an increase in the average surface roughness from 8.9 μm to 38.6 μm. For a constant porosity of 26.5%, increasing the powder size from 25 μm to 75 μm resulted in an increase in the average surface roughness from 8.9 μm to 18.3 μm. Larger open pore spaces were acquired for PTLs with higher surface roughness, resulting in higher liquid water permeabilities (two-phase permeability). Therefore, PTLs with higher porosities and larger particle sizes provide superior liquid water permeation and gas removal. Figure 1. The 3D reconstruction of the PTL generated with titanium powder diameter of (a) 25 µm, (b) 50 µm, and (c) 75 µm at overall porosity of 40.5%. References S. A. Grigoriev, P. Millet, S. A. Volobuev and V. N. Fateev, Int J Hydrogen Energy, 34, 11, p. 4968-4973 (2009). J. O. Majasan, F. Iacoviello, P. R. Shearing and D. J. Brett, Energy Procedia, 151 (2018). L. Zielke, A. Fallisch, N. Paust, R. Zengerle and S. Thiele, Royal Society of Chemistry Advances, 4, p. 58888-58894 (2014). Figure 1

Balancing Reactant Transport and PTL-CL Contact in PEM Electrolyzers by Optimizing PTL Design Parameters via Stochastic Pore Network Modeling

The impacts of sintered titanium powder diameter and porous transport layer (PTL) porosity on reactant transport and PTL-catalyst layer (CL) contact in the polymer electrolyte membrane (PEM) electrolyzer were studied using stochastic generation and a pore network model. Enhanced reactant transport was established with increased powder diameter and porosity, observed through increases in single- and two-phase permeabilities. Compared to increasing the powder diameter, increasing the PTL porosity dominated increases in permeabilities, especially at higher porosities (e > 40%). However, we observed a trade-off whereby increasing the powder diameter led to increased surface roughness at the PTL-CL interface. High roughnesses were observed at porosities > 40%. In conclusion, the powder diameter and porosity must be strategically selected for the desired target operating conditions of the PEM electrolyzer.

Multi-scaled pore network modeling of gas-water flow in shale formations

Abstract Multiphase flow is commonly encountered within shale reservoirs, however, the previous studies are more focused on single phase flow. Due to the extremely low permeability of shale formations, the experimental measurements are not capable to be performed. Attempts are made by applying the techniques of digital rock analysis and pore network modeling to investigate the multiphase flow mechanisms in shale reservoirs. This work follows this way. Firstly, a stochastic pore network generation algorithm and a two-phase flow simulation method are presented. This algorithm is applied and validated in Berea sandstone. By applying the proposed algorithm, the organic and inorganic pore networks are generated for shale formations, then the multi-scaled pore network is established after upscaling the organic pores to an organic path. Finally, the gas-water flow is simulated within this established multi-scaled pore network and some analysis and discussions are conducted. The results imply that the characteristics of pore systems in shale formations pose an extreme impact on the gas-water flow mechanisms, especially the proportion of organic pores and pore-throat aspect ratio.

Towards stochastic generation of 3D pore network models of building materials

Pore-scale-based prediction of the hygric properties of porous building materials is on the rise as an attractive alternative for the current experimental procedure. Pore-scale simulations do however require a complete pore network model for the building material. With the currently available characterization techniques, such complete pore network model cannot be established, instead typically fragmented direct (pores sizes, shapes, positions, connections, …) or indirect (pore size distribution, pore surface area, …) information is obtained. The aim of this paper is to present stochastic pore network generation, wherein the fragmented pore structure information is used to generate a complete pore network for the building material involved. The novelty of our approach lies in the generation of a PNM by matching the distributions of direct parameters as well as indirect parameters of the input data and the model. Additionally, the position of the pores are no longer bound to a cubic lattice. This workflow will first be tested on a single scale material with a relatively straightforward pore space such as sintered glass. Finally, the hygric properties of the generated network will be compared to the measured properties of the real material as a validation step.

Friction-Driven Scission of Membrane Tubes

Membrane scission is essential for intracellular trafficking. Whereas curved BAR domain proteins such as endophilin have been reported to be involved in dynamin-independent scission of tubular membrane necks, the cutting mechanism remained unknown. In this talk, I will present recent work, combining a theoretical model, in vitro, and in vivo experiments, that reveals how a protein scaffold --- a rigid sleeve made up of these proteins --- can cut tubular membranes connected to a quasi-flat membrane reservoir. We found that the scaffold --- which assembles from protein subunits in solution onto the tube and near the junction with the reservoir--- bound to the underlying tube creates a frictional barrier for lipid diffusion; tube elongation thus builds up local membrane tension until the membrane undergoes scission through lysis. As I will discuss, the lysis step was modeled as a stochastic pore nucleation event at the scaffold/bare tube boundary that leads to scission. We call this mechanism friction-driven scission (FDS). In cells, motors pull tubes, in particular during endocytosis. Through reconstitution, we showed that motors can not only pull out and extend protein-scaffolded tubes, but also cut them by FDS.