RSS 1.0Computational Transport Phenomena Lab
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Recent Submissions
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Enhancing the Accuracy of Physics-Informed Neural Network Surrogates in Flash Calculations Using Sparse Grid Guidance(Elsevier BV, 2023-09-30) [Preprint]Flash calculations pose a significant performance bottleneck in compositional-flow simulations. While sparse grids have helped mitigate this bottleneck by shifting it to the offline stage, the accuracy of the surrogate model based on physics-informed neural networks (PINN) is still inferior to that of the sparse grid surrogate in many cases. To address this issue, we propose the sparse-grid guided PINN training algorithm. This approach involves rearranging the collocation points using sparse grids at each epoch to capture changes in the residual space. By doing so, the PINN surrogate achieves the required accuracy using the fewest collocation points possible, thereby avoiding potential performance bottlenecks. Moreover, the training time complexity of the sparse-grid guided PINN training is significantly lower compared to the normal training while maintaining the same level of accuracy. Consequently, the sparse-grid guided PINN training method enhances the accuracy of the PINN surrogate with minimal computational overhead.
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An energy-stable and conservative numerical method for multicomponent Maxwell–Stefan model with rock compressibility(Physics of Fluids, AIP Publishing, 2023-09-26) [Article]Numerical simulation of gas flow in porous media is becoming increasingly attractive due to its importance in shale and natural gas production and carbon dioxide sequestration. In this paper, taking molar densities as the primary unknowns rather than the pressure and molar fractions, we propose an alternative formulation of multicomponent Maxwell–Stefan (MS) model with rock compressibility. Benefiting from the definitions of gas and solid free energies, this MS formulation has a distinct feature that it follows an energy dissipation law, and namely, it is consistent with the second law of thermodynamics. Additionally, the formulation obeys the famous Onsager's reciprocal principle. An efficient energy-stable numerical scheme is constructed using the stabilized energy factorization approach for the Helmholtz free energy density and certain carefully designed formulations involving explicit and implicit mixed treatments for the coupling between molar densities, pressure, and porosity. We rigorously prove that the scheme inherits the energy dissipation law at the discrete level. The fully discrete scheme has the ability to ensure the mass conservation law for each component as well as preserve the Onsager's reciprocal principle. Numerical tests are conducted to verify our theories, and in particular, to demonstrate the good performance of the proposed scheme in energy stability and mass conservation as expected from our theories.
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Transport Properties of Oil-Co2 Mixtures in Nanopores: Physics and Machine Learning Models(Elsevier BV, 2023-09-22) [Preprint]Fundamental understanding and quantitative models of the transport properties of oil-CO2 mixtures in nanopores are indispensable for physics-based models of CO2-enhanced oil recovery in unconventional oil reservoirs. This study determines the Maxwell-Stefan (M-S) diffusivities of CO2-decane (1: CO2; 2: decane /C10) mixtures in calcite nanopore with compositions relevant to CO2 Huff-n-Puff by molecular dynamics (MD) simulations. In the compositional space explored, D12 characterizing CO2-C10 interactions is relatively insensitive to composition, in contrast to that of bulk mixtures with similar compositions. D1,s characterizing CO2-wall interactions increases sharply with CO2 loading in the nanopore. In contrast, D2,s characterizing C10-wall interactions shows a nonmonotonic dependence on C10 loading. In addition, surprisingly, D2,s is negative, opposite to the expectations for dense fluid mixtures or pure decane confined in nanopores. These features of the M-S diffusivities can ultimately be traced to the fact that CO2 molecules adsorb far more strongly on pore walls than the C10 molecules, which leads to significantly heterogeneous distribution of CO2 and C10 in the nanopore and a low mobility of the adsorbed CO2 molecules. As MD simulations are computationally expensive, a non-parametric machine learning technique called the multitask Gaussian process regression method, is used to build a surrogate model to predict M-S diffusivities based on limited MD data. The surrogate model performs well in the compositional space it was trained with a relative root mean square error less than 10%.
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Doublet Huff and Puff (Dhp): A New Technology Towards Optimum Scco2 Sequestration with Stable Geothermal Recovery(Elsevier BV, 2023-09-11) [Preprint]The heat energy extracted from the geothermal reservoirs is clean and plays an important role in decarbonizing the energy sector. Carbon emissions increase in day-to-day operations due to the utilization of hydrocarbons, which contributes to global warming. Therefore, it is crucial to capture and storeSCCO2 while developing clean energy technologies. In this study, we develop a new technology that stores SCCO2 while extracting clean energy from geothermal reservoirs. Our goal is to achieve sustainable thermal recovery and maximize SCCO2 storage capabilities in geothermal reservoirs. To investigate the thermal recovery and SCCO2 storage behavior of geothermal reservoirs, we use a thermo-hydro (two-phase) mechanical (THM) model. This technology is adapted from conventional Huff-Puff technology used in the hydrocarbon industry and applied using well pairs with different injection and perforation operating cycles. We also compared the numerical results with the CO2 plume geothermal (CPG) models. The levelized cost of energy (LCOE) analysis is conducted and compared with the CPG models. The numerical results show that the reduction in production temperature is less than 10 % of the original temperature (base case), the injected SCCO2 accumulates at the top of the reservoir, and the cold front progresses in the vicinity of wells over time. We also investigate the sensitivity of the rock and operating parameters on the heat power and the amount of SCCO2 stored. The implementation of DHP technology is more economical than CPG in geothermal reservoirs (LCOEDHP
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Molecular insights into fluid-solid interfacial tensions in water + gas + solid systems at various temperatures and pressures.(The Journal of chemical physics, AIP Publishing, 2023-09-01) [Article]The fluid-solid interfacial tension is of great importance to many applications including the geological storage of greenhouse gases and enhancing the recovery of geo-resources, but it is rarely studied. Extensive molecular dynamics simulations are conducted to calculate fluid-solid interfacial properties in H2O + gas (H2, N2, CH4, and CO2) + rigid solid three-phase systems at various temperatures (298-403 K), pressures (0-100 MPa), and wettabilities (hydrophilic, neutral, and hydrophobic). Our results on the H2O + solid system show that vapor-solid interfacial tension should not be ignored in cases where the fluid-solid interaction energy is strong or the contact angle is close to 90°. As the temperature rises, the magnitude of H2O's liquid-solid interfacial tension declines because the oscillation of the interfacial density/pressure profile weakens at high temperatures. However, the magnitude of H2O vapor-solid interfacial tension is enhanced with temperature due to the stronger adsorption of H2O. Moreover, the H2O-solid interfacial tension in H2O + gas (H2 or N2) + solid systems is weakly dependent on pressure, while the pressure effects on H2O-solid interfacial tensions in systems with CH4 or CO2 are significant. We show that the assumption of pressure independent H2O-solid interfacial tensions should be cautiously applied to Neumann's method for systems containing non-hydrophilic surfaces with strong gas-solid interaction. Meanwhile, the magnitude of gas-solid interfacial tension increases with pressure and gas-solid interaction. High temperatures generally decrease the magnitude of gas-solid interfacial tensions. Further, we found that the increment of contact angle due to the presence of gases follows this order: H2 < N2 < CH4 < CO2.
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Adsorption of Gases on Fullerene-like X12Y12 (X = Be, Mg, Ca, B, Al, Ga, C; Y = C, Si, N, P, O) Nanocages(Energy & Fuels, American Chemical Society (ACS), 2023-08-30) [Article]Density functional theory calculations are carried out to investigate the adsorption behaviors of CO2, NO, CO, and NH3 on 12 fullerene-like X12Y12 (B12N12, Al12N12, Ga12N12, B12P12, Al12P12, Ga12P12, Be12O12, Mg12O12, Ca12O12, C12Si12, C12N12, and C24) nanocages. The molecular electrostatic potential (MESP) analysis suggests that, for example, for the B12N12, Al12N12, and Ga12N12 nanocages, the electron-rich regions are centered on the N atoms. The deepest MESP minimum (Vmin) values suggest that replacement of C atoms in C24 by XY units increases the electron-rich nature of the nanocage. Generally, CO2 is found to be physisorbed, while NH3 is chemisorbed on the X12Y12 nanocages. NO is found to be strongly adsorbed on the B12P12, Be12O12, Ca12O12, and C24 nanocages, and CO is strongly adsorbed on the B12N12, B12P12, Be12O12, and C24 nanocages. An important result is that the Vmin values of the X12Y12 nanocages are linearly proportional to their CO2 or NO adsorption energies. The quantum theory of atoms in molecules analysis suggests strong covalent interactions in the CO2/Ca12O12, NO/Ca12O12, NO/C24, CO/C24, and NH3/C24 systems.
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Adsorption of hazardous gases on Cyclo[18]carbon and its analogues(Journal of Molecular Liquids, Elsevier BV, 2023-08-30) [Article]Density functional theory calculations were performed to study the adsorption behavior of hazardous gases (NH3, CO2, CO, and NO) on twelve adsorbents (cyclo[18]carbon (C18) and its analogues Al9N9, B9N9, C6B6N6, C12B3N3, C14B2N2, d-C14B2N2, C16BN, C17Si; cyclo[12]carbon (C12) and its analogues Al6N6 and B6N6). The molecular electrostatic potential (MESP) maps of C18 revealed its polyynic structure with alternating electron-rich and electron-deficient regions. The most negative-valued MESP point (Vmin) indicates that the replacement of carbon atoms of C18/C12 by BN/AlN/Si units increases the electron-rich environment in the molecules. In general, NH3 and CO2 are found to be physisorbed on C18/C12 and its analogues. An important result is that the Vmin of C18/C12 and its analogues is linearly correlated with the NH3 and CO2 adsorption energies. The quantum theory of atoms in molecules (QTAIM) results indicate that the interactions of NH3 and CO2 with C18/C12 and its analogues are non-covalent in nature. In general, CO and NO are found to be chemisorbed on C18/C12 and its analogues. In contrast to the cases of NH3 and CO2 adsorption, the Vmin of C18/C12 and its analogues is generally inversely related to the CO and NO adsorption energies. The QTAIM results indicate the strong covalent character of the bonding for CO/C18, CO/C6B6N6, CO/d-C14B2N2, CO/C12, NO/C18, NO/C17Si, and NO/C12 systems. The adsorption process significantly influenced the chemical potential and/or hardness, especially for CO– and NO-adsorbed C18/C12 and its analogues.
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Interfacial Properties of the Hexane + Carbon Dioxide + Brine System in the Presence of Hydrophilic Silica(Industrial & Engineering Chemistry Research, American Chemical Society (ACS), 2023-08-21) [Article]Molecular dynamics simulations were performed to understand the interfacial properties of brine (up to 5.4 mol/kg NaCl) and brine + silica systems in the presence of CO2, hexane, and their equimolar mixture under geological conditions. Simulation results of brine + CO2, brine + hexane, and brine + CO2 + hexane systems agree reasonably well with the theoretical results predicted using the density gradient theory based on the cubic-plus-association equation of state (with Debye–Hückel electrostatic term). In all these systems, the interfacial tension (IFT) increases linearly with increasing NaCl concentration. Here, simulated slopes of the NaCl concentration dependence of IFT are about 1.99 mN/(m mol kg–1), under all conditions. We observe a negative surface excess for NaCl, which may explain the increase in IFT with increasing NaCl concentration. The contact angle (CA) of H2O + CO2 + silica and brine + CO2 + silica systems increases with pressure and decreases with temperature. However, the CA of H2O + hexane + silica and brine + hexane + silica systems is nearly independent of temperature and pressure. These CAs are not significantly affected by the presence of CO2. An important result is that in all investigated systems, the CA increases with increasing salt content. Our simulated CA is in the ranges of 51.4–95.0°, 69.1–86.0°, and 72.0–87.9° for brine + CO2 + silica, brine + hexane + silica, and brine + CO2 + hexane + silica systems, respectively. The density profiles indicate that the positively charged hydrogen atom of the surface hydroxyl group attracts Cl– ions to the surface. In all investigated systems, the adhesion tensions decrease with increasing NaCl concentration.
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Absorption of Carbon Dioxide in Kerogen Nanopores: A Mechanism Study using the Molecular Dynamics Monte Carlo Method(arXiv, 2023-08-08) [Preprint]Carbon capture and storage (CCS) technology has been applied successfully in recent decades to reduce carbon emissions and alleviate global warming. In this regard, shale reservoirs present tremendous potential for carbon dioxide (CO2) sequestration as they have a large number of nanopores. Molecular dynamics (MD) and MD-Monte Carlo (MDMC) methods were employed in this work to study the absorption behavior of CO2 in shale organic porous media. The MDMC method is used to analyze the spatial states of CO2, and the results are in good agreement with MD results, and it also performs well in the acceleration compared to the classical MD. With regard to the kerogen matrix, its properties, such as the pore size distribution (PSD), pore volume, and surface area, are determined to describe its different compression states and the effects of CO2 absorption on it. The potential energy distribution and potential of mean force are analyzed to verify the spatial distribution of CO2 molecules. The heterogeneity of the pore structure resulted in heterogeneous distributions of CO2 molecules in kerogen porous media. Moreover, strong compression of the matrix reduces the number of large pores, and the PSD is mainly between 0 and 15 Angstrom. Despite the high interaction force of the kerogen matrix, the high-potential-energy region induced by the kerogen skeleton also contributes to the formation of low-energy regions that encourage the entry of CO2. An increase in temperature facilitates the absorption process, allowing CO2 molecules to enter the isolated pores with stronger thermal motion, thereby increasing the storage capacity for CO2. However, the development of geothermal energy may not be suitable for CO2 sequestration.
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Flashlight Search Medial Axis: A Pixel-Free Pore-Network Extraction Algorithm(arXiv, 2023-08-05) [Preprint]Pore-network models (PNMs) have become an important tool in the study of fluid flow in porous media over the last few decades, and the accuracy of their results highly depends on the extraction of pore networks. Traditional methods of pore-network extraction are based on pixels and require images with high quality. Here, a pixel-free method called the flashlight search medial axis (FSMA) algorithm is proposed for pore-network extraction in a continuous space. The search domain in a two-dimensional space is a line, whereas a surface domain is searched in a three-dimensional scenario. Thus, the FSMA algorithm follows the dimensionality reduction idea; the medial axis can be identified using only a few points instead of calculating every point in the void space. In this way, computational complexity of this method is greatly reduced compared to that of traditional pixel-based extraction methods, thus enabling large-scale pore-network extraction. Based on cases featuring two- and three-dimensional porous media, the FSMA algorithm performs well regardless of the topological structure of the pore network or the positions of the pore and throat centers. This algorithm can also be used to examine both closed- and open-boundary cases. Finally, the FSMA algorithm can search dead-end pores, which is of great significance in the study of multiphase flow in porous media.
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Enhancing wettability prediction in the presence of organics for hydrogen geo-storage through data-driven machine learning modeling of rock/H2/brine systems(Fuel, Elsevier BV, 2023-08-04) [Article]The success of geological H2 storage relies significantly on rock–H2–brine interactions and wettability. Experimentally assessing the H2 wettability of storage/caprocks as a function of thermos-physical conditions is arduous because of high H2 reactivity and embrittlement damages. Data-driven machine learning (ML) modeling predictions of rock–H2–brine wettability are less strenuous and more precise. They can be conducted at geo-storage conditions that are impossible or hazardous to attain in the laboratory. Thus, ML models were utilized in this research to accurately model the wettability behavior of a ternary system consisting of H2, rock minerals (quartz and mica), and brine at different operating geological conditions. The results revealed that the ML models accurately captured the wettability behavior at different geo-storage conditions by yielding less than 5% mean absolute percent error and above 0.95 coefficient of determination values. The partial dependency or sensitivity plots were generated to evaluate the impact of individual features on the trained models. These plots revealed that the models accurately captured the physics behind the problem. Furthermore, a mathematical equation is derived from the trained ML model to predict the wettability behavior without using any ML software. The accuracy of the predictions of the ML model can be beneficial for exactly predicting the H2 geo-storage capacities and assessing of H2 containment security of storage and caprocks for large-scale geo-storage projects.
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WETTABILITY ANALYSIS IN SHALE ORGANIC PORES AT THE NANOSCALE 页岩纳米有机质孔隙中的润湿性研究(Lixue Xuebao/Chinese Journal of Theoretical and Applied Mechanics, Chinese Society of Theoretical and Applied Mechanics, 2023-08-01) [Article]In view of the problems that wettability is difficult to distinguish in shale nanoscale organic matter pores and the organic matter model cannot truly characterize the pore properties of reservoirs, molecular dynamics research on wettability in shale gas nanoscale pores based on real kerogen organic matter model is proposed. The simulation of smooth and rough graphene ideal models as well as the actual organic matter model of kerogen are built, and wetting behavior characteristics in kerogen pores are analyzed by using the model visualization, the distribution of the density of space, and the analysis of potential energy. There is also an investigation of the effects of temperature, the size of the pores, and the size of the liquid bridge on the wetting condition. Since the traditional organic matter model is based on ideal assumptions, it is difficult to accurately describe the wetting behavior of water in graphene models. As a result of the complex molecular structure and various element types, the kerogen model is more realistic in characterization of wettability of water phase in the organic pore. The water phase in the organic nanopores presents two types of regions: high density region and low density region. Water molecules in the low density region concentrates on the gas-liquid phase interface, where the hydrogen bond interaction is weaker compared with that in the water bulk phase, indicating that this part of molecules are able to diffuse into the gas phase. In addition, the diffused water molecules can also be easily trapped by the kerogen matrix due to its strong attractive interaction. Afterwards, the water molecules will adsorb on the kerogen matrix, presenting a fake wetting condition from the visualization. However, the water phase in the high density region shows the presence of non-wetting condition, which is more realistic for water in the organic pores.
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An Unconditionally Energy-Stable and Orthonormality-Preserving Iterative Scheme for the Kohn-Sham Gradient Flow Based Model(arXiv, 2023-07-28) [Preprint]We propose an unconditionally energy-stable, orthonormality-preserving, component-wise splitting iterative scheme for the Kohn-Sham gradient flow based model in the electronic structure calculation. We first study the scheme discretized in time but still continuous in space. The component-wise splitting iterative scheme changes one wave function at a time, similar to the Gauss-Seidel iteration for solving a linear equation system. Rigorous mathematical derivations are presented to show our proposed scheme indeed satisfies the desired properties. We then study the fully-discretized scheme, where the space is further approximated by a conforming finite element subspace. For the fully-discretized scheme, not only the preservation of orthogonality and normalization (together we called orthonormalization) can be quickly shown using the same idea as for the semi-discretized scheme, but also the highlight property of the scheme, i.e., the unconditional energy stability can be rigorously proven. The scheme allows us to use large time step sizes and deal with small systems involving only a single wave function during each iteration step. Several numerical experiments are performed to verify the theoretical analysis, where the number of iterations is indeed greatly reduced as compared to similar examples solved by the Kohn-Sham gradient flow based model in the literature.
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An end-to-end approach to predict physical properties of heterogeneous porous media: Coupling deep learning and physics-based features(Fuel, Elsevier BV, 2023-07-06) [Article]Digital rock physics (DRP) has become an effective tool to predict the petrophysical properties of rocks and reveal the mass transport mechanisms in porous media. Accurate prediction of the physical properties of heterogeneous rocks based on DRP requires 3D high-resolution (HR) and large-view images. It is, however, extremely challenging to acquire such images since the current imaging technologies cannot resolve the dilemma between the high resolution and large field of view and we often end up with low-resolution (LR) images but with a large field of view or HR images with a small field of view. Moreover, available HR images are limited and always unpaired with accessible LR images, so it is of great difficulty to train a deep learning model based on the limited unpaired images. To address these issues, we used a fast and stabilized generative adversarial network (FastGAN) to synthesize thousands of plausible LR and HR images based on ∼100 unpaired images. Taking the synthetic images as training images, we then utilized a cycle-consistent GAN (CycleGAN) to reconstruct the 3D HR large-scale digital rocks by assimilating the fine-scale structures from 2D HR images into 3D LR images. The accuracy of the proposed method (FastGAN-CycleGAN) is validated by comparing the porosity, pore size distribution, multiple-point correlation, and permeability of the reconstructed digital rocks of shale and carbonate samples with laboratory measurements. The proposed unsupervised approach does not require prior image processing knowledge. Furthermore, it can be also applied to other types of images such as magnetic resonance and fluorescence microscopy images in the future.
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Transport of Heptane Molecules across Water-Vapor Interfaces Laden with Surfactants.(The journal of physical chemistry. B, American Chemical Society (ACS), 2023-07-06) [Article]Molecular transport across liquid-vapor interfaces covered by surfactant monolayers plays a key role in applications such as fire suppression by foams. The molecular understanding of such transport, however, remains incomplete. This work uses molecular dynamics simulations to investigate the heptane transport across water-vapor interfaces populated with sodium dodecyl sulfate (SDS) surfactants. Heptane molecules' potential of mean force (PMF) and local diffusivity profiles across SDS monolayers with different SDS densities are calculated to obtain heptane's transport resistance. We show that a heptane molecule experiences a finite resistance as it crosses water-vapor interfaces covered by SDS. Such interfacial transport resistance is contributed significantly by heptane molecules' high PMF in the SDS headgroup region and their slow diffusion there. This resistance increases linearly as the SDS density rises from zero but jumps as the density approaches saturation when its value is equivalent to that afforded by a 5 nm thick layer of bulk water. These results are understood by analyzing the micro-environment experienced by a heptane molecule crossing SDS monolayers and the local perturbation it brings to the monolayers. The implications of these findings for the design of surfactants to suppress heptane transport through water-vapor interfaces are discussed.
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Numerical investigations and evaluation of a puga geothermal reservoir with horizontal wells using a fully coupled thermo-hydro-geomechanical model (THM) and EDAS associated with AHP(Geoenergy Science and Engineering, Elsevier BV, 2023-06-27) [Article]Puga geothermal reservoir in India gives promising results for the extraction of geothermal energy. On the other hand, no systematic studies were conducted to analyze the Puga geothermal reservoir's thermo-hydro-geomechanical behavior while heat extraction. Most of the researchers concentrated more on the geological and geophysical aspects of the Puga hot spring and provided basic geological data. This information is now being examined as input towards the construction of geothermal reservoirs. In this study, the THM model is enhanced by including additional dynamic fluid, rock, and fracture features, and an integrated assessment approach is anticipated to improve the heat extraction possibilities of the Puga geothermal reservoir. The variation in rock temperature in the vicinity of the production well is influenced less compared to the vicinity of the injection well. The low-temperature region is initially befalling in the vicinity of hydraulic fractures with high conductivity, flow rate, and strong heat convection further it extends to the rock matrix. Twelve injection-production scenarios were proposed for the Puga geothermal reservoir to extract heat energy with single and dual production wells and single injection well. Scenario-2 and scenario-8 are significantly showing high production temperatures when compared to other proposed scenarios. A multi-index-based evaluation system that consists of geothermal reservoir life, thermal breakthrough time, reservoir impedance, heat power, and heat recovery is employed to examine the geothermal extraction from the Puga geothermal reservoir. An integrated evaluation technique was projected for geothermal extraction which is created by coupling the analytical hierarchy process (AHP) and evaluation based on distance from average solution (EDAS) techniques. The performance of twelve injection-production scenarios of the Puga geothermal reservoir are evaluated using the integrated evaluation technique. The results show that scenario-11 and scenario-9 were found to be the top two scenarios for the extraction of heat from the Puga geothermal reservoir. The results demonstrate that the proposed integrated evaluation system and improved THM model can be used for the evaluation of geothermal reservoirs effectively.
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Component-wise and Unconditionally Energy-Stable VT Flash Calculation(Springer Nature Switzerland, 2023-06-26) [Conference Paper]Flash calculations of the hydrocarbon mixture are essential for determining how the mixture phase behaves, which will ultimately affect subsurface flow and transport. In this paper, a novel numerical scheme is proposed for calculating the two-phase equilibrium of Peng-Robinson (PR) fluid at constant volume, temperature, and moles, namely the volume-temperature (VT) flash framework based on the dynamic model. Since the dynamic model is based on the energy dissipation law and the Onsager’s reciprocal principle, we proposed a linear energy-stable scheme with the help of the convex-concave splitting technique, the energy factorization approach, and the component-wise iteration framework. The scheme eventually results in a fully explicit algorithm, and it avoids the challenges of solving non-linear systems and other difficulties in the traditional flash calculation methods. This scheme inherits the original energy stability and significantly reduces the implementation burden. It also achieves convergence unconditionally, even with a huge time step. Numerical experiments are carried out to illustrate its accuracy.
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Molecular perspectives of interfacial properties of the hydrogen+water mixture in contact with silica or kerogen(Journal of Molecular Liquids, Elsevier BV, 2023-06-21) [Article]Interfacial behaviours in multiphase systems containing H2 are crucial to underground H2 storage but are not well understood. Molecular dynamics simulations were carried out to investigate interfacial properties of the H2+H2O and H2+H2O+silica/kerogen systems over a broad range of temperatures (298 - 523 K) and pressures (1 - 160 MPa). The combination of the H2 model with the INTERFACE force field and TIP4P/2005 H2O model can accurately predict the experimental interfacial tensions (IFTs) of the H2+H2O mixture. The IFTs from simulations are also in accordance with predictions from density gradient theory combined with the PC-SAFT equation of state. In general, the IFT decreases with pressure and temperature. However, at relatively high temperatures and pressures, the IFTs increase with pressure. The opposite pressure influence on IFTs can be explained by the inversion of the sign of the relative adsorption of H2. The H2 enrichment in the interfacial regions was identified in density distributions. Meanwhile, the behaviours of contact angles (CAs) in the H2+H2O+silica system are noticeably different from those in the H2+H2O+kerogen system. The H2O CAs for the H2+H2O+silica and H2+H2O+kerogen systems increase with pressure and decrease with temperature. However, the influence of temperature and pressure on these CAs is less pronounced for the H2+H2O+silica system at low temperatures. The behaviours of CAs were understood based on the variations of IFTs in the H2+H2O system (fluid-fluid interaction) and adhesion tensions (fluid-solid interaction). Furthermore, the analysis of the atomic density distributions indicates that the presence of H2 in between the H2O and the silica/kerogen is almost negligible. Nevertheless, the adsorption of H2O on the silica outside the H2O is strong, while less H2O adsorption is seen on the kerogen.
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Molecular Dynamics Simulations of Ion Transport through Protein Nanochannels in Peritoneal Dialysis(International Journal of Molecular Sciences, MDPI AG, 2023-06-13) [Article]In recent decades, the development of dialysis techniques has greatly improved the survival rate of renal failure patients, and peritoneal dialysis is gradually showing dominance over hemodialysis. This method relies on the abundant membrane proteins in the peritoneum, avoiding the use of artificial semipermeable membranes, and the ion fluid transport is partly controlled by the protein nanochannels. Hence, this study investigated ion transport in these nanochannels by using molecular dynamics (MD) simulations and an MD Monte Carlo (MDMC) algorithm for a generalized protein nanochannel model and a saline fluid environment. The spatial distribution of ions was determined via MD simulations, and it agreed with that modeled via the MDMC method; the effects of simulation duration and external electronic fields were also explored to validate the MDMC algorithm. The specific atomic sequence within a nanochannel was visualized, which was the rare transport state during the ion transport process. The residence time was assessed through both methods to represent the involved dynamic process, and its values showed the temporal sequential order of different components in the nanochannel as follows: H2O > Na+ > Cl−. The accurate prediction using the MDMC method of the spatial and temporal properties proves its suitability to handle ion transport problems in protein nanochannels.
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A Disturbance Frequency Index in Earthquake Forecast Using Radio Occultation Data(Remote Sensing, MDPI AG, 2023-06-13) [Article]Earthquake forecasting is the process of forecasting the time, location, and magnitude of an earthquake, hoping to gain some time to prepare to reduce the disasters caused by earthquakes. In this paper, the possible relationship between the maximum electron density, the corresponding critical frequency, and the occurrence of earthquakes is explored by means of radio occultation data based on mechanism analysis and actual earthquake-nearby data. A new disturbance frequency index is proposed in this paper as a novel method to help forecast earthquakes. Forecasting of the location and timing of earthquakes is based on the connection between proven new frequency distributions and earthquakes. The effectiveness of this index is verified by backtracking observation around the 2022 Ya’an earthquake. Using this index, occultation data can forecast the occurrence of earthquakes five days ahead of detection, which can help break the bottleneck in earthquake forecasting.
