Transport in Porous Media最新文献

{"title":"Data-Driven Modeling of Hysteresis in Porous Media: Neural-Network Surrogates Coupled with the OPM Flow Reservoir Simulator","authors":"Birane Kane,&nbsp;Espen Jettestuen,&nbsp;Tor Harald Sandve,&nbsp;Johan Olav Helland,&nbsp;David Landa-Marbán,&nbsp;Olav Aursjø","doi":"10.1007/s11242-026-02337-x","DOIUrl":"10.1007/s11242-026-02337-x","url":null,"abstract":"<div><p>Relative permeability hysteresis in porous media presents a significant challenge for accurate reservoir simulation due to its path-dependent nature. Traditional empirical and geometric models often fall short in capturing the complexity of hysteresis, especially under cyclic drainage and imbibition conditions. This study investigates the use of machine learning (ML), specifically neural networks, as surrogate models to approximate relative permeability relationships, including hysteresis effects, with high fidelity for applications in reservoir simulations. Focusing on two-phase oil–water systems, the study uses separate training datasets derived from classical hysteresis models (Killough and Carlson) and pore-scale simulation results from a workflow using level set and lattice Boltzmann models (LS-LBM) to generate training data. The proposed ML models incorporate saturation history to predict relative permeability. Three surrogate models are developed: ML-Killough and ML-Carlson, trained on synthetic/model-generated datasets, and ML-LS-LBM, trained on a physics-based dataset. To demonstrate practical applicability, the proposed ML surrogates are applied to a core-scale simulation case implemented in the OPM Flow reservoir simulator. Results demonstrate that the ML surrogates accurately reproduce scanning curves and nonlinear hysteresis effects, perform well on test data drawn from the same distribution, and maintain physical consistency. Their differentiable structure and computationally efficient inference make them suitable for integration into full-field reservoir simulators, offering a promising alternative for simulation-time prediction in enhanced oil recovery and CO<span>(_2)</span> storage applications.</p></div>","PeriodicalId":804,"journal":{"name":"Transport in Porous Media","volume":"153 7","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11242-026-02337-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148459176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Numerical Reactive Flow and Transport Model for Cementation Processes in Bio-concrete Production","authors":"Johannes Hommel,&nbsp;Kerem Bozkurt,&nbsp;Christoph Nething,&nbsp;Erik Eppinger,&nbsp;Yue Wang,&nbsp;Lucio Blandini,&nbsp;Holger Class","doi":"10.1007/s11242-026-02336-y","DOIUrl":"10.1007/s11242-026-02336-y","url":null,"abstract":"<div><p>Concrete is the most widely used construction material worldwide, yet Portland-cement production accounts for approximately 8% of global CO<span>(_2)</span> emissions. Bio-cementation processes based on calcium carbonate precipitation offer a promising low-carbon alternative, but their engineering application is limited by a lack of predictive models for coupled transport, reaction, and cementation processes. This study presents a 1D numerical model for bio-concrete production using urease-active calcite powder (UACP). Unlike previous models based on in-situ bacterial growth, urease is initially and homogeneously distributed by mixing UACP with sand, reducing model complexity in terms of the number of degrees of freedom. The model captures the coupled evolution of fluid flow, ureolysis-driven carbonate precipitation, and porosity–permeability reduction, with a novel conceptual formulation to limit the ureolysis rate for agreement with experiments. Parameters are calibrated using a selected quasi-1D experiment and validated against four additional setups. The model predicts whether cementation is complete or incomplete and reproduces final average porosities with errors below 7.5%. The model already captures the dominant processes governing UACP-based bio-cementation and provides a reliable basis for in-silico optimization of injection strategies and process parameters. It also serves as a foundation for further refinement and extension to multidimensional systems, supporting the development and scale-up of bio-cemented materials in geotechnical and construction applications.</p></div>","PeriodicalId":804,"journal":{"name":"Transport in Porous Media","volume":"153 7","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11242-026-02336-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148459174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stochastic and Deterministic Controls on Pore Size Evolution During Cementation in Porous Geological Media: A Population Dynamics Approach","authors":"Rolando Carbonari,&nbsp;Simon Emmanuel","doi":"10.1007/s11242-026-02339-9","DOIUrl":"10.1007/s11242-026-02339-9","url":null,"abstract":"<div><p>The distribution of pore sizes in a rock evolves continuously throughout its diagenetic history, strongly affecting flow and storage properties. One of the most important drivers of this evolution is mineral cementation, although existing models have not simultaneously represented the distinct effects of both carbonate and quartz cement within a single framework. Here we develop a modified population dynamics model that represents cementation as a combination of deterministic, size-dependent pore closure and stochastic, size-independent porosity reduction. We test the model against pore size distributions derived from digital rock image analysis of three sandstone samples with contrasting cementation histories, and demonstrate that the hybrid approach outperforms both purely deterministic and purely stochastic models. Carbonate cement preferentially occludes large pores, truncating the tail of the pore size distribution and disproportionately reducing permeability relative to the volume of porosity lost. Quartz cement, by contrast, preferentially reduces the abundance of smaller pores through uniform grain-surface overgrowth, leaving the largest flow pathways largely intact. Analysis of the optimized model parameters reveals that the deterministic component is only well-constrained where carbonate cementation is sufficiently abundant to impose a detectable size-selective signature. Our results demonstrate that the framework provides a computationally efficient basis for connecting cementation history to pore structure evolution in porous media.</p></div>","PeriodicalId":804,"journal":{"name":"Transport in Porous Media","volume":"153 7","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11242-026-02339-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148459175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On the Scope of Pride’s Electroacoustic Theory","authors":"Nicolás Rezzano,&nbsp;Leonardo B. Monachesi,&nbsp;Fabio I. Zyserman","doi":"10.1007/s11242-026-02338-w","DOIUrl":"10.1007/s11242-026-02338-w","url":null,"abstract":"<div><p>One of the prevalent theories used to describe electrokinetic phenomena that occur in saturated porous media, due to the existence of electric double layers (EDLs) at solid–fluid interfaces—namely, Pride’s theory-, is revisited in this paper. Among the central assumptions of this theory, it is considered that the diffuse layers of the EDLs remain unperturbed by the action of an external source, which is justified if there exists a high electric permittivity contrast between the constituents of the media. However, this contrast may not be high enough in typical scenarios of interest, and, in addition, the perturbation of the diffuse layers plays an important physical role in electrokinetic phenomena. In this work it is shown that, maintaining the rest of its assumptions, the theory’s range of validity can be extended to scenarios of arbitrary permittivity contrast. The main remaining assumptions that allow this result to be obtained are (i) the thin EDL hypothesis, (ii) ideal electrolyte behavior, (iii) bulk electroneutrality, (iv) moderate <span>(zeta )</span>-potentials (less than 100 mV for the thickest possible EDLs in a thin EDL regime), and (v) a steady-state regime of charge continuity at the pore-scale. Assumption (v) in particular implies that the complete dielectric dispersion caused by the perturbation of the diffuse layers lies outside the scope of Pride’s theory; a criterion is given in order to determine porous media and frequencies where this assumption holds. A comparison with an established electrokinetic model is made, showing good results; and a final discussion is given regarding the scope of the theory.</p></div>","PeriodicalId":804,"journal":{"name":"Transport in Porous Media","volume":"153 7","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148459172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physics-Guided Graph Neural Networks for Pressure-Diffusion Simulation in Porous Media","authors":"Finn Nicholson,&nbsp;Serveh Kamrava","doi":"10.1007/s11242-026-02334-0","DOIUrl":"10.1007/s11242-026-02334-0","url":null,"abstract":"<div><p>Accurate prediction of pressure diffusion in heterogeneous porous media is essential for production forecasting, reservoir behavior analysis, and field development. Physics-based numerical simulators provide reliable pressure solutions, but their computational cost can become limiting for high-resolution heterogeneous models or repeated forward simulations. In this work, a graph neural-network (GNN)-based surrogate model is developed to predict final-time pressure distributions in heterogeneous porous media. Training data are generated by solving the pressure-diffusion equation on an unstructured triangular mesh with spatially varying permeability derived from lithology samples. The mesh is represented as a graph, where nodes contain spatial coordinates, pressure-related inputs, boundary-condition information, and permeability values, while edges represent local mesh connectivity. An edge-based pressure-gradient loss is evaluated as a physics-guided regularization term to encourage local pressure-gradient consistency across connected mesh nodes. The model is evaluated using held-out test cases, independent training runs and additional cross-lithology tests in which models trained on one lithology slice are evaluated on five unseen slices. These evaluations assess predictive accuracy, stability, spatial error behavior, and computational efficiency. The results show that the surrogate reproduces the dominant pressure front and pressure magnitude with low error relative to the full pressure range, while reducing prediction time by approximately 47 times compared with the finite-element solver. The cross-lithology tests achieved a mean unseen-lithology <i>R</i>² of 0.9199, indicating that the model retains predictive capability on previously unseen permeability realizations. The remaining errors are spatially localized, indicating where future graph-structure improvements such as permeability-informed edge weights should be examined.</p></div>","PeriodicalId":804,"journal":{"name":"Transport in Porous Media","volume":"153 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148323569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mesoscopic Numerical Study of CO2 Reactive Transport in Fractured Porous Rock Formations","authors":"Jizong Duan,&nbsp;Qin Lou","doi":"10.1007/s11242-026-02333-1","DOIUrl":"10.1007/s11242-026-02333-1","url":null,"abstract":"<div><p>This study employs a lattice Boltzmann model to investigate CO<span>(_2)</span> reactive transport in fractured porous media, focusing on the effects of Reynolds number (Re), porosity (<span>(varepsilon )</span>), and fracture geometry. Results indicate that the steady-state average reaction rate exhibits coupled dependencies on these parameters. At low Re, the steady-state average reaction rate increases monotonically with <span>(varepsilon )</span>. In contrast, a non-monotonic relationship is observed at high Re, governed by a critical porosity threshold (<span>(varepsilon _c)</span>). For <span>(varepsilon &lt; varepsilon _c)</span>, the steady-state reaction rate increases with <span>(varepsilon )</span>, while it remains constant or decreases for <span>(varepsilon &gt; varepsilon _c)</span>. The critical porosity <span>(varepsilon _c)</span> decreases initially with Re before stabilizing. Similarly, the reaction rate’s dependence on Re is modulated by porosity. At low <span>(varepsilon )</span>, the reaction rate rises with Re. At high <span>(varepsilon )</span>, a critical Reynolds number (<span>(textrm{Re}_textrm{c})</span>) emerges. Below <span>(textrm{Re}_textrm{c})</span>, the steady-state reaction rate increases with Re, but it remains invariant when Re exceeds <span>(textrm{Re}_textrm{c})</span>. The value of <span>(textrm{Re}_c)</span> decreases and then stabilizes as <span>(varepsilon )</span> increases. Furthermore, the reactive transport process is governed by two distinct regimes: diffusion-dominated and convection-dominated regimes. For the diffusion-dominated regime, variations in fracture geometry parameters (including fracture width, inclination angle, number, and cross configuration) exert negligible influence on reactive transport. Under the convection-dominated regime, however, increasing fracture width enhances reactant transport toward the downstream side of the porous medium and intensifies the spatial heterogeneity of the dissolution rate. Among the geometric factors, horizontal fractures exert the strongest influence on CO<span>(_2)</span> transport and generate the most pronounced dissolution heterogeneity, whereas vertical fractures have the weakest effect. An increase in fracture number correlates with a reduction in the dissolution rate. The effects of cross-fracture configurations on transport are highly similar to those of a single fracture.</p></div>","PeriodicalId":804,"journal":{"name":"Transport in Porous Media","volume":"153 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148323909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated Geothermal Reservoir Modeling with Geological Uncertainty and Well Placement Optimization","authors":"M. A. Rustamova","doi":"10.1007/s11242-026-02335-z","DOIUrl":"10.1007/s11242-026-02335-z","url":null,"abstract":"<div><p>This study investigates the thermal and hydraulic performance of a geothermal reservoir through integrated numerical simulation, geological uncertainty quantification, and surrogate-based well placement optimization. A three-dimensional single-phase geothermal reservoir model is developed using the MATLAB Reservoir Simulation Toolbox (MRST), incorporating coupled mass and energy conservation equations for fluid flow and heat transport in porous media. Reservoir performance is evaluated using key indicators, including produced-fluid temperature, water production rates, instantaneous heat extraction, and cumulative thermal energy recovery. To assess the impact of subsurface heterogeneity, an ensemble of one hundred permeability realizations is generated using sequential Gaussian simulation, representing realistic geological uncertainty in sandstone reservoirs. The resulting ensemble simulations demonstrate significant variability in thermal breakthrough timing and cumulative heat extraction, highlighting the strong influence of permeability heterogeneity on geothermal system performance. Furthermore, a surrogate-based global optimization algorithm is employed to optimize producer’s well locations with the objective of maximizing cumulative extracted thermal energy over a ten-year production period. The optimization results show that producer–injector spacing plays a dominant role in delaying thermal breakthrough and improving heat recovery. Compared to a random well configuration, the optimized layouts can increase cumulative thermal energy extraction by more than 30% in the studied case, while marginal improvements are achieved over a conventional corner-well configuration. Overall, the results demonstrate that combining numerical simulation, uncertainty analysis, and surrogate-based optimization provides a promising and computationally efficient framework for evaluating geothermal reservoir performance and supporting well placement decisions under geological uncertainty.</p></div>","PeriodicalId":804,"journal":{"name":"Transport in Porous Media","volume":"153 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148323438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Augmenting a Pure and Hybrid Vertical Equilibrium Scheme Via Data-Driven Surrogate Modelling","authors":"Ivan Buntic,&nbsp;Bernd Flemisch","doi":"10.1007/s11242-026-02325-1","DOIUrl":"10.1007/s11242-026-02325-1","url":null,"abstract":"<div><p>Vertical equilibrium (VE) models have been introduced as computationally efficient alternatives to traditional mass and momentum balance equations for fluid flow in porous media. Since VE models are only accurate in regions where phase equilibrium holds and traditional simulations are computationally demanding, hybrid methods have been proposed to combine the accuracy of the full-dimensional approach with the efficiency of VE model. However, coupling both models introduces computational overhead that can make hybrid simulations slower than fully traditional ones. To address the computational overhead introduced by coupling interfaces in hybrid models, we utilize data-driven surrogates to accelerate the overall scheme. To this end, we predict the gas plume distance and coarse-level mobilities in the VE model, and also enhance the computation of the coupling scheme via surrogates. We focus on surrogate models with short inference times to minimize computational overhead during frequent function calls. The proposed approach preserves key physical properties, such as mass conservation, despite the deployment of data-driven models, while substantially reducing simulation runtimes. Overall, combining data-driven methods with the hybrid VE scheme yields an enhanced model that outperforms traditional simulations in speed while introducing only negligible errors.</p></div>","PeriodicalId":804,"journal":{"name":"Transport in Porous Media","volume":"153 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11242-026-02325-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148281806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sodium Silicate Grouting: Mechanisms, Environmental Impacts, and Research Directions","authors":"Mohammad Valibeknejad,&nbsp;Thomas Sweijen,&nbsp;Alraune Zech,&nbsp;Julian Quodbach,&nbsp;Noushine Shahidzadeh,&nbsp;Mariette Wolthers,&nbsp;Amir Raoof","doi":"10.1007/s11242-026-02323-3","DOIUrl":"10.1007/s11242-026-02323-3","url":null,"abstract":"<div><p>Sodium silicate grouting is a widely used technique for reducing soil permeability and reinforcing unconsolidated soils. Despite decades of use, its field performance remains inconsistent, with efficiency strongly influenced by soil heterogeneity, groundwater composition, and contaminant interactions. In addition, the environmental risks associated with silica gels, such as leaching of diluted grout into groundwater and long-term degradation, are not fully understood. This review, the first comprehensive synthesis since the 1990s, integrates insights from scientific studies, field applications, and industry practice. We examine the coupled processes governing injection, gelation, and post-gelation evolution across micro-, pore-, and field scales, and identify the key hydraulic, chemical, thermal, and environmental parameters controlling grouting performance. Particular attention is given to sand–gel interactions, microstructural development, permeability reduction mechanisms, and factors governing strength enhancement. The review also evaluates environmental impact and discusses the potential of Electrical Resistivity Tomography (ERT) for monitoring grout continuity. Finally, we outline critical research directions needed to develop constitutive relationships for grout properties, improve predictive modelling, and enable more reliable, sustainable, and environmentally compatible applications of silicate grouting.</p></div>","PeriodicalId":804,"journal":{"name":"Transport in Porous Media","volume":"153 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11242-026-02323-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148281744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Atomistic MD Assessment of Al2SiO5 Aluminosilicate for Desalination Water/Ion Selectivity and Complementary Machine Learning Forecasting of Reverse Osmosis Performance","authors":"Nour El Haq El Macouti,&nbsp;Mohamed El Bouanounou,&nbsp;Abdelmajid Assila,&nbsp;El Kebir Hlil,&nbsp;Yahia Boughaleb,&nbsp;Abdellatif Aarfane,&nbsp;Abdelowahed Hajjaji,&nbsp;Said Laasri","doi":"10.1007/s11242-026-02331-3","DOIUrl":"10.1007/s11242-026-02331-3","url":null,"abstract":"&lt;div&gt;&lt;p&gt;Despite growing global water stress, the rational design of desalination membranes remains constrained by a gap between atomistic transport mechanisms and operational performance prediction. Here, we present, to our knowledge, the first dedicated atomistic desalination transport assessment of Al&lt;sub&gt;2&lt;/sub&gt;SiO&lt;sub&gt;5&lt;/sub&gt; aluminosilicate as an ultrathin reverse osmosis model membrane candidate, together with complementary machine learning regression models trained on conventional RO operational data. The MD component provides molecular-scale insight into Al&lt;sub&gt;2&lt;/sub&gt;SiO&lt;sub&gt;5&lt;/sub&gt; water/ion selectivity, whereas the ML component demonstrates system-level forecasting of flux and salt rejection from routine RO monitoring variables. Because the operational dataset was not obtained from Al&lt;sub&gt;2&lt;/sub&gt;SiO&lt;sub&gt;5&lt;/sub&gt; membranes, the two components are interpreted as complementary rather than directly coupled. Non-equilibrium molecular dynamics simulations were performed for 5 ns at ~ 300 K using an intentionally elevated transmembrane pressure (~ 150 MPa) to access statistically meaningful permeation events on nanosecond timescales. To ensure physically rigorous treatment of long-range interactions, the simulation cell was expanded to a 3 × 3 periodic array in the membrane plane (approximately 37.4 × 42.1 × 160.0 Å), enabling the use of a standard 12.0 Å non-bonded cutoff that satisfies the minimum image convention and is consistent with TIP4P/2005 water and ClayFF aluminosilicate force fields. The results are, therefore, interpreted mechanistically rather than as direct industrial flux predictions. The Al&lt;sub&gt;2&lt;/sub&gt;SiO&lt;sub&gt;5&lt;/sub&gt; framework remained structurally intact throughout production (RMSD = 0.76 ± 0.16 Å; membrane thickness = 6.66 ± 0.16 Å), with preserved aluminosilicate coordination confirmed by persistent Si–O (~ 1.48 Å) and Al–O (~ 1.70 Å) RDF signatures. Continuous water permeation was observed across the 3 × 3 membrane, with an early-stage permeation rate of 469.5 ± 1.4 water molecules ns&lt;sup&gt;−1&lt;/sup&gt; from the 0.2 to 2.0 ns linear regime, corresponding to an MD-apparent permeance of 2.14 × 10&lt;sup&gt;3&lt;/sup&gt; LMH bar&lt;sup&gt;−1&lt;/sup&gt; under accelerated driving conditions. The later reduction in slope was consistent with finite feed depletion in the nanoscale simulation cell. Ion transport was strongly suppressed, with a final ion rejection of approximately 94.2%: Out of 180 Na⁺ and 180 Cl&lt;sup&gt;−&lt;/sup&gt; ions in the feed, only 9 Na⁺ and approximately 12 Cl&lt;sup&gt;−&lt;/sup&gt; ions reached the permeate side over the full 5 ns production window. Apparent free-energy profiles provide a mechanistic explanation for this selectivity, revealing substantially higher barriers for Na⁺ (3.06 kcal mol&lt;sup&gt;−1&lt;/sup&gt;, ~ 5.1 &lt;i&gt;k&lt;/i&gt;&lt;sub&gt;&lt;i&gt;B&lt;/i&gt;&lt;/sub&gt;&lt;i&gt;T&lt;/i&gt;) and Cl&lt;sup&gt;−&lt;/sup&gt; (2.58 kcal mol⁻&lt;sup&gt;1&lt;/sup&gt;, ~ 4.3 &lt;i&gt;k&lt;/i&gt;&lt;sub&gt;&lt;i&gt;B&lt;/i&gt;&lt;/sub&gt;&lt;i&gt;T&lt;/i&gt;) than for water (0.70 kcal mol⁻&lt;sup&gt;1&lt;/sup&gt;, ~ 1.2 &lt;i&gt;k&lt;/i&gt;&lt;sub&gt;&lt;i&gt;B&lt;/i&gt;&lt;/sub&gt;&lt;i&gt;T&lt;/i&gt;) near the membrane region. At","PeriodicalId":804,"journal":{"name":"Transport in Porous Media","volume":"153 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148281029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}