Search Results (108)

Clay minerals are significant constituents of shale reservoirs, yet the confinement-induced phase behavior of hydrocarbons within clay nanopores has received comparatively less attention than in carbonaceous materials. In this study, Grand Canonical Monte Carlo (GCMC) simulations were performed to investigate the confinement-induced shifts in the critical properties of hydrocarbons within illite slit pores ranging from 2 to 20 nm. The simulation results indicate apparent reductions in both critical temperature (T_c) and critical pressure (P_c) under confined conditions. The relative shift in critical properties is more pronounced for n-pentane than for methane, which is attributed to the larger molecular size and complex chain-like structure of n-pentane compared to methane. The simulation results also show that the extent of these shifts varies among different pore geometries and materials due to the differences in fluid–solid interactions and specific surface areas. Illite exerts a weaker confinement effect than graphite, while cylindrical pores intensify the shift compared to slit pores. As the pore size increases from 2 to 20 nm, the nanoconfinement-induced shifts in the critical properties of alkanes in illite slit pores progressively diminish, and the critical properties approach their corresponding bulk values at a pore size of 20 nm. Finally, new correlations are proposed to quantify the critical property shifts in illite slit nanopores. Overall, this study provides a quantitative characterization of confinement-induced critical-property shifts for the investigated hydrocarbons in illite slit nanopores. Full article

Underground hydrogen storage in depleted gas reservoirs has emerged as a key technology for large-scale hydrogen energy storage. However, the occurrence state of hydrogen is governed by residual methane and reservoir mineral surfaces. This study combines grand canonical Monte Carlo and molecular dynamics simulations to investigate the competitive adsorption and diffusion of hydrogen and methane in quartz, kaolinite, and calcite. The results show that at low methane contents (<0.2), the adsorption capacity of hydrogen is primarily governed by its interaction with the mineral surface, exhibiting the strongest adsorption in calcite and the weakest in quartz, whereas the diffusivity follows the opposite trend. As the methane content increases, the occurrence state of hydrogen becomes increasingly controlled by the distribution of methane. The preferential occupation of surface adsorption sites by methane substantially suppresses hydrogen adsorption in quartz and calcite, whereas the abundant methane remaining in the bulk region of kaolinite imposes the strongest restriction on hydrogen diffusion. Increasing temperature promotes methane desorption, releasing interfacial adsorption sites, restoring the near-wall hydrogen adsorption peak, and enhancing hydrogen diffusivity, whereas increasing pressure shifts hydrogen from interfacial adsorption at low pressures to bulk-phase filling at high pressures while reducing its diffusivity. Full article

Hydrogen (H₂) is expected to play a critical role in modern industry, particularly in ammonia synthesis, petroleum refining, and low-carbon transportation. The safe storage of H₂ remains a major challenge due to its low volumetric density under ambient conditions. Metal–Organic Frameworks (MOFs), highly porous crystalline materials, have emerged as promising H₂ storage candidates owing to their high surface areas and tuneable pore structures. Molecular simulations such as grand canonical Monte Carlo or density functional theory are costly and limited in exploring large material spaces, motivating efficient predictive tools to accelerate discovery. Here, Machine Learning (ML) techniques are compared to an explainable artificial intelligence (XAI) approach using symbolic regression (SR), trained on 10,123 experimentally measured H₂ adsorption datapoints from real-world MOFs. The best performing model achieved a goodness of fit of 0.9986 with lower computational demand, but reduced interpretability, addressed using XAI analysis and clustering. SR achieves a lower goodness of fit of 0.914 but produces a physically meaningful equation highlighting structural features driving high gravimetric efficiencies. These results demonstrate strong ML capability for predicting how MOF properties and environmental conditions affect H₂ uptake. This offers engineers and researchers a practical means of screening potential MOFs for H₂ storage applications, with the XAI analyses providing additional confidence in the predictions. They allow researchers to understand the physical reasoning behind each output, assess the reliability of individual predictions, and make fully informed decisions, enabling predictive models to be acted upon with confidence in real-world contexts. Full article

Shale reservoirs feature widely developed nanopores, and the diverse crystal structures and surface functional groups of constituent minerals induce pronounced wettability heterogeneity, rendering conventional experimental methods incapable of characterizing nanoscale interfacial evolution. This work aims to reveal the multi-factor regulated wettability mechanisms of typical shale minerals at the molecular scale. Coupled molecular dynamics (MD) and grand canonical Monte Carlo (GCMC) simulations are performed on four shale minerals (hydroxylated graphene, quartz, calcite, kaolinite) under single-factor conditions (313–373 K, 10–40 MPa, 4–10 nm pores) and coupled pressure–pore deformation scenarios (15–35 MPa, 4–9.1 nm), with wetting mechanisms elucidated from hydrogen bond evolution, water molecular packing, nanoconfinement effect, and mineral crystal structure. The results show that rising temperature linearly reduces contact angles (average 0.33–0.35°/K) by strengthening hydrogen bonding; elevated pressure impairs wettability, with calcite exhibiting the highest-pressure sensitivity; nanoconfinement dominates pore scale wetting; and quartz presents the strongest pore size dependence. Synchronous pressure–pore expansion generates a superimposed wettability deterioration effect. This study quantifies the wettability evolution laws of shale minerals under diverse conditions, providing microscopic theoretical support for reservoir stimulation and enhanced oil recovery. Full article

Here, macromolecular representation and CO₂-CH₄ competitive adsorption properties of mylonitic coal (MC) were revealed based on ¹³C nuclear magnetic resonance, Fourier transform infrared spectroscopy, high-resolution transmission electron microscopy, and grand canonical Monte Carlo simulation. Results suggested that MC has a higher content of aromatic carbon, non-protonated aromatic carbon, and alkyl-substituted aromatic carbon compared with primary coal (PC). There were much longer aliphatic chains and lower branching degrees for MC than PC. The basic structural units of MC were characterized by a higher percentage of longer aromatic fringes (>1 nm) with higher structural alignment (38–48%, 41% in average) than PC (31–38%, 35% in average). Molecular probe results suggested that MC has more free volumes than PC at a given occupied volume. Single adsorption of CO₂ and CH₄ revealed a higher saturation adsorption capacity of CO₂ and CH₄ and more predominant energy reduction of MC. Competitive selectivity of CO₂ over CH₄ (S_CO2/CH4) was >1, indicating the adsorption advantages of CO₂ over CH₄. At pressures of <3.0 MPa, the S_CO2/CH4 of MC was higher than PC. For pressures of 3~4 MPa, they were close, indicating that the competitive adsorption advantages of CO₂ over CH₄ become weak at higher pressures for MC reservoirs. For temperature dependence, it decreases with the increasing temperature, suggesting that high temperature could exert a more significantly unfavorable impact on CO₂ adsorption than for CH₄ adsorption. Both the swelling ratios decrease with the increasing temperature for PC and MC; however, that of MC was higher than that of PC, suggesting that MC possess stronger swelling deformation at a given temperature. The outcomes of this paper indicated that compared with PC, the higher tendency of gas outburst for the MC zone was jointly controlled by a higher proportion of large aromatic fringes, more extensive development of structural defects, higher specific surface area of micropores, and stronger adsorption affinity of CH₄. Competitive adsorption results suggested that MC reservoirs are more favorable for CO₂-ECBM engineering than those of PC. Full article

CO₂ methanation with renewable hydrogen is a promising strategy for carbon valorization and synthetic natural gas (SNG) production. However, the molecular mechanisms behind catalyst-dependent adsorption and mass transport in zeolite-confined spaces are still not fully elucidated. Herein, we performed comparative molecular simulations on HZSM-5, Ni/ZSM-5 and Ru/ZSM-5 by combining density functional theory (DFT), grand canonical Monte Carlo (GCMC) and molecular dynamics (MD) methods, aiming to clarify the thermodynamic and mass transport mechanisms of reactant enrichment and product desorption in CO₂ methanation. The electronic structures of the three systems were systematically evaluated via Mulliken charge analysis, differential charge density mapping, and frontier molecular orbital calculations. We further quantified the adsorption thermodynamics and diffusion kinetics of reactants and products, focusing specifically on the effects of temperature and framework Si/Al ratio for Ni/ZSM-5. The results show that Ni doping greatly modulates the local electronic environment of the ZSM-5 framework, enhancing the adsorption of CO₂ (−121.9 kJ·mol⁻¹) and H₂ (−81.6 kJ·mol⁻¹) and weakening the adsorption of CH₄ and H₂O. A higher Si/Al ratio reduces CO₂ adsorption capacity, while elevated temperatures inhibit reactant adsorption and lower the diffusion selectivity of CH₄. This demonstrates that moderately low temperatures and moderate Si/Al ratios can optimize the adsorption and diffusion behaviors of reactants and products. This work provides molecular-level insights into the adsorption and diffusion behaviors of Ni/ZSM-5 and offers theoretical references for the rational development of high-performance CO₂ methanation catalysts. Full article

To elucidate the molecular structural characteristics of weakly caking coal and the microscopic mechanism by which CO₂ inhibits coal–oxygen complexation, a weakly caking coal sample from the Dahaize coal mine in Shaanxi, China, was investigated using proximate and ultimate analyses, FTIR, XPS, and ¹³C NMR. On this basis, a representative coal macromolecular model was constructed and further analyzed using density functional theory (DFT) and grand canonical Monte Carlo (GCMC) simulations. The molecular formula of the representative weakly caking coal from the Dahaize mine (RNM) unit was determined as C₁₇₆H₁₅₆N₂O₁₉S₂. The aromatic carbon fraction was 65.41%, and the bridge carbon/peripheral carbon ratio was 0.25, indicating a certain degree of aromatic condensation but a limited content of highly fused aromatic structures. DFT calculations revealed that the reactive sites were mainly located around edge oxygen-containing functional groups and bridging structures, with a maximum Fukui index of approximately 0.024. Adsorption simulations showed that O₂ and CO₂ adsorption on RNM followed Langmuir-type behavior over 303.15–363.15 K: adsorption capacity increased with pressure and decreased with temperature. At 8000 kPa, the CO₂ uptake was approximately 1.6 times that of O₂. In the binary O₂-CO₂ system, CO₂ preferentially occupied pore surfaces and high-energy adsorption sites, reducing the local enrichment of O₂. These results provide a molecular-level explanation for the inhibition of coal–oxygen complexation by CO₂ through competitive adsorption, site shielding, and decreased oxidation probability at active sites. Full article

Conventional liquid springs enable storage of energy in the form of interfacial tension at forcibly wetted lyophobic surfaces. The pressure–volume work performed to compress the liquid into a poorly wettable porous medium is recovered during spontaneous expulsion when pressure falls below the capillary pressure characteristic of a given system. Our study explores generalizations to easily wettable materials where liquid infiltration is opposed solely by steric hindrance exerted on liquid molecules in micro-sized pores. The concept is exemplified in molecular simulations of prototypical model systems with methanol intruding narrow slits between hydrocarbon or graphene surfaces. While these materials show significant wetting propensities at macroscopic interfaces with liquid methanol, substantial compression is required to wet molecular-sized pores barely accommodating a monolayer of liquid molecules. The observed O(10³) bar intrusion pressures secure stored energy densities competitive with supercapacitors and amenable to improvement. Wall–liquid attraction and small pore diameters lead to intrusion–expulsion pathways along cooperative-adsorption isotherms. The process avoids abrupt liquid/vapor transitions and associated nucleation barriers, responsible for cycle hysteresis in experiments with water in hydrophobic capillaries. Using open ensemble (Grand Canonical) Monte Carlo sampling, we identify the range of porosities supporting reversible energy storage/recovery operation in lyophilic media; the results can assist with the design of molecular spring devices with competitive storage and power capacities in pragmatic contexts. Full article

To elucidate coalbed methane (CBM) adsorption mechanisms in deep coal reservoirs, the macromolecular structures of coal samples with different coal ranks were characterized using FTIR, XPS, and C NMR, followed by the construction of corresponding molecular models. Grand Canonical Monte Carlo (GCMC) simulations were employed to investigate methane adsorption behavior within the coal matrix at 313.15 K and pressures up to 20 MPa. The results showed that as coal rank increased (R_o,max = 1.63% to 3.18%), the coal macromolecular structure transformed from a side-chain-rich configuration to a highly aromatized and directionally stacked structure. This structural maturation leads to a more compact coal matrix, evidenced by a reduction in free volume from 5108.39 ų to 3999.87 ų and a decline in accessible free volume from 8.23% to 6.26%, thereby restricting the effective space for methane storage. At 20 MPa, although the pore walls of high-rank coal exhibit stronger localized adsorption capacity, the bulk adsorption capacity follows the order: DZ > ZC > SH. This suggests that under deep, high-pressure conditions, the pore-volume compression effect associated with increasing coal rank governs the upper limit of adsorption per unit mass of coal. As pressure increases into the deep reservoir regime, the state of methane in coal micropores gradually shifts from surface adsorption to a high-density, quasi-liquid filling behavior. Consequently, the influence of specific surface area diminishes, while effective free volume emerges as the primary determinant of high-pressure adsorption capacity. The impact of coal rank on deep methane adsorption reflects a competition between enhanced adsorption potential and restricted storage space. The densification-induced compression of effective free volume is identified as the dominant factor limiting the adsorption capacity of deep CBM. This study provides a molecular-scale understanding of deep CBM occurrence mechanisms and establishes a theoretical framework for resource evaluation. Full article

The increasing discharge of synthetic dyes into industrial wastewater necessitates sustainable and low-cost treatment strategies. This study valorizes orange seed powder (OSP), an abundant agro-food residue, as a novel biosorbent for Congo red (CR) removal through a combined experimental and molecular simulation approach. Raw OSP was prepared solely by drying and grinding, without chemical activation, emphasizing its practical applicability and environmental sustainability. Physicochemical characterization using FTIR, SEM, and EDX confirmed adsorption-induced structural and compositional changes. Batch experiments evaluated the effects of initial dye concentration, adsorbent dosage, pH, temperature, and contact time. Equilibrium data were well fitted by the Langmuir and Freundlich isotherm models (R² ≈ 0.99), with a maximum adsorption capacity of 258.39 mg g⁻¹ at 25 °C and pH 4, and a removal efficiency exceeding 99.55%. The adsorption kinetics followed a pseudo-second-order model, while intraparticle diffusion contributed to the rate-controlling mechanism, as indicated by the Weber–Morris model. OSP demonstrated excellent regeneration performance over five adsorption–desorption cycles, retaining more than 96% of its initial CR removal efficiency when regenerated with methanol. Grand Canonical Monte Carlo (GCMC) simulations revealed that adsorption is primarily driven by electrostatic interactions, hydrogen bonding, and π–π stacking interactions, in good agreement with the experimental findings. Overall, raw OSP represents an efficient, regenerable, and sustainable biosorbent, highlighting the originality of integrating experimental investigations with GCMC simulations for wastewater treatment applications. Full article

Rising atmospheric CO₂ levels have increased the demand for robust, scalable adsorbents for practical CO₂ capture and separation. Porous organic polymers (POPs) are attractive candidates because their pore architecture and binding site properties can be precisely tuned via building blocks and linkage formation. This review summarizes experimental and computational studies of azo-linked POPs and, more broadly, nitrogen–nitrogen (N–N) linked systems, emphasizing how synthetic routes, building blocks, and framework topology govern CO₂ uptake. We highlight key synthetic strategies and representative systems, including porphyrin–azo networks, and discuss the relatively sparse experimental literature on alternative N–N linked POPs incorporating azoxy and azodioxy motifs. Emphasis is placed on reversible nitroso/azodioxide chemistry as a potential pathway to ordered porous organic materials. Computational studies provide a practical route to connect structure with adsorption behavior in largely amorphous or partially ordered networks. We review hierarchical workflows combining periodic DFT and electrostatic potential properties, grand canonical Monte Carlo (GCMC) simulations, and binding energy calculations to rationalize trends and identify favorable binding environments. Computational findings demonstrate that pore accessibility and stacking models can strongly influence predicted CO₂ adsorption. This review provides guidelines for designing POPs with enhanced CO₂ adsorption, offering an outlook and discussing challenges for future studies. Full article

The separation of xenon (Xe) and krypton (Kr) is very important for industrial applications and environmental protection. However, the lack of permanent dipoles, low polarizabilities arising from their spherical nature, and similar kinetic diameters make their efficient separation by porous adsorbents exceptionally challenging. This study explored the effects of pore geometry and surface polarity of a series of aluminum-based metal–organic frameworks (CAU-10-H, MIL-160, KMF-1, CAU-23) on Xe/Kr separation performance using a heteroatom engineering strategy. These MOFs are composed of AlO₆ clusters and bent dicarboxylic acid linkers, enabling us to systematically investigate the effects of pore size and heteroatom types on Xe/Kr separation performance. Among them, MIL-160 has a polar linker based on furan, showing the best balance performance. At 298 K and 1.0 bar, the uptake of Xe is 4.12 mmol g⁻¹ and the IAST selectivity is 7.63 for a Xe/Kr (20/80) mixture. The practical performance was verified by dynamic breakthrough experiments, which yielded a long Xe breakthrough time of 42.9 min g⁻¹. Grand Canonical Monte Carlo (GCMC) simulations and first-principles density functional theory (DFT) calculations revealed that the enhanced performance originates from cooperative confinement and polarization effects, with the furanyl oxygen atoms providing optimal Xe-binding sites. This work clarifies the structure–property relationships governing Xe/Kr separation in aluminum-based MOFs (Al-MOFs), highlighting the potential of heteroatom engineering for designing efficient noble gas adsorbents. Full article

While advanced imaging techniques and ordered porous materials like MOFs have gained prominence, gas sorption remains the indispensable tool for characterizing the multiscale heterogeneity of industrially important disordered solids, such as catalysts and shales. This review examines recent developments in gas sorption methodologies specifically tailored for rigid, disordered porous media. We discuss experimental advances, including the choice of adsorbate and the utility of the overcondensation method for probing macroporosity and ensuring saturation. Furthermore, we critically evaluate theoretical approaches for determining pore size distributions (PSDs), contrasting classical methods with Density Functional Theory (DFT) and Grand Canonical Monte Carlo (GCMC) simulations. Special emphasis is placed on the impact of pore-to-pore cooperative effects, such as advanced condensation, cavitation, and pore-blocking, on the interpretation of sorption isotherms. We highlight how complementary techniques, including integrated mercury porosimetry, NMR, and computerized X-ray tomography (CXT), are essential for deconvolving these complex network effects and validating void space descriptors. We conclude that, while “brute force” molecular simulations on image-based reconstructions are progressing, “minimalist” pore network models, which incorporate cooperative mechanisms, currently offer the most empirically adequate approach. Ultimately, gas sorption remains unique in its ability to statistically characterize void spaces from Angstroms to millimeters in a single experiment. Full article

The escalation of thermal runaway in lithium-ion batteries presents severe safety hazards that necessitate advanced monitoring protocols to ensure early warning of potential failures. Carbon dioxide (CO₂) is released during preliminary decomposition well before catastrophic failure occurs, thereby providing a strategic advantage for early-stage warning. Consequently, identifying materials with high-selective CO₂ recognition is an essential prerequisite for developing reliable sensing platforms. This study integrates Grand Canonical Monte Carlo simulations with Random Forest (RF) models to systematically screen 1470 MOFs from the CoRE-MOF 2019 database. The screening process evaluates selective CO₂ recognition under multicomponent competitive adsorption conditions involving CO₂, C₂H₄, and O₂. The performance evaluation is based on working capacity, selectivity, and the trade-off between working capacity and selectivity (TSN). The RF model achieves high predictive accuracy, with tested R² exceeding 0.92 on the test samples. Shapley Additive Explanations (SHAP) interpretability analysis identifies Q⁰_st(CO₂), Q⁰_st(C₂H₄), WEPA, K_H(C₂H₄), and ETR as key performance drivers. The results indicate that CO₂ selectivity is constrained by the binding strength of competing C₂H₄. Optimal materials tend to have hard Lewis acid centers and polar inorganic clusters to minimize non-specific π-interactions with interfering species. Top-performing MOFs require balanced structural features, concentrating in moderate surface areas (965–1975 m²/g), narrow pore windows (PLD ≈ 4–7 Å, LCD ≈ 5.5–9.6 Å), high void fractions above 0.6, and low densities below 1.3 g/cm³. AJOTEY emerges as the optimal candidate with a TSN of 6.43 mol/kg, combining substantial working capacity (4.57 mol/kg) with strong selectivity (25.52). These results will accelerate the discovery of sensing materials and provide a practical pathway for MOF-based CO₂ sensor development to enhance lithium-ion battery safety. Full article

Halomethanes (CH₃X, where X = F, Cl, Br) are potent atmospheric pollutants, and their removal via adsorption on activated carbons (ACs) is a critical remediation strategy. However, the molecular-level influence of AC surface chemistry on adsorption, especially under realistic environmental conditions, is not fully understood. This work utilizes Grand Canonical Monte Carlo (GCMC) simulations to investigate the adsorption of CH₃F, CH₃Cl, and CH₃Br on realistic carbon models, comparing unfunctionalized graphitic surfaces (AC0) with surfaces functionalized with alcohol (AC1), carbonyl (AC2), and carboxyl (AC3) groups. We analyze the process for both pure components and in realistic mixtures (Quarantine and Pre-Shipment concentrations). Our findings reveal a critical inversion in adsorption preference. For pure components, CH₃Br adsorption is highest on the unfunctionalized (AC0) surface, driven by strong adsorbate–adsorbate interactions leading to condensation, characterized by a rising isosteric heat of adsorption ($Q_{st}\approx 35–45$ kJ/mol) that matches the enthalpy of sublimation. Conversely, in realistic humid mixtures, the pristine surface suffers a capacity collapse (>90% loss). The functionalized surfaces (especially AC3) demonstrate superior performance, exhibiting a thermodynamic selectivity of $S_{C{H}_{3}Br/Air}>100$ (compared to $S\approx 15$ for AC0) and retaining approximately 60% of their dry-condition affinity. This study elucidates the distinct roles of surface chemistry and intermolecular forces, providing a molecular basis for designing carbon materials optimized for high selectivity in complex environmental gas streams. Full article