Hydrogen can play a central role in a fossil-free energy economy, yet its implementation is hindered by the lack of safe, dense, and efficient storage methods. Hybrid H₂ physisorption-hydrate formation, which combines physisorption in porous materials with encapsulation in clathrate hydrates, presents a promising route, but the fundamental synergistic mechanisms remain largely elusive. Here, we perform microsecond-scale molecular dynamics simulations to study the hybrid H₂ storage process in the hydrophobic metal–organic framework ZIF-8 seeded with THF hydrate nanoparticles. The results indicate that ZIF-8 rapidly physisorbs H₂, while effectively excluding H₂O and THF. Our simulations reveal a dynamic, three-step hybrid storage pathway, i.e. , (1) ZIF-8 selectively adsorbs and enriches H₂ within its pores, creating a high local H₂ concentration; (2) The growing binary H₂-THF hydrate crystals selectively capture the H₂; (3) Transfer of H₂ from the ZIF-8 to the hydrate until the hydrogen source transfer reaches a dynamic equilibrium. This hybrid storage method results in a total H₂ storage capacity reaching 1.82 wt%, exceeding the storage capacity of either physisorption or THF-driven hydrate formation alone. These findings provide critical molecular-level insights, showing that coupling hydrophobic ZIF-8 with hydrate promoters is a highly effective strategy for developing next-generation H₂ storage methods.

Electrochemical CO₂ reduction to CO offers a sustainable route for converting CO₂ into value-added chemicals and fuels. However, CO₂ streams derived from industrial sources often contain SO₂ impurities that severely poison conventional metal-based catalysts. Here, we report a nitrogen-doped carbon catalyst that exhibits pronounced tolerance and stability for CO₂-to-CO conversion in the presence of SO₂ (100–10,000 ppm). The catalyst maintains over 90% Faradaic efficiency toward CO during 8 h of electrolysis at −1.0 V vs RHE with 100 ppm of SO₂, whereas Ag foil electrodes undergo rapid deactivation. Density functional theory calculations combined with surface analyses indicate that weak SO₂ adsorption and the absence of stable sulfur accumulation on nitrogen-doped carbon strengthen its resistance to impurity-induced deactivation, in contrast to Ag catalysts that form Ag₂S. Gas-fed tests in a membrane electrode assembly (MEA) electrolyzer further confirm that nitrogen-doped carbon sustains high CO selectivity at elevated current densities, while Ag nanoparticles suffer irreversible sulfur poisoning. These results demonstrate that nitrogen-doped carbon is intrinsically resistant to SO₂-induced deactivation and highlight its potential as a robust catalyst for CO₂ electroreduction under impurity-containing conditions.

Knowledge of the effect of different organic molecules on spontaneous hydrate nucleation is crucial for understanding the formation of gas hydrates in marine reservoirs. Herein, microsecond MD simulations are conducted to investigate the spontaneous nucleation of CH₄ hydrates in oceanic sediments. The simulation results indicate that hydrate nucleation is influenced by the coupling effects of organic molecules, clay surfaces and salt ions, where organic molecules alter hydrate nucleation by modulating the diffusion fluctuation of CH₄ molecules via controlling the shape and size of CH₄ nanobubbles. Furthermore, CH₄ hydrates are primarily concentrated at a moderate distance away from the nanobubbles, with fewer hydrates located either close or at a more distant from the nanobubbles. In the region about 1.0 nm away from the nanobubbles, the hydrates become more unstable when closer to the nanobubbles, whereas hydrates have better stability when locating above 1.0 nm away from the nanobubbles. Different organic molecules exert distinct effects on spontaneous hydrate nucleation. Specifically, propanol adsorbed to the nanobubble surface kinetically promotes hydrate nucleation, exhibiting a distinct advantage over other organic molecules. These molecular insights expand the understanding of the formation of natural gas hydrate resources and help to effectively utilize this resource.

Per- and polyfluoroalkyl substances (PFAS) persist in water systems and resist conventional removal methods such as activated carbon, which shows reduced efficiency with short-chain PFAS and in the presence of dissolved organic matter. Cyclodextrin-based polymers (CDPs) have emerged as sustainable alternatives, with competitive and selective PFAS adsorption capabilities. These polymers consist of glucose-based cyclodextrin (CD) units that can form host–guest inclusion complexes with PFAS pollutants. However, these binding interactions are not fully understood or quantified. We conducted an evaluation of machine learning approaches to model these host–guest interactions, providing insights into predictive capabilities for later CDP design. This study systematically compares molecular representations (Mordred, ECFP, ChemBERTa, UniMol2, etc.) across several machine learning architectures to predict CD-PFAS binding energies. First, we generated molecular embeddings of 3459 experimental host–guest pairs in the OpenCycloDB data set and 63 external CD-PFAS pairs. We then compared these embeddings via AlignedUMAP visualizations and nearest neighbor analyses. Next, we trained and evaluated predictive models using these embeddings on the OpenCycloDB data set, exploring the effectiveness of transfer learning and finetuning techniques. We finally tested model generalizability on two external experimental CD-PFAS binding data sets. All embeddings captured relevant chemical features, where UniMol2 differed most from other methods in embedding space analysis. Predictive models performed variably based on embedding choice and architecture, with the best-performing combination achieving moderate accuracy on the OpenCycloDB data set. Embeddings pretrained on large molecular data sets and finetuning the ChemBERTa embeddings both showed predictive improvements. However, external validation revealed limited generalizability to CD-PFAS complexes, highlighting domain shift challenges. Notably, leave-one-out cross-validation on the external PFAS-specific data indicated that training on in-domain data improved predictive performance at the cost of generalizability. This work demonstrates that molecular representation choice is critical for small-data host–guest binding prediction. However, domain shift between general CD data and specialized CD–PFAS applications remains a fundamental challenge, for which transfer learning and finetuning may offer potential solutions for future data-driven pipelines for CDP design and sustainable PFAS removal.

Grotthuss transfer is responsible for a large increase in the self-diffusion of hydroxide and hydronium ions in aqueous solutions compared to similarly sized ions. Recent advances in machine-learning molecular dynamics have shown some success in capturing this process. In the present work, we show that classical molecular dynamics combined with experimentally measured electrical conductivities can also be used to determine self-diffusion coefficients and the lifetimes of hydroxide and hydronium ions in aqueous KOH, NaOH, and HCl solutions. This was tested and validated across a wide range of concentrations at 25 and 60 °C. The approach relies on augmenting classically computed trajectories with a biased random walk, which together accounts for both vehicular transport and Grotthuss transfer. The concentration and temperature dependence of this random walk are calibrated by comparing simulated electrical conductivities with available experimental electrical conductivity data. The computed self-diffusion coefficients match measurements at infinite dilution and results from machine learning molecular dynamics. Ion lifetimes reported by machine learning and ab initio molecular dynamics studies depend strongly on the precise definition of what constitutes a Grotthuss transfer event. Our approach for calculating ion lifetimes does not have this drawback. We also show that our self-diffusion coefficients and electrical conductivities are insensitive to the precise definition of what constitutes a Grotthuss transfer event.

One of the most promising energy carriers for transport applications are hydrogen-based energy carriers. NaBH₄ is a hydrogen energy carrier and produces hydrogen bubbles when it is dissolved in water. The formation of hydrogen bubbles hinders experimental measurements of the thermodynamic and transport properties of aqueous NaBH₄ solutions at elevated temperatures. Accurate knowledge of these properties is essential for the NaBH₄ hydrolysis reactor modeling and design. Molecular dynamics (MD) simulations provide the option to study the thermodynamic and transport properties of NaBH₄ aqueous solutions without hindering hydrogen bubble formation. In this work, a new force field is developed for BH₄^-, namely, the Delft force field of BH₄^- (DFF/BH₄^-), which, combined with additional force fields, can accurately describe experimental densities and viscosities of 0 to 5 m (mol salt/kg water) NaBH₄, 0 to 3 m NaB(OH)₄, and 1 m NaOH aqueous solutions at 295 K within 1.8% and 10.8% maximum deviation, respectively. Empirical fitting correlations are created for densities, viscosities, and self-diffusivities obtained from the MD simulations of 0 to 5 m NaBH₄, 0 to 5 m NaB(OH)₄, and 0 to 1 m NaOH aqueous solutions at 295-363 K for NaBH₄ hydrolysis reactor modeling and design purposes.

Finite-size effects of transport properties computed from molecular dynamics simulations are investigated for Weeks-Chandler-Andersen systems at reduced densities of 0.05 (dilute gas), 0.45 (dense gas), and 0.85 (fluid close to the solid-liquid transition). Viscosities, self-diffusivities, Onsager coefficients, and electrical conductivities are computed for various system sizes ranging from 64 to 8192 WCA particles at each density. At dilute and intermediate densities, finite-size corrections to the transport properties significantly deviate from the widely used Yeh–Hummer correction, which was originally developed for the liquid phase.

Knowledge on the kinetics of gas hydrate dissociation in clay pores at static and dynamic fluid conditions is a fundamental scientific issue for improving gas production efficiency from hydrate deposits using thermal stimulation and depressurization respectively. Here, molecular dynamics simulations were used to investigate poly- and mono-crystalline methane hydrates in Na-montmorillonite clay nanopores. Simulation results show that hydrate dissociation is highly sensitive to temperature and pressure gradients, but their effects differ. Temperature changes increase thermal instability of water and gas molecules, leading to layer-by-layer dissociation from the outer surface. Under flow conditions, laminar flow predominates in nano-pores, and non-Darcy flow occurs due to clay-fluid interactions. Viscous flow disrupts hydrogen bonding at the hydrate surface, enhancing kinetic instability of water. Grain boundaries of polycrystalline hydrates are less stable compared to bulk phases and preferentially decompose, forming new dissociation fronts. This accelerates dissociation compared to monocrystalline hydrates. Fracture occurs at the grain boundaries of polycrystalline hydrate in the fluid, resulting in separate hydrate crystal grains. This fracture process further accelerates hydrate dissociation. In flow systems, methane nanobubbles form in fluid and readily transport with fluid flow. Unlike surface nanobubbles at static conditions, these liquid nanobubbles exhibit mobility. The findings of this study can contribute to a better understanding of the complex phase transition behavior of hydrate in confined environment, and provide theoretical support for improving production control technology.

Vapor-Liquid Equilibria (VLE) of hydrogen (H₂) and aqueous electrolyte (KOH and NaCl) solutions are central to numerous industrial applications such as alkaline electrolysis and underground hydrogen storage. Continuous fractional component Monte Carlo simulations are performed to compute the VLE of H₂ and aqueous electrolyte solutions at 298-423 K, 10-400 bar, 0-8 mol KOH/kg water, and 0-6 mol NaCl/kg water. The densities and activities of water in aqueous KOH and NaCl solutions are accurately modeled (within 2% deviation from experiments) using the non-polarizable Madrid-2019 Na⁺/Cl⁻ ion force fields for NaCl and the Madrid-Transport K⁺ and Delft Force Field of OH⁻ for KOH, combined with the TIP4P/2005 water force field. A free energy correction (independent of pressure, salt type, and salt molality) is applied to the computed infinite dilution excess chemical potentials of H₂ and water, resulting in accurate predictions (within 5% of experiments) for the solubilities of H₂ in water and the saturated vapor pressures of water for a temperature range of 298-363 K. The compositions of water and H₂ are computed using an iterative scheme from the liquid phase excess chemical potentials and densities, in which the gas phase fugacities are computed using the GERG-2008 equation of state. For the first time, the VLE of H₂ and aqueous KOH/NaCl systems are accurately captured with respect to experiments (i.e., for both the liquid and gas phase compositions) without compromising the liquid phase properties or performing any refitting of force fields.

An in-depth review of the available experimental and molecular simulation studies of CO₂ diffusion in H₂O, which is a central property in important industrial and environmental processes, such as carbon capture and storage, enhanced oil recovery, and in the food industry is presented. The cases of both bulk and confined systems are covered. The experimental and molecular simulation data gathered are analyzed, and simple and computationally efficient correlations are devised. These correlations are applicable to conditions from 273 K and 0.1 MPa up to 473 K and 45 MPa. The available experimental data for diffusion coefficients of CO₂ in brines are also collected, and their dependency on temperature, pressure, and salinity is examined in detail. Other engineering models and correlations reported in literature are also presented. The review of the simulation studies focuses on the force field combinations, the data for diffusivities at low and high pressures, finite-size effects, and the correlations developed based on the Molecular Dynamics data. Regarding the confined systems, we review the main methods to measure and compute the diffusivity of confined CO₂ and discuss the main natural and artificial confining media (i.e., smectites, calcites, silica, MOFs, and carbon materials). Detailed discussion is provided regarding the driving force for diffusion of CO₂ and H₂O under confinement, and on the role of effects such as H₂O adsorption on hydrophilic confining media on the diffusivity of CO₂. Finally, an outlook of future research paths for advancing the field of CO₂ diffusivity in H₂O at the bulk phase and in confinement is laid out.

H₂-CO₂ mixtures find wide-ranging applications, including their growing significance as synthetic fuels in the transportation industry, relevance in capture technologies for carbon capture and storage, occurrence in subsurface storage of hydrogen, and hydrogenation of carbon dioxide to form hydrocarbons and alcohols. Here, we focus on the thermodynamic properties of H₂-CO₂ mixtures pertinent to underground hydrogen storage in depleted gas reservoirs. Molecular dynamics simulations are used to compute mutual (Fick) diffusivities for a wide range of pressures (5 to 50 MPa), temperatures (323.15 to 423.15 K), and mixture compositions (hydrogen mole fraction from 0 to 1). At 5 MPa, the computed mutual diffusivities agree within 5% with the kinetic theory of Chapman and Enskog at 423.15 K, albeit exhibiting deviations of up to 25% between 323.15 and 373.15 K. Even at 50 MPa, kinetic theory predictions match computed diffusivities within 15% for mixtures comprising over 80% H₂ due to the ideal-gas-like behavior. In mixtures with higher concentrations of CO₂, the Moggridge correlation emerges as a dependable substitute for the kinetic theory. Specifically, when the CO₂ content reaches 50%, the Moggridge correlation achieves predictions within 10% of the computed Fick diffusivities. Phase equilibria of ternary mixtures involving CO₂-H₂-NaCl were explored using Gibbs Ensemble (GE) simulations with the Continuous Fractional Component Monte Carlo (CFCMC) technique. The computed solubilities of CO₂ and H₂ in NaCl brine increased with the fugacity of the respective component but decreased with NaCl concentration (salting out effect). While the solubility of CO₂ in NaCl brine decreased in the ternary system compared to the binary CO₂-NaCl brine system, the solubility of H₂ in NaCl brine increased less in the ternary system compared to the binary H₂-NaCl brine system. The cooperative effect of H₂-CO₂ enhances the H₂ solubility while suppressing the CO₂ solubility. The water content in the gas phase was found to be intermediate between H₂-NaCl brine and CO₂-NaCl brine systems. Our findings have implications for hydrogen storage and chemical technologies dealing with CO₂-H₂ mixtures, particularly where experimental data are lacking, emphasizing the need for reliable thermodynamic data on H₂-CO₂ mixtures.

Knowledge of the microscopic behavior of CO₂ hydrates in oceanic sediments is crucial to evaluate the efficiency and stability of hydrate-based CO₂ sequestration in oceans. Here, systematic molecular dynamics simulations are executed to investigate the growth and dissociation of CO₂ hydrates, and the mechanical instability of CO₂ hydrate-Illite interface in the brine-urea-Illite system. Simulation results show that the CO₂ hydrate growth is jointly affected by the confined space, Illite surface properties, and presence of urea. Specifically, the interfacial H₂O and the ion layer on the Illite surface hinder the growth of CO₂ hydrate crystals toward Illite surfaces. Urea molecules can bind salt ions and increase CO₂ concentrations in the water, thus kinetically promoting CO₂ hydrate growth. The dissociation of the CO₂ hydrate is affected by Illite surface properties and the CO₂ hydrate structure. CO₂ hydrate starts from the regions where hydrate particles are minimally in contact and extends on both sides. The mechanical tension and compression of the CO₂ hydrate-Illite interface exhibit nonlinear characteristics by changing the hydrogen bonds and the CO₂ hydrate structure. The molecular insight into the microscopic behavior of CO₂ hydrates in the brine-urea-Illite system contributes to a broader understanding of hydrate-based CO₂ sequestration.

Focused ultrasound has experimentally been found to enhance the diffusion of nanoparticles; our aim with this work is to study this effect closer using both experiments and non-equilibrium molecular dynamics. Measurements from single particle tracking of 40 nm polystyrene nanoparticles in an agarose hydrogel with and without focused ultrasound are presented and compared with a previous experimental study using 100 nm polystyrene nanoparticles. In both cases, we observed an increase in the mean square displacement during focused ultrasound treatment. We developed a coarse-grained non-equilibrium molecular dynamics model with an implicit solvent to investigate the increase in the mean square displacement and its frequency and amplitude dependencies. This model consists of polymer fibers and two sizes of nanoparticles, and the effect of the focused ultrasound was modeled as an external oscillating force field. A comparison between the simulation and experimental results shows similar mean square displacement trends, suggesting that the particle velocity is a significant contributor to the observed ultrasound-enhanced mean square displacement. The resulting diffusion coefficients from the model are compared to the diffusion equation for a two-time continuous time random walk. The model is found to have the same frequency dependency. At lower particle velocity amplitude values, the model has a quadratic relation with the particle velocity amplitude as described by the two-time continuous time random walk derived diffusion equation, but at higher amplitudes, the model deviates, and its diffusion coefficient reaches the non-hindered diffusion coefficient. This observation suggests that at higher ultrasound intensities in hydrogels, the non-hindered diffusion coefficient can be used.

Thermodynamic factors for diffusion connect the Fick and Maxwell-Stefan diffusion coefficients used to quantify mass transfer. Activity coefficient models or equations of state can be fitted to experimental or simulation data, from which thermodynamic factors can be obtained by differentiation. The accuracy of thermodynamic factors determined using indirect routes is dictated by the specific choice of an activity coefficient model or an equation of state. The Permuted Widom’s Test Particle Insertion (PWTPI) method developed by Balaji et al. enables direct determination of thermodynamic factors in binary and multicomponent systems. For highly dense systems, for example, typical liquids, it is well known that molecular test insertion methods fail. In this article, we use the Continuous Fractional Component Monte Carlo (CFCMC) method to directly calculate thermodynamic factors by adopting the PWTPI method. The CFCMC method uses fractional molecules whose interactions with their surrounding molecules are modulated by a coupling parameter. Even in highly dense systems, the CFCMC method efficiently handles molecule insertions and removals, overcoming the limitations of the PWTPI method. We show excellent agreement between the results of the PWTPI and CFCMC methods for the calculation of thermodynamic factors in binary systems of Lennard-Jones molecules and ternary systems of Weeks-Chandler-Andersen molecules. The CFCMC method applied to calculate the thermodynamic factors of realistic molecular systems consisting of binary mixtures of carbon dioxide and hydrogen agrees well with the NIST REFPROP database. Our study highlights the effectiveness of the CFCMC method in determining thermodynamic factors for diffusion, even in densely packed systems, using relatively small numbers of molecules.