Atomistic molecular dynamics simulations of CO₂ diffusivity in H₂O for a wide range of temperatures and pressures

Confinement-induced clustering of H2 and CO2 gas molecules in hydrated nanopores

Gas molecule clustering within nanopores holds significance in the fields of nanofluidics, biology, gas adsorption/desorption, and geological gas storage. However, the intricate roles of nanoconfinement and surface chemistry that govern the formation of gas clusters remain inadequately explored. In this study, through free energy calculation in molecular simulations, we systematically compared the tendencies of H2 and CO2 molecules to aggregate within hydrated hydrophobic pyrophyllite and hydrophilic gibbsite nanopores. The results indicate that nanoconfinement enhances gas dimer formation in the nanopores, irrespective of surface chemistry. However, surface hydrophilicity prohibits the formation of gas clusters larger than dimers, while large gas clusters form easily in hydrophobic nanopores. Despite H2 and CO2 both being non-polar, the larger quadrupole moment of CO2 leads to a stronger preference for dimer/cluster formation compared to H2. Our results also indicate that gases prefer to enter the nanopores as individual molecules, but exit the nanopores as dimers/clusters. This investigation provides a mechanistic understanding of gas cluster formation within nanopores, which is relevant to various applications, including geological gas storage.

Interfacial Tensions, Solubilities, and Transport Properties of the H2/H2O/NaCl System: A Molecular Simulation Study

Data for several key thermodynamic and transport properties needed for technologies using hydrogen (H2), such as underground H2 storage and H2O electrolysis are scarce or completely missing. Force field-based Molecular Dynamics (MD) and Continuous Fractional Component Monte Carlo (CFCMC) simulations are carried out in this work to cover this gap. Extensive new data sets are provided for (a) interfacial tensions of H2 gas in contact with aqueous NaCl solutions for temperatures of (298 to 523) K, pressures of (1 to 600) bar, and molalities of (0 to 6) mol NaCl/kg H2O, (b) self-diffusivities of infinitely diluted H2 in aqueous NaCl solutions for temperatures of (298 to 723) K, pressures of (1 to 1000) bar, and molalities of (0 to 6) mol NaCl/kg H2O, and (c) solubilities of H2 in aqueous NaCl solutions for temperatures of (298 to 363) K, pressures of (1 to 1000) bar, and molalities of (0 to 6) mol NaCl/kg H2O. The force fields used are the TIP4P/2005 for H2O, the Madrid-2019 and the Madrid-Transport for NaCl, and the Vrabec and Marx for H2. Excellent agreement between the simulation results and available experimental data is found with average deviations lower than 10%.

Preparation of a Stable Superhydrophobic Mortar Surface Using a One-Step Method

Research efforts have intensified on developing superhydrophobic surfaces on concrete structures to limit the damage caused by the natural porosity and hydrophilicity of cementitious materials. However, the feasibility idea is impeded by the complex preparation process and weak adhesion/stability performance. Therefore, superhydrophobic coatings were rapidly prepared on mortar surfaces by a straightforward and effective one-step method using zinc oxide (ZnO) modified with stearic acid and epoxy resin. The microstructure, physical/chemical properties, hydrophobic properties, and stability of the coatings were systematically investigated. The experimental results showed that the water contact angle of the samples reached a maximum value of 164.2° and a sliding angle of 4.6° when the stearic acid content was 0.5 g. The water absorption of the coated superhydrophobic mortar was reduced by approximately 61% compared to that of ordinary mortar, and neither particulate pollutants nor liquid pollutants could contaminate the superhydrophobic mortar. The coating maintained a superhydrophobic state and exhibited good physical durability after sandpaper abrasion, tape peeling, and high-temperature resistance tests. The water cluster diffusion coefficient on surface of the ordinary coating was 0.1645 × 10-4 and 0.0328 × 10-4 cm2/s on surface of the modified coating after molecular dynamics simulation.

Space-Resolved OH Vibrational Spectra of the Hydration Shell around CO2

The CO2 molecule is weakly bound in water. Here we analyze the influence of a dissolved CO2 molecule on the structure and OH vibrational spectra of the surrounding water. From the analysis of ab initio molecular dynamics simulations (BLYP-D3) we present static (structure, coordination, H-bonding, tetrahedrality) and dynamical (OH vibrational spectra) properties of the water molecules as a function of distance from the solute. We find a weakly oscillatory variation ("ABBA") in the 'solution minus bulk water' spectrum. The origin of these features can largely be traced back to solvent-solute hard-core interactions which lead to variations in density and tetrahedrality when moving from the solute's vicinity out to the bulk region. The high-frequency peak in the solute-affected spectra is specifically analyzed and found to originate from both water OH groups that fulfill the geometric H-bond criteria, and from those that do not (dangling ones). Effectively, neither is hydrogen-bonded.

Time-resolved optical probing of the non-equilibrium supercritical state in molecular media under ns laser-plasma impact

We proposed a complex method based on a combination of shadow photography and time-resolved Raman spectroscopy to observe the non-stationary laser-induced supercritical state in molecular media. Shadow photography is applied for retrieving pressure values, while Raman spectroscopy with molecular dynamics for temperature estimation. Time resolution of 0.25 ns is achieved by varying the delay between the pump (creating an extreme energy delivery) and the probe laser pulses by the self-made digital delay electronic circuit . The proposed method was employed in liquid carbon dioxide and water. Under nanosecond laser pulse impact, the estimated temperatures and pressures (∼700 K and ∼0.5 GPa) achieved in media are higher than the critical parameters of the samples.

Diffusivity of α-, β-, γ-cyclodextrin and the inclusion complex of β-cyclodextrin: Ibuprofen in aqueous solutions; A molecular dynamics simulation study

Cyclodextrins (CDs) are widely used in drug delivery, catalysis, food and separation processes. In this work, a comprehensive simulation study on the diffusion of the native α-, β- and γ-CDs in aqueous solutions is carried out using Molecular Dynamics simulations. The effect of the system size on the computed self-diffusivity is investigated and it is found that the required correction can be as much as 75% of the final value. The effect of the water force field is examined and it is shown that the q4md-CD/TIP4P/2005 force field combination predicts the experimentally measured self-diffusion coefficients of CDs very accurately. The self-diffusion coefficients of the three native CDs were also computed in aqueous-NaCl solutions using the Joung and Cheatham (JC) and the Madrid-2019 force fields. It is found that Na+ ions have higher affinity towards the CDs when the JC force field is used and for this reason the predicted diffusivity of CDs is lower compared to simulations using the Madrid-2019 force field. As a model system for drug delivery and waste-water treatment applications, the diffusion of the β-CD:Ibuprofen inclusion complex in water is studied. In agreement with experiments for similar components, it is shown that the inclusion complex and the free β-CD have almost equal self-diffusion coefficients. Our analysis revealed that this is most likely caused by the almost full inclusion of the ibuprofen in the cavity of the β-CD. Our findings show that Molecular Dynamics simulation can be used to provide reasonable diffusivity predictions, and to obtain molecular-level understanding useful for industrial applications of CDs.

Solubility of Carbon Dioxide, Hydrogen Sulfide, Methane, and Nitrogen in Monoethylene Glycol; Experiments and Molecular Simulation

Knowledge on the solubility of gases, especially carbon dioxide (CO₂), in monoethylene glycol (MEG) is relevant for a number of industrial applications such as separation processes and gas hydrate prevention. In this study, the solubility of CO₂ in MEG was measured experimentally at temperatures of 333.15, 353.15, and 373.15 K. Experimental data were used to validate Monte Carlo (MC) simulations. Continuous fractional component MC simulations in the osmotic ensemble were performed to compute the solubility of CO₂ in MEG at the same temperatures and at pressures up to 10 bar. MC simulations were also used to study the solubility of methane (CH₄), hydrogen sulfide (H₂S), and nitrogen (N₂) in MEG at 373.15 K. Solubilities from experiments and simulations are in good agreement at low pressures, but deviations were observed at high pressures. Henry coefficients were also computed using MC simulations and compared to experimental values. The order of solubilities of the gases in MEG at 373.15 K was computed as H₂S > CO₂ > CH₄ > N₂. Force field modifications may be required to improve the prediction of solubilities of gases in MEG at high pressures and low temperatures.

Machine Learning-Based Upscaling of Finite-Size Molecular Dynamics Diffusion Simulations for Binary Fluids

Molecular diffusion coefficients calculated using molecular dynamics (MD) simulations suffer from finite-size (i.e., finite box size and finite particle number) effects. Results from finite-sized MD simulations can be upscaled to infinite simulation size by applying a correction factor. For self-diffusion of single-component fluids, this correction has been well-studied by many researchers including Yeh and Hummer (YH); for binary fluid mixtures, a modified YH correction was recently proposed for correcting MD-predicted Maxwell-Stephan (MS) diffusion rates. Here we use both empirical and machine learning methods to identify improvements to the finite-size correction factors for both self-diffusion and MS diffusion of binary Lennard-Jones (LJ) fluid mixtures. Using artificial neural networks (ANNs), the error in the corrected LJ fluid diffusion is reduced by an order of magnitude versus existing YH corrections, and the ANN models perform well for mixtures with large dissimilarities in size and interaction energies where the YH correction proves insufficient.

Molecular Mechanism of Gas Solubility in Liquid: Constant Chemical Potential Molecular Dynamics Simulations

Accurate prediction of gas solubility in a liquid is crucial in many areas of chemistry, and a detailed understanding of the molecular mechanism of the gas solvation continues to be an active area of research. Here, we extend the idea of the constant chemical potential molecular dynamics (CμMD) approach to the calculation of the gas solubility in the liquid under constant gas chemical potential conditions. As a representative example, we utilize this method to calculate the isothermal solubility of carbon dioxide in water. Additionally, we provide microscopic insight into the mechanism of solvation that preferentially occurs in areas of the surface where the hydrogen network is broken.

Generalized Form for Finite-Size Corrections in Mutual Diffusion Coefficients of Multicomponent Mixtures Obtained from Equilibrium Molecular Dynamics Simulation

The system-size dependence of computed mutual diffusion coefficients of multicomponent mixtures is investigated, and a generalized correction term is derived. The generalized finite-size correction term was validated for the ternary molecular mixture chloroform/acetone/methanol as well as 28 ternary LJ systems. It is shown that only the diagonal elements of the Fick matrix show system-size dependency. The finite-size effects of these elements can be corrected by adding the term derived by Yeh and Hummer (J. Phys. Chem. B2004, 108, 15873–15879). By performing an eigenvalue analysis of the finite-size effects of the matrix of Fick diffusivities we show that the eigenvector matrix of Fick diffusivities does not depend on the size of the simulation box. Only eigenvalues, which describe the speed of diffusion, depend on the size of the system. An analytic relation for finite-size effects of the matrix of Maxwell–Stefan diffusivities was developed. All Maxwell–Stefan diffusivities depend on the system size, and the required correction depends on the matrix of thermodynamic factors.

The effect of temperature on water desalination through two-dimensional nanopores

Two-dimensional (2D) materials such as graphene, molybdenum sulfide, and hexagonal boron nitride are widely studied for separation applications such as water desalination. Desalination across such 2D nanoporous membranes is largely influenced by the bulk transport properties of water, which are, in turn, sensitive to the operating temperature. However, there have been no studies on the effect of temperature on desalination through 2D nanopores. We investigated water desalination through hydrogen functionalized graphene nanopores of varying pore areas at temperatures 275.0 K, 300.0 K, 325.0 K, and 350.0 K. The water flux showed a direct relation with the diffusion coefficient and an inverse relation with the hydrogen-bond lifetime. As a direct consequence, the water flux was found to be related to the temperature as per the Arrhenius equation, similar to an activated process. The results from the present study improve the understanding on water and ion permeation across nanoporous 2D materials at different temperatures. Furthermore, the present investigation suggests a kinetic model, which can predict the water and ion permeation based on the characteristics of the nanopore.

Structure and dynamics of water in molecular models of hydrated polyvinylamine membranes

Facilitated transport membranes (FTMs) constitute an emerging class of polymer materials with promising properties for carbon capture applications. The key feature of these membranes is the presence of chemical groups which, in the presence of water, engage in a reaction with dissolved carbon dioxide, thus enhancing the permeability and selectivity of the membrane. Currently, little is known about the organization of these membranes on a molecular level, reaction mechanisms and detailed chemical balance, transport of water, ion species and dissolved gas molecules. The nature of the actual facilitation mechanism and the factors responsible for this effect remain unclear. Here, we use a case of polyvinylamine (PVAm), one of the most studied fixed carrier material for FTMs, to propose molecular models of the hydrated polymers. We aim to understand how transport of water is governed by structural properties of the membrane, such as the free volume, pore limiting diameter, and degree of protonation. We observe that even at the highest experimentally used hydration level, the mobility of water in PVAm matrices is significantly lower than that in bulk water; unlike in bulk systems, chloride ions exhibit much slower diffusion in confined water; this, in turn, affects the diffusion of water, which also diminishes in the presence of chloride ions.

Markov-state model for CO2 binding with carbonic anhydrase under confinement

Enzyme immobilization with a nanostructure material can enhance its stability and facilitate reusability. However, the apparent activity is often compromised due to additional diffusion barriers and complex interactions with the substrates and solvent molecules. The present study elucidates the effects of the surface hydrophobicity of nano-confinement on CO₂ diffusion to the active site of human carbonic anhydrase II (CA), an enzyme that is able to catalyze CO₂ hydration at extremely high turnover rates. Using the Markov-state model in combination with coarse-grained molecular dynamics simulations, we demonstrate that a hydrophobic cage increases CO₂ local density but hinders its diffusion towards the active site of CA under confinement. By contrast, a hydrophilic cage hinders CO₂ adsorption but promotes its binding with CA. An optimal surface hydrophobicity can be identified to maximize both the CO₂ occupation probability and the diffusion rate. The simulation results offer insight into understanding enzyme performance under nano-confinement and help us to advance broader applications of CA for CO₂ absorption and recovery.

Finite-Size Effects of Binary Mutual Diffusion Coefficients from Molecular Dynamics

Molecular dynamics simulations were performed for the prediction of the finite-size effects of Maxwell-Stefan diffusion coefficients of molecular mixtures and a wide variety of binary Lennard-Jones systems. A strong dependency of computed diffusivities on the system size was observed. Computed diffusivities were found to increase with the number of molecules. We propose a correction for the extrapolation of Maxwell-Stefan diffusion coefficients to the thermodynamic limit, based on the study by Yeh and Hummer ( J. Phys. Chem. B , 2004 , 108 , 15873 - 15879 ). The proposed correction is a function of the viscosity of the system, the size of the simulation box, and the thermodynamic factor, which is a measure for the nonideality of the mixture. Verification is carried out for more than 200 distinct binary Lennard-Jones systems, as well as 9 binary systems of methanol, water, ethanol, acetone, methylamine, and carbon tetrachloride. Significant deviations between finite-size Maxwell-Stefan diffusivities and the corresponding diffusivities at the thermodynamic limit were found for mixtures close to demixing. In these cases, the finite-size correction can be even larger than the simulated (finite-size) Maxwell-Stefan diffusivity. Our results show that considering these finite-size effects is crucial and that the suggested correction allows for reliable computations.

Molecular Modeling of Thermodynamic and Transport Properties for CO2 and Aqueous Brines

Molecular simulation techniques using classical force-fields occupy the space between ab initio quantum mechanical methods and phenomenological correlations. In particular, Monte Carlo and molecular dynamics algorithms can be used to provide quantitative predictions of thermodynamic and transport properties of fluids relevant for geologic carbon sequestration at conditions for which experimental data are uncertain or not available. These methods can cover time and length scales far exceeding those of quantum chemical methods, while maintaining transferability and predictive power lacking from phenomenological correlations. The accuracy of predictions depends sensitively on the quality of the molecular models used. Many existing fixed-point-charge models for water and aqueous mixtures fail to represent accurately these fluid properties, especially when descriptions covering broad ranges of thermodynamic conditions are needed. Recent work on development of accurate models for water, CO₂, and dissolved salts, as well as their mixtures, is summarized in this Account. Polarizable models that can respond to the different dielectric environments in aqueous versus nonaqueous phases are necessary for predictions of properties over extended ranges of temperatures and pressures. Phase compositions and densities, activity coefficients of the dissolved salts, interfacial tensions, viscosities and diffusivities can be obtained in near-quantitative agreement to available experimental data, using relatively modest computational resources. In some cases, for example, for the composition of the CO₂-rich phase in coexistence with an aqueous phase, recent results from molecular simulations have helped discriminate among conflicting experimental data sets. The sensitivity of properties on the quality of the intermolecular interaction model varies significantly. Properties such as the phase compositions or electrolyte activity coefficients are much more sensitive than phase densities, viscosities, or component diffusivities. Strong confinement effects on physical properties in nanoscale media can also be directly obtained from molecular simulations. Future work on molecular modeling for CO₂ and aqueous brines is likely to be focused on more systematic generation of interaction models by utilizing quantum chemical as well as direct experimental measurements. New ion models need to be developed for use with the current generation of polarizable water models, including ion-ion interactions that will allow for accurate description of dense, mixed brines. Methods will need to be devised that go beyond the use of effective potentials for incorporation of quantum effects known to be important for water, and reactive force fields developed that can handle bond creation and breaking in systems with carbonate and silicate minerals. Another area of potential future work is the integration of molecular simulation methods in multiscale models for the chemical reactions leading to mineral dissolution and flow within the porous media in underground formations.