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

Atomic-Scale Insights into the Phase Behavior of Carbon Dioxide and Water from 313 to 573 K and 8 to 30 MPa

We performed molecular dynamics (MD) simulations of CO2 + H2O systems by employing widely used force fields (EPM2, TraPPE, and PPL models for CO2; SPC/E and TIP4P/2005 models for H2O). The phase behavior observed in our MD simulations is consistent with the coexistence lines obtained from previous experiments and SAFT-based theoretical models for the equations of state. Our structural analysis reveals a pronounced correlation between phase transitions and the structural orderliness. Specifically, the coordination number of Ow (oxygen in H2O) around other Ow significantly correlates with phase changes. In contrast, coordination numbers pertaining to the CO2 molecules show less sensitivity to the thermodynamic state of the system. Furthermore, our data indicate that a predominant number of H2O molecules exist as monomers without forming hydrogen bonds, particularly in a CO2-rich mixture, signaling a breakdown in the hydrogen bond network's orderliness, as evidenced by a marked decrease in tetrahedrality. These insights are crucial for a deeper atomic-level understanding of phase behaviors, contributing to the well-grounded design of CO2 injection under high-pressure and high-temperature conditions, where an atomic-scale perspective of the phase behavior is still lacking.

Accurate Free Energies of Aqueous Electrolyte Solutions from Molecular Simulations with Non-polarizable Force Fields

Non-polarizable force fields fail to accurately predict free energies of aqueous electrolytes without compromising the predictive ability for densities and transport properties. A new approach is presented in which (1) TIP4P/2005 water and scaled charge force fields are used to describe the interactions in the liquid phase and (2) an additional Effective Charge Surface (ECS) is used to compute free energies at zero additional computational expense. The ECS is obtained using a single temperature-independent charge scaling parameter per species. Thereby, the chemical potential of water and the free energies of hydration of various aqueous salts (e.g., NaCl and LiCl) are accurately described (deviations less than 5% from experiments), in sharp contrast to calculations where the ECS is omitted (deviations larger than 20%). This approach enables accurate predictions of free energies of aqueous electrolyte solutions using non-polarizable force fields, without compromising liquid-phase properties.

Machine Learning-Based Interfacial Tension Equations for (H2 + CO2)-Water/Brine Systems over a Wide Range of Temperature and Pressure

Large-scale underground hydrogen storage (UHS) plays a vital role in energy transition. H2-brine interfacial tension (IFT) is a crucial parameter in structural trapping in underground geological locations and gas-water two-phase flow in subsurface porous media. On the other hand, cushion gas, such as CO2, is often co-injected with H2 to retain reservoir pressure. Therefore, it is imperative to accurately predict the (H2 + CO2)-water/brine IFT under UHS conditions. While there have been a number of experimental measurements on H2-water/brine and (H2 + CO2)-water/brine IFT, an accurate and efficient (H2 + CO2)-water/brine IFT model under UHS conditions is still lacking. In this work, we use molecular dynamics (MD) simulations to generate an extensive (H2 + CO2)-water/brine IFT databank (840 data points) over a wide range of temperature (from 298 to 373 K), pressure (from 50 to 400 bar), gas composition, and brine salinity (up to 3.15 mol/kg) for typical UHS conditions, which is used to develop an accurate and efficient machine learning (ML)-based IFT equation. Our ML-based IFT equation is validated by comparing to available experimental data and other IFT equations for various systems (H2-brine/water, CO2-brine/water, and (H2 + CO2)-brine/water), rendering generally good performance (with R2 = 0.902 against 601 experimental data points). The developed ML-based IFT equation can be readily applied and implemented in reservoir simulations and other UHS applications.

Thermal conductivity and structural behavior of confined H2from molecular dynamics simulation

In this work, we perform equilibrium molecular dynamics simulation to study the thermal conductivity of hydrogen molecules (H2) under extreme confinement within graphene nanochannel. We analyze the structural behavior of H2molecules inside the nanochannel and also examine the effect of nanochannel height, the number of H2molecules, and temperature of the system on the thermal conductivity. Our results reveal that H2molecules exhibit a strong propensity for absorption onto the nanochannel wall, consequently forming a dense packed layer in close to the wall. This phenomenon significantly impacts the thermal conductivity of the confined system. We made a significant discovery, revealing a strong correlation between the mass density near the nanochannel wall and the thermal conductivity. This finding highlights the crucial role played by the density near the wall in determining the thermal conductivity behavior. Surprisingly, the average thermal conductivity for nanochannels with a height (h) less than 27 Å exhibited an astonishing increase of over 12 times when compared to the bulk. Moreover, we observe that increasing the nanochannel height, while the number of H2molecules fixed, leads to a notable decrease in thermal conductivity. Furthermore, we investigate the influence of temperature on thermal conductivity. Our simulations demonstrate that higher temperature enhance the thermal conductivity due to increased phonon activity and energy states, facilitating more efficient heat transfer and higher thermal conductivity. To gain deeper insights into the factors affecting thermal conductivity, we explored the phonon density of states. Studying the behavior of hydrogen in confined environments can offer valuable insights into its transport properties and its potential for industrial applications.

Molecular modeling of interfacial properties of the hydrogen + water + decane mixture in three-phase equilibrium

The understanding of interfacial phenomena between H2 and geofluids is of great importance for underground H2 storage, but requires further study. We report the first investigation on the three-phase fluid mixture containing H2, H2O, and n-C10H22. Molecular dynamics simulation and PC-SAFT density gradient theory are employed to estimate the interfacial properties under various conditions (temperature ranges from 298 to 373 K and pressure is up to around 100 MPa). Our results demonstrate that interfacial tensions (IFTs) of the H2-H2O interface in the H2 + H2O + C10H22 three-phase mixture are smaller than IFTs in the H2 + H2O two-phase mixture. This decrement of IFT can be attributed to C10H22 adsorption in the interface. Importantly, H2 accumulates in the H2O-C10H22 interface in the three-phase systems, which leads to weaker increments of IFT with increasing pressure compared to IFTs in the water + C10H22 two-phase mixture. In addition, the IFTs of the H2-C10H22 interface are hardly influenced by H2O due to the limited amount of H2O dissolved in nonaqueous phases. Nevertheless, positive surface excesses of H2O are seen in the H2-C10H22 interfacial region. Furthermore, the values of the spreading coefficient are mostly negative revealing the presence of the three-phase contact for the H2 + H2O + C10H22 mixture under studied conditions.

Interfacial Tension-Temperature-Pressure-Salinity Relationship for the Hydrogen-Brine System under Reservoir Conditions: Integration of Molecular Dynamics and Machine Learning

Hydrogen (H2) underground storage has attracted considerable attention as a potentially efficient strategy for the large-scale storage of H2. Nevertheless, successful execution and long-term storage and withdrawal of H2 necessitate a thorough understanding of the physical and chemical properties of H2 in contact with the resident fluids. As capillary forces control H2 migration and trapping in a subsurface environment, quantifying the interfacial tension (IFT) between H2 and the resident fluids in the subsurface is important. In this study, molecular dynamics (MD) simulation was employed to develop a data set for the IFT of H2-brine systems under a wide range of thermodynamic conditions (298-373 K temperatures and 1-30 MPa pressures) and NaCl salinities (0-5.02 mol·kg-1). For the first time to our knowledge, a comprehensive assessment was carried out to introduce the most accurate force field combination for H2-brine systems in predicting interfacial properties with an absolute relative deviation (ARD) of less than 3% compared with the experimental data. In addition, the effect of the cation type was investigated for brines containing NaCl, KCl, CaCl2, and MgCl2. Our results show that H2-brine IFT decreases with increasing temperature under any pressure condition, while higher NaCl salinity increases the IFT. A slight decrease in IFT occurs when the pressure increases. Under the impact of cation type, Ca2+ can increase IFT values more than others, i.e., up to 12% with respect to KCl. In the last step, the predicted IFT data set was used to provide a reliable correlation using machine learning (ML). Three white-box ML approaches of the group method of data handling (GMDH), gene expression programming (GEP), and genetic programming (GP) were applied. GP demonstrates the most accurate correlation with a coefficient of determination (R2) and absolute average relative deviation (AARD) of 0.9783 and 0.9767%, respectively.

Computation of Electrical Conductivities of Aqueous Electrolyte Solutions: Two Surfaces, One Property

In this work, we computed electrical conductivities under ambient conditions of aqueous NaCl and KCl solutions by using the Einstein-Helfand equation. Common force fields (charge q = ±1 e) do not reproduce the experimental values of electrical conductivities, viscosities, and diffusion coefficients. Recently, we proposed the idea of using different charges to describe the potential energy surface (PES) and the dipole moment surface (DMS). In this work, we implement this concept. The equilibrium trajectories required to evaluate electrical conductivities (within linear response theory) were obtained by using scaled charges (with the value q = ±0.75 e) to describe the PES. The potential parameters were those of the Madrid-Transport force field, which accurately describe viscosities and diffusion coefficients of these ionic solutions. However, integer charges were used to compute the conductivities (thus describing the DMS). The basic idea is that although the scaled charge describes the ion-water interaction better, the integer charge reflects the value of the charge that is transported due to the electric field. The agreement obtained with experiments is excellent, as for the first time electrical conductivities (and the other transport properties) of NaCl and KCl electrolyte solutions are described with high accuracy for the whole concentration range up to their solubility limit. Finally, we propose an easy way to obtain a rough estimate of the actual electrical conductivity of the potential model under consideration using the approximate Nernst-Einstein equation, which neglects correlations between different ions.