Continuous Fractional Component Monte Carlo: An Adaptive Biasing Method for Open System Atomistic Simulations

The Impact of Metal Centers in the M-MOF-74 Series on Formic Acid Production

The confinement effect of porous materials on the thermodynamical equilibrium of the CO2 hydrogenation reaction presents a cost-effective alternative to transition metal catalysts. In metal-organic frameworks, the type of metal center has a greater impact on the enhancement of formic acid production than the scale of confinement resulting from the pore size. The M-MOF-74 series enables a comprehensive study of how different metal centers affect HCOOH production, minimizing the effect of pore size. In this work, molecular simulations were used to analyze the adsorption of HCOOH and the CO2 hydrogenation reaction in M-MOF-74, where M = Ni, Cu, Co, Fe, Mn, Zn. We combine classical simulations and density functional theory calculations to gain insights into the mechanisms that govern the low coverage adsorption of HCOOH in the surrounding of the metal centers of M-MOF-74. The impact of metal centers on the HCOOH yield was assessed by Monte Carlo simulations in the grand-canonical ensemble, using gas-phase compositions of CO2, H2, and HCOOH at chemical equilibrium at 298.15-800 K, 1-60 bar. The performance of M-MOF-74 in HCOOH production follows the same order as the uptake and the heat of HCOOH adsorption: Ni > Co > Fe > Mn > Zn > Cu. Ni-MOF-74 increases the mole fraction of HCOOH by ca. 105 times compared to the gas phase at 298.15 K, 60 bar. Ni-MOF-74 has the potential to be more economically attractive for CO2 conversion than transition metal catalysts, achieving HCOOH production at concentrations comparable to the highest formate levels reported for transition metal catalysts and offering a more valuable molecular form of the product.

Thermophysical Properties and Phase Behavior of CO2 with Impurities: Insight from Molecular Simulations

Experimentally determining thermophysical properties for various compositions commonly found in CO2 transportation systems is extremely challenging. To overcome this challenge, we performed Monte Carlo (MC) and Molecular Dynamics (MD) simulations of CO2 rich mixtures to compute thermophysical properties such as densities, thermal expansion coefficients, isothermal compressibilities, heat capacities, Joule-Thomson coefficients, speed of sound, and viscosities at temperatures of (235-313) K and pressures of (20-200) bar. We computed thermophysical properties of pure CO2 and CO2 rich mixtures with N2, Ar, H2, and CH4 as impurities of (1-10) mol % and showed good agreement with available Equations of State (EoS). We showed that impurities decrease the values of thermal expansion coefficients, isothermal compressibilities, heat capacities, and Joule-Thomson coefficients in the gas phase, while these values increase in the liquid and supercritical phases. In contrast, impurities increase the value of speed of sound in the gas phase and decrease it in the liquid and supercritical phases. We present an extensive data set of thermophysical properties for CO2 rich mixtures with various impurities, which will help to design the safe and efficient operation of CO2 transportation systems.

Effect of dissolved KOH and NaCl on the solubility of water in hydrogen: A Monte Carlo simulation study

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.

Donnan equilibrium in charged slit-pores from a hybrid nonequilibrium molecular dynamics/Monte Carlo method with ions and solvent exchange

Ion partitioning between different compartments (e.g., a porous material and a bulk solution reservoir), known as Donnan equilibrium, plays a fundamental role in various contexts such as energy, environment, or water treatment. The linearized Poisson-Boltzmann (PB) equation, capturing the thermal motion of the ions with mean-field electrostatic interactions, is practically useful to understand and predict ion partitioning, despite its limited applicability to conditions of low salt concentrations and surface charge densities. Here, we investigate the Donnan equilibrium of coarse-grained dilute electrolytes confined in charged slit-pores in equilibrium with a reservoir of ions and solvent. We introduce and use an extension to confined systems of a recently developed hybrid nonequilibrium molecular dynamics/grand canonical Monte Carlo simulation method ("H4D"), which enhances the efficiency of solvent and ion-pair exchange via a fourth spatial dimension. We show that the validity range of linearized PB theory to predict the Donnan equilibrium of dilute electrolytes can be extended to highly charged pores by simply considering renormalized surface charge densities. We compare with simulations of implicit solvent models of electrolytes and show that in the low salt concentrations and thin electric double layer limit considered here, an explicit solvent has a limited effect on the Donnan equilibrium and that the main limitations of the analytical predictions are not due to the breakdown of the mean-field description but rather to the charge renormalization approximation, because it only focuses on the behavior far from the surfaces.

Efficient generation of barrier crossing trajectories using approximate Brownian bridges

We examine continuous random walks that are conditioned to reach one region before another. These conditioned processes are used to generate stochastic trajectories for barrier crossing events, which are generally rare and difficult to sample. The processes are generated using a Brownian bridge technique, resulting in near perfect sampling efficiency without accruing error in the conditional statistics of the process. The construction requires the hitting probability or committer function, which is a solution to the backward Fokker-Planck equation, a partial-differential equation that can be difficult to solve through general means. Therefore, we derive a one-dimensional approximation through asymptotic methods for barrier crossing trajectories. We show that this approximation has a simple analytical representation and approaches the true solution as the barrier height increases. Brownian bridge trajectories generated with this approximate solution are then shown to result in accurate conditional statistics when used in conjunction with importance sampling, even in the case when potential energy barriers are not large. We show this idea's effectiveness by simulating rare events in a stochastic chemical reaction network (Schögl reaction) with multiple steady states. This methodology shows great promise for future implementation to simulate rare barrier crossing events for a wide variety of physical processes.

A Reverse Nonequilibrium Molecular Dynamics Algorithm for Coupled Mass and Heat Transport in Mixtures

We present a new method for introducing stable nonequilibrium concentration gradients in molecular dynamics simulations of mixtures. This method extends earlier reverse nonequilibrium molecular dynamics (RNEMD) methods, which use kinetic energy scaling moves to create temperature or velocity gradients. In the new scaled particle flux (SPF-RNEMD) algorithm, energies and forces are computed simultaneously for a molecule existing in two nonadjacent regions of a simulation box, and the system evolves under a linear combination of these interactions. A continuously increasing particle scaling variable is responsible for the migration of the molecule between the regions as the simulation progresses, allowing for simulations under an applied particle flux. To test the method, we investigate diffusivity in mixtures of identical but distinguishable particles and in a simple mixture of multiple Lennard-Jones particles. The resulting concentration gradients provide Fick diffusion constants for mixtures. We also discuss using the new method to obtain coupled transport properties using simultaneous particle and thermal fluxes to compute the temperature dependence of the diffusion coefficient and activation energies for diffusion from a single simulation. Lastly, we demonstrate the use of this new method in interfacial systems by computing the diffusive permeability of a molecular fluid moving through a nanoporous graphene membrane.

Mutual Diffusivities of Mixtures of Carbon Dioxide and Hydrogen and Their Solubilities in Brine: Insight from Molecular Simulations

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.

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.

The molecular scale mechanism of deposition ice nucleation on silver iodide

Heterogeneous ice nucleation is a ubiquitous process in the natural and built environment. Deposition ice nucleation, i.e. heterogeneous ice nucleation that - according to the traditional view - occurs in a subsaturated water vapor environment and in the absence of supercooled water on the solid, ice-forming surface, is among the most important ice formation processes in high-altitude cirrus and mixed-phase clouds. Despite its importance, very little is known about the mechanism of deposition ice nucleation at the microscopic level. This study puts forward an adsorption-based mechanism for deposition ice nucleation through results from a combination of atomistic simulations, experiments and theoretical modelling. One of the most potent laboratory surrogates of ice nucleating particles, silver iodide, is used as a substrate for the simulations. We find that water initially adsorbs in clusters which merge and grow over time to form layers of supercooled water. Ice nucleation on silver iodide requires at minimum the adsorption of 4 molecular layers of water. Guided by the simulations we propose the following fundamental freezing steps: (1) Water molecules adsorb on the surface, forming nanodroplets. (2) The supercooled water nanodroplets merge into a continuous multilayer when they grow to about 3 molecular layers thick. (3) The layer continues to grow until the critical thickness for freezing is reached. (4) The critical ice cluster continues to grow.

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%.

Calculating Thermodynamic Factors for Diffusion Using the Continuous Fractional Component Monte Carlo Method

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.

Metal-Organic Frameworks for Phthalate Capture

Indoor air contamination by phthalate ester (PAE) derivatives has become a significant concern since traces of PAEs can cause endocrine disruption, among other health issues. PAE abatement from the environment is thus mandatory to further ensure a good quality of indoor air. Herein, we explored the physisorption-based capture of volatile PAEs by metal-organic frameworks (MOFs). A high-throughput computational screening approach was first applied on databases compiling more than 20,000 MOF structures in order to identify the best MOFs for adsorbing traces of dimethyl phthalate (DMP), considered as a representative molecule of the family of PAE contaminants. Among the 20 top candidates, MOF-74(Ni), which combines substantial DMP uptake at the 10 ppm concentration level (∼0.20 g g-1) with high adsorption enthalpy at infinite dilution (-ΔHads(DMP),0 = 109.9 kJ mol-1), was revealed as an excellent porous material to capture airborne DMP. This prediction was validated by further experiments: gravimetric sorption isotherms were carried out on MOF-74(Ni), replacing DMP by dimethyl maleate (DMM), a molecule with a higher vapor pressure and indeed easier to manipulate compared to DMP while mimicking the adsorption behavior of DMP by MOFs, as evidenced by Monte Carlo calculations. Notably, saturation of DMM by MOF-74(Ni) (∼0.35 g g-1 at 343 K) occurs at very low equivalent concentration of the sorbate, i.e., 15 ppm, while half of the DMM molecules remain trapped in the MOF pores, even by heating the system up to 473 K under vacuum. This computational-experimental study reveals for the first time the potential of MOFs for the capture of phthalate ester contaminants as vapors of key importance to address indoor air quality issues.

Grand-canonical molecular dynamics simulations powered by a hybrid 4D nonequilibrium MD/MC method: Implementation in LAMMPS and applications to electrolyte solutions

Molecular simulations in an open environment, involving ion exchange, are necessary to study various systems, from biosystems to confined electrolytes. However, grand-canonical simulations are often computationally demanding in condensed phases. A promising method [L. Belloni, J. Chem. Phys. 151, 021101 (2019)], one of the hybrid nonequilibrium molecular dynamics/Monte Carlo algorithms, was recently developed, which enables efficient computation of fluctuating number or charge density in dense fluids or ionic solutions. This method facilitates the exchange through an auxiliary dimension, orthogonal to all physical dimensions, by reducing initial steric and electrostatic clashes in three-dimensional systems. Here, we report the implementation of the method in LAMMPS with a Python interface, allowing facile access to grand-canonical molecular dynamics simulations with massively parallelized computation. We validate our implementation with two electrolytes, including a model Lennard-Jones electrolyte similar to a restricted primitive model and aqueous solutions. We find that electrostatic interactions play a crucial role in the overall efficiency due to their long-range nature, particularly for water or ion-pair exchange in aqueous solutions. With properly screened electrostatic interactions and bias-based methods, our approach enhances the efficiency of salt-pair exchange in Lennard-Jones electrolytes by approximately four orders of magnitude, compared to conventional grand-canonical Monte Carlo. Furthermore, the acceptance rate of NaCl-pair exchange in aqueous solutions at moderate concentrations reaches about 3% at the maximum efficiency.

Two-Dimensional Energy Histograms as Features for Machine Learning to Predict Adsorption in Diverse Nanoporous Materials

A major obstacle for machine learning (ML) in chemical science is the lack of physically informed feature representations that provide both accurate prediction and easy interpretability of the ML model. In this work, we describe adsorption systems using novel two-dimensional energy histogram (2D-EH) features, which are obtained from the probe-adsorbent energies and energy gradients at grid points located throughout the adsorbent. The 2D-EH features encode both energetic and structural information of the material and lead to highly accurate ML models (coefficient of determination R2 ∼ 0.94-0.99) for predicting single-component adsorption capacity in metal-organic frameworks (MOFs). We consider the adsorption of spherical molecules (Kr and Xe), linear alkanes with a wide range of aspect ratios (ethane, propane, n-butane, and n-hexane), and a branched alkane (2,2-dimethylbutane) over a wide range of temperatures and pressures. The interpretable 2D-EH features enable the ML model to learn the basic physics of adsorption in pores from the training data. We show that these MOF-data-trained ML models are transferrable to different families of amorphous nanoporous materials. We also identify several adsorption systems where capillary condensation occurs, and ML predictions are more challenging. Nevertheless, our 2D-EH features still outperform structural features including those derived from persistent homology. The novel 2D-EH features may help accelerate the discovery and design of advanced nanoporous materials using ML for gas storage and separation in the future.

Closer Look at Adsorption of Sarin and Simulants on Metal-Organic Frameworks

The development of effective protection against exposure to chemical warfare agents (CWAs), such as sarin, relies on studies of its adsorption on the capturing materials and seeking candidates capable of adsorbing large amounts of sarin gas. Many metal-organic frameworks (MOFs) are promising materials for the effective capture and degradation of sarin and simulant substances. Among the simulants capable of mimicking thermodynamic properties of the agent, not all of them have been investigated on the ability to act similarly in the adsorption process, in particular, whether the agent and a simulant have similar mechanisms of binding to the MOF surface. Molecular simulation studies not only provide a safe way to investigate the aforementioned processes but can also help reveal the mechanisms of interactions between the adsorbents and the adsorbing compounds at the molecular level. We performed Monte Carlo simulations of the adsorption of sarin and three simulants, dimethyl methylphosphonate (DMMP), diisopropyl methylphosphonate (DIMP), and diisopropyl fluorophosphate (DIFP), on selected MOFs that have previously shown strong capabilities to adsorb sarin. On the basis of the calculated adsorption isotherms, enthalpy of adsorption, and radial distribution functions, we revealed common mechanisms among the particularly efficient adsorbents as well as the ability of simulants to mimic them. The findings can help in selecting a suitable simulant compound to study CWA adsorption on MOFs and guide further synthesis of efficient MOFs for the capture of organophosphorus compounds.

Enhanced Grand Canonical Sampling of Occluded Water Sites Using Nonequilibrium Candidate Monte Carlo

Water molecules play a key role in many biomolecular systems, particularly when bound at protein-ligand interfaces. However, molecular simulation studies on such systems are hampered by the relatively long time scales over which water exchange between a protein and solvent takes place. Grand canonical Monte Carlo (GCMC) is a simulation technique that avoids this issue by attempting the insertion and deletion of water molecules within a given structure. The approach is constrained by low acceptance probabilities for insertions in congested systems, however. To address this issue, here, we combine GCMC with nonequilibium candidate Monte Carlo (NCMC) to yield a method that we refer to as grand canonical nonequilibrium candidate Monte Carlo (GCNCMC), in which the water insertions and deletions are carried out in a gradual, nonequilibrium fashion. We validate this new approach by comparing GCNCMC and GCMC simulations of bulk water and three protein binding sites. We find that not only is the efficiency of the water sampling improved by GCNCMC but that it also results in increased sampling of ligand conformations in a protein binding site, revealing new water-mediated ligand-binding geometries that are not observed using alternative enhanced sampling techniques.

Alchemical Osmostat for Monte Carlo Simulation: Sampling Aqueous Electrolyte Solution in Open Systems

Molecular simulations involving electrolytes are usually performed at a fixed amount of salt ions in the simulation box, reproducing macroscopic concentration. Although this statement is valid in the bulk, the concentration of an electrolyte confined in nanoporous materials such as MOFs or zeolites is greatly affected and remains a priori unknown. The nanoporous material in equilibrium with the bulk electrolyte exchange water and ions at a given chemical potential Δμ in the semi-grand-canonical ensemble, that must be calibrated in order to determine the concentration in the nanoporous material. In this work, we propose an algorithm based on nonequilibrium candidate Monte Carlo (NCMC) moves to ultimately perform MC simulations in contact with a saline reservoir. First, we adapt the Widom insertion technique to calibrate the chemical potential by alchemically transmuting water molecules into ions by using NCMC moves. The chemical potential defines a Monte Carlo osmostat in the semi-grand-constant volume and temperature ensemble (Δμ, N, V, T) to be added in a Monte Carlo simulation where the number of ions fluctuates. In order to validate the method, we adapted the NCMC move to determine the free energy of water solvation and subsequently explore thermodynamics of electrolyte solvation at infinite dilution in water. Finally, we implemented the osmostat in MC simulations initialized with bulk water that are driven toward electrolyte solutions of similar concentration as the saline reservoir. Our results demonstrate that alchemical osmostat for MC simulation is a promising tool for use to sample electrolyte insertion in nanoporous materials.

Solubility of CO2 in Aqueous Formic Acid Solutions and the Effect of NaCl Addition: A Molecular Simulation Study

There is a growing interest in the development of routes to produce formic acid from CO₂, such as the electrochemical reduction of CO₂ to formic acid. The solubility of CO₂ in the electrolyte influences the production rate of formic acid. Here, the dependence of the CO₂ solubility in aqueous HCOOH solutions with electrolytes on the composition and the NaCl concentration was studied by Continuous Fractional Component Monte Carlo simulations at 298.15 K and 1 bar. The chemical potentials of CO₂, H₂O, and HCOOH were obtained directly from single simulations, enabling the calculation of Henry coefficients and subsequently considering salting in or salting out effects. As the force fields for HCOOH and H₂O may not be compatible due to the presence of strong hydrogen bonds, the Gibbs-Duhem integration test was used to test this compatibility. The combination of the OPLS/AA force field with a new set of parameters, in combination with the SPC/E force field for water, was selected. It was found that the solubility of CO₂ decreases with increasing NaCl concentration in the solution and increases with the increase of HCOOH concentration. This continues up to a certain concentration of HCOOH in the solution, after which the CO₂ solubility is high and the NaCl concentration has no significant effect.

A New Force Field for OH- for Computing Thermodynamic and Transport Properties of H2 and O2 in Aqueous NaOH and KOH Solutions

The thermophysical properties of aqueous electrolyte solutions are of interest for applications such as water electrolyzers and fuel cells. Molecular dynamics (MD) and continuous fractional component Monte Carlo (CFCMC) simulations are used to calculate densities, transport properties (i.e., self-diffusivities and dynamic viscosities), and solubilities of H2 and O2 in aqueous sodium and potassium hydroxide (NaOH and KOH) solutions for a wide electrolyte concentration range (0-8 mol/kg). Simulations are carried out for a temperature and pressure range of 298-353 K and 1-100 bar, respectively. The TIP4P/2005 water model is used in combination with a newly parametrized OH- force field for NaOH and KOH. The computed dynamic viscosities at 298 K for NaOH and KOH solutions are within 5% from the reported experimental data up to an electrolyte concentration of 6 mol/kg. For most of the thermodynamic conditions (especially at high concentrations, pressures, and temperatures) experimental data are largely lacking. We present an extensive collection of new data and engineering equations for H2 and O2 self-diffusivities and solubilities in NaOH and KOH solutions, which can be used for process design and optimization of efficient alkaline electrolyzers and fuel cells.

A data-driven and topological mapping approach for the a priori prediction of stable molecular crystalline hydrates

Predictions of the structures of stoichiometric, fractional, or nonstoichiometric hydrates of organic molecular crystals are immensely challenging due to the extensive search space of different water contents, host molecular placements throughout the crystal, and internal molecular conformations. However, the dry frameworks of these hydrates, especially for nonstoichiometric or isostructural dehydrates, can often be predicted from a standard anhydrous crystal structure prediction (CSP) protocol. Inspired by developments in the field of drug binding, we introduce an efficient data-driven and topologically aware approach for predicting organic molecular crystal hydrate structures through a mapping of water positions within the crystal structure. The method does not require a priori specification of water content and can, therefore, predict stoichiometric, fractional, and nonstoichiometric hydrate structures. This approach, which we term a mapping approach for crystal hydrates (MACH), establishes a set of rules for systematic determination of favorable positions for water insertion within predicted or experimental crystal structures based on considerations of the chemical features of local environments and void regions. The proposed approach is tested on hydrates of three pharmaceutically relevant compounds that exhibit diverse crystal packing motifs and void environments characteristic of hydrate structures. Overall, we show that our mapping approach introduces an advance in the efficient performance of hydrate CSP through generation of stable hydrate stoichiometries at low cost and should be considered an integral component for CSP workflows.

Effect of Branching on Mutual Solubility of Alkane-CO2 Systems by Molecular Simulations

Mutual solubilities of hydrocarbon-CO₂ systems are important in a broad range of applications. Experimental data and theoretical understanding of phase behavior of large hydrocarbon molecules and CO₂ are limited. This is especially true in relation to the molecular structure of hydrocarbons when the carbon number exceeds 12. In this work, the continuous fractional component Gibbs ensemble Monte Carlo simulations are used to investigate mutual solubility of different alkane and CO₂ systems and the molecular structure. We investigate the mutual solubility of n-decane, n-hexadecane, n-eicosane, and the corresponding structural isomers in the CO₂-rich and hydrocarbon-rich phase. The focus will be solubility of the heavy normal alkanes and their structural isomers in CO₂. The simulation results are verified by comparing the experimental data when measurements are available. The simulation of phase behavior of the n-decane-CO₂ system agrees with the experiments. We also present simulation results of n-hexadecane-CO₂ and n-eicosane-CO₂ systems away from the critical region partly due to the finite size effect. We establish that solubility of the hydrocarbons in CO₂ is improved by change of the molecular structure in heavier alkanes. The enhanced solubility is limited in decane isomers, but the isomers of hexadecane and eicosane show 2- to 3-time solubility enhancement. The molecular dynamics simulations suggest that the improvement is from a higher coordination number of CO₂ for methyl (CH₃) rather than for methylene (CH₂) groups. This study sets the stage for molecular engineering and synthesis of hydrocarbons that are soluble in CO₂ not only by considering functionality but also by changing the molecular structure. The solubility enhancement is the first step in viscosification of CO₂ which broadens the use of CO₂.

Modelling Sorption and Transport of Gases in Polymeric Membranes across Different Scales: A Review

Professor Giulio C. Sarti has provided outstanding contributions to the modelling of fluid sorption and transport in polymeric materials, with a special eye on industrial applications such as membrane separation, due to his Chemical Engineering background. He was the co-creator of innovative theories such as the Non-Equilibrium Theory for Glassy Polymers (NET-GP), a flexible tool to estimate the solubility of pure and mixed fluids in a wide range of polymers, and of the Standard Transport Model (STM) for estimating membrane permeability and selectivity. In this review, inspired by his rigorous and original approach to representing membrane fundamentals, we provide an overview of the most significant and up-to-date modeling tools available to estimate the main properties governing polymeric membranes in fluid separation, namely solubility and diffusivity. The paper is not meant to be comprehensive, but it focuses on those contributions that are most relevant or that show the potential to be relevant in the future. We do not restrict our view to the field of macroscopic modelling, which was the main playground of professor Sarti, but also devote our attention to Molecular and Multiscale Hierarchical Modeling. This work proposes a critical evaluation of the different approaches considered, along with their limitations and potentiality.

Crystallization of Flexible Chains of Tangent Hard Spheres under Full Confinement

We present results from extensive Monte Carlo simulations on the crystallization of athermal polymers under full confinement. Polymers are represented as freely jointed chains of tangent hard spheres of uniform size. Confinement is applied through the presence of flat, parallel, and impenetrable walls in all dimensions. We analyze crystallization as the summation of two contributions: one that occurs in the bulk volume of the system (bulk crystallization), and one on the wall surfaces (surface crystallization). Depending on volume fraction initially amorphous (disordered) hard-sphere chain packings transit to the stable crystal phase. The established ordered morphologies consist primarily of hexagonal close-packed (HCP) crystals in the bulk volume and of triangular (TRI) crystals on the surface. As in the case of athermal packings in the bulk (without confinement), a structural competition is observed between the 5-fold local symmetry and the formation of close-packed crystallites. Effectively, the full confinement inside a cube favors the growth of the HCP crystal, as the FCC one is quite incompatible with the imposed spatial constraints. Consequently, we observe the formation of noncompact ordered motifs which grow from the surface to the inner volume of the simulation cell. We further compare the 2D and 3D crystals formed by monomeric hard spheres under the same simulation conditions. Significant differences are observed at low densities that tend to diminish as concentration increases.

Microscopic Simulations of Electrochemical Double-Layer Capacitors

Electrochemical double-layer capacitors (EDLCs) are devices allowing the storage or production of electricity. They function through the adsorption of ions from an electrolyte on high-surface-area electrodes and are characterized by short charging/discharging times and long cycle-life compared to batteries. Microscopic simulations are now widely used to characterize the structural, dynamical, and adsorption properties of these devices, complementing electrochemical experiments and in situ spectroscopic analyses. In this review, we discuss the main families of simulation methods that have been developed and their application to the main family of EDLCs, which include nanoporous carbon electrodes. We focus on the adsorption of organic ions for electricity storage applications as well as aqueous systems in the context of blue energy harvesting and desalination. We finally provide perspectives for further improvement of the predictive power of simulations, in particular for future devices with complex electrode compositions.

Boundary-Monte Carlo Method for Neutral and Charged Confined Fluids

In this work, we describe a new Monte Carlo (MC) simulation method to investigate highly coupled fluids in confined geometries at a constant chemical potential. This method is based on so-called multi-scale Hamiltonian methods, wherein the chemical potential is determined using a more amenable Hamiltonian for a fluid in an "outer" region, which facilitates standard methods, such as grand canonical MC simulations or Widom's particle insertion method. The (inner region) fluid of interest is placed in diffusive contact with the simpler outer fluid via a boundary zone wherein the Hamiltonian is transformed. The current method utilizes an ideal fluid for the outer regions, which allows for implicit rather than explicit simulations. Only the boundary and inner region need explicit consideration; hence, the nomenclature used is boundary-Monte Carlo. We illustrate the utility of the method for simple neutral and charged fluids in cylindrical and planar pores. In the latter case, we use a dense room-temperature ionic liquid model and illustrate how the boundary zone establishes a proper Donnan equilibrium between inner and outer fluids in the presence of charged planar electrodes. Thus, the method allows direct calculation of properties such as the differential capacitance, without the need for additional difficult calculations of the requisite Donnan potential.

Brownian bridges for stochastic chemical processes-An approximation method based on the asymptotic behavior of the backward Fokker-Planck equation

A Brownian bridge is a continuous random walk conditioned to end in a given region by adding an effective drift to guide paths toward the desired region of phase space. This idea has many applications in chemical science where one wants to control the endpoint of a stochastic process-e.g., polymer physics, chemical reaction pathways, heat/mass transfer, and Brownian dynamics simulations. Despite its broad applicability, the biggest limitation of the Brownian bridge technique is that it is often difficult to determine the effective drift as it comes from a solution of a Backward Fokker-Planck (BFP) equation that is infeasible to compute for complex or high-dimensional systems. This paper introduces a fast approximation method to generate a Brownian bridge process without solving the BFP equation explicitly. Specifically, this paper uses the asymptotic properties of the BFP equation to generate an approximate drift and determine ways to correct (i.e., re-weight) any errors incurred from this approximation. Because such a procedure avoids the solution of the BFP equation, we show that it drastically accelerates the generation of conditioned random walks. We also show that this approach offers reasonable improvement compared to other sampling approaches using simple bias potentials.

Solubilities and Transport Properties of CO2, Oxalic Acid, and Formic Acid in Mixed Solvents Composed of Deep Eutectic Solvents, Methanol, and Propylene Carbonate

Recently, deep eutectic solvents (DES) have been considered as possible electrolytes for the electrochemical reduction of CO₂ to value-added products such as formic and oxalic acids. The applicability of pure DES as electrolytes is hindered by high viscosities. Mixtures of DES with organic solvents can be a promising way of designing superior electrolytes by exploiting the advantages of each solvent type. In this study, densities, viscosities, diffusivities, and ionic conductivities of mixed solvents comprising DES (i.e., reline and ethaline), methanol, and propylene carbonate were computed using molecular simulations. To provide a quantitative assessment of the affinity and mass transport of CO₂ and oxalic and formic acids in the mixed solvents, the solubilities and self-diffusivities of these solutes were also computed. Our results show that the addition of DES to the organic solvents enhances the solubilities of oxalic and formic acids, while the solubility of CO₂ in the ethaline-containing mixtures are in the same order of magnitude with the respective pure organic components. A monotonic increase in the densities and viscosities of the mixed solvents is observed as the mole fraction of DES in the mixture increases, with the exception of the density of ethaline-propylene carbonate which shows the opposite behavior due to the high viscosity of the pure organic component. The self-diffusivities of all species in the mixtures significantly decrease as the mole fraction of DES approaches unity. Similarly, the self-diffusivities of the dissolved CO₂ and the oxalic and formic acids also decrease by at least 1 order of magnitude as the composition of the mixture shifts from the pure organic component to pure DES. The computed ionic conductivities of all mixed solvents show a maximum value for mole fractions of DES in the range from 0.2 to 0.6 and decrease as more DES is added to the mixtures. Since for most mixtures studied here no prior experimental measurements exist, our findings can serve as a first data set based on which further investigation of DES-containing electrolyte solutions can be performed for the electrochemical reduction of CO₂ to useful chemicals.

Machine learning accelerated high-throughput screening of zeolites for the selective adsorption of xylene isomers

A combination of machine learning and high throughput simulation has identified several potential zeolite structures that appear to outperform the leading commercially used material and explained the key factors for high selectivity.

Reactive Grand-Canonical Monte Carlo Simulations for Modeling Hydration of MgCl2

Thermochemical heat-storage applications, based on the reversible endo-/exothermic hydration reaction of salts, are intensively investigated to search for compact heat-storage devices. To achieve a truly valuable storage system, progressively complex salts are investigated. For these salts, the equilibrium temperature and pressure conditions are not always easy to predict. However, these conditions are crucial for the design of thermochemical heat-storage systems. A biased grand-canonical Monte Carlo (GCMC) tool is developed, enabling the study of equilibrium conditions at the molecular level. The GCMC algorithm is combined with reactive force field molecular dynamics (ReaxFF), which allows bond formation within the simulation. The Weeks-Chandler-Andersen (WCA) potential is used to scan multiple trial positions for the GCMC algorithm at a small cost. The most promising trial positions can be selected for recomputation with the more expensive ReaxFF. The developed WCA-ReaxFF-GCMC tool was used to study the hydration of MgCl2·nH2O. The simulation results show a good agreement with experimental and thermodynamic equilibriums for multiple hydration levels. The hydration shows that water, present at the surface of crystalline salt, deforms the surface layers and promotes further hydration of these deformed layers. Additionally, the WCA-ReaxFF-GCMC algorithm can be used to study other, non-TCM-related, reactive sorption processes.

Simu-D: A Simulator-Descriptor Suite for Polymer-Based Systems under Extreme Conditions

We present Simu-D, a software suite for the simulation and successive identification of local structures of atomistic systems, based on polymers, under extreme conditions, in the bulk, on surfaces, and at interfaces. The protocol is built around various types of Monte Carlo algorithms, which include localized, chain-connectivity-altering, identity-exchange, and cluster-based moves. The approach focuses on alleviating one of the main disadvantages of Monte Carlo algorithms, which is the general applicability under a wide range of conditions. Present applications include polymer-based nanocomposites with nanofillers in the form of cylinders and spheres of varied concentration and size, extremely confined and maximally packed assemblies in two and three dimensions, and terminally grafted macromolecules. The main simulator is accompanied by a descriptor that identifies the similarity of computer-generated configurations with respect to reference crystals in two or three dimensions. The Simu-D simulator-descriptor can be an especially useful tool in the modeling studies of the entropy- and energy-driven phase transition, adsorption, and self-organization of polymer-based systems under a variety of conditions.

Computational Screening of Physical Solvents for CO2 Pre-combustion Capture

A computational scheme was used to screen physical solvents for CO₂ pre-combustion capture by integrating the commercial NIST database, an in-house computational database, chem-informatics, and molecular modeling. A commercially available screened hydrophobic solvent, diethyl sebacate, was identified from the screening with favorable physical properties and promising absorption performance. The promising performance to use diethyl sebacate in CO₂ pre-combustion capture has also been confirmed from experiments. Water loading in diethyl sebacate is very low, and therefore, water is kept with H₂ in the gas stream. The favorable CO₂ interaction with diethyl sebacate and the intermediate solvent free volume fraction leads to both high CO₂ solubility and high CO₂/H₂ solubility selectivity in diethyl sebacate. An in-house NETL computational database was built to characterize CO₂, H₂, N₂, and H₂O interactions with 202 different chemical functional groups. It was found that 13% of the functional groups belong to the strong interaction category with the CO₂ interaction energy between -15 and -21 kJ/mol; 62% of the functional groups interact intermediately with CO₂ (-8 to -15 kJ/mol). The remaining 25% of functional groups interact weakly with CO₂ (below -8 kJ/mol). In addition, calculations show that CO₂ interactions with the functional groups are stronger than N₂ and H₂ interactions but are weaker than H₂O interactions. The CO₂ and H₂O interactions with the same functional groups exhibit a very strong linear positive correlation coefficient of 0.92. The relationship between CO₂ and H₂ gas solubilities and solvent fractional free volume (FFV) has been systematically studied for seven solvents at 298.2 K. A skewed bell-shaped relation was obtained between CO₂ solubility and solvent FFV. When an organic compound has a density approximately 10% lower than its density at 298.2 K and 1 bar, it exhibits the highest CO₂ loading at that specific solvent density and FFV. Note that the solvent densities were varied using simulations, which are difficult to be obtained from the experiment. In contrast, H₂ solubility results exhibit an almost perfect positive linear correlation with the solvent FFV. The theoretical maximum and minimum physical CO₂ solubilities in any organic compound at 298.2 K were estimated to be 11 and 0.4 mol/MPa L, respectively. An examination of 182 experimental CO₂ physical solubility data and 29 simulated CO₂ physical solubilities shows that all the CO₂ physical solubility data are within the maximum and minimum with only a few exceptions. Finally, simulations suggest that in order to develop physical solvents with both high CO₂ solubility and high CO₂/H₂ solubility selectivity, the solvents should contain functional groups which are available to interact strongly with CO₂ while minimizing FFV.

Vapor pressures and vapor phase compositions of choline chloride urea and choline chloride ethylene glycol deep eutectic solvents from molecular simulation

Despite the widespread acknowledgment that deep eutectic solvents (DESs) have negligible vapor pressures, very few studies in which the vapor pressures of these solvents are measured or computed are available. Similarly, the vapor phase composition is known for only a few DESs. In this study, for the first time, the vapor pressures and vapor phase compositions of choline chloride urea (ChClU) and choline chloride ethylene glycol (ChClEg) DESs are computed using Monte Carlo simulations. The partial pressures of the DES components were obtained from liquid and vapor phase excess Gibbs energies, computed using thermodynamic integration. The enthalpies of vaporization were computed from the obtained vapor pressures, and the results were in reasonable agreement with the few available experimental data in the literature. It was found that the vapor phases of both DESs were dominated by the most volatile component (hydrogen bond donor, HBD, i.e., urea or ethylene glycol), i.e., 100% HBD in ChClEg and 88%-93% HBD in ChClU. Higher vapor pressures were observed for ChClEg compared to ChClU due to the higher volatility of ethylene glycol compared to urea. The influence of the liquid composition of the DESs on the computed properties was studied by considering different mole fractions (i.e., 0.6, 0.67, and 0.75) of the HBD. Except for the partial pressure of ethylene glycol in ChClEg, all the computed partial pressures and enthalpies of vaporization showed insensitivity toward the liquid composition. The activity coefficient of ethylene glycol in ChClEg was computed at different liquid phase mole fractions, showing negative deviations from Raoult's law.

New Features of the Open Source Monte Carlo Software Brick-CFCMC: Thermodynamic Integration and Hybrid Trial Moves

We present several new major features added to the Monte Carlo (MC) simulation code Brick-CFCMC for phase- and reaction equilibria calculations (https://gitlab.com/ETh_TU_Delft/Brick-CFCMC). The first one is thermodynamic integration for the computation of excess chemical potentials (μ^ex). For this purpose, we implemented the computation of the ensemble average of the derivative of the potential energy with respect to the scaling factor for intermolecular interactions (). Efficient bookkeeping is implemented so that the quantity is updated after every MC trial move with negligible computational cost. We demonstrate the accuracy and reliability of the calculation of μ^ex for sodium chloride in water. Second, we implemented hybrid MC/MD translation and rotation trial moves to increase the efficiency of sampling of the configuration space. In these trial moves, short Molecular Dynamics (MD) trajectories are performed to collectively displace or rotate all molecules in the system. These trajectories are accepted or rejected based on the total energy drift. The efficiency of these trial moves can be tuned by changing the time step and the trajectory length. The new trial moves are demonstrated using MC simulations of a viscous fluid (deep eutectic solvent).

Entropy scaling close to criticality: From simple to metallic systems

Entropy has recently drawn considerable interest both as a marker to detect the onset of phase transitions and as a reaction coordinate, or collective variable, to span phase transition pathways. We focus here on the behavior of entropy along the vapor-liquid phase coexistence and identify how the difference in entropy between the two coexisting phases vary in ideal and metallic systems along the coexistence curve. Using flat-histogram simulations, we determine the thermodynamic conditions of coexistence, critical parameters, including the critical entropy, and entropies along the binodal. We then apply our analysis to a series of systems that increasingly depart from ideality and adopt a metal-like character, through the gradual onset of the Friedel oscillation in an effective pair potential, and for a series of transition metals modeled with a many-body embedded-atoms force field. Projections of the phase boundary on the entropy-pressure and entropy-temperature planes exhibit two qualitatively different behaviors. While all systems modeled with an effective pair potential lead to an ideal-like behavior, the onset of many-body effects results in a departure from ideality and a markedly greater exponent for the variation of the entropy of vaporization with temperature away from the critical temperature.

Molecularly Informed Field Theories from Bottom-up Coarse-Graining

Polymer formulations possessing mesostructures or phase coexistence are challenging to simulate using atomistic particle-explicit approaches due to the disparate time and length scales, while the predictive capability of field-based simulations is hampered by the need to specify interactions at a coarser scale (e.g., χ-parameters). To overcome the weaknesses of both, we introduce a bottom-up coarse-graining methodology that leverages all-atom molecular dynamics to molecularly inform coarser field-theoretic models. Specifically, we use relative-entropy coarse-graining to parametrize particle models that are directly and analytically transformable into statistical field theories. We demonstrate the predictive capability of this approach by reproducing experimental aqueous poly(ethylene oxide) (PEO) cloud-point curves with no parameters fit to experimental data. This synergistic approach to multiscale polymer simulations opens the door to de novo exploration of phase behavior across a wide variety of polymer solutions and melt formulations.

Effect of Water Content on Thermodynamic Properties of Compressed Hydrogen

Force field-based molecular simulations were used to calculate thermal expansivities, heat capacities, and Joule-Thomson coefficients of binary (standard) hydrogen-water mixtures for temperatures between 366.15 and 423.15 K and pressures between 50 and 1000 bar. The mole fraction of water in saturated hydrogen-water mixtures in the gas phase ranges from 0.004 to 0.138. The same properties were calculated for pure hydrogen at 323.15 K and pressures between 100 and 1000 bar. Simulations were performed using the TIP3P and a modified TIP4P force field for water and the Marx, Vrabec, Cracknell, Buch, and Hirschfelder force fields for hydrogen. The vapor-liquid equilibria of hydrogen-water mixtures were calculated along the melting line of ice Ih, corresponding to temperatures between 264.21 and 272.4 K, using the TIP3P force field for water and the Marx force field for hydrogen. In this temperature range, the solubilities and the chemical potentials of hydrogen and water were obtained. Based on the computed solubility data of hydrogen in water, the freezing-point depression of water was computed ranging from 264.21 to 272.4 K. The modified TIP4P and Marx force fields were used to improve the solubility calculations of hydrogen-water mixtures reported in our previous study [Rahbari A.;J. Chem. Eng. Data2019, 64, 4103-4115] for temperatures between 323 and 423 K and pressures ranging from 100 to 1000 bar. The chemical potentials of ice Ih were calculated as a function of pressure between 100 and 1000 bar, along the melting line for temperatures between 264.21 and 272.4 K, using the IAPWS equation of state for ice Ih. We show that at low pressures, the presence of water has a large effect on the thermodynamic properties of compressed hydrogen. Our conclusions may have consequences for the energetics of a hydrogen refueling station using electrochemical hydrogen compressors.

Competitive Adsorption of Xylenes at Chemical Equilibrium in Zeolites

The separation of xylenes is one of the most important processes in the petrochemical industry. In this article, the competitive adsorption from a fluid-phase mixture of xylenes in zeolites is studied. Adsorption from both vapor and liquid phases is considered. Computations of adsorption of pure xylenes and a mixture of xylenes at chemical equilibrium in several zeolite types at 250 °C are performed by Monte Carlo simulations. It is observed that shape and size selectivity entropic effects are predominant for small one-dimensional systems. Entropic effects due to the efficient arrangement of xylenes become relevant for large one-dimensional systems. For zeolites with two intersecting channels, the selectivity is determined by a competition between enthalpic and entropic effects. Such effects are related to the orientation of the methyl groups of the xylenes. m-Xylene is preferentially adsorbed if xylenes fit tightly in the intersection of the channels. If the intersection is much larger than the adsorbed molecules, p-xylene is preferentially adsorbed. This study provides insight into how the zeolite topology can influence the competitive adsorption and selectivity of xylenes at reaction conditions. Different selectivities are observed when a vapor phase is adsorbed compared to the adsorption from a liquid phase. These insight have a direct impact on the design criteria for future applications of zeolites in the industry. MRE-type and AFI-type zeolites exclusively adsorb p-xylene and o-xylene from the mixture of xylenes in the liquid phase, respectively. These zeolite types show potential to be used as high-performing molecular sieves for xylene separation and catalysis.

Chemical Potential Differences in the Macroscopic Limit from Fluctuations in Small Systems

We present a new method for computing chemical potential differences of macroscopic systems by sampling fluctuations in small systems. The small system method, presented by Schnell et al. [Schnell et al., J. Phys. Chem. B, 2011, 115, 10911], is used to create small embedded systems from molecular dynamics simulations, in which fluctuations of the number of particles are sampled. The sampled fluctuations represent the Boltzmann distributed probability of the number of particles. The overlapping region of two such distributions, sampled from two different systems, is used to compute their chemical potential difference. Since the thermodynamics of small systems is known to deviate from the classical thermodynamic description, the particle distributions will deviate from the macroscopic behavior as well. We show how this can be utilized to calculate the size dependence of chemical potential differences and eventually extract the chemical potential difference in the thermodynamic limit. The macroscopic chemical potential difference is determined with a relative error of 3% in systems containing particles that interact through the truncated and shifted Lennard-Jones potential. In addition to computing chemical potential differences in the macroscopic limit directly from molecular dynamics simulation, the new method provides insights into the size dependency that is introduced to intensive properties in small systems.

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.

Entropy in Molecular Fluids: Interplay between Interaction Complexity and Criticality

Using flat-histogram simulations, we calculate the entropy of molecular fluids along the vapor-liquid phase boundary. Our simulation approach is based on the evaluation of the canonical and grand-canonical partition functions, which, in turn, provide access to entropy through the statistical mechanics formalism. The results allow us to determine the critical entropy of molecular fluids and to uncover that the transition occurs symmetrically from an entropic standpoint. This can best be seen through the patterns exhibited by the thermodynamic variables temperature and pressure when plotted against the entropy of the coexisting phases. This behavior is found to hold for apolar, quadrupolar, and dipolar fluids. Finally, we identify functional forms that characterize the relation between thermodynamic variables and entropy along the coexistence curve up to the critical point.

Brick-CFCMC: Open Source Software for Monte Carlo Simulations of Phase and Reaction Equilibria Using the Continuous Fractional Component Method

We present a new molecular simulation code, Brick-CFCMC, for performing Monte Carlo simulations using state-of-the-art simulation techniques. The Continuous Fractional Component (CFC) method is implemented for simulations in the NVT/NPT ensembles, the Gibbs Ensemble, the Grand-Canonical Ensemble, and the Reaction Ensemble. Molecule transfers are facilitated by the use of fractional molecules which significantly improve the efficiency of the simulations. With the CFC method, one can obtain phase equilibria and properties such as chemical potentials and partial molar enthalpies/volumes directly from a single simulation. It is possible to combine trial moves from different ensembles. This enables simulations of phase equilibria in a system where also a chemical reaction takes place. We demonstrate the applicability of our software by investigating the esterification of methanol with acetic acid in a two-phase system.

Deep Eutectic Solvents Mixed with Fluorinated Refrigerants for Absorption Refrigeration: A Molecular Simulation Study

Molecular simulations were performed to evaluate mixtures of fluorinated refrigerants with deep eutectic solvents (DESs), for potential use in single-effect absorption refrigeration cycles that use low quality waste heat sources at temperatures of ∼80 °C. The refrigerants considered were the hydrofluorocarbon R245fa and the hydrofluoroolefins R1234zeE and HFO1336mzzE, whereas the DESs evaluated were 1:2 molar mixtures of choline chloride with either ethylene glycol (ethaline) or levulinic acid (levuline) as hydrogen bond donors (HBDs). Assuming the same cycle operating conditions, the waste heat cycle efficiency η was computed for all working fluid mixtures from molecular simulation results of the mixture densities and Henry's law constants of the refrigerants in the DESs, coupled with phase equilibrium calculations and the enthalpies of the pure refrigerants. The largest efficiency was obtained for the mixture R245fa-ethaline (η = 6.82), followed by R245fa-levuline (η = 4.64) and HFO1336mzzE-levuline (η = 2.10). These modest efficiency values could be further increased by tailoring the cycle operating conditions to each particular refrigerant-DES system, as well as optimizing our choice of working fluid mixtures, neither of which we attempted in this study. Strong interactions were observed between the chlorine anions and some of the hydrogen atoms of the refrigerants, but in general the cation-refrigerant and HBD-refrigerant interactions are weaker compared to the refrigerant-refrigerant interactions. Refrigerant molecules have the largest diffusivities and make the cations, anions and HBD to move faster compared to systems of DESs without refrigerant; in general, species in refrigerant-ethaline mixtures have larger diffusivities compared to those for refrigerant-levuline mixtures. We also computed waste heat cycle efficiencies for the same R134a-DES mixtures studied in our previous work, finding significant differences between the efficiencies determined from molecular simulation data and those determined before using the COSMO-RS approach using two standard parametrizations. This observation suggests that further work is needed to improve the accuracy of the COSMO-RS predictions for these systems.

Multiple Free Energy Calculations from Single State Point Continuous Fractional Component Monte Carlo Simulation Using Umbrella Sampling

We introduce an alternative method to perform free energy calculations for mixtures at multiple temperatures and pressures from a single simulation, by combining umbrella sampling and the continuous fractional component Monte Carlo method. One can perform a simulation of a mixture at a certain pressure and temperature and accurately compute the chemical potential at other pressures and temperatures close to the simulation conditions. This method has the following advantages: (1) Accurate estimates of the chemical potential as a function of pressure and temperature are obtained from a single state simulation without additional postprocessing. This can potentially reduce the number of simulations of a system for free energy calculations for a specific temperature and/or pressure range. (2) Partial molar volumes and enthalpies are obtained directly from the estimated chemical potentials. We tested our method for a Lennard-Jones system, aqueous mixtures of methanol at T = 298 K and P = 1 bar, and a mixture of ammonia, nitrogen, and hydrogen at T = 573 K and P = 800 bar. For pure methanol (N = 410 molecules), we observed that the estimated chemical potentials from umbrella sampling are in excellent agreement with the reference values obtained from independent simulations, for ΔT = ±15 K and ΔP = 100 bar (with respect to the simulated system). For larger systems, this range becomes smaller because the relative fluctuations of energy and volume become smaller. Without sufficient overlap, the performance of the method will become poor especially for nonlinear variations of the chemical potential.