Due to the intermittency of renewable energy sources, alkaline water electrolyzers are typically operated at partial load compared to the nominal design value. It is well-known that gas crossover is dominant at low current densities leading to higher anodic hydrogen content and higher cathodic oxygen content in the separator tanks. High anodic hydrogen content is tantamount to loss of product hydrogen which results in an explosive atmosphere in the gas phase if the volumetric hydrogen content in oxygen exceeds 4%. We have developed a transient model of a multi-cell stack which can describe the operation of the electrolyzer with mixed electrolyte flows (anolyte and catholyte), separated flows, or a combination thereof (dynamic switching). This is a major extension of the steady-state model developed by Haug et al. (International Journal of Hydrogen Energy, 2017, 42, 15,689–15707). In sharp contrast to the steady-state model by Haug et al., the transient model can calculate the gas crossover as the operating conditions (e.g. electrolyte flow cycles) dynamically change in time. Depending on the size of the stack and the separator tanks, the model estimates different rates for impurities to build up. The transient model is validated using independent experimental results by Haug et al. and Brauns et al. (Electrochimica Acta, 2022, 404, 139,715) The results show that the dynamic model can follow experimental results for fluctuating current densities for a period of several days. We found that the dynamic response and transition time to steady state depend significantly on the geometrical volume of the gas separators with respect to the single-cell stack. For a multi-cell stack, we find that the impurities build-up faster when increasing the number of cells in the stack. This model serves as a tool for sizing and process management of the electrolyzer system and the separator tanks especially with respect to explosion safety.

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.

One of the important parameters in water management of proton exchange membranes is the electro-osmotic drag (EOD) coefficient of water. The value of the EOD coefficient is difficult to justify, and available literature data on this for Nafion membranes show scattering from in experiments and simulations. Here, we use a classical all-atom model to compute the EOD coefficient and thermodynamic properties of water from molecular dynamics simulations for temperatures between 330 and 420 K, and for different water contents between λ = 5 and λ = 20. λ is the ratio between the moles of water molecules to the moles of sulfonic acid sites. This classical model does not capture the Grotthuss mechanism; however, it is shown that it can predict the EOD coefficient within the range of experimental values for λ = 5 where the vehicular mechanism dominates proton transfer. For λ > 5, the Grotthuss mechanism becomes dominant. To obtain the EOD coefficient, average velocities of water and ions are computed by imposing different electric fields to the system. Our results show that the velocities of water and hydronium scale linearly with the electric field, resulting in a constant ratio of ca. 0.4 within the error bars. We find that the EOD coefficient of water linearly increases from 2 at λ = 5 to 8 at λ = 20 and the results are not sensitive to temperature. The EOD coefficient at λ = 5 is within the range of experimental values, confirming that the model can capture the vehicular transport of protons well. At λ = 20, due to the absence of proton hopping in the model, the EOD coefficient is overestimated by a factor of 3 compared to experimental values. To analyze the interactions between water and Nafion, the partial molar enthalpies and partial molar volumes of water are computed from molecular dynamics simulations. At different water uptakes, multiple linear regression is used on raw simulation data within a narrow composition range of water inside the Nafion membrane. The partial molar volumes and partial molar excess enthalpies of water asymptotically approach the molar volumes and molar excess enthalpies of pure water for water uptakes above 5. This confirms the model can capture the bulklike behavior of water in the Nafion at high water uptakes.

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.;et al. J. Chem. Eng. Data 2019, 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.

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 (μex). 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 (⟨∂U∂λ⟩). Efficient bookkeeping is implemented so that the quantity ∂U∂λ is updated after every MC trial move with negligible computational cost. We demonstrate the accuracy and reliability of the calculation of μex 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).

In this paper, we review recent advances in the Continuous Fractional Component Monte Carlo (CFCMC) methodology and present a historic overview of the most important developments that have led to this method. The CFCMC method has gained attention for Monte Carlo simulations of adsorption at high loading, and phase and reaction equilibria of dense systems. It has recently been extended to reactive systems. The main features of the CFCMC method are: (1) Increased molecule exchange efficiency between different phases in single and multicomponent (reactive) systems, which improves the efficiency and accuracy of phase equilibria simulations at high densities; (2) Direct calculation of the chemical potential from a single simulation; (3) Direct calculation of partial molar properties from a single simulation. The developed simulation techniques are incorporated in the open-source molecular simulation software Brick-CFCMC.

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.

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.

Partial molar properties are of fundamental importance for understanding properties of non-ideal mixtures. Josephson and co-workers (Mol. Phys. 2019, 117, 3589–3602) used least squares multiple linear regression to obtain partial molar properties in open constant-pressure ensembles. Assuming composition-independent partial molar properties for the narrow composition range encountered throughout simulation trajectories, we rigorously prove the equivalence of two approaches for computing thermodynamic derivatives in open ensembles of an n-component system: (1) multiple linear regression, and (2) thermodynamic fluctuations. Multiple linear regression provides a conceptually simple and computationally efficient way of computing thermodynamic derivatives for multicomponent systems. We show that in the reaction ensemble, the reaction enthalpy can be computed directly by simple multiple linear regression of the enthalpy as a function of the number of reactant molecules. Non-linear regression and a Gaussian process model taking into account the compositional dependence of partial molar properties further support that multiple linear regression captures the correct physics.

The CFCMC simulation methodology considers an expanded ensemble to solve the problem of low insertion/deletion acceptance probabilities in open ensembles. It allows for a direct calculation of the chemical potential by binning of the coupling parameter λ and using the probabilities p(λ = 0) and p(λ = 1), which require extrapolation. Here, we show that this extrapolation leads to systematic errors when the distribution p(λ) is steep. We propose an alternative binning scheme which improves the accuracy of computed chemical potentials. We also investigate the use of multiple fractional molecules needed in simulations of multiple components, and show that these fractional molecules are very weakly correlated and that calculations of chemical potentials are not affected. The statistics of Boltzmann averages in systems with multiple fractional molecules is shown to be poor. Good agreement is found between CFCMC averages (uncorrected for the bias) and Boltzmann averages when the number of fractional molecules is less than 1% of the total number of all molecules. We found that, in dense systems, biased averages have a smaller uncertainty compared to Boltzmann averages.

Hydrogen is one of the most popular alternatives for energy storage. Because of its low volumetric energy density, hydrogen should be compressed for practical storage and transportation purposes. Recently, electrochemical hydrogen compressors (EHCs) have been developed that are capable of compressing hydrogen up to P = 1000 bar, and have the potential of reducing compression costs to 3 kWh/kg. As EHC compressed hydrogen is saturated with water, the maximum water content in gaseous hydrogen should meet the fuel requirements issued by the International Organization for Standardization (ISO) when refuelling fuel cell electric vehicles. The ISO 14687-2:2012 standard has limited the water concentration in hydrogen gas to 5 μmol water per mol hydrogen fuel mixture. Knowledge on the vapor liquid equilibrium of H₂O-H₂ mixtures is crucial for designing a method to remove H₂O from compressed H₂. To the best of our knowledge, the only experimental high pressure data (P > 300 bar) for the H₂O-H₂ phase coexistence is from 1927 [J. Am. Chem. Soc., 1927, 49, 65-78]. In this paper, we have used molecular simulation and thermodynamic modeling to study the phase coexistence of the H₂O-H₂ system for temperatures between T = 283 K and T = 423 K and pressures between P = 10 bar and P = 1000 bar. It is shown that the Peng-Robinson equation of state and the Soave Redlich-Kwong equation of state with van der Waals mixing rules fail to accurately predict the equilibrium coexistence compositions of the liquid and gas phase, with or without fitted binary interaction parameters. We have shown that the solubility of water in compressed hydrogen is adequately predicted using force-field-based molecular simulations. The modeling of phase coexistence of H₂O-H₂ mixtures will be improved by using polarizable models for water. In the Supporting Information, we present a detailed overview of available experimental vapor-liquid equilibrium and solubility data for the H₂O-H₂ system at high pressures.

The combination of the TraPPE and OPLS/2016 force fields with five water models, TIP3P, SPC/E, OPC, TIP4P/2005 and TIP4P/EW was used to compute mixing enthalpies, excess chemical potentials and activity coefficients of water and methanol. Excess chemical potentials and activity coefficients were computed in an expanded version of the NPT ensemble. We found the best agreement between experimental data for all the computed properties of water–methanol mixtures for the TIP4P/2005-TraPPE force fields. The performance of the spherical cutoff methods in MC and MD simulations was compared to the Ewald summation. The radial distribution functions obtained from the Ewald summation and the Damped-Shifted Force (DSF) method were in excellent agreement. Numerical artifacts appeared at the cutoff radius when the original Wolf method was used to calculate the electrostatic interactions. The calculated excess mixing enthalpies, excess chemical potentials, and activity coefficients of water and methanol obtained from the Wolf method were in good agreement with the DSF method. Our simulation results show that the numerical artifacts of the original Wolf method have little effect for energy calculations in aqueous methanol mixtures.

The effect of confinement on the equilibrium reactive system containing nitrogen dioxide and dinitrogen tetroxide is studied by molecular simulation and the reactive Monte Carlo (RxMC) approach. The bulk-phase reaction was successfully reproduced and five all-silica zeolites (i.e. FAU, FER, MFI, MOR, and TON) with different topologies were selected to study their adoption behavior. Dinitrogen tetroxide showed a stronger affinity than nitrogen dioxide in all the zeolites due to size effects, but exclusive adsorption sites in MOR allowed the adsorption of nitrogen dioxide with no competition at these sites. From the study of the adsorption isotherms and isobars of the reacting mixture, confinement enhanced the formation of dimers over the full range of pressure and temperature, finding the largest deviations from bulk fractions at low temperature and high pressure. The channel size and shape of the zeolite have a noticeable influence on the dinitrogen tetroxide formation, being more important in MFI, closely followed by TON and MOR, and finally FER and FAU. Preferential adsorption sites in MOR lead to an unusually strong selective adsorption towards nitrogen dioxide, demonstrating that the topological structure has a crucial influence on the composition of the mixture and must be carefully considered in systems containing nitrogen dioxide.

An alternative method for calculating partial molar excess enthalpies and partial molar volumes of components in Monte Carlo (MC) simulations is developed. This method combines the original idea of Frenkel, Ciccotti, and co-workers with the recent continuous fractional component Monte Carlo (CFCMC) technique. The method is tested for a system of Lennard–Jones particles at different densities. As an example of a realistic system, partial molar properties of a [NH₃, N₂, H₂] mixture at chemical equilibrium are computed at different pressures ranging from P = 10 to 80 MPa. Results obtained from MC simulations are compared to those obtained from the PC-SAFT Equation of State (EoS) and the Peng–Robinson EoS. Excellent agreement is found between the results obtained from MC simulations and PC-SAFT EoS, and significant differences were found for PR EoS modelling. We find that the reaction is much more exothermic at higher pressures.

Syngas is an important intermediate in the chemical process industry. It is used for the production of hydrocarbons, acetic acid, oxo-alcohols, and other chemicals. Depending on the target product and stoichiometry of the reaction, an optimum (molar) ratio between hydrogen and carbon monoxide (H₂:CO) in the syngas is required. Different technologies are available to control the H₂:CO molar ratio in the syngas. The combination of steam reforming of methane (SRM) and the water-gas shift (WGS) reaction is the most established approach for syngas production. In this work, to adjust the H₂:CO ratio, we have considered formic acid (FA) as a source for both hydrogen and carbon monoxide. Using thermochemical equilibrium calculations, we show that the syngas composition can be controlled by cofeeding formic acid into the SRM process. The H₂:CO molar ratio can be adjusted to a value between one and three by adjusting the concentration of FA in the reaction feed. At steam reforming conditions, typically above 900 K, FA can decompose to water and carbon monoxide and/or to hydrogen and carbon dioxide. Our results show that cofeeding FA into the SRM process can adjust the H₂:CO molar ratio in a single step. This can potentially be an alternative to the WGS process.

Chemical potentials of coexisting gas and liquid phases for water, methanol, hydrogen sulphide and carbon dioxide for the temperature range (Formula presented.) K to (Formula presented.) K are computed using two different methodologies: (1) Widom’s test particle insertion (WTPI) method in the conventional Gibbs Ensemble (GE), and (2) the Continuous Fractional Component Gibbs Ensemble Monte Carlo (CFCGE MC) method. It is shown that the WTPI method fails to accurately compute the chemical potentials of water and methanol in the liquid phase at low temperatures, while accurate chemical potentials in the liquid phase are computed using CFCGE MC method. For the CFCGE MC method, the statistical uncertainty for computed chemical potentials of water and methanol in the liquid phase are considerably smaller compared to the WTPI method. For the water models considered in this study (SPC, TIP3P-EW, TIP4P-EW, TIP5P-EW), computed excess chemical potentials based on three-site models are in better agreement with the chemical potentials computed from an empirical equation of state from the NIST database. For water, orientational biasing is applied during test particle insertion to check whether certain orientations of test particle are energetically unfavourable. A two-dimensional Overlapping Distribution Method (ODM) in the NVT ensemble is derived for this purpose. It is shown that failure of the WTPI method for systems with a strong hydrogen bonding network does not depend on orientation of the test molecule in that system. For all systems in this study, the WTPI method breaks down when the void fraction of the system drops below approximately 0.50.

It is shown that ensemble averages computed in the Gibbs Ensemble with Continuous Fractional Component Monte Carlo (CFCMC GE) are different from those computed in the conventional Gibbs Ensemble (GE). However, it is possible to compute averages corresponding to the conventional GE while performing simulations in the CFCMC GE. In this way, one can benefit from the nice features of CFCMC GE (e.g. more efficient particle exchange) and at the same time compute the ensemble averages that correspond to the conventional GE. As a case study, the equilibrium pressure and densities of the systems of 256 and 512 LJ particles at different reduced temperatures ((Formula presented.)) are computed in the conventional GE and CFCMC GE. The validity of the expressions derived for computation of the thermodynamic pressure and densities corresponding to the conventional GE and computed in the CFCMC GE is examined numerically. The thermodynamic pressure in the conventional GE and CFCMC GE typically differs by at most 4%. It is shown that a very good estimate of the average pressure and densities corresponding to the conventional GE can be obtained by performing simulation in CFCMC GE and ignoring the contributions of the fractional molecule. It is also shown that the fractional molecule does not have an influence on the structure of the liquid, even for very small system sizes (e.g. 40 particles). The approach used here to compute the equilibrium pressure and densities of the conventional GE using the CFCMC GE can be easily extended to other thermodynamic properties and other ensembles.