Transferable Potentials for Phase Equilibria. 10. Explicit-Hydrogen Description of Substituted Benzenes and Polycyclic Aromatic Compounds

The explicit-hydrogen version of the transferable potentials for phase equilibria (TraPPE-EH) force field is extended to various substituted benzenes through the parametrization of the exocyclic groups F, Cl, Br, CN, and OH and to polycyclic aromatic hydrocarbons through the parametrization of the aromatic linker carbon atom for multiple rings. The linker carbon together with the TraPPE-EH parameters for aromatic heterocycles constitutes a force field for fused-ring heterocycles. Configurational-bias Monte Carlo simulations in the Gibbs ensemble were carried out to compute vapor–liquid coexistence curves for fluorobenzene; chlorobenzene; bromobenzene; di-, tri-, and hexachlorobenzene isomers; 2-chlorofuran; 2-chlorothiophene; benzonitrile; phenol; dihydroxybenzene isomers; 1,4-benzoquinone; naphthalene; naphthalene-2-carbonitrile; naphthalen-2-ol; quinoline; benzo­[<i>b</i>]­thiophene; benzo­[<i>c</i>]­thiophene; benzoxazole; benzisoxazole; benzimidazole; benzothiazole; indole; isoindole; indazole; purine; anthracene; and phenanthrene. The agreement with the limited experimental data is very satisfactory, with saturated liquid densities and vapor pressures reproduced to within 1.5% and 15%, respectively. The mean unsigned percentage errors in the normal boiling points, critical temperatures, and critical densities are 0.9%, 1.2%, and 1.4%, respectively. Additional simulations were carried out for binary systems of benzene/benzonitrile, benzene/phenol, and naphthalene/methanol to illustrate the transferability of the developed potentials to binary systems containing compounds of different polarity and hydrogen-bonding ability. A detailed analysis of the liquid-phase structures is provided for selected neat systems and binary mixtures

Assessment and Optimization of Configurational-Bias Monte Carlo Particle Swap Strategies for Simulations of Water in the Gibbs Ensemble

Particle swap moves between phases are usually the rate-limiting step for Gibbs ensemble Monte Carlo (GEMC) simulations of fluid phase equilibria at low reduced temperatures because the acceptance probabilities for these moves can become very low for molecules with articulated architecture and/or highly directional interactions. The configurational-bias Monte Carlo (CBMC) technique can greatly increase the acceptance probabilities, but the efficiency of the CBMC algorithm is influenced by multiple parameters. In this work we assess the performance of different CBMC strategies for GEMC simulations using the SPC/E and TIP4P water models at 283, 343, and 473 K, demonstrate that much higher acceptance probabilities can be achieved than previously reported in the literature, and make recommendations for CBMC strategies leading to optimal efficiency

Transferable Potentials for Phase Equilibria. 10. Explicit-Hydrogen Description of Substituted Benzenes and Polycyclic Aromatic Compounds

The explicit-hydrogen version of the transferable potentials for phase equilibria (TraPPE-EH) force field is extended to various substituted benzenes through the parametrization of the exocyclic groups F, Cl, Br, CN, and OH and to polycyclic aromatic hydrocarbons through the parametrization of the aromatic linker carbon atom for multiple rings. The linker carbon together with the TraPPE-EH parameters for aromatic heterocycles constitutes a force field for fused-ring heterocycles. Configurational-bias Monte Carlo simulations in the Gibbs ensemble were carried out to compute vapor–liquid coexistence curves for fluorobenzene; chlorobenzene; bromobenzene; di-, tri-, and hexachlorobenzene isomers; 2-chlorofuran; 2-chlorothiophene; benzonitrile; phenol; dihydroxybenzene isomers; 1,4-benzoquinone; naphthalene; naphthalene-2-carbonitrile; naphthalen-2-ol; quinoline; benzo­[<i>b</i>]­thiophene; benzo­[<i>c</i>]­thiophene; benzoxazole; benzisoxazole; benzimidazole; benzothiazole; indole; isoindole; indazole; purine; anthracene; and phenanthrene. The agreement with the limited experimental data is very satisfactory, with saturated liquid densities and vapor pressures reproduced to within 1.5% and 15%, respectively. The mean unsigned percentage errors in the normal boiling points, critical temperatures, and critical densities are 0.9%, 1.2%, and 1.4%, respectively. Additional simulations were carried out for binary systems of benzene/benzonitrile, benzene/phenol, and naphthalene/methanol to illustrate the transferability of the developed potentials to binary systems containing compounds of different polarity and hydrogen-bonding ability. A detailed analysis of the liquid-phase structures is provided for selected neat systems and binary mixtures

Prediction of Vapor–Liquid Coexistence Properties and Critical Points of Polychlorinated Biphenyls from Monte Carlo Simulations with the TraPPE–EH Force Field

Gibbs ensemble Monte Carlo simulations using the explicit-hydrogen version of the transferable potentials for phase equilibria (TraPPE–EH) force field were carried out to predict the vapor–liquid coexistence and critical properties of biphenyl, monochlorinated biphenyls, and of 16 polychlorinated biphenyls. The predictions are in very good agreement with the limited experimental data. Transferring the TraPPE–EH Lennard-Jones parameters from benzene to construct biphenyl yields predicted critical properties and normal boiling temperature with an average deviation of less than 1 %. The saturated vapor pressures for biphenyl, 2-chorobiphenyl, and 4-chlorobiphenyl fall within 10 % of the experimental data. Overall, the critical temperatures increase nearly linearly with the number of chlorine substituents and are correlated with the dipole moment for the monochlorinated isomers. In contrast, 4,4′-dichlorobiphenyl, the most elongated compound, exhibits the highest critical temperature among the disubstituted biphenyls

TraPPE-zeo: Transferable Potentials for Phase Equilibria Force Field for All-Silica Zeolites

The transferable potentials for phase equilibria (TraPPE) force field is extended to all-silica zeolites. This novel force field is parametrized to match the experimental adsorption isotherms of <i>n</i>-heptane, propane, carbon dioxide, and ethanol with the Lennard-Jones parameters for sorbate–framework interactions determined in a consistent manner using the Lorentz–Berthelot combining rules as for other parts of the TraPPE force field. The TraPPE-zeo force field allows for accurate predictions for both adsorption and diffusion of alkanes, alcohols, carbon dioxide, and water over a wide range of pressures and temperatures. In order to achieve transferability to a wider range of molecule types, ranging from nonpolar to dipolar and hydrogen-bonding compounds, Lennard-Jones interaction sites and partial charges are placed at both the oxygen and the silicon atoms of the zeolite lattice, which allows for a better balance of dispersive and first-order electrostatic interactions than is achievable with the Lennard-Jones potential used only for the oxygen atoms. The use of the Lorentz–Berthelot combining rules for unlike interactions makes the TraPPE-zeo force field applicable to any sorbate as long as the relevant TraPPE sorbate–sorbate parameters are available. The TraPPE-zeo force field allows for greatly improved predictive power compared to force fields that explicitly tabulate the individual cross-interaction parameters

Development of the Transferable Potentials for Phase Equilibria Model for Hydrogen Sulfide

The transferable potentials for phase equilibria force field is extended to hydrogen sulfide. The pure-component and binary vapor–liquid equilibria with methane and carbon dioxide and the liquid-phase relative permittivity are used for the parametrization of the Lennard–Jones (LJ) and Coulomb interactions, and models with three and four interaction sites are considered. For the three-site models, partial point charges are placed on the sites representing the three atoms, while the negative partial charge is moved to an off-atom site for the four-site models. The effect of molecular shape is probed using either only a single LJ interaction site on the sulfur atom or adding sites also on the hydrogen atoms. This procedure results in four distinct models, but only those with three LJ sites can accurately reproduce all properties considered for the parametrization. These two are further assessed for predictions of the liquid-phase structure, the lattice parameters and relative permittivity for the face-centered-cubic solid, and the triple point. An effective balance between LJ interactions and the dipolar and quadrupolar terms of the first-order electrostatic interactions is struck in order to obtain a four-site model that describes the condensed-phase properties and the phase equilibria with high accuracy

Using the <i>k</i>‑d Tree Data Structure to Accelerate Monte Carlo Simulations

The <i>k</i>-d tree data structure is implemented in a Monte Carlo (MC) molecular simulation program to accelerate the range search for particles or interaction sites within the cutoff distance when Lennard-Jones and Coulomb interactions are computed. MC simulations are performed for different molecules in various ensembles to assess the efficiency enhancements due to the <i>k</i>-d tree data structure. It is found that the use of <i>k</i>-d trees accelerates significantly simulations for Lennard-Jones particles in the <i>NVT</i> and <i>NVT</i>-Gibbs ensembles and for <i>n</i>-butane and 2,4,6,8,10,12,14,16,18,20,22-undecamethylpentacosane represented by the TraPPE–UA force field in the <i>NpT</i> ensemble. Simulations for TraPPE–UA ethanol in the <i>NpT</i> ensemble and for the rigid TIP4P water model in the Gibbs ensemble gain slightly in efficiency with the <i>k</i>-d tree, whereas simulations for TIP4P water in the <i>NpT</i> ensemble do not benefit from the use of the <i>k</i>-d tree. The speed-up can be attributed to the reduction in the number of distance calculations in the range search from scaling as O(N) to O(log2⁡N). In addition, these tests suggest that the efficiency gain from the use of the <i>k</i>-d tree data structure depends on the flexibility of the molecular model (requiring configurational-bias MC moves to sample changes in conformation), on the ensemble (with open ensembles requiring special MC moves to aid particle transfers), and on the number of interaction sites per molecule (with compact multisite models not seeing an efficiency gain). Overall, the use of the <i>k</i>-d tree data structure can substantially enhance MC simulation efficiency for a variety of systems, and it will enable simulations for larger system sizes in the future

Deconstructing Hydrogen-Bond Networks in Confined Nanoporous Materials: Implications for Alcohol–Water Separation

Essential topological indices of the hydrogen-bond networks of water, methanol, ethanol, and their binary mixtures adsorbed in microporous silicalite-1 (a hydrophobic zeolite with potential application for biofuel processing) are analyzed and compared to their bulk liquid counterparts. These include the geodesic distribution (the shortest H-bond pathways between molecular vertices), the average length, the geodesic index, the orientation and distance of the adsorbate to the interior of the zeolite, and the sorbate–sorbate and sorbate–sorbent distributions of H-bonds. In combination, they describe how the H-bond networks are altered when going from the bulk to the confined silicalite-1 environment. The speciation of the adsorbed compounds is quantified in terms of their network connectivity, revealing that pure water has a high probability of forming long, contiguous H-bonded chains in silicalite-1 at high loading, while alcohols form small dimeric/trimeric clusters. The extent to which the H-bond network of binary water–alcohol systems is altered relative to either unary system is quantified, demonstrating an enhanced interconnectivity that is reflected in the tendency of individual H₂O molecules to become co-adsorbed with alcohol clusters in the zeolite framework. Selectivity for the alcohol over water diminishes with increasing alcohol loading as the H-bonded clusters serve as favorable adsorption sites for H₂O

Understanding Diffusion in Hierarchical Zeolites with House-of-Cards Nanosheets

Introducing mesoporosity to conventional microporous sorbents or catalysts is often proposed as a solution to enhance their mass transport rates. Here, we show that diffusion in these hierarchical materials is more complex and exhibits non-monotonic dependence on sorbate loading. Our atomistic simulations of <i>n</i>-hexane in a model system containing microporous nanosheets and mesopore channels indicate that diffusivity can be smaller than in a conventional zeolite with the same micropore structure, and this observation holds true even if we confine the analysis to molecules completely inside the microporous nanosheets. Only at high sorbate loadings or elevated temperatures, when the mesopores begin to be sufficiently populated, does the overall diffusion in the hierarchical material exceed that in conventional microporous zeolites. Our model system is free of structural defects, such as pore blocking or surface disorder, that are typically invoked to explain slower-than-expected diffusion phenomena in experimental measurements. Examination of free energy profiles and visualization of molecular diffusion pathways demonstrates that the large free energy cost (mostly enthalpic in origin) for escaping from the microporous region into the mesopores leads to more tortuous diffusion paths and causes this unusual transport behavior in hierarchical nanoporous materials. This knowledge allows us to re-examine zero-length-column chromatography data and show that these experimental measurements are consistent with the simulation data when the crystallite size instead of the nanosheet thickness is used for the nominal diffusional length

Energetics of Atmospherically Implicated Clusters Made of Sulfuric Acid, Ammonia, and Dimethyl Amine

The formation of atmospheric aerosol particles through clustering of condensable vapors is an important contributor to the overall concentration of these atmospheric particles. However, the details of the nucleation process are not yet well understood and are difficult to probe by experimental means. Computational chemistry is a powerful tool for gaining insights about the nucleation mechanism. Here, we report accurate electronic structure calculations of the potential energies of small clusters made from sulfuric acid, ammonia, and dimethylamine. We also assess and validate the accuracy of less expensive methods that might be used for the calculation of the binding energies of larger clusters for atmospheric modeling. The PW6B95-D3 density-functional-plus-molecular-mechanics calculation with the MG3S basis set stands out as yielding excellent accuracy while still being affordable for very large clusters