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Multi-criteria optimization is used for developing molecular models for ethylene carbonate (EC) and propylene carbonate (PC), organic solvents commonly used in Li-ion batteries. The molecular geometry and partial charges of the solvents are obtained from quantum mechanical calculations. Using a novel optimization strategy that combines systematic variations of the Lennard-Jones parameters with a reduced units approach, the models are fitted to experimental data on the liquid density, vapor pressure, relative permittivity, and self-diffusion coefficient. Since no experimental data for the self-diffusion coefficient of pure EC were available in the literature, they are measured in this work using a gradient-based nuclear magnetic resonance technique. For all pure component properties, excellent agreement between experiment and simulation is obtained. Moreover, the predictive capabilities of the new solvent models are assessed by comparison to experimental data for the liquid density and relative permittivity of mixtures of EC and PC. In addition, molecular models for the anions P F 6 − , B F 4 − , and C l O 4 − in solutions of their lithium electrolytes in PC are developed using experimental data on the solution densities. Finally, the self-diffusion coefficients of LiPF6 in PC and in aqueous solution are predicted and compared, showing that diffusion is much slower in the organic solution due to the formation of larger solvent shells around the ions. Furthermore, an analysis of the radial distribution functions in these solutions suggests that the ions have much less impact on the structure of the solvent PC than on water. [ABSTRACT FROM AUTHOR]

A set of molecular models for the alkali nitrates (LiNO3, NaNO3, KNO3, RbNO3, and CsNO3) in aqueous solutions is presented and used for predicting the thermophysical properties of these solutions with molecular dynamics simulations. The set of models is obtained from a combination of a model for the nitrate anion from the literature with a set of models for the alkali cations developed in previous works of our group. The water model is SPC/E and the Lorentz–Berthelot combining rules are used for describing the unlike interactions. This combination is shown to yield fair predictions of thermophysical and structural properties of the studied aqueous solutions, namely the density, the water activity and the mean ionic activity coefficient, the self-diffusion coefficients of the ions, and radial distribution functions, which were studied at 298 K and 1 bar; except for the density of the solutions of all five nitrates and the activity properties of solutions of NaNO3, which were also studied at 333 K. For calculating the water the activity and the mean ionic activity coefficient, the OPAS (osmotic pressure for the activity of selvents) method was applied. The new models extend an ion model family for the alkali halides developed in previous works of our group in a consistent way. [ABSTRACT FROM AUTHOR]

Molecular simulations enable the prediction of physicochemical properties of mixtures based on pair-interaction models of the pure components and combining rules to describe the unlike interactions. However, if no adjustment to experimental data is made, the existing combining rules often do not yield sufficiently accurate predictions of mixture data. To address this problem, adjustable binary parameters ξij describing the pair interactions in mixtures (i + j) are used. In this work, we present the first method for predicting ξij for unstudied mixtures based on a matrix completion method (MCM) from machine learning (ML). Considering molecular simulations of Henry's law constants as an example, we demonstrate that ξij for unstudied mixtures can be predicted with high accuracy. Using the predicted ξij significantly increases the accuracy of the Henry's law constant predictions compared to using the default ξij = 1. Our approach is generic and can be transferred to molecular simulations of other mixture properties and even to combining rules in equations of state, granting predictive access to the description of unlike intermolecular interactions. [ABSTRACT FROM AUTHOR]

In the present work, the application of dielectric barrier discharge (DBD) cold plasma technology for the partial oxidation of methane was systematically studied. Conversion of the reactants and selectivities were measured using an elaborate product analysis from a recent work by Müller et al. varying the reactant ratio in the feed, the mole fraction of the inert carrier gas argon in the feed, and the specific energy input at operating conditions close to ambient. The results from 20 new experiments carried out in the present work complement 23 previous experiments and provide an unprecedented comprehensive quantitative data set. This extends the available knowledge of partial oxidation of methane in DBD cold plasma considerably and is useful for testing mechanistic models. [ABSTRACT FROM AUTHOR]

Explosions of droplets that are caused by superheating of the liquid phase occur in many combustion processes but are difficult to investigate experimentally. We have studied this process for nanodroplets using non-equilibrium molecular dynamics simulations. Starting from an equilibrium state in which a spherical droplet is surrounded by a vapor phase, a local thermostat is used to impose a high temperature in a small control volume in the droplet center and the following process is studied for varying set temperatures. The fluid is modeled using the Lennard–Jones truncated and shifted potential. Depending on the set temperature, three different system responses were observed: (i) Low set temperatures lead to a shrinking of the droplet due to evaporation that follows the well-known d2 law. (ii) At intermediate set temperatures, a vapor bubble emerges in the droplet center and the liquid phase is formed into spherical shell that expands as the bubble inside of it grows. However, that spherical shell is only temporarily stable and eventually breaks apart. (iii) For high set temperatures, the abrupt and violent formation of the vapor bubble leads to an immediate breakup of the droplet. For case (ii), unexpected phenomena were observed. Oscillations in the diameter of the vapor bubble surrounded by the liquid film occurred. In some simulations, small holes formed temporarily in the liquid shell during its expansion, which closed again over the course of the simulation. Moreover, for one specific set temperature, a transition of the spherical droplet shell into a torus-like object was observed. [ABSTRACT FROM AUTHOR]

The concentration dependence of the dielectric constant and the density of 11 aqueous alkali halide solutions (LiCl, NaCl, KCl, RbCl, CsCl, LiI, NaI, KI, CsI, KF, and CsF) is investigated by molecular simulation. Predictions using eight non-polarizable ion force fields combined with the TIP4P/ε water model are compared to experimental data. The influence of the water model and the temperature on the results for the NaCl brine are also addressed. The TIP4P/ε water model improves the accuracy of dielectric constant predictions compared to the SPC/E water model. The solution density is predicted well by most ion models. Almost all ion force fields qualitatively capture the decline of the dielectric constant with the increase of concentration for all solutions and with the increase of temperature for NaCl brine. However, the sampled dielectric constant is mostly in poor quantitative agreement with experimental data. These results are related to the microscopic solution structure, ion pairing, and ultimately the force field parameters. Ion force fields with excessive contact ion pairing and precipitation below the experimental solubility limit generally yield higher dielectric constant values. An adequate reproduction of the experimental solubility limit should therefore be a prerequisite for further investigations of the dielectric constant of aqueous electrolyte solutions by molecular simulation. [ABSTRACT FROM AUTHOR]