Henry's law constant of hydrocarbons in air-water system: the cavity ovality effect on the non-electrostatic contribution term of solvation free energy

Solubilities of Ethylene and Carbon Dioxide Gases in Lithium-Ion Battery Electrolyte

During Li-ion battery operation, (electro)chemical side reactions occur within the cell that can promote or degrade performance. These complex reactions produce byproducts in the solid, liquid, and gas phases. Studying byproducts in these three phases can help optimize battery lifetimes. To relate the measured gas-phase byproducts to species dissolved in the liquid-phase, equilibrium proprieties such as the Henry's law constants are required. The present work implements a pressure decay experiment to determine the thermodynamic equilibrium concentrations between the gas and liquid phases for ethylene (C2H4) and carbon dioxide (CO2), which are two gases commonly produced in Li-ion batteries, with an electrolyte of 1.2 M LiPF6 in 3:7 wt/wt ethylene carbonate/ethyl methyl carbonate and 3 wt % fluoroethylene carbonate (15:25:57:3 wt % total composition). The experimentally measured pressure decay curve is fit to an analytical dissolution model and extrapolated to predict the final pressure at equilibrium. The relationship between the partial pressures and concentration of dissolved gas in electrolyte at equilibrium is then used to determine Henry's law constants of 2.0 × 104 kPa for C2H4 and k CO2 = 1.1 × 104 kPa for CO2. These values are compared to Henry's law constants predicted from density functional theory and show good agreement within a factor of 3.

In silico package models for deriving values of solute parameters in linear solvation energy relationships

Environmental partitioning influences fate, exposure and ecological risks of chemicals. Linear solvation energy relationship (LSER) models may serve as efficient tools for estimating environmental partitioning parameter values that are commonly deficient for many chemicals. Nonetheless, scarcities of empirical solute parameter values of LSER models restricted the application. This study developed and evaluated in silico methods and models to derive the values, in which excess molar refraction, molar volume and logarithm of hexadecane/air partition coefficient were computed from density functional theory; dipolarity/polarizability parameter, solute H-bond acidity and basicity parameters were predicted by quantitative structure-activity relationship models developed with theoretical molecular descriptors. New LSER models on four physicochemical properties relevant with environmental partitioning (n-octanol/water partition coefficients, n-octanol/air partition coefficients, water solubilities, sub-cooled liquid vapour pressures) were constructed using the in silico solute parameter values, which exhibited comparable performance with conventional LSER models using the empirical solute parameter values. The package models for deriving the LSER solute parameter values, with advantages that they are free of instrumental determinations, may lay the foundation for high-throughput estimating environmental partition parameter values of diverse organic chemicals.

Estimations of the thermodynamic properties of halogenated benzenes as they relate to their environment mobility

In this work, several simple new equations for predicting important environmental mobility properties, at T = 298.15 K, were derived for halogenated benzenes: standard Gibbs energy of hydration, aqueous solubility, octanol-water partition coefficients, and Henry's law constants. A discussion on our previous estimates of other related properties (standard Gibbs energy and vapor pressure of sublimation and of vaporization) and their relation with entropy of fusion is also presented. As we aimed to estimate these properties for any of the ca. 1500 halogenated benzenes that may exist theoretically, an equation for estimating the temperature of fusion was also derived, since some of the proposed predictive equations (solubility of solids and Gibbs energy of sublimation) require its knowledge. For the other estimated properties just the number of each halogen that replaces hydrogen atoms in the halogenated benzene is needed. It was found that the coefficients that multiply the number of halogen atoms in the predictive equations vary linearly with the volume of the halogen atom.

Prediction of Henry's Law Constants via group-specific quantitative structure property relationships

Henry's Law Constants (HLCs) for several hundred organic compounds in water at 25 °C were predicted by Quantitative Structure Property Relationship (QSPR) models, with the division of organic compounds into specific classes to yield more accurate models than generalised ones. Both multiple linear regression (MLR) and artificial neural network (ANN) versions of models were produced for three general cases, encompassing the entire data set; one used the six best descriptors, as determined by maximising the correlation coefficient; another used the twelve best descriptors in a similar manner, whilst the third used the same twelve descriptors as English and Carroll (2001). These achieved, respectively, root-mean square errors (RMSEs) of 0.719, 0.52 and 0.607 log(Hcc) units for the MLR version and 0.601, 0.394 and 0.431 for the test set of the ANN models, where Hcc is the ratio of the compound's concentration in the vapour phase to that in the liquid phase. These were compared with models for six specific chemical classes: (i) alkanes, (ii) cyclic alkanes, (iii) alkenes, (iv) halogenated compounds, (v) aldehydes, ketones and esters grouped together, and (vi) monoaromatics. These group-specific models had RMSEs of 0.153, 0.141. 0.097, 0.168, 0.122 and 0.104 respectively for the MLR versions and 0.684, 0.719, 0.856, 0.784, 0.875 and 0.861 for the test set of the ANN models. It was found that the class-specific models achieved lower RMSEs than the general models, when using MLR models. The use of ANN was found to improve the predictive accuracy of the general models but failed to improve that for the class-specific models vis-à-vis MLR.

Air-liquid partition coefficient for a diverse set of organic compounds: Henry's Law Constant in water and hexadecane

The SPARC vapor pressure and activity coefficient models were coupled to successfully estimate Henry's Law Constant (HLC) in water and in hexadecane for a wide range of organic compounds without modification to, or additional parametrization of, either SPARC model. The vapor pressure model quantifies the solute-solute intermolecular interactions in the pure liquid phase, whereas the activity coefficient model quantifies the solute-solvent and solvent-solvent (in addition to the solute-solute) interactions upon placing solute, i, in solvent, j. These intermolecular interactions are factored into dispersion, induction, dipole-dipole, and H-bonding components upon moving a solute molecule from the gas to the liquid phase. The SPARC HLC calculator so produced was tested and validated on the largest experimental HLC data set to date: 1356 organic solutes, spanning a wide range of functional groups, dipolarities and H-bonding capabilities, such as PAHs, PCBs,VOCs, amides, pesticides, and pharmaceuticals. The rms deviation errors for the calculated versus experimental log HLCs for 1222 compounds in water and 563 in hexadecane were 0.456 and 0.192 log [(mol/L)/(mol/L)] units, respectively, spanning a range of more than 13 and 20 log HLC dimensionless units for the compounds in water and hexadecane, respectively. The SPARC calculator web version is available for public use, free of charge, and can be accessed at http://sparc.chem.uga.edu.