Predicting the solvation of organic compounds in aqueous environments: from alkanes and alcohols to pharmaceuticals

The development of accurate models to predict the solvation, solubility, and partitioning of nonpolar and amphiphilic compounds in aqueous environments remains an important challenge. We develop state-of-the-art group-interaction models that deliver an accurate description of the thermodynamic properties of alkanes and alcohols in aqueous solution. The group-contribution formulation of the statistical associating fluid theory based on potentials with a variable Mie form (SAFT-γ Mie) is shown to provide accurate predictions of the phase equilibria, including liquid–liquid equilibria, solubility, free energies of solvation, and other infinite-dilution properties. The transferability of the model is further exemplified with predictions of octanol–water partitioning and solubility for a range of organic and pharmaceutically relevant compounds. Our SAFT-γ Mie platform is reliable for the prediction of challenging properties such as mutual solubilities of water and organic compounds which can span over 10 orders of magnitude, while remaining generic in its applicability to a wide range of compounds and thermodynamic conditions. Our work sheds light on contradictory findings related to alkane–water solubility data and the suitability of models that do not account explicitly for polarity

New and extended parameterization of the thermodynamic model AIOMFAC: calculation of activity coefficients for organic-inorganic mixtures containing carboxyl, hydroxyl, carbonyl, ether, ester, alkenyl, alkyl, and aromatic functional groups

We present a new and considerably extended parameterization of the thermodynamic activity coefficient model AIOMFAC (Aerosol Inorganic-Organic Mixtures Functional groups Activity Coefficients) at room temperature. AIOMFAC combines a Pitzer-like electrolyte solution model with a UNIFAC-based group-contribution approach and explicitly accounts for interactions between organic functional groups and inorganic ions. Such interactions constitute the salt-effect, may cause liquid-liquid phase separation, and affect the gas-particle partitioning of aerosols. The previous AIOMFAC version was parameterized for alkyl and hydroxyl functional groups of alcohols and polyols. With the goal to describe a wide variety of organic compounds found in atmospheric aerosols, we extend here the parameterization of AIOMFAC to include the functional groups carboxyl, hydroxyl, ketone, aldehyde, ether, ester, alkenyl, alkyl, aromatic carbon-alcohol, and aromatic hydrocarbon. Thermodynamic equilibrium data of organic-inorganic systems from the literature are critically assessed and complemented with new measurements to establish a comprehensive database. The database is used to determine simultaneously the AIOMFAC parameters describing interactions of organic functional groups with the ions H^+, Li^+, Na^+, K^+, NH_(4)^+, Mg^(2+), Ca^(2+), Cl^−, Br^−, NO_(3)^−, HSO_(4)^−, and SO_(4)^(2−). Detailed descriptions of different types of thermodynamic data, such as vapor-liquid, solid-liquid, and liquid-liquid equilibria, and their use for the model parameterization are provided. Issues regarding deficiencies of the database, types and uncertainties of experimental data, and limitations of the model, are discussed. The challenging parameter optimization problem is solved with a novel combination of powerful global minimization algorithms. A number of exemplary calculations for systems containing atmospherically relevant aerosol components are shown. Amongst others, we discuss aqueous mixtures of ammonium sulfate with dicarboxylic acids and with levoglucosan. Overall, the new parameterization of AIOMFAC agrees well with a large number of experimental datasets. However, due to various reasons, for certain mixtures important deviations can occur. The new parameterization makes AIOMFAC a versatile thermodynamic tool. It enables the calculation of activity coefficients of thousands of different organic compounds in organic-inorganic mixtures of numerous components. Models based on AIOMFAC can be used to compute deliquescence relative humidities, liquid-liquid phase separations, and gas-particle partitioning of multicomponent mixtures of relevance for atmospheric chemistry or in other scientific fields

Cloud condensation nucleus (CCN) behavior of organic aerosol particles generated by atomization of water and methanol solutions

Cloud condensation nucleus (CCN) experiments were carried out for malonic acid, succinic acid, oxalacetic acid, DL-malic acid, glutaric acid, DL-glutamic acid monohydrate, and adipic acid, using both water and methanol as atomization solvents, at three operating supersaturations (0.11%, 0.21%, and 0.32%) in the Caltech three-column CCN instrument (CCNC3). Predictions of CCN behavior for five of these compounds were made using the Aerosol Diameter Dependent Equilibrium Model (ADDEM). The experiments presented here expose important considerations associated with the laboratory measurement of the CCN behavior of organic compounds. Choice of atomization solvent results in significant differences in CCN activation for some of the compounds studied, which could result from residual solvent, particle morphology differences, and chemical reactions between the particle and gas phases. Also, significant changes in aerosol size distribution occurred after classification in a differential mobility analyzer (DMA) for malonic acid and glutaric acid. Filter analysis of adipic acid atomized from methanol solution indicates that gas-particle phase reactions may have taken place after atomization and before the methanol was removed from the sample gas stream. Careful consideration of these experimental issues is necessary for successful design and interpretation of laboratory CCN measurements

Predicting Skin Permeability by means of Computational Approaches : Reliability and Caveats in Pharmaceutical Studies

© 2019 American Chemical Society.The skin is the main barrier between the internal body environment and the external one. The characteristics of this barrier and its properties are able to modify and affect drug delivery and chemical toxicity parameters. Therefore, it is not surprising that permeability of many different compounds has been measured through several in vitro and in vivo techniques. Moreover, many different in silico approaches have been used to identify the correlation between the structure of the permeants and their permeability, to reproduce the skin behavior, and to predict the ability of specific chemicals to permeate this barrier. A significant number of issues, like interlaboratory variability, experimental conditions, data set building rationales, and skin site of origin and hydration, still prevent us from obtaining a definitive predictive skin permeability model. This review wants to show the main advances and the principal approaches in computational methods used to predict this property, to enlighten the main issues that have arisen, and to address the challenges to develop in future research.Peer reviewedFinal Accepted Versio

Benchmarking the SPARC software program for estimating solubilities of naphthalene and anthracene in organic solvents

The SPARC software program was benchmarked for calculating the solubilities of two representative polyaromatic hydrocarbons (PAHs), naphthalene and anthracene, in a range of organic solvents at various temperatures. Although SPARC was able to reasonably approximate the solubilities of naphthalene in some organic solvents, gross errors were obtained for other solvents. For anthracene, poor prediction performance was observed in all solvents considered. Overall, the results suggest that SPARC is currently not suitable for accurately predicting the solubilities of representative PAHs relevant for the petroleum sector in various organic solvents

Effect of stirring on the safety of flammable liquid mixtures

Flash point is the most important variable employed to characterize fire and explosion hazard of liquids. The models developed for predicting the flash point of partially miscible mixtures in the literature to date are all based on the assumption of liquid-liquid equilibrium. In real-world environments, however, the liquid-liquid equilibrium assumption does not always hold, such as the collection or accumulation of waste solvents without stirring, where complete stirring for a period of time is usually used to ensure the liquid phases being in equilibrium. This study investigated the effect of stirring on the flash point behavior of binary partially miscible mixtures. Two series of partially miscible binary mixtures were employed to elucidate the effect of stirring. The first series was aqueous-organic mixtures, including water + 1-butanol, water + 2-butanol, water + isobutanol, water + 1-pentanol, and water + octane ; the second series was the mixtures of two flammable solvents, which included methanol + decane, methanol + 2,2,4-trimethylpentane, and methanol + octane. Results reveal that for binary aqueous-organic solutions the flash-point values of unstirred mixtures were located between those of the completely stirred mixtures and those of the flammable component. Therefore, risk assessment could be done based on the flammable component flash point value. However, for the assurance of safety, it is suggested to completely stir those mixtures before handling to reduce the risk

Modeling the gas-particle partitioning of secondary organic aerosol: the importance of liquid-liquid phase separation

The partitioning of semivolatile organic compounds between the gas phase and aerosol particles is an important source of secondary organic aerosol (SOA). Gas-particle partitioning of organic and inorganic species is influenced by the physical state and water content of aerosols, and therefore ambient relative humidity (RH), as well as temperature and organic loading levels. We introduce a novel combination of the thermodynamic models AIOMFAC (for liquid mixture non-ideality) and EVAPORATION (for pure compound vapor pressures) with oxidation product information from the Master Chemical Mechanism (MCM) for the computation of gas-particle partitioning of organic compounds and water. The presence and impact of a liquid-liquid phase separation in the condensed phase is calculated as a function of variations in relative humidity, organic loading levels, and associated changes in aerosol composition. We show that a complex system of water, ammonium sulfate, and SOA from the ozonolysis of α-pinene exhibits liquid-liquid phase separation over a wide range of relative humidities (simulated from 30% to 99% RH). Since fully coupled phase separation and gas-particle partitioning calculations are computationally expensive, several simplified model approaches are tested with regard to computational costs and accuracy of predictions compared to the benchmark calculation. It is shown that forcing a liquid one-phase aerosol with or without consideration of non-ideal mixing bears the potential for vastly incorrect partitioning predictions. Assuming an ideal mixture leads to substantial overestimation of the particulate organic mass, by more than 100% at RH values of 80% and by more than 200% at RH values of 95%. Moreover, the simplified one-phase cases stress two key points for accurate gas-particle partitioning calculations: (1) non-ideality in the condensed phase needs to be considered and (2) liquid-liquid phase separation is a consequence of considerable deviations from ideal mixing in solutions containing inorganic ions and organics that cannot be ignored. Computationally much more efficient calculations relying on the assumption of a complete organic/electrolyte phase separation below a certain RH successfully reproduce gas-particle partitioning in systems in which the average oxygen-to-carbon (O:C) ratio is lower than ~0.6, as in the case of α-pinene SOA, and bear the potential for implementation in atmospheric chemical transport models and chemistry-climate models. A full equilibrium calculation is the method of choice for accurate offline (box model) computations, where high computational costs are acceptable. Such a calculation enables the most detailed predictions of phase compositions and provides necessary information on whether assuming a complete organic/electrolyte phase separation is a good approximation for a given aerosol system. Based on the group-contribution concept of AIOMFAC and O:C ratios as a proxy for polarity and hygroscopicity of organic mixtures, the results from the α-pinene system are also discussed from a more general point of view

Influence of pH, Temperature and Impurities on the Solubility of an Active Pharmaceutical Ingredient (API)

Solubility, which defines the liquid /solid equilibrium, is a key parameter to control a crystallization process. This work is focused on the effects of pH, temperature and impurities on the aqueous solubility of an Active Pharmaceutical Ingredient (API).As the API is a weak acid (pKa = 3.7), its solubility increases with the pH. On the basis of the experimental curve of solubility, a model was defined to fit the evolution of the solubility as a function of pH. In the case of this compound, studies revealed a weak influence of the temperature in comparison with the pH. So, the solubility of the compound is slightly impacted by the temperature.Some experiments were carried out in order to compare the solubility of the API, at the same pH and temperature, for different concentrations of impurities found in the process. The results revealed a solubility increase in presence of acetic acid and a high solubility decrease in presence of sodium chloride. By carrying out experiments on common ions salts, the anion chloride Cl- has been identified as the cause of the solubility decrease