COSMO-RS solute partition ratios for solvent mixtures of unknown composition: Henry's law constants as descriptors for mixture sigma profiles

Henry's law constants (H) for selected probe molecules have been used as descriptors to estimate the COSMO-RS sigma profiles of solvents and solvent mixtures. Henry's law constants were calculated with COSMOtherm for small sets of probe molecules in 155 organic solvents (training set), and these constants subsequently used as descriptors to model the solvent sigma profiles with 61 multiple linear regression (MLR) equations. Subsequent input into COSMOtherm of weighted basis molecule solvent mixtures whose sigma profiles closely matched those modelled for the training set solvents allowed estimation of air-solvent and water-solvent partition ratios for solutes in solvents and solvent mixtures without input of the solvent or solvent mixture identity. The best performing model had 16 descriptors and gave both a training and test set average root-mean square error (RMSE) of 0.008 and an average relative square error (RSE) of 0.07. Partition ratios (K) were then generated for a test set of 251 additional organic solute molecules in solvent/water media where solvents were test set compounds and H constants for the same probe molecules were used as descriptors. The best performing sigma profile model yielded log K RMSE values ranging from 0.17 to 0.92. Finally, this approach was applied to several mixtures ranging from simple binary mixtures to two mixtures considered to be of unknown or variable composition, complex reaction productions or biological materials (UVCBs), namely gasoline and an essential oil mixture. Mixture/water partition ratios were estimated for 251 solutes giving log K RMSE values ranging from 0.24 to 0.88.

The System of Self-Consistent Models: The Case of Henry's Law Constants

Data on Henry's law constants make it possible to systematize geochemical conditions affecting atmosphere status and consequently triggering climate changes. The constants of Henry's law are desired for assessing the processes related to atmospheric contaminations caused by pollutants. The most important are those that are capable of long-term movements over long distances. This ability is closely related to the values of Henry's law constants. Chemical changes in gaseous mixtures affect the fate of atmospheric pollutants and ecology, climate, and human health. Since the number of organic compounds present in the atmosphere is extremely large, it is desirable to develop models suitable for predictions for the large pool of organic molecules that may be present in the atmosphere. Here, we report the development of such a model for Henry's law constants predictions of 29,439 compounds using the CORAL software (2023). The statistical quality of the model is characterized by the value of the coefficient of determination for the training and validation sets of about 0.81 (on average).

Experimental Determination of Air/Water Partition Coefficients for 21 Per- and Polyfluoroalkyl Substances Reveals Variable Performance of Property Prediction Models

Per- and polyfluoroalkyl substances (PFAS) are a group of chemicals of high environmental concern. However, reliable data for the air/water partition coefficients (K_aw), which are required for fate, exposure, and risk analysis, are available for only a few PFAS. In this study, K_aw values at 25 °C were determined for 21 neutral PFAS by using the hexadecane/air/water thermodynamic cycle. Hexadecane/water partition coefficients (K_Hxd/w) were measured with batch partition, shared-headspace, and/or modified variable phase ratio headspace methods and were divided by hexadecane/air partition coefficients (K_Hxd/air) to obtain K_aw values over 7 orders of magnitude (10^-4.9 to 10^2.3). Comparison to predicted K_aw values by four models showed that the quantum chemically based COSMOtherm model stood out for accuracy with a root-mean-squared error (RMSE) of 0.42 log units, as compared to HenryWin, OPERA, and the linear solvation energy relationship with predicted descriptors (RMSE, 1.28-2.23). The results indicate the advantage of a theoretical model over empirical models for a data-poor class like PFAS and the importance of experimentally filling data gaps in the chemical domain of environmental interest. K_aw values for 222 neutral (or neutral species of) PFAS were predicted using COSMOtherm as current best estimates for practical and regulatory use.

Henry's Law Constant─A General-Purpose Fragment Model to Predict Log Kaw from Molecular Structure

Henry's law constant is important for assessing the environmental fate of organic compounds, including polar accumulation, indoor contamination, and the impact of airborne predominance on persistence. Moreover, it can be used in the context of alternative 3R bioassays to inform about the compound loss through volatilization as a confounding factor. For 2636 compounds, curated experimental log K_aw (air/water partition coefficient) data at 25° covering 23.6 orders of magnitude (from -18.6 to 5.0) have been collected from the literature. Subsequently, a new fragment model for predicting log K_aw from molecular structures has been developed. According to the root-mean-squared error (rms) and the maximum negative and positive errors (mne and mpe), this general-purpose model outperforms COSMOtherm, EPISuite HENRYWIN, OPERA, and LSER with calculated input parameters significantly (rms 0.50 vs 0.92 vs 1.25 vs 1.28 vs 1.38, mne -2.74 vs -6.78 vs -9.11 vs -6.24 vs -6.27, mpe 2.25 vs 6.22 vs 8.27 vs 11.5 vs 7.69 log units). Initial separation into a training and prediction set (80%:20%), mutual leave-50%-out validation, and target value scrambling (temporarily wrong compound-K_aw allocations) demonstrate the prediction capability, statistical robustness, and mechanistically sound basis of the fragment scheme. The new model is available to the public in fully computerized form through the ChemProp software, and can be combined with a separate existing model to extend the log K_aw prediction to temperatures different from 25 °C.

Henry's Law Constants and Indoor Partitioning of Microbial Volatile Organic Compounds

Microbial volatile organic compounds (MVOCs) play an essential role in many environmental fields, such as indoor air quality. Long-term exposure to odorous and toxic MVOCs can negatively affect the health of occupants. Recently, the involvement of surface reservoirs in indoor chemistry has been realized, which signifies the importance of the phase partitioning of volatile organic pollutants. However, reliable partition coefficients of many MVOCs are currently lacking. Equilibrium partition coefficients, such as Henry's law constant, H, are crucial for understanding the environmental behavior of chemicals. This study aims to experimentally determine the H values and their temperature dependence for key MVOCs under temperature relevant to the indoor environment. The H values were determined with the inert gas-stripping (IGS) method and variable phase ratio headspace (VPR-HS) technique. A two-dimensional partitioning model was applied to predict the indoor phase distribution of MVOCs and potential exposure pathways to the residences. The findings show that the MVOCs are likely distributed between the gas and weakly polar (e.g., organic-rich) reservoirs indoors. Temperature and the volume of reservoirs can sensitively affect indoor partitioning. Our results give a more comprehensive view of indoor chemical partitioning and exposure.

Surface volatilization modeling of (semi-)volatile hydrophobic organic compounds: The role of reference compounds

Volatilization of hazardous hydrophobic organic compounds is often observed in many water, wastewater and soil treatment (bio)processes. Several models have been developed to quantify and predict gas-liquid pollutant transfer, being the proportionality coefficient model (PCM) one of the most commonly used, particularly in wastewater treatment. The PCM is based on the use of oxygen as a reference compound, which has a low resistance to the transfer in the gas phase. However, this resistance might be important for (semi-)volatile organic compounds - or (semi-)VOCs, which may render the use of the PCM model inaccurate. This study proposes an experimental methodology and a modeling approach for the use of the two-reference compound model (2RCM) that considers both the liquid-side and the gas-side resistances, by using water and oxygen as references. Results showed that the 2RCM predicts more accurately the overall mass transfer coefficients than the PCM for a VOC and two semi-VOCs tested in this study. In addition, the 2RCM was found to be a more robust method to estimate mass transfer coefficient of any compound and its use can be extrapolated to all substances. Finally, the relevance and limitations of both models was established.

A QSPR model for estimating Henry's law constant of H2S in ionic liquids by ELM algorithm

Ionic liquids (ILs) as green solvents have been studied in the application of gas sweetening. However, it is a huge challenge to obtain all the experimental values because of the high costs and generated chemical wastes. This study pioneered a quantitative structure-property relationship (QSPR) model for estimating Henry's law constant (HLC) of H₂S in ILs. A dataset consisting of the HLC data of H₂S for 22 ILs within a wide range of temperature (298.15-363.15 K) were collected from published reports. The electrostatic potential surface area (S_EP) and molecular volume of these ILs were calculated and used as input descriptors together with temperature. The extreme learning machine (ELM) algorithm was employed for nonlinear modelling. Results showed that the determination coefficient (R²) of the training set, test set and total set were 0.9996, 0.9989,0.9994, respectively, while the average absolute relative deviation (AARD%) of them were 1.3383, 2,4820 and 1.5820, respectively. The statistical parameters for the measurement of the model exhibited the great reliability, stability, and predictive power of the ELM model. The Applicability Domain (AD) of the ELM model is also investigated. It proves that the majority of ILs in the training and test sets are located in the model's AD and verifies the reliability of the model. The proposed model is potentially applicable to guide the application of ILs for gas sweetening.

Measuring the Henry's Law Constant for Carbon Dioxide and Water with UV-visible Absorption Spectroscopy

The Henry's law constant defines the solubility of a gas in a liquid solution. In this study, a new method for measuring the Henry's law constant is described. This new colorimetric method is suited for gases which react with water to form acidic or basic solutions when they dissolve, and makes use of measuring the concentration of two forms of a colorimetric pH indicator. By measuring the concentration of the protonated and deprotonated forms of the indicator with UV-visible absorption spectroscopy, the concentration of the hydronium in solution was determined. After determining the hydronium concentration, the equilibrium expression for the dissolved gas reacting with water was solved to determine the concentration of the dissolved gas. The concentration of the dissolved gas and the measured partial pressure of the dissolved gas at equilibrium were then used to calculate the Henry's law constant for the gas. The efficacy of the method is demonstrated by measuring the Henry's law constant for carbon dioxide in water over a range of pressures (0.680 - 5.10 atm). The results obtained with this method are comparable to the value for the Henry's law constant that have been previously reported via more traditional methods, and yielded values for the Henry's law constant for carbon dioxide that ranged from 3.45 × 10^-2 to 3.99 × 10^-2 M atm^-1.

New findings on the incorporation of essential oil components into liposomes composed of lipoid S100 and cholesterol

The encapsulation of essential oil components into liposomes was demonstrated to improve their solubility and chemical stability. In this study, we investigated the effect of chemical structure, Henry's law constant (H_c), and aqueous solubility of essential oil components on their liposomal encapsulation. Estragole, eucalyptol, isoeugenol, pulegone, terpineol, and thymol were encapsulated in lipoid S100-liposomes using the ethanol injection method. The H_c values were determined. The incorporation in liposomes was more efficient (encapsulation efficiency > 90%) for the essential oil components exhibiting low aqueous solubility (estragole, isoeugenol, and pulegone). Moreover, efficient entrapment into vesicles (loading rate > 18%) was obtained for isoeugenol, terpineol, and thymol. This result suggests that the presence of a hydroxyl group in the structure and a low Hc value enhance the entrapment of essential oil components into liposomes. Furthermore, drug release rate from liposomes was controlled by the loading rate of essential oil components into liposomes, the size of particles, the location of essential oil components within the lipid bilayer, and the cholesterol incorporation rate of liposomes. Finally, considerable concentrations of isoeugenol, pulegone, terpineol, and thymol were retained in liposomes after 10 months with respect to the initial concentration.

A simple method for the accurate determination of the Henry's law constant for highly sorptive, semivolatile organic compounds

A novel technique is developed to determine the Henry's law constants (HLCs) of seven volatile fatty acids (VFAs) with significantly high solubility using a combined application of thermal desorber/gas chromatography/mass spectrometry (TD/GC/MS). In light of the strong sorptive properties of these semi-volatile organic compounds (SVOCs), their HLCs were determined by properly evaluating the fraction lost on the surface of the materials used to induce equilibrium (vial, gas-tight syringe, and sorption tube). To this end, a total of nine repeated experiments were conducted in a closed (static) system at three different gas/liquid volume ratios. The best estimates for HLCs (M/atm) were thus 7,200 (propionic acid), 4,700 (i-butyric acid), 4,400 (n-butyric acid), 2,700 (i-valeric acid), 2,400 (n-valeric acid), 1,000 (hexanoic acid), and 1,500 (heptanoic acid). The differences in the HLC values between this study and previous studies, if assessed in terms of the percent difference, ranged from 9.2% (n-valeric acid) to 55.7% (i-valeric acid). We overcame the main cause of errors encountered in previous studies by performing the proper correction of the sorptive losses of the SVOCs that inevitably took place, particularly on the walls of the equilibration systems (mainly the headspace vial and/or the glass tight syringe).

Temperature dependencies of Henry's law constants for different plant sesquiterpenes

Sesquiterpenes are plant-produced hydrocarbons with important ecological functions in plant-to-plant and plant-to-insect communication, but due to their high reactivity they can also play a significant role in atmospheric chemistry. So far, there is little information of gas/liquid phase partition coefficients (Henry's law constants) and their temperature dependencies for sesquiterpenes, but this information is needed for quantitative simulation of the release of sesquiterpenes from plants and modeling atmospheric reactions in different phases. In this study, we estimated Henry's law constants (Hpc) and their temperature responses for 12 key plant sesquiterpenes with varying structure (aliphatic, mono-, bi- and tricyclic sesquiterpenes). At 25 °C, Henry's law constants varied 1.4-fold among different sesquiterpenes, and the values were within the range previously observed for monocyclic monoterpenes. Hpc of sesquiterpenes exhibited a high rate of increase, on average ca. 1.5-fold with a 10 °C increase in temperature (Q10). The values of Q10 varied 1.2-fold among different sesquiterpenes. Overall, these data demonstrate moderately high variation in Hpc values and Hpc temperature responses among different sesquiterpenes. We argue that these variations can importantly alter the emission kinetics of sesquiterpenes from plants.

Development of Monopole Interaction Models for Ionic Compounds. Part I: Estimation of Aqueous Henry's Law Constants for Ions and Gas Phase pKa Values for Acidic Compounds

The SPARC (SPARC Performs Automated Reasoning in Chemistry) physicochemical mechanistic models for neutral compounds have been extended to estimate Henry's Law Constant (HLC) for charged species by incorporating ionic electrostatic interaction models. Combinations of absolute aqueous pKa values, relative pKa values in the gas phase, and aqueous HLC for neutral compounds have been used to develop monopole interaction models that quantify the energy differences upon moving an ionic solute molecule from the gas phase to the liquid phase. Inter-molecular interaction energies were factored into mechanistic contributions of monopoles with polarizability, dipole, H-bonding, and resonance. The monopole ionic models were validated by a wide range of measured gas phase pKa data for 450 acidic compounds. The RMS deviation error and R(2) for the OH, SH, CO2 H, CH3 and NR2 acidic reaction centers (C) were 16.9 kcal/mol and 0.87, respectively. The calculated HLCs of ions were compared to the HLCs of 142 ions calculated by quantum mechanics. Effects of inter-molecular interaction of the monopoles with polarizability, dipole, H-bonding, and resonance on acidity of the solutes in the gas phase are discussed.