Effect of Mass Fraction on Leaching Kinetics of Hydrophobic Ultraviolet Stabilizers in Low-Density Polyethylene.

The leaching kinetics of five hydrophobic ultraviolet (UV) stabilizers from low-density polyethylene (LDPE) (micro)fibers into water was evaluated in this study, with variation of the mass fraction (ω = 0.1-2.0 wt %) of the stabilizers. A one-dimensional convection-diffusion model for a cylindrical geometry, requiring partitioning between the LDPE fibers and water (KLDPEw) and the internal diffusion coefficients (DLDPE), was used to evaluate the leaching process and the leaching half-life of the target UV stabilizers at ω < 0.5 wt % (Case I). Diffusion through the aqueous boundary layer is the rate-determining step, and the leaching half-life is predicted to be very long (a few months to years) under unaffected conditions. When the UV stabilizers are supersaturated within LDPE fibers (i.e., ω > 0.5 wt %, Case II), the possible formation of a surficial crystal layer of the additives on the LDPE fiber extends the time scale for leaching compared to that in Case I due to the requirement of overcoming the crystallization energy. This study provides a fundamental understanding of the leaching profiles of plastic additives for assessing their potential chemical risks in aquatic environments; further studies under the relevant environmental conditions are required.

Revisiting the Use of Quantum Chemical Calculations in LogPoctanol-water Prediction.

The partition coefficients of drug and drug-like molecules between an aqueous and organic phase are an important property for developing new therapeutics. The predictive power of computational methods is used extensively to predict partition coefficients of molecules. The application of quantum chemical calculations is used to develop methods to develop structure-activity relationship models for such prediction, either based on molecular fragment methods, or via direct calculation of solvation free energy in solvent continuum. The applicability, merits, and shortcomings of these developments are revisited here.

Quantum Chemical Calculation and Evaluation of Partition Coefficients for Classical and Emerging Environmentally Relevant Organic Compounds.

Octanol/water (KOW), octanol/air (KOA), and hexadecane/air (KHdA) partition coefficients are calculated for 67 organic compounds of environmental concern using computational chemistry. The extended CRENSO workflow applied here includes the calculation of extensive conformer ensembles with semiempirical methods and refinement through density functional theory, taking into account solvation models, especially COSMO-RS, and thermostatistical contributions. This approach is particularly advantageous for describing large and nonrigid molecules. With regard to KOW and KHdA, one can refer to many experimental data from direct and indirect measurement methods, and very good matches with results from our quantum chemical workflow are evident. In the case of the KOA values, however, good matches are only obtained for the experimentally determined values. Larger systematic deviations between data computed here and available, nonexperimental quantitative structure-activity relationship literature data occur in particular for phthalic acid esters and organophosphate esters. From a critical analysis of the coefficients calculated in this work and comparison with available literature data, we conclude that the presented quantum chemical composite approach is the most powerful so far for calculating reliable partition coefficients because all physical contributions to the conformational free energy are considered and the structure ensembles for the two phases are generated independently and consistently.

In Situ Equilibrium Polyethylene Passive Sampling of Soil Gas VOC Concentrations: Modeling, Parameter Determinations, and Laboratory Testing.

The use of low-density polyethylene (PE) sheets as equilibrium passive soil gas samplers to quantify volatile organic compounds (VOCs) such as benzene, toluene, ethylbenzene, and xylenes, and chlorinated solvents (e.g., trichloroethene and tetrachloroethene) in unsaturated subsurface environments was evaluated via modeling and benchtop testing. Two methods were devised to quantify such VOCs in PE. Key chemical properties, including PE-water (KPEw) and PE-air (KPEa) partition coefficients and diffusivities in the PE (Dpe), were determined. These KPEw, KPEa, and Dpe values were consistent with extrapolations of data based on larger compounds. Using these parameter values, field equilibration times of less than 1 day were estimated for such VOCs when using 70-100 µm thick PE sheets. Further, benchtop batch tests carried out in jars filled with VOC-contaminated soils, after 1 or 2 days, showed concentrations in soil air deduced from PE that were consistent with concentrations deduced by analyzing either water or headspace gases recovered from the same tests. Thus, PE-based measurements may overcome inaccuracies from using total soil concentrations and equilibrium partitioning models that may overestimate vapor phase concentrations up to 2 orders of magnitude.

Modelling of Breath and Various Blood Volatilomic Profiles-Implications for Breath Volatile Analysis.

Researchers looking for biomarkers from different sources, such as breath, urine, or blood, frequently search for specific patterns of volatile organic compounds (VOCs), often using pattern recognition or machine learning techniques. However, they are not generally aware that these patterns change depending on the source they use. Therefore, we have created a simple model to demonstrate that the distribution patterns of VOCs in fat, mixed venous blood, alveolar air, and end-tidal breath are different. Our approach follows well-established models for the description of dynamic real-time breath concentration profiles. We start with a uniform distribution of end-tidal concentrations of selected VOCs and calculate the corresponding target concentrations. For this, we only need partition coefficients, mass balance, and the assumption of an equilibrium state, which avoids the need to know the volatiles' metabolic rates and production rates within the different compartments.

ClassicalGSG: Prediction of log P using classical molecular force fields and geometric scattering for graphs.

This work examines methods for predicting the partition coefficient (log P) for a dataset of small molecules. Here, we use atomic attributes such as radius and partial charge, which are typically used as force field parameters in classical molecular dynamics simulations. These atomic attributes are transformed into index-invariant molecular features using a recently developed method called geometric scattering for graphs (GSG). We call this approach "ClassicalGSG" and examine its performance under a broad range of conditions and hyperparameters. We train ClassicalGSG log P predictors with neural networks using 10,722 molecules from the OpenChem dataset and apply them to predict the log P values from four independent test sets. The ClassicalGSG method's performance is compared to a baseline model that employs graph convolutional networks. Our results show that the best prediction accuracies are obtained using atomic attributes generated with the CHARMM generalized force field and 2D molecular structures.

Multiple linear regression models for predicting the n­octanol/water partition coefficients in the SAMPL7 blind challenge.

A multiple linear regression model called MLR-3 is used for predicting the experimental n-octanol/water partition coefficient (log PN) of 22 N-sulfonamides proposed by the organizers of the SAMPL7 blind challenge. The MLR-3 method was trained with 82 molecules including drug-like sulfonamides and small organic molecules, which resembled the main functional groups present in the challenge dataset. Our model, submitted as "TFE-MLR", presented a root-mean-square error of 0.58 and mean absolute error of 0.41 in log P units, accomplishing the highest accuracy, among empirical methods and also in all submissions based on the ranked ones. Overall, the results support the appropriateness of multiple linear regression approach MLR-3 for computing the n-octanol/water partition coefficient in sulfonamide-bearing compounds. In this context, the outstanding performance of empirical methodologies, where 75% of the ranked submissions achieved root-mean-square errors < 1 log P units, support the suitability of these strategies for obtaining accurate and fast predictions of physicochemical properties as partition coefficients of bioorganic compounds.

Closed-Loop Recycling Dual-Mode Counter-Current Chromatography with Specified Sample Loading Durations: Modeling of Preparative and Industrial-Scale Separations.

We previously reported on a new counter-current chromatography (CCC) operating mode called closed-loop recycling dual-mode counter-current chromatography (CLR DM CCC), which incorporates the advantages of closed-loop recycling (CLR) and dual-mode (DM) counter-current chromatography and includes sequential separation of compounds in the closed-loop recycling mode with the mobile x-phase and in the inverted-phase counter-current mode with the mobile y-phase. The theoretical analysis of several implementations of this separation method was carried out under impulse sample injection conditions. This study is dedicated to the further development of CLR DM CCC theory applied to preparative and industrial separations, where high-throughput operation is required. Large sample volumes can be loaded via continuous loading within a specified time. To simulate CLR DM CCC separations with specified sample loading durations, equations are developed and presented in "Mathcad" software.

Trace element partitioning between pyrochlore, microlite, fersmite and silicate melts.

We present experimentally determined trace element partition coefficients (D) between pyrochlore-group minerals (Ca2(Nb,Ta)2O6(O,F)), Ca fersmite (CaNb2O6), and silicate melts. Our data indicate that pyrochlores and fersmite are able to strongly fractionate trace elements during the evolution of SiO2-undersaturated magmas. Pyrochlore efficiently fractionates Zr and Hf from Nb and Ta, with DZr and DHf below or equal to unity, and DNb and DTa significantly above unity. We find that DTa pyrochlore-group mineral/silicate melt is always higher than DNb, which agrees with the HFSE partitioning of all other Ti-rich minerals such as perovskite, rutile, ilmenite or Fe-Ti spinel. Our experimental partition coefficients also show that, under oxidizing conditions, DTh is higher than corresponding DU and this implies that pyrochlore-group minerals may fractionate U and Th in silicate magmas. The rare earth element (REE) partition coefficients are around unity, only the light REE are compatible in pyrochlore-group minerals, which explains the high rare earth element concentrations in naturally occurring magmatic pyrochlores.

Prediction of the n-octanol/water partition coefficients in the SAMPL6 blind challenge from MST continuum solvation calculations.

The IEFPCM/MST continuum solvation model is used for the blind prediction of n-octanol/water partition of a set of 11 fragment-like small molecules within the SAMPL6 Part II Partition Coefficient Challenge. The partition coefficient of the neutral species (log P) was determined using an extended parametrization of the B3LYP/6-31G(d) version of the Miertus-Scrocco-Tomasi continuum solvation model in n-octanol. Comparison with the experimental data provided for partition coefficients yielded a root-mean square error (rmse) of 0.78 (log P units), which agrees with the accuracy reported for our method (rmse = 0.80) for nitrogen-containing heterocyclic compounds. Out of the 91 sets of log P values submitted by the participants, our submission is within those with an rmse < 1 and among the four best ranked physical methods. The largest errors involve three compounds: two with the largest positive deviations (SM13 and SM08), and one with the largest negative deviations (SM15). Here we report the potentiometric determination of the log P for SM13, leading to a value of 3.62 ± 0.02, which is in better agreement with most empirical predictions than the experimental value reported in SAMPL6. In addition, further inclusion of several conformations for SM08 significantly improved our results. Inclusion of these refinements led to an overall error of 0.51 (log P units), which supports the reliability of the IEFPCM/MST model for predicting the partitioning of neutral compounds.

COSMO-RS based predictions for the SAMPL6 logP challenge.

Within the framework of the 6th physical property blind challenge (SAMPL6) the authors have participated in predicting the octanol-water partition coefficients (logP) for several small drug like molecules. Those logP values where experimentally known by the organizers but only revealed after the submissions of the predictions. Two different sets of predictions were submitted by the authors, both based on the COSMOtherm implementation of COSMO-RS theory. COSMOtherm predictions using the FINE parametrization level (hmz0n) obtained the highest accuracy among all submissions as measured by the root mean squared error. COSMOquick predictions using a fast algorithm to estimate σ-profiles and an a posterio machine learning correction on top of the COSMOtherm results (3vqbi) scored 3rd out of 91 submissions. Both results underline the high quality of COSMO-RS derived molecular free energies in solution.

Predictive potential of eigenvalue-based topological molecular descriptors.

This study is directed toward assessing the predictive potential of eigenvalue-based topological molecular descriptors. The graph energy, Estrada index, resolvent energy, and the Laplacian energy were tested as parameters for the prediction of boiling points, heats of formation, and octanol/water partition coefficients of alkanes. It was shown that an eigenvalue-based molecular descriptor cannot be individually used for successful prediction of these physico-chemical properties, but the first Zagreb index, the number of zeros in the spectrum and the number of methyl groups must be also involved in the models. Performed statistics show that the models constructed using the Estrada index and resolvent energy are significantly better than ones with the energy of a graph and the Laplacian energy. Such a trend is even more noticeable in the case of octanol/water partition coefficients of alkanes.

Seasonal dynamics of metal phase distributions in the perennial tropical (Brahmaputra) river: Environmental fate and transport perspective.

An evaluation of the seasonal dynamics of metal (Cd, Cr, Cu, Pb and Zn) phase distribution and speciation, along with different hydrogeochemical facies, was conducted along the entire stretch of a perennial tropical (Brahmaputra) River. Water samples were collected from twelve locations during the monsoon, post-monsoon and pre-monsoon seasons. A characteristic trend in bioavailability was observed in the sequence of Zn > Cu > Pb > Cr > Cd, reflecting non-significant seasonal changes in dissolved and particulate phase metal fractions at all twelvelocations. Partition (or distribution) coefficients (Kds) for Cu (5.30-6.50), Zn (4.47-6.44), Pb (3.69-4.97) and Cr (3.25-5.15), reflect the influences of anionic inorganic constitutents (aqua ion complexes), environmental variables, and river hydrology. MINTEQA2 calculations showed that metal forms complexes with other inorganic ions such as Cl-, SO42-, HCO3- and strong binding as organic complexes (for Cu and Pb) reduces their leaching potential to groundwater system. High log Kd values (≥5.3) and significant spatial variations at locations R3 to R8 of Pb, Cu, and Zn during pre-monsoon period may be explained by the formation of complexes with organic ligands in sewage and domestic wastes (humic and fulvic acids). Multivariate statistical analysis revealed multi-metal co-contamination, mainly of Zn, Cu, Cd and Pb and dissolved nutrients, loading in different clusters, emphasizing the importance of climatic, anthropogenic, terrigenous and lithological sources as controlling factors for seasonal metal dynamics in the river water.

Physiologically based toxicokinetic models and in silico predicted partition coefficients to estimate tetrachlorodibenzo-p-dioxin transfer from feed into growing pigs.

Tetrachlorodibenzo-p-dioxin (TCDD) is a ubiquitous, toxic, persistent and bioaccumulative organic pollutant. TCDD can potentially enter the food chain through contaminated food of animal origin as a consequence of feed contamination. Prediction of the TCDD transfer from feed into animal products is thus important for human health risk assessment. Here, we develop several physiologically based toxicokinetic (PBTK) models of TCDD transfer from contaminated feed into growing pigs (Sus scrofa) exposed to doses ranging from 24.52 to 3269.25 ng of TCDD. We test the consequences of explicit dose-dependent absorption (DDA) versus the indirect effects of a self-induced liver metabolism (SIM). The DDA and SIM models showed similar fit to experimental data, although currently it is not possible to unequivocally make statement on a mechanistic preference. The performance of both toxicokinetic models was successfully evaluated using the 1999 Belgian case of contaminated fats for feeding. In combination with toxicokinetic models of other dioxin congeners, they can be used to formulate maximum allowance levels of dioxins in feedstuffs for pigs. Additionally, the implementation of in silico-predicted partition coefficients was explored as a useful alternative to predict TCDD tissue distribution in low-dose scenarios without recurring to animal experiments.

Predicting skin permeability using the 3D-RISM-KH theory based solvation energy descriptors for a diverse class of compounds.

The state-of-the-art molecular solvation theory is used to predict skin permeability of a large set of compounds with available experimental skin permeability coefficient (logKP). Encouraging results are obtained pointing to applicability of a novel quantitative structure activity model that uses statistical physics based 3D-RISM-KH theory for solvation free energy calculations as a primary descriptor for the prediction of logKP with relative mean square error of 0.77 units.

An efficient high-speed countercurrent chromatography method for preparative separation of javanicin from Fusarium solani, a fungus isolated from the fruiting body of the mushroom Trametes trogii.

To develop an efficient method for large preparation of javanicin from Fusarium solani, a rapid and simple method by high-speed countercurrent chromatography was established based on average polarity (P' values) and partition coefficients (K values) of crude samples. A suitable solvent system for high-speed countercurrent chromatography was selected from many possible biphasic solvent systems. HSCCC was successfully applied to separate and purify javanicin, the main bioactive component of solid cultures of the fungus F. solani isolated from the fruiting body of Trametes trogii, with petroleum ether-ethyl acetate-methanol-water (4:3:2:1, v/v) as solvent system. A total amount of 40.6 mg of javanicin was obtained from 100 mg crude sample. The purity of javanicin was 92.2% with a recovery of 95.1%, as determined by high-performance liquid chromatrography. The molecular structure was identified primarily by NMR and MS methods. The results indicated that high-speed countercurrent chromatography could be a powerful technology for separating naphthoquinones from the solid cultures of the fungus F. solani. It is also of significance that the separation of javanicin from natural source was carried out for the first time utilizing high-speed countercurrent chromatography.

Developing Predictive Models for Carrying Ability of Micro-Plastics towards Organic Pollutants.

Microplastics, which have been frequently detected worldwide, are strong adsorbents for organic pollutants and may alter their environmental behavior and toxicity in the environment. To completely state the risk of microplastics and their coexisting organics, the adsorption behavior of microplastics is a critical issue that needs to be clarified. Thus, the microplastic/water partition coefficient (log Kd) of organics was investigated by in silico method here. Five log Kd predictive models were developed for the partition of organics in polyethylene/seawater, polyethylene/freshwater, polyethylene/pure water, polypropylene/seawater, and polystyrene/seawater. The statistical results indicate that the established models have good robustness and predictive ability. Analyzing the descriptors selected by different models finds that hydrophobic interaction is the main adsorption mechanism, and π-π interaction also plays a crucial role for the microplastics containing benzene rings. Hydrogen bond basicity and cavity formation energy of compounds can determine their partition tendency. The distinct crystallinity and aromaticity make different microplastics exhibit disparate adsorption carrying ability. Environmental medium with high salinity can enhance the adsorption of organics and microplastics by increasing their induced dipole effect. The models developed in this study can not only be used to estimate the log Kd values, but also provide some necessary mechanism information for the further risk studies of microplastics.

Influence of electrolyte composition and pH on glyphosate sorption by cow-dung amended soil.

This study investigated the pH-dependent relationship between glyphosate and soils before (NS) and after amendment with cow-dung, CD (SACD). Sorption isotherms were generated using batch equilibration techniques from CaCl2, KCl, CaSO4 and Ca(H2PO4)2 background electrolytes. Linear partition coefficients decreased with increase in pH in the order: CaCl2>KCl > CaSO4>Ca(H2PO4)2, which reflect both the effect of the inorganic anion in terms of competition and the cation in terms of bridging interactions. However, soil amendment with CD minimized the inhibitory effect of pH increase on glyphosate sorption. Variations in glyphosate sorption from CaCl2 and Ca(H2PO4)2 were attributed to fraction of hydrophilic contribution while variations in sorption from CaCl2 and KCl were attributed to Ca-bridging and ranged from 22 to 70% across the two soils. Estimated hydrophobic partitioning ( KOCpH ) systematically decreased with increasing soil solution pH from 36 to 3% and 5 to <1% in NS and SACD, respectively. Greater sorption in NS over SACD was partly attributed to higher phosphate level in SACD which is preferentially sorbed over glyphosate. This study noted CD application as soil amendment for agriculture could impede glyphosate sorption and facilitate its off-site leaching and contamination of surface and groundwater.

Partition coefficients of methylated DNA bases obtained from free energy calculations with molecular electron density derived atomic charges.

Partition coefficients serve in various areas as pharmacology and environmental sciences to predict the hydrophobicity of different substances. Recently, they have also been used to address the accuracy of force fields for various organic compounds and specifically the methylated DNA bases. In this study, atomic charges were derived by different partitioning methods (Hirshfeld and Minimal Basis Iterative Stockholder) directly from the electron density obtained by electronic structure calculations in a vacuum, with an implicit solvation model or with explicit solvation taking the dynamics of the solute and the solvent into account. To test the ability of these charges to describe electrostatic interactions in force fields for condensed phases, the original atomic charges of the AMBER99 force field were replaced with the new atomic charges and combined with different solvent models to obtain the hydration and chloroform solvation free energies by molecular dynamics simulations. Chloroform-water partition coefficients derived from the obtained free energies were compared to experimental and previously reported values obtained with the GAFF or the AMBER-99 force field. The results show that good agreement with experimental data is obtained when the polarization of the electron density by the solvent has been taken into account, and when the energy needed to polarize the electron density of the solute has been considered in the transfer free energy. These results were further confirmed by hydration free energies of polar and aromatic amino acid side chain analogs. Comparison of the two partitioning methods, Hirshfeld-I and Minimal Basis Iterative Stockholder (MBIS), revealed some deficiencies in the Hirshfeld-I method related to the unstable isolated anionic nitrogen pro-atom used in the method. Hydration free energies and partitioning coefficients obtained with atomic charges from the MBIS partitioning method accounting for polarization by the implicit solvation model are in good agreement with the experimental values. © 2018 Wiley Periodicals, Inc.

Headspace analysis for screening of volatile organic compound profiles of electronic juice bulk material.

The use of electronic nicotine delivery systems continues to gain popularity, and there is concern for potential health risks from inhalation of aerosol and vapor produced by these devices. An analytical method was developed that provided quantitative and qualitative chemical information for characterizing the volatile constituents of bulk electronic cigarette liquids (e-liquids) using a static headspace technique. Volatile organic compounds (VOCs) were screened from a convenience sample of 146 e-liquids by equilibrating 1 g of each e-liquid in amber vials for 24 h at room temperature. Headspace was transferred to an evacuated canister and quantitatively analyzed for 20 VOCs as well as tentatively identified compounds using a preconcentrator/gas chromatography/mass spectrometer system. The e-liquids were classified into flavor categories including brown, fruit, hybrid dairy, menthol, mint, none, tobacco, and other. 2,3-Butanedione was found at the highest concentration in brown flavor types, but was also found in fruit, hybrid dairy, and menthol flavor types. Benzene was observed at concentrations that are concerning given the carcinogenicity of this compound (max 1.6 ppm in a fruit flavor type). The proposed headspace analysis technique coupled with partition coefficients allows for a rapid and sensitive prediction of the volatile content in the liquid. The technique does not require onerous sample preparation, dilution with organic solvents, or sampling at elevated temperatures. Static headspace screening of e-liquids allows for the identification of volatile chemical constituents which is critical for identifying and controlling emission of potentially hazardous constituents in the workplace.