Linear Solvation Energy Relationship Model Research Articles

A QSAR prediction model for adsorption of organic contaminants on microplastics: Dubinin-Astakhov plus linear solvation energy relationships

Numerous pharmaceuticals and personal care products (PPCPs) co-exist with various types of microplastics (MPs) in the environment, making it extremely hard to experimentally measure all their adsorption interactions. Thus, a precise prediction model is on demand. In this study, we combined the commonly used Dubinin-Astakhov (DA) model and the linear solvation energy relationships (LSERs) model to predict the adsorption capacity (Q0) and adsorption affinity (E) of MPs for PPCPs, including the key parameters of MP (specific surface area, oxygen-containing functional groups), and the Kamlet-Taft solvation parameters of organic contaminants. The model was validated with the experimental data of 8 PPCPs and 8 MPs (i.e. pristine and aged PE, PET, PS, PVC) plus some published adsorption data. This new model also indicated that the adsorption of PPCPs on those MPs was primarily governed by hydrophobic interaction and hydrogen bonding. The developed model can predict the adsorption of PPCPs onto MPs with a high accuracy and can also provide insights into the understanding of interaction forces in the adsorption process.

Equilibrium solubility, solvent effect, and equation correlations of cyclosporine in twenty mono solvents and four binary mixtures

In this study, the solid–liquid equilibrium solubility of cyclosporine in 20 pure solvents and four binary mixtures at 298.15 K were determined using shake-flask technique. Solid-state characterization exhibited that no solvate formation or polymorphic transformation occurred during the dissolution of cyclosporine in any of the solvent systems investigated. The experimental solubilities of cyclosporine in 20 pure mono solvents were ranked as follows: DEGME (2.21 × 10−1) > ethanol (1.22 × 10−1) > NMP (1.15 × 10−1) = 1-butanol (1.15 × 10−1) > dichloromethane (1.07 × 10−1) > acetonitrile (1.02 × 10−1) > PEG 200 (9.78 × 10−2) > PEG 300 (9.12 × 10−2) > chloroform (8.98 × 10−2) > PEG 400 (8.11 × 10−2) > DMF (7.65 × 10−2) > 2-propanol (7.09 × 10−2) > 1-propanol (6.57 × 10−2) > methanol (6.14 × 10−2) > propylene glycol (6.08 × 10−2) > tetrahydrofuran (4.69 × 10−2) > DMSO (2.64 × 10−2) > acetone (1.28 × 10−2) > glycerol (1.35 × 10−5) > water (4.29 × 10−7). In the four binary solvents (DEGME + water, PEG 200 + water, PEG 300 + water, and PEG 400 + water), the mole fraction solubility of cyclosporine increased with increasing mass fractions of the four different organic solvents. Based on the Kamlet-Taft linear solvation energy relationship (KAT-LSER) model, the solubility of cyclosporine was mainly affected by the self-cohesiveness of the solvent, which is related to the interaction between the solvent and the solvent. Additionally, the solubility parameter was used to explain and understand the solubility of cyclosporine in four different binary solvents. To correlate the solubility data of cyclosporine, two models (the Yalkowsky Log-Linear and simplified CNIBS/R–K models) were applied. The calculated data based on two mathematical models and experimental mole fraction solubility data for cyclosporine could provide information for the separation, extraction, purification, crystallization, and selection of suitable a solvent system.

Separation of carbohydrates using dynamically adsorbed borate stationary phase for hydrophilic interaction liquid chromatography

In this work, a chromatographic method for the separation of carbohydrates was proposed. Tris-(hydroxymethyl)-amine (TRIS) functionalized silica-based hydrophilic interaction liquid chromatography (HILIC) stationary was synthesized. The dynamically absorbed borate layer is generated by using borate buffer as a polar modifier due to the complexation of borate with TRIS ligand in the stationary phase. The chromatographic systems were analyzed by the linear solvation energy relationship model. The calculated system constants revealed the enhancement of anionic exchange by the addition of borate in the mobile phase system. In addition, ligand exchange is critical for the retention and elution order of sugars and sugar alcohols. Carbohydrates displayed prolonged retention with different selectivity profiles relating to their complexation coefficients with borate. Experiment results showed that the effect of borate in this chromatographic system was stable within the range of pH 3–7 and borate concentration of 5–15 mM. This work provides a complementary solution for the separation of carbohydrates. It can also be extended to the separation of glycosides.

Simulation of gas chromatographic separations and estimation of distribution-centric retention parameters using linear solvation energy relationships

For method development in gas chromatography, suitable computer simulations can be very helpful during the optimization process. For such computer simulations retention parameters are needed, that describe the interaction of the analytes with the stationary phase during the separation process. There are different approaches to describe such an interaction, e.g. thermodynamic models like Blumberg's distribution-centric 3-parameter model (K-centric model) or models using chemical properties like the Linear Solvation Energy Relationships (LSER).In this work LSER models for a Rxi-17Sil MS and a Rxi-5Sil MS GC column are developed for different temperatures. The influences of the temperature to the LSER system coefficients are shown in a range between 40 and 200 °C and can be described with Clark and Glew's ABC model as fit function. A thermodynamic interpretation of the system constants is given and its contribution to enthalpy and entropy is calculated. An estimation method for the retention parameters of the K-centric model via LSER models were presented. The predicted retention parameters for a selection of 172 various compounds, such as FAMEs, PCBs and PAHs are compared to isothermal determined values. 40 measurements of temperature programmed GC separations are compared to computer simulations using the differently determined or estimated K-centric retention parameters. The mean difference (RSME) between the measured and predicted retention time is less than 8 s for both stationary phases using the isothermal retention parameters. With the LSER predicted parameters the difference is 20 s for the Rxi-5Sil MS and 38 s for the Rxi-17Sil MS. Therefore, the presented estimation method can be recommended for first method development in gas chromatography.

Synthesis and evaluation of aromatic stationary phases based on linear solvation energy relationship model for expanded application in supercritical fluid chromatography

In the last decade, the separation application based on aromatic stationary phases has been demonstrated in supercritical fluid chromatography (SFC). In this paper, four aromatic stationary phases involving aniline (S-aniline), 1-aminonaphthalene (S-1-ami-naph), 1-aminoanthracene (S-1-ami-anth) and 1-aminopyrene (S-1-ami-py) were synthesized based on full porous particles (FPP) silica, which were not end-capped for providing extra electrostatic interaction. Retention mechanism of these phases in SFC was investigated using a linear solvation energy relationship (LSER) model. The aromatic stationary phases with five positive parameters (a, b, s, e and d+) can provide hydrogen bonding, π-π, dipole-dipole and cation exchange interactions, which belong to the moderate polar phases. The LSER results obtained using routine test solutes demonstrated that the aforementioned interactions of four aromatic stationary phases were influenced by the type and bonding density of the ligand, but to a certain extent. Furthermore, the LSER data verified that the S-1-ami-anth column based on full porous particles silica had higher cation exchange capacity (d+ value), compared to the commercialized 1-AA column (based on the ethylene-bridged hybrid particles). The relationship between the d+ value and SFC additive was quantitatively proved so as to regulate electrostatic interaction reasonably. This value was greatly increased by phosphoric acid, slightly increased by trifluoroacetic acid and formic acid, but significantly reduced by ammonium formate and diethylamine. Taking the S-1-ami-naph column as an example, better peek shape of the flavonoids was obtained after the addition of 0.1 % phosphoric acid in MeOH while isoquinoline alkaloids were eluted successfully within 11 min after adding 0.1 % diethylamine in MeOH. Combined with the unique π-π interaction and controllable electrostatic interaction, the aromatic stationary phases in this study have been proven to have expandable application potential in SFC separation.

Revisiting the Total Hildebrand and Partial Hansen Solubility Parameters of Analgesic Drug Meloxicam

The reported total Hildebrand solubility parameter (δ2) value of meloxicam, as calculated based on the group contribution method proposed by Fedors, was compared with those estimated based on the maximum solubility peaks observed in different aqueous cosolvent systems at T = 298.15 K. Thus, the observed δ2 values varied from (19.8 to 29.1) MPa1/2, respectively. Moreover, the Hansen solubility parameters (HSPs) and the total Hildebrand solubility parameter were also determined by using the Bustamante regression method with the reported experimental solubility values of meloxicam in 31 neat solvents (30 organic solvents and water), obtaining the values: δd = 19.9 MPa1/2, δp = 16.9 MPa1/2, δh = 5.7 MPa1/2, and δT = 26.7 MPa1/2. Furthermore, the HSPs of meloxicam were also estimated based on the Hoftyzer–van Krevelen group contribution method, obtaining the values: δd = 17.9 MPa1/2, δp = 20.3 MPa1/2, and δh = 9.2 MPa1/2, and the total solubility parameter as: δT = 28.6 MPa1/2. In addition, the Kamlet–Abboud–Taft linear solvation energy relationship (KAT-LSER) model was also employed to evaluate the role of different intermolecular interactions on the dissolution of meloxicam in different solvents that varied in terms of polarity and hydrogen bonding capability.

Investigation on the solvent and temperature effect of climbazole solubility

The thermodynamic behavior of objective compounds plays an important role in crystallization and purification. In this work, the solubility of climbazole in nine pure solvents at (288.15–318.15 K) and in a water–ethanol mixed solution at (278.15–313.15 K) was determined by a gravimetric method. It was found that the solubility is positively related to temperature and ethanol content. Three well-known thermodynamic models (modified Apelblat equation, NRTL equation, λh equation) were used to correlate the experimental data, and the modified Apelblat equation showed better correlation results. Meanwhile, the thermodynamic properties of climbazole in selected solvents were investigated, and it was found that the dissolution process of climbazole is spontaneous, endothermic and entropy driven. Furthermore, the solvent effect was evaluated and discussed by Kamlet and Taft linear solvation energy relationship model (KAT-LSER) and Hansen solubility parameters (HSPs). The solvent–solvent interactions and the nonspecific dipolarity/polarizability interactions have a great influence on solubility. Additionally, the molecular surface characteristics and intermolecular interactions were studied by molecular simulation to reveal the molecular mechanism behind the solubility behavior of climbazole.

COSMO-RS and LSER models of solution thermodynamics: Towards a COSMO-LSER equation of state model of fluids

The present work examines the formulation of a statistical thermodynamic framework for the direct interconnection of the quantum-mechanics based COSMO-RS (Conductor Screening Model for Realistic Solvation) model with Abraham’s LSER (Linear Solvation Energy Relationship) model and LSER molecular descriptors. The focus is on the hydrogen-bonding (HB) contribution to solvation enthalpy. An extensive comparison is made between COSMO-RS predictions of the HB contribution to solvation enthalpy of a variety of solute – solvent systems and the corresponding LSER predictions. A rather good agreement is observed in most of the studied systems. The cases of large discrepancies are also compared with corresponding equation-of-state calculations. The perspectives for a combination of COSMO-RS, LSER and equation-of-state approaches, which would lead to the development of a COSMO-LSER equation-of-state framework are critically discussed.

Linear solvation energy relationships for adsorption of aromatic organic compounds by microplastics

This study develops predictive models for adsorption of organic compounds (OC) by microplastics using linear solvation energy relationship (LSER). The adsorption mechanism of aromatic OCs by microplastics was investigated by delineating the effect of molecular weight of the OCs, polymer type of MPs, and background water chemistry. The benchmark model for adsorption of OCs (n = 28) by polyethylene yielded an R2 = 0.85 (n = 28), RMSE = 0.38, Q2LOO = 0.73. Further narrowing the dataset down by decreasing the molecular weight cutoff to OCs < 192 g/mol improved the model to R2 = 0.98 (n = 13). Validation techniques tested the predictive strength of the benchmark model, which included new experimental adsorption data and performing leave-one-out cross validation. Among LSER model descriptors, the molecular volume was the most predominant descriptor in all scenarios, suggesting the importance of non-specific interactions and OC hydrophobicity. The results demonstrated that LSER is a promising approach for predicting the adsorption of aromatic OCs by MPs.

Predicting partitioning from low density polyethylene to blood and adipose tissue by linear solvation energy relationship models.

The variety of polymers utilized in medical devices demands for testing of extractables and leachables according to ISO 10993-18:2020 in combination with ISO 10993-1:2018. The extraction of the materials involves the use of organic solvents as well as aqueous buffers to cover a wide range of polarity and pH-values, respectively. To estimate patient exposure to chemicals leaching from a polymer in direct body contact, simulating solvents are applied to best mimic the solubilization and partitioning behavior of the related tissue or body fluid. Here we apply linear solvation energy relationship (LSER) models to predict blood/water and adipose tissue/water partition coefficients. We suggest this predictive approach to project levels of potential leachables, design extraction experiments, and to identify the optimal composition of simulating extraction solvents. We compare our predictions to LSER predictions for commonly applied surrogates like ethanol/water mixtures, butanol, and octanol as well as olive oil, butanone, 1,4-dioxane for blood and adipose tissue, respectively. We therefore selected a set of 26 experimentally determined blood/water partition coefficients and 33 adipose tissue/water partition coefficients, where we demonstrate that based on the root mean squared error rmse the LSER approach performs better than surrogates like octanol or butanol and equally well as 60:40 ethanol/water for blood. For adipose tissue/water partitioning, the experimentally determined octanol/water partition coefficient performs best but the rmse is at the same range as our LSER approach based on experimentally determined descriptors. Further, we applied our approach for 248 extractables where we calculated blood/low density polyethylene (LDPE) and adipose tissue/LDPE partition coefficients. By this approach, we successfully identified chemicals of potential interest to a toxicological evaluation based on the total risk score.

An attempt to apply a subtraction model for characterization of non-polar stationary phase in supercritical fluid chromatography

This study verified the feasibility of using a subtraction model to characterize the non-polar stationary phases (including C4, C8, and phenyl-type) in supercritical fluid chromatography (SFC). The model with 6 terms was expressed as log α = η'H + θ'P + β'A + α'B + κ'C + σ'S, where a term θ'P indicating dipole or induced dipole interaction was intentionally supplemented. Ethylbenzene and SunFire C8 were respectively defined as the reference solute and column. A 7-step modeling procedure was proposed: in the first 6 steps, except σ'S, by the use of a bidirectional fitting method, other parameters were calculated based on the equation: log α = log (ki/kref) ≈ η'H + θ'P + β'A + α'B + κ'C; and in the 7th step, residual analysis was employed to describe the σ'S term according to the equation: σ'S = log αexp. - log αpre. Furthermore, six columns that were not involved in modeling process and 12 compounds with unknown retention were used for methodology validation. It showed good predictions of log k, as demonstrated by adjusted determination coefficient (R2adj) from 0.9927 to 0.9998 (column) and from 0.9940 to 0.9999 (compound), respectively. The subtraction model emphasized the contribution of dipole or induced dipole interaction to the retention in SFC, and it obtained the σ'S term through residual analysis. Moreover, it made reasonable physical-chemical sense as the linear solvation energy relationship (LSER) model did, with the distinct advantages of better fitting and more accurate prediction. This study provided some new insights into the characterization of non-polar stationary phases in SFC.

Study on the synchronous removal mechanisms of typical refractory hydrophilic and hydrophobic organics in the biochemical effluent of coal gasification by semicoke-PSAFS

To study the synchronous removal mechanisms of hydrophilic organics 2,4-di-tert-butylphenol and 2-palmitoyl-rac-glycerol and the hydrophobic organics n-octadecane and 2-stearoyl-rac-glycerol coexisting in the biochemical effluent of coal gasification processes treated by a semicoke-polysilicate aluminum ferric sulfate (PSAFS) process, the fitting results of the D-R adsorption isotherm model show that the maximum equilibrium adsorption qe for hydrophobic organics was 3.2–7.8 times that of hydrophilic organics. Based on the contrast with 8 kJ/mol of the average adsorption free energy, physical adsorption occurred in the hydrophobic organics, and chemical adsorption occurred in the hydrophilic organics. Adsorption kinetics analysis showed that the adsorption rates of three typical organics except for 2-palmitoyl-rac-glycerol increased by more than 40.0% in semicoke-PSAFS compared with the semicoke adsorption. To analyze the adsorption driving forces, a linear solvation energy relationship (LSER) model was selected and showed that the hydrogen-bond acid effect contributed by PSAFS had the largest regression coefficients among the five adsorption forces. The typical hydrophilic organics had lower zeta potentials than hydrophobic organics, which suggests that hydrophilic organics that were easily ionized at neutral pH were electrostatically neutralized with the Fe and Al cations in PSAFS. The floc in hydrophilic organic solutions had larger D50 and Df than those in hydrophobic organic solutions, which indicates that the hydrophilic organics had polar functional groups that combined with the silicon, iron and aluminum polymers in PSAFS through a hydrogen-bonded acid effect to form larger and denser floc structures. Hydrophobic organics were adsorbed in the pores of semicoke; then, in combination with semicoke, they were captured by the iron and aluminum polymers in PSAFS.

Linear Free-Energy Relationships and Solvation Thermodynamics: The Thermodynamic Basis of LFER Linearity

The Abraham solvation parameter model, known alternatively as the Linear Solvation Energy Relationships (LSER) model, is widely used in numerous applications in the broader chemical, biochemical, and environmental sector with remarkable success. So far, there is no explanation at the fundamental thermodynamic level for the very linearity of this model. This is, however, essential for the evaluation and exchange of thermodynamic quantities between models and databases. The present work offers such an explanation by combining the equation-of-state solvation thermodynamics with the statistical thermodynamics of hydrogen bonding. It shows what this linearity entails and in what way it is interpreted and handled so far. In addition, it proposes new ways of extending it for estimations over a broad range of external conditions and, eventually, in predicting solvent LFER coefficients from the corresponding molecular descriptors, which are known for thousands of compounds. This would enhance significantly the predictive capacity of the model in practical applications, such as solvent screening, solute partitioning, activity coefficients at infinite dilution, or hydration/solvation energies. Various examples of calculations are reported. A critical discussion of perspectives and challenging emerging issues are also presented.

Linear Solvation–Energy Relationships (LSER) and Equation-of-State Thermodynamics: On the Extraction of Thermodynamic Information from the LSER Database

There is a remarkable wealth of thermodynamic information in freely accessible databases, the LSER database being a classical example. The LSER, or Abraham solvation parameter model, is a very successful predictive tool in a variety of applications in the (bio)chemical and environmental sector. The model and the associated database are very rich in thermodynamic information and information on intermolecular interactions, which, if extracted properly, would be particularly useful in various thermodynamic developments for further applications. Partial Solvation Parameters (PSP), based on equation-of-state thermodynamics, are designed as a versatile tool that would facilitate this extraction of information. The present work explores the possibilities of such an LSER–PSP interconnection and the challenging issues this effort is faced with. The thermodynamic basis of the very linearity of the LSER model is examined, especially, with respect to the contribution of strong specific interactions in the solute/solvent system. This is done by combining the equation-of-state solvation thermodynamics with the statistical thermodynamics of hydrogen bonding. It is verified that there is, indeed, a thermodynamic basis of the LFER linearity. Besides the provenance of the sought linearity, an insight is gained on the thermodynamic character and content of coefficients and terms of the LSER linearity equations. The perspectives from this insight for the further development of LSER and related databases are discussed. The thermodynamic LSER–PSP interconnection is examined as a model for the exchange in information between QSPR-type databases and equation-of-state developments and the associated challenges are examined with representative calculations.

An in-depth investigation of supercritical fluid chromatography retention mechanisms by evaluation of a series of specially designed alkylsiloxane-bonded stationary phases based on linear solvation energy relationship

Fundamental research on supercritical fluid chromatography (SFC) has gained considerable interest, with many studies focusing on its retention mechanism based on the linear solvation energy relationship (LSER) model. In this paper, a series of alkylsiloxane-bonded stationary phases were specifically designed and synthesized, then evaluated using the mobile phase composed of CO2 with 10% (v/v) methanol. The study demonstrated the close relationship between the interactions (manner and magnitude) of stationary phases and the C-chain length, bonding density and the endcapping treatment. All C8 phases provide positive e, v and negative s, whose magnitude was regularly affected by bonding density. It was worth mentioning the non-endcapped C8 phases could provide H-bonding (positive a and b) by reducing the bonding density of the alkyl chain. Once it was endcapped, the interaction manner did not vary with bonding density adjustment. The non-endcapped C4 phases with higher bonding density could establish additional dispersion interaction (positive v). It can be seen that two synthesis strategies, 1) non-endcapped, long C-chain (C8) combined with low bonding density, and 2) non-endcapped, short C-chain (C4) combined with high bonding density, can obtain the alkylsiloxane-bonded stationary phases (C8-1 and C4-3) to provide both polar and dispersion interactions, showing different separation selectivity. Furthermore, the LSER model with ionic terms was applied to evaluate partial C8 columns, and its rationality was verified. The non-endcapped C8 showed great d+ values, which originated from the silanol groups. C8SCX also possessed a great d+ value due to the benzenesulfonic acid groups. A remarkable result showed that C8SAX exhibited prominent d− and d+ values simultaneously due to the combined effect of silanol and quaternary ammonium groups, which indicates the unique selectivity when separating ionic compounds. This study provides in-depth insights into the retention mechanism of alkylsiloxane-bonded stationary phases in SFC, as well as a reference for the design of SFC stationary phases.

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

ABSTRACT 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.

Modified linear solvation energy relationships for adsorption of perfluorocarboxylic acids by polystyrene microplastics

Microplastics (MPs) could act as vectors of organic pollutants such as per- and polyfluoroalkyl substances (PFAS). Therefore, understanding adsorptive interactions are essential steps towards unraveling the fate of PFAS in the natural waters where MPs are ubiquitous. Linear solvation energy relationships (LSER)-based predictive models are utilitarian tools to delineate the complexity of adsorption interactions. However, commonly studied PFAS are in their ionic forms at environmentally relevant conditions and LSER modeling parameters do not account for their ionization. This study aims to develop the first LSER model for the adsorption of PFAS by MPs using a subset of ionizable perfluoroalkyl carboxylic acids (PFCA). The adsorption of twelve PFCAs by polystyrene (PS) MPs was used for model training. The study provided mechanistic insights regarding the impacts of PFCA chain length, PS oxidation state, and water chemistry. Results show that the polarizability and hydrophobicity of anionic PFCA are the most significant contributors to their adsorption by MPs. In contrast, van der Waals interactions between PFCA and water significantly decrease PFCA binding affinity. Overall, LSER is demonstrated as a promising approach for predicting the adsorption of ionizable PFAS by MPs after the correction of Abraham's solute descriptors to account for their ionization.

Investigation of the effective interactions of two bioactive compounds in different media

Numerous biological, pharmacological, medical, and therapeutic researches frequently employ Triazole and the closely related molecules. Solvent induced effects can modify their function in various fields. In order to study the likelihood of interactions between the solvent molecules and the Triazole medications and to calculate their dipole moments, the spectrum characteristics of two Triazole pharmaceuticals were recorded in a variety of solvents. Both the experimental solvatochromic approach for detecting the dipole moments and the linear solvation energy relationship models (Kamlet–Abboud–Taft and Catalán) were taken into consideration. The experimental data validated the results from computational method. The findings demonstrated that solvent basicity and polarity/polarizability, rather than solvent acidity, dominate the regulation of these medicines. The values of the dipole moment in the ground and excited states are indicative of intra–molecular charge transfer. The assessment of active sites was made easier by the existence of a solvent-accessible surface. These results might help researchers and pharmacists create novel medicines or decide how to use existing ones.

Solubility Determination and Thermodynamic Properties of 5-Bromo-2-pyridinecarboxylic Acid in 10 Monosolvents and 3 Binary Solvents at T = (278.15–323.15) K

The static equilibrium method combined with high-performance liquid chromatography was used to determine the solubility of 5-bromo-2-pyridinecarboxylic acid at T = 278.15–323.15 K in 10 monosolvents (methanol, ethyl alcohol, acetonitrile, methyl acetate, ethyl acetate, n-propanol, isopropanol, n-butanol, tetrahydrofuran, and 1,4-dioxane) and 3 kinds of binary solvents (ethyl acetate + tetrahydrofuran, ethyl acetate + methanol, and ethyl acetate + 1,4-dioxane). The results show that 5-bromo-2-pyridinecarboxylic acid is positively related to temperature, and the solubility of 5-bromo-2-pyridinecarboxylic acid in tetrahydrofuran was the highest. In monosolvents, the modified Apelblat model and λh model were used to fit the solubility data of 5-bromo-2-pyridinecarboxylic acid. The solubility data of binary solvents were obtained by combining the nearly ideal binary solvent/Redlich–Kister model and Jouyban–Acree model, which showed that the experimental data were in good agreement with the fitting data. Furthermore, we chose the Kamlet, Abboud, and Taft linear solvation energy relationship model to analyze the relationship between the solute–solvent intermolecular interaction and the solubility of 5-bromo-2-pyridinecarboxylic acid. The results show that the increase of solvent–solvent interaction is beneficial to the dissolution of 5-bromo-2-pyridinecarboxylic acid.

Modeling headspace solid-phase microextraction of volatile organic compounds from water samples with porous coatings using finite element analysis

• Model was developed for simulation of HSSPME of VOCs from water by Car/PDMS at 25 °C. • Diffusivity in fluids was estimated by Fuller, and Wilke and Chang methods. • Fiber-air distribution constants were estimated using LSER model. • Southworth approach was accurate to model mass transport from water to headspace. • The model was applied for optimizing extraction parameters and preincubation time. This research was aimed at the development of the COMSOL Multiphysics® (CMP) model for simulating the headspace (HS) solid-phase microextraction (SPME) of volatile organic compounds (VOCs) from water using Carboxen/polydimethylsiloxane coating at 25 °C. The developed model is mainly based on existing theory and previous research on the numerical modeling of SPME. Fuller method was used to estimate diffusion coefficients in air as well as pores and voids of the coating. Coating-headspace distribution constants were estimated using linear solvation energy relationship (LSER) model and multiple regression obtained by Prikryl and Sevcik. Headspace-water constants were estimated using vapor pressures and activity coefficients were determined using UNIFAC model. Wilke and Chang method was chosen for estimating diffusion coefficients in water without stirring. Liss and Slater, and Southworth approaches were tested for estimating mass transfer coefficients at the headspace-water boundary under stirring. Southworth approach allowed obtaining benzene, toluene, ethylbenzene and o -xylene (BTEX) extraction profiles from water, which were closest to experimental profiles compared to other approaches. When using Southworth approach, root mean square deviation (RMSD) between experimental and simulated values for BTEX were 8.7–10% indicating the high accuracy of the model. The developed model was successfully applied for computational optimization of extraction parameters (stirring speed, fiber insertion depth, pressure, sample volume and the concentration of added salt). After minor modification, the model was also applied for optimization of preincubation time. It can be recommended for optimization of HSSPME-based analytical methods for VOCs quantification in water.