•System maps for acetone-water compositions for five different column provided.•For acetone mobile phases intermolecular interactions responsible for retention are characterized.•Retention properties ...of acetone, acetonitrile and methanol compared.•Solvation properties of acetone is closer to acetonitrile than methanol.
The solvation parameter model is used for the selectivity evaluation of siloxane-bonded reversed-phase columns with mobile phases containing from 20-70 % (v/v) acetone-water. System constants determined at 10 % (v/v) increments of acetone solvent were utilized for the construction of system maps and correlation diagrams on five columns with different stationary phase chemistry; superficially porous octadecylsiloxane-bonded silica (Kinetex C18), electrostatic-shielded octadecylsiloxane-bonded silica (Luna Omega PS C18, diisobutyloctadecyl-bonded silica(Kinetex XB-C18), phenylhexyl-bonded silica (Kinetex Phenyl-Hexyl) and octylsiloxane-bonded silica (Kinetex C8). For all columns and acetone-water compositions the calibration n = 34 to 39 had a range for the coefficient of determination from 0.988 to 0.998, Fisher statistic from 277 to 1551 and a standard error of the estimate from 0.024 to 0.097. A comparison of the system constants for acetonitrile and methanol compositions for the same separation conditions confirms that the general solvation properties of acetone mobiles phases are more similar to that of acetonitrile than methanol and that method transfer should not be difficult.
•System maps for three tetrahydrofuran-2-propanol mixed solvents provided.•The selectivity space of the three mixed organic solvents were explored.•Intermolecular interactions contributing retention ...of the three mixed solvents explored.
Three mixed mobile phase organic modifiers, tetrahydrofuran: 2-propanol 1:1 (v/v), tetrahydrofuran: 2-propanol: 1:3 (v/v), and tetrahydrofuran: 2-propanol: 3:1 (v/v) were studied at 20–70% (v/v) total organic solvent compositions. The solvent strength parameters for the three mixed organic modifiers and system properties were compared to those of more established binary solvent systems, acetonitrile-water and methanol-water. To interpret intermolecular interactions responsible for retention for the three mixed mobile phase organic modifiers, system maps were constructed and compared with acetonitrile and methanol. Three mixed organic mobile phase modifiers on one stationary phase chemistry (Kinetex C18) provide different selectivity than the more established acetonitrile and methanol mobile phase modifiers on the same stationary phase (Kinetex C18) as well as different stationary phase chemistries (Kinetex Biphenyl, Kinetex Phenyl-Hexyl, Kinetex F5, Kinetex XB-C18, and Kinetex EVO C18). The solvation parameter models for all three mixed mobile phase systems the coefficient of determination ranged from 0.991 to 0.999, the Fisher statistic from 338 to 1850, and the standard error of the estimate ranged from 0.024 to 0.097.
The solvation parameter model was used in this study to investigate various intermolecular interactions that influence retention on the standard C18 stationary phase for the solvent system ...acetonitrile:methanol (ACN:MeOH, 1:1). In comparison to the organic mobile phase modifiers acetonitrile, acetone, methanol, 2‐propanol, and tetrahydrofuran, the solvent strength for the ACN:MeOH (1:1) solvent system was evaluated. To facilitate the interpretation of various intermolecular interactions that contribute to retention on a standard C18 stationary phase for the solvent system ACN:MeOH (1:1), system maps were constructed and compared with those of acetone, tetrahydrofuran, acetonitrile, 2‐propanol, and methanol. The solvation parameter models were constructed for the ternary solvent system ACN:MeOH (1:1)‐water, and in the models constructed, the coefficient of determination values were from 0.998 to 0.999, the Fisher statistic values for the models were from 1687 to 4015, and the standard error of the estimate values ranged from 0.022 to 0.029. The solvent system ACN:MeOH (1:1) has retention properties more similar to methanol than acetonitrile, indicating methanol's influence is more dominant.
The solvation parameter model system constants and retention factors were used to interpret retention properties of 39 calibration compounds on a biphenylsiloxane‐bonded stationary phase (Kinetex ...biphenyl) for acetone‐water binary mobile phase systems containing 30–70% v/v. Variation in system constants, phase ratios, and retention factors of acetone‐water binary mobile phases systems were compared with more commonly used acetonitrile and methanol mobile phase systems. Retention properties of acetone mobile phases on a Kinetex biphenyl column were more similar to that of acetonitrile than methanol mobile phases except with respect to selectivity equivalency. Importantly, selectivity differences arising between acetone and acetonitrile systems (the lower hydrogen‐bond basicity of acetone‐water mobile phases and differences in hydrogen‐bond acidity, cavity formation and dispersion interactions) could be exploited in reversed‐phase liquid chromatography method development on a Kinetex biphenyl stationary phase.
•Surrogate chromatographic models to predict environmental properties.•Calculation of solute descriptors using chromatographic measurements.•Application of the solvation parameter model to ...characterize environmental processes.
The transfer of neutral compounds between immiscible phases in chromatographic or environmental systems can be described by six solute properties (solute descriptors) using the solvation parameter model. The solute descriptors are size (McGowan's characteristic volume), V, excess molar refraction, E, dipolarity/polarizability, S, hydrogen-bond acidity and basicity, A and B, and the gas-liquid partition constant on n-hexadecane at 298.15 K, L. V and E for liquids are accessible by calculation but the other descriptors and E for solids are determined experimentally by chromatographic, liquid-liquid partition, and solubility measurements. These solute descriptors are available for several thousand compounds in the Abraham solute descriptor databases and for several hundred compounds in the WSU experimental solute descriptor database. In the first part of this review, we highlight features important in defining each descriptor, their experimental determination, compare descriptor quality for the two organized descriptor databases, and methods for estimating Abraham solute descriptors. In the second part we focus on recent applications of the solvation parameter model to characterize environmental systems and its use for the identification of surrogate chromatographic models for estimating environmental properties.
•Overview of analytical derivatizations methods.•Pros and cons of analytical derivatization methods in environmental analysis.•Challenges and future directions of derivatization method in ...environmental analysis.
Analytical derivatization is a technique that alters the structure of an analyte and produces a product more suitable for analysis. While this process can be time-consuming and add reagents to the procedure, it can also facilitate the isolation of the analyte(s), enhance analytes’ stability, improve separation and sensitivity, and reduce matrix interferences. Since derivatization is a functional group analysis, it improves selectivity by separating reactive from neutral compounds during sample preparation. This technique introduces detector-orientated tags into analytes that lack suitable physicochemical properties for detection at low concentrations. Notably, many regulatory bodies, especially those in the environmental field, require these characteristics in analytical methods. This review focuses on note-worthy analytical derivatization methods employed in environmental analyses with functional groups, phenol, carboxylic acid, aldehyde, ketone, and thiol in aqueous, soil, and atmospheric sample matrices. Both advantages and disadvantages of analytical derivatization techniques are discussed. In addition, we discuss the future directions of analytical derivatization methods in environmental analysis and the potential challenges.
•Solvent strength parameter is compound and column dependent.•Solvation parameter model predicts compound-specific solvent strength parameters accurately.•Compound-specific log kw values are column ...and solvent dependent.•Average solvent strength parameter is a poor choice for method development.
The solvent strength parameter (slope) and intercept (log kw) of the linear solvent strength model are determined for methanol-water (17 columns), acetonitrile-water (15 columns), acetone-water (7 columns), tetrahydrofuran-water (6 columns), and 2-propanol-water (4 columns) for varied compounds. It is shown that the linear region of the plots of the retention factor (log k) against the volume fraction of organic solvent (ϕ) is largely a system property independent of solute type for compounds with accessible retention factors. Solvent strength parameters for methanol (3.12 ± 0.12), acetonitrile (2.78 ± 0.18), acetone (2.71 ± 0.11), and tetrahydrofuran (2.95 ± 0.24) are assigned for siloxane-bonded silica and porous graphitic carbon columns as an average of the compound-specific experimental values. Statistical analysis indicates that the compound-specific solvent strength parameters are column dependent and limited as a general solvent property. Evaluation of the column-specific solvent strength parameters provides further evidence that the average solvent strength parameter is column dependent. The column-specific solvent strength values are compared with the hypothetical water-organic solvent distribution systems using the system constants of the solvation parameter models as variables confirming the column dependence of the solvent strength parameter. The column-specific solvent strength parameters can be predicted by the solvation parameter model with a typical deviation of about 0.12 over a range of 1.69 to 6.33 for the experimentally determined values. The intercept of the linear solvent strength model is shown to be both column and organic solvent dependent. Compound column-specific values are adequately described by the solvation parameter model. Log kw cannot be recommended as a descriptor of solute properties since it has no clear connection to a real distribution system.
•Overview of sample preparation methods for citrinin analysis.•Overview of separation and detection methods for citrinin analysis.•Pros and cons of each technique described.•Recent trends and future ...directions.
Citrinin is a toxic small organic molecule produced as a secondary metabolite by fungi types Penicillium, Monascus and Aspergillus and is known to contaminate various food commodities during postharvest stages of food production. During the last 10 years, most reported methods for citrinin analysis employed enzyme-linked immunosorbent assays or high-performance liquid chromatography. Over this same time period, liquid extraction, solid-phase extraction, dispersive liquid-liquid microextraction and QuEChERS were the most cited sample preparation and clean-up methods. In this review the advantages and disadvantages of the various sample preparation, separation and detection methods for citrinin analysis over the last decade are evaluated. Furthermore, current trends, emerging technologies and the future prospects of these methods are discussed.
•Overview of solid-phase analytical derivatization in environmental analysis.•Pros and cons of solid-phase analytical derivatization methods.•Challenges and future directions of solid-phase ...analytical derivatization.
The increased accumulation of organic pollutants in various ecological systems in recent decades is a growing concern since these pollutants have detrimental effects on humans, animals, and plants. Two major contributing factors are pharmaceuticals and industrial waste chemicals from anthropogenic sources. To better understand the hazards environmental pollutants, represent to living beings, it is essential to develop sensitive, rapid, and reliable analytical methods. A subset of functional group analysis termed "analytical derivatization" modifies an analyte's structure to make it better suited for chromatographic analysis. Despite being an extra time-consuming step in sample preparation, analytical derivatization improves sensitivity, chromatographic separation, and selectivity in analytical method development. Solid-phase analytical derivatization, which combines extraction and derivatization steps, satisfies many requirements for an efficient sample preparation technique, which include reduced organic solvent usage, low cost, simplicity in automation with gas and liquid chromatographic systems, and applicability in a wide range of complex sample matrices. The focus of this review is on solid-phase analytical derivatization methodologies applied to analytical method development in environmental analysis, such as monitoring air pollution, water quality, and soil matrices. This review discusses the benefits and drawbacks of the solid-phase analytical derivatization approach in environmental analysis, the challenges ahead, and potential applications.
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•Direct methods for the prediction of equilibrium constants.•Main limitation of direct methods is the heterogeneity of the retention mechanism.•Indirect methods in the form of correlation models are ...the most common.•The paucity of surrogate chromatographic models is the main limitation of indirect methods.•Statistical parameters discussed for model selection and predictive capability.
The physicochemical properties of small molecules that can be determined by retention measurements in reversed-phase liquid chromatography include solvent-based properties inferred from equilibrium processes occurring predominantly in the mobile phase and sorption properties for materials which can be used as stationary phases inferred from solute-stationary phase interactions. In addition, physicochemical properties can be estimated from correlation models based on surrogate chromatographic systems with a similar capability for intermolecular interactions to the chemical or biological system. Examples of properties determined by direct methods include molecular descriptors (solvation parameter model), acid dissociation constants, formation constants, and surface properties of solids determined by inverse liquid chromatography. Examples of properties estimated by indirect methods include hydrophobicity, lipophilicity, n-octanol-water partition constant, soil-water sorption constant, non-specific toxicity to fish and microorganisms, and permeation coefficients for the blood-brain and skin-water barriers. Since all approaches depend on an accurate measurement of chromatographic retention parameters typical operational and mechanistic problems are discussed from the perspective of data quality. Fundamentally the accuracy of direct methods is limited by stationary phase heterogeneity and indirect methods by the limited number of suitable surrogate chromatographic models.
