Comparison of two free energy of solvation models for characterizing selectivity of stationary phases used in gas-liquid chromatography

Particle Size Regulation of Single-Crystalline Covalent Organic Frameworks for High Performance of Gas Chromatography

Although polycrystalline covalent organic frameworks (PCOFs) have already shown great potential as stationary phases for chromatography, irregular shape and size distribution of PCOFs make regulation of particle size of PCOFs for high separation performance impossible, which is accessible by the application of single-crystalline COFs (SCOFs). Herein, we showed preparation of three-dimensional SCOF (SCOF-303) bonded capillaries (SCOF-303-capillary) with different particle sizes (about 0.4-1.6 μm) and further investigated gas chromatographic separation ability of these SCOF-303-capillaries for isomers of xylene, dichlorobenzene, and pinene. It was found resolution and column efficiency of SCOF-303-capillaries for isomers decreased with the increase in particle size, mainly resulting from the weaker size-exclusion effect and higher mass transfer resistance of the larger particle size of flexible SCOF-303. The obtained SCOF-303-capillary (particle size of ∼0.4 μm) offered baseline separation of xylene isomers with the high resolution of 2.26-3.52, great efficiency of 7879 plates m^-1 for p-xylene, better than PCOF-303-capillary, and commercial DB-5 and HP-FFAP capillary columns as well as many reported capillaries. This work not only shows the great potential of SCOFs for gas chromatography but also provides the theoretical direction for the design of the efficient COF based stationary phase by adjusting the particle sizes.

Characterization of a dicationic imidazolium-based ionic liquid as a gas chromatography stationary phase

Here we report the characteristics of a new synthesized ionic liquid, 1,9-di(N-naphthalen-2-ylimidazolium)nonane bis[(trifluoromethyl)sulfonyl]imide ([C₉(2NPTim)₂][(NTf₂)₂]), as a stationary phase by inverse gas chromatography. The McReynolds constants demonstrated that the [C₉(2NPTim)₂][(NTf₂)₂] had an average polarity of 667 and polarity number P.N.=75, suggesting its polar nature. The solvation properties of the new stationary phase were determined by the calculation of Abraham solvation system constants, whereby the results showed that its major interactions with the analytes included H-bond basicity (a), dipole-dipole (s) and dispersive (l) interactions. The activity coefficients (γ^∞) and selectivities (S_IJ^∞) at infinite dilution were also determined for various polar and nonpolar organic solutes at different temperatures. The separation performance of the [C₉(2NPTim)₂][(NTf₂)₂] stationary phase was evaluated by GC separations of different analytes, including normal alkanes and aromatic compounds. The TGA results showed that the stationary phase had high thermal stability up to 420°C.

Separation characteristics of wall-coated open-tubular columns for gas chromatography

The application of the solvation parameter model for the classification of wall-coated open-tubular columns for gas chromatography is reviewed. A system constants database for 50 wall-coated open-tubular columns at five equally spaced temperatures between 60 and 140 degrees C is constructed and statistical and chemometric techniques used to identify stationary phases with equivalent selectivity, the effect of monomer chemistry on selectivity, and the selection of stationary phases for method development. The system constants database contains examples of virtually all commercially available common stationary phases.

Neural networks in analytical chemistry

This chapter covers a part of the spectrum of neural-network uses in analytical chemistry. Different architectures of neural networks are described briefly. The chapter focuses on the development of three-layer artificial neural network for modeling the anti-HIV activity of the HETP derivatives and activity parameters (pIC50) of heparanase inhibitors. The use of a genetic algorithm-kernel partial least squares algorithm combined with an artificial neural network (GA-KPLS-ANN) is described for predicting the activities of a series of aromatic sulfonamides. The retention behavior of terpenes and volatile organic compounds and predicting the response surface of different detection systems are presented as typical applications of ANNs in chromatographic area. The use of ANNs is explored in electrophoresis with emphasizes on its application on peptide mapping. Simulation of the electropherogram of glucagons and horse cytochrome C is described as peptide models. This chapter also focuses on discussing the role of ANNs in the simulation of mass and 13C-NMR spectra for noncyclic alkenes and alkanes and lignin and xanthones, respectively.

The chemical interpretation and practice of linear solvation energy relationships in chromatography

This review focuses on the use of linear solvation energy relationships (LSERs) to understand the types and relative strength of the chemical interactions that control retention and selectivity in the various modes of chromatography ranging from gas chromatography to reversed phase and micellar electrokinetic capillary chromatography. The most recent, widely accepted symbolic representation of the LSER model, as proposed by Abraham, is given by the equation: SP=c + eE + sS + aA + bB + vV, in which, SP can be any free energy related property. In chromatography, SP is most often taken as logk' where k' is the retention factor. The letters E, S, A, B, and V denote solute dependent input parameters that come from scales related to a solute's polarizability, dipolarity (with some contribution from polarizability), hydrogen bond donating ability, hydrogen bond accepting ability, and molecular size, respectively. The e-, s-, a-, b-, and v-coefficients and the constant, c, are determined via multiparameter linear least squares regression analysis of a data set comprised of solutes with known E, S, A, B, and V values and which span a reasonably wide range in interaction abilities. Thus, LSERs are designed to probe the type and relative importance of the interactions that govern solute retention. In this review, we include a synopsis of the various solvent and solute scales in common use in chromatography. More importantly, we emphasize the development and physico-chemical basis of - and thus meaning of - the solute parameters. After establishing the meaning of the parameters, we discuss their use in LSERs as applied to understanding the intermolecular interactions governing various gas-liquid and liquid-liquid phase equilibria. The gas-liquid partition process is modeled as the sum of an endoergic cavity formation/solvent reorganization process and exoergic solute-solvent attractive forces, whereas the partitioning of a solute between two solvents is thermodynamically equivalent to the difference in two gas/liquid solution processes. We end with a set of recommendations and advisories for conducting LSER studies, stressing the proper chemical and statistical application of the methodology. We intend that these recommendations serve as a guide for future studies involving the execution, statistical evaluation, and chemical interpretation of LSERs.

System constants of synthesized poly(methyl-3,3,3-trifluoropropyl) siloxanes

The method of solvation model has been applied to five poly (methyl-trifluoropropyl) siloxanes (TFPSXX) prepared in our laboratories, at five trifluoropropyl (TFP) group contents, XX = 0, 11.5, 26.3, 35.5 and 50.0%, at 80, 100, 120 and 140 degrees C. Previously, specific retention volumes of 60-odd solutes of varied polarities were measured upon each of these stationary phases within the above temperature range. Constant s prevails over all other constants, TFPSXX stationary phases showing strong dipole/induced dipole forces with the solutes, moderate acidity and no basicity at all. Constant e is zero in the stationary phase without TFP groups, but has negative low-medium values for the other fluorine contents, XX from 11.5 to 50.0%, hinting at repulsive forces, as expected. Normal values for constant l, decreasing from the less cohesive TFPS00 to the more cohesive TFPS50, were found. For each TFP content constants s, a and l show a negative temperature dependence, while constant e increases as temperature increases. Constant c also decreases with increasing temperature. At each temperature, constants s and a increase with increasing %TFP (or increasing stationary phase polarity), whereas constants e and l show the opposite trend, diminishing with increasing polarity of the stationary phase. Principal component analysis shows that the five stationary phases presented in this work conform a group with other earlier synthesized trifluoropropyl siloxanes and other fluorinated stationary phases taken from literature: VB-210, QF-1, DB-200, DB-210 and PFS6, showing the same selectivity which only the fluorine atom confers. A dendrogram of 38 stationary phases supports these results.

Development of fluorinated low temperature glassy carbon films for solid-phase microextraction

Solid-phase microextraction (SPME) fibers with supported fluorinated glassy carbon are demonstrated for the first time. Oligo[1,3-dibutadiynylene-1,3-(tetrafluoro)phenylene] was synthesized and heated to temperatures that varied from 200 to 1000 degrees C to produce the fluorinated glassy carbon. The extent of graphitization of the glassy carbon increased as the processing temperature increased. The fluorinated glassy carbon selectively extracted monohalogenated benzenes from an aqueous solution when compared to the extraction of toluene. The selectivity increased in the order of phi-F < phi-Cl < phi-Br < phi-I. The selectivity for the halogenated compounds was greatest for the fluorinated glassy carbon phase processed at temperature below approximately 400 degrees C. Preliminary studies on the retention mechanism of the LTGC phase show that dispersive interactions are very important to the retention of halocarbons on the fluorinated LTGC. Finally, the selectivity of the fluorinated LTGC for halogenated compounds was compared to that of commercially available SPME fibers, such as poly(dimethylsiloxane), poly(dimethylsiloxane)/divinylbenzene (PDMS/DVB), and poly(dimethylsiloxane)/Carboxen (PDMS/Carboxen) fibers. As expected the fluorinated LTGC was more selectivity for the halogenated compounds. Interestingly the order of the increase in selectivity is opposite when comparing the fluorinated-LTGC and the three commercial fibers. A decrease in selectivity was observed going from fluorobenzene to iodobenzene using PDMS/DVB and PDMS/Carboxen fibers. While for the pure PDMS phase, there is a slight increase in selectivity from fluorobenzene to chlorobenzene but the remaining trend shows little change for bromobenzene and iodobenzene.

Determination of thermodynamic properties by supercritical fluid chromatography

This survey attempts to summarise thermodynamic applications of supercritical fluid chromatography (SFC) with an emphasis on the results published during the last 10 years. In addition to a review of thermodynamic measurements by SFC, it contains brief sections on instrumental considerations and on the sources of auxiliary information needed when processing the retention data.

Development of comprehensive descriptors for multiple linear regression and artificial neural network modeling of retention behaviors of a variety of compounds on different stationary phases

A new series of six comprehensive descriptors that represent different features of the gas-liquid partition coefficient, K(L), for commonly used stationary phases is developed. These descriptors can be considered as counterparts of the parameters in the Abraham solvatochromic model of solution. A separate multiple linear regression (MLR) model was developed by using the six descriptors for each stationary phase of poly(ethylene glycol adipate) (EGAD), N,N,N',N'-tetrakis(2-hydroxypropyl) ethylenediamine (THPED), poly(ethylene glycol) (Ucon 50 HB 660) (U50HB), di(2-ethylhexyl)phosphoric acid (DEHPA) and tetra-n-butylammonium N,N-(bis-2-hydroxylethyl)-2-aminoethanesulfonate (QBES). The results obtained using these models are in good agreement with the experiment and with the results of the empirical model based on the solvatochromic theory. A 6-6-5 neural network was developed using the descriptors appearing in the MLR models as inputs. Comparison of the mean square errors (MSEs) shows the superiority of the artificial neural network (ANN) over that of the MLR. This indicates that the retention behavior of the molecules on different columns show some nonlinear characteristics. The experimental solvatochromic parameters proposed by Abraham can be replaced by the calculated descriptors in this work.

Calculation of Abraham solute descriptors from McReynolds gas chromatographic retention data

Quantitative descriptors of solubility properties are useful in the investigation of a wide variety of chemical and biological phenomena. Several solutes which may be useful in such studies are not suitable because these values have not been previously determined experimentally. Several solute descriptors used in the linear solvation energy relationship developed by Abraham and co-workers have been calculated either algebraically or by multiple linear regression analysis. Values for those descriptors which have been calculated are reported and the methods of calculation of these descriptors are also discussed. It is shown that both methods of determination of missing solute descriptor values agree statistically with each other and that the values reported for the calculated descriptors correlate well with data previously reported for similar homologs.

Solvent selection for whole cell biotransformations in organic media

Although they were used historically as antimicrobial agents, there is a modern requirement to devise organic solvent systems for exploitation in the biotransformation by intact cells of substrates that are poorly soluble in water. Water-immiscible solvents are normally less cytotoxic than are water-miscible ones. While a unitary mechanism is excluded, damage to the membrane remains the likeliest major mechanism of cytotoxicity, and may be conveniently assessed using an electronic biomass probe. Studies designed to account for the mechanisms of action of general anesthetics and of uncouplers parallel those designed to account for the cytotoxicity of organic solvents. Although there are hundreds of potential physical descriptors of solvent properties, many are broadly similar to each other, such that the intrinsic dimensionality of solvent space is relatively small (< 10). This opens up the possibility of providing a rational biophysical basis for the optimization of the solvents used for biotransformations. The widely used descriptor of solvent behavior, log P (the octanol:water partition coefficient), is a composite of more fundamental molecular descriptors; this explains why there are rarely good correlations between cytotoxicity and log P when a wide variety of solvents is studied. Although the intrinsic dimensionality of solvent space is relatively small, pure solvents still populate it rather sparsely. Thus, mixtures of solvents can and do provide the opportunity of obtaining a solvent optimal for a biotransformation of interest.