Leandro W. Hantao

Ionic Liquids in Analytical Chemistry: Fundamentals, Advances, and Perspectives

265 Application of IL-DLLME in the Analysis of Pharmaceutical Entities 265 IL-DLLME in the Analysis of Metal Ions 266 Application of IL-DLLME in the Analysis of Organic Environmental Pollutants 266

Multivariate curve resolution combined with gas chromatography to enhance analytical separation in complex samples: a review.

This review describes the major advantages and pitfalls of iterative and non-iterative multivariate curve resolution (MCR) methods combined with gas chromatography (GC) data using literature published since 2000 and highlighting the most important combinations of GC coupled to mass spectrometry (GC-MS) and comprehensive two-dimensional gas chromatography with flame ionization detection (GC×GC-FID) and coupled to mass spectrometry (GC×GC-MS). In addition, a brief summary of some pre-processing strategies will be discussed to correct common issues in GC, such as retention time shifts and baseline/background contributions. Additionally, algorithms such as evolving factor analysis (EFA), heuristic evolving latent projection (HELP), subwindow factor analysis (SFA), multivariate curve resolution-alternating least squares (MCR-ALS), positive matrix factorization (PMF), iterative target transformation factor analysis (ITTFA) and orthogonal projection resolution (OPR) will be described in this paper. Even more, examples of applications to food chemistry, lipidomics and medicinal chemistry, as well as in essential oil research, will be shown. Lastly, a brief illustration of the MCR method hierarchy will also be presented.

Chemical immobilization of crosslinked polymeric ionic liquids on nitinol wires produces highly robust sorbent coatings for solid-phase microextraction☆

Super elastic nitinol (NiTi) wires were exploited as highly robust supports for three distinct crosslinked polymeric ionic liquid (PIL)-based coatings in solid-phase microextraction (SPME). The oxidation of NiTi wires in a boiling (30%w/w) H2O2 solution and subsequent derivatization in vinyltrimethoxysilane (VTMS) allowed for vinyl moieties to be appended to the surface of the support. UV-initiated on-fiber copolymerization of the vinyl-substituted NiTi support with monocationic ionic liquid (IL) monomers and dicationic IL crosslinkers produced a crosslinked PIL-based network that was covalently attached to the NiTi wire. This alteration alleviated receding of the coating from the support, which was observed for an analogous crosslinked PIL applied on unmodified NiTi wires. A series of demanding extraction conditions, including extreme pH, pre-exposure to pure organic solvents, and high temperatures, were applied to investigate the versatility and robustness of the fibers. Acceptable precision of the model analytes was obtained for all fibers under these conditions. Method validation by examining the relative recovery of a homologous group of phthalate esters (PAEs) was performed in drip-brewed coffee (maintained at 60 °C) by direct immersion SPME. Acceptable recoveries were obtained for most PAEs in the part-per-billion level, even in this exceedingly harsh and complex matrix.

Quantitative analysis of essential oils in perfume using multivariate curve resolution combined with comprehensive two-dimensional gas chromatography

The use of multivariate curve resolution (MCR) to build multivariate quantitative models using data obtained from comprehensive two-dimensional gas chromatography with flame ionization detection (GC×GC-FID) is presented and evaluated. The MCR algorithm presents some important features, such as second order advantage and the recovery of the instrumental response for each pure component after optimization by an alternating least squares (ALS) procedure. A model to quantify the essential oil of rosemary was built using a calibration set containing only known concentrations of the essential oil and cereal alcohol as solvent. A calibration curve correlating the concentration of the essential oil of rosemary and the instrumental response obtained from the MCR-ALS algorithm was obtained, and this calibration model was applied to predict the concentration of the oil in complex samples (mixtures of the essential oil, pineapple essence and commercial perfume). The values of the root mean square error of prediction (RMSEP) and of the root mean square error of the percentage deviation (RMSPD) obtained were 0.4% (v/v) and 7.2%, respectively. Additionally, a second model was built and used to evaluate the accuracy of the method. A model to quantify the essential oil of lemon grass was built and its concentration was predicted in the validation set and real perfume samples. The RMSEP and RMSPD obtained were 0.5% (v/v) and 6.9%, respectively, and the concentration of the essential oil of lemon grass in perfume agreed to the value informed by the manufacturer. The result indicates that the MCR algorithm is adequate to resolve the target chromatogram from the complex sample and to build multivariate models of GC×GC-FID data.

Tuning the Selectivity of Ionic Liquid Stationary Phases for Enhanced Separation of Nonpolar Analytes in Kerosene Using Multidimensional Gas Chromatography

In this study, a series of ionic liquids (ILs) are evaluated as stationary phases in comprehensive two-dimensional gas chromatography (GC × GC) for the separation of aliphatic hydrocarbons from kerosene. IL-based stationary phases were carefully designed to evaluate the role of cavity formation/dispersive interaction on the chromatographic retention of nonpolar analytes by GC × GC. The maximum allowable operating temperature (MAOT) of the IL-based columns was compared to that of commercial IL-based columns. Evaluation of the solvation characteristics of GC columns guided the selection of the best performing IL-based stationary phases for the resolution of aliphatic hydrocarbons, namely, trihexyl(tetradecyl)phosphonium tetrachloroferrate ([P66614][FeCl4]) and trihexyl(tetradecyl)phosphonium tris(pentafluoroethyl)trifluorophosphate ([P66614][FAP]) ILs. The best performing [P66614][FeCl4] IL-based column exhibited a MAOT of 320 °C, higher than the commercial SUPELCOWAX 10 (MAOT of 280 °C) and commercial IL-based columns (MAOT up to 300 °C). The structurally tuned [P66614][FeCl4] IL stationary phase exhibited improved separation of aliphatic hydrocarbons by GC × GC compared to the commercial columns examined (e.g., OV-1701, SUPELCOWAX 10, SLB-IL60, SLB-IL100, and SLB-IL111).

Determination of disease biomarkers in Eucalyptus by comprehensive two-dimensional gas chromatography and multivariate data analysis

In this paper is reported the use of the chromatographic profiles of volatiles to determine disease markers in plants - in this case, leaves of Eucalyptus globulus contaminated by the necrotroph fungus Teratosphaeria nubilosa. The volatile fraction was isolated by headspace solid phase microextraction (HS-SPME) and analyzed by comprehensive two-dimensional gas chromatography-fast quadrupole mass spectrometry (GC×GC-qMS). For the correlation between the metabolic profile described by the chromatograms and the presence of the infection, unfolded-partial least squares discriminant analysis (U-PLS-DA) with orthogonal signal correction (OSC) were employed. The proposed method was checked to be independent of factors such as the age of the harvested plants. The manipulation of the mathematical model obtained also resulted in graphic representations similar to real chromatograms, which allowed the tentative identification of more than 40 compounds potentially useful as disease biomarkers for this plant/pathogen pair. The proposed methodology can be considered as highly reliable, since the diagnosis is based on the whole chromatographic profile rather than in the detection of a single analyte.

Detection of extraction artifacts in the analysis of honey volatiles using comprehensive two-dimensional gas chromatography

Extraction using headspace solid phase microextraction (HS-SPME) coupled to comprehensive two-dimensional gas chromatography with flame ionisation detection (GC×GC-FID) was employed to evaluate the effect of SPME fractionation conditions (heating time and temperature) on the generation of artifacts. The occurrence of artifacts was more pronounced at higher fractionation temperatures and times which caused significant changes in the chromatographic profiles. The identification of the volatile fraction of the honey blend was performed through a two-dimensional gas chromatograph coupled to a mass spectrometer with time of flight analyser (GC×GC-ToFMS) by comparing the first dimension linear temperature programmed retention index ((1)D-LTPRI) with the peaks identities provided by the mass spectral similarity search. Several artifacts were found and identified - such as hydroxymethylfurfural, methyl-furone and furfural - and some of them were not previously detected as such in honey samples. These compounds were either the result of hydrolysis or thermal decomposition of components already present in the honey samples. This occurrence was attributed to the increased detectability provided by GC×GC compared to conventional GC. The possible emergence of previously unknown extraction artifacts as a general tendency related use of GC×GC instead of conventional GC is discussed as a result of these observations.

Identification of volatiles from pineapple (Ananas comosus L.) pulp by comprehensive two‐dimensional gas chromatography and gas chromatography/mass spectrometry

Combining qualitative data from the chromatographic structure of 2-D gas chromatography with flame ionization detection (GC×GC-FID) and that from gas chromatography-mass spectrometry (GC/MS) should result in a more accurate assignment of the peak identities than the simple analysis by GC/MS, where coelution of analytes is unavoidable in highly complex samples (rendering spectra unsuitable for qualitative purposes) or for compounds in very low concentrations. Using data from GC×GC-FID combined with GC/MS can reveal coelutions that were not detected by mass spectra deconvolution software. In addition, some compounds can be identified according to the structure of the GC×GC-FID chromatogram. In this article, the volatile fractions of fresh and dehydrated pineapple pulp were evaluated. The extraction of the volatiles was performed by dynamic headspace extraction coupled to solid-phase microextraction (DHS-SPME), a technique appropriate for slurries or solid matrices. Extracted analytes were then analyzed by GC×GC-FID and GC/MS. The results obtained using both techniques were combined to improve compound identifications.

A chemometric approach toward the detection and quantification of coffee adulteration by solid-phase microextraction using polymeric ionic liquid sorbent coatings.

Solid-phase microextraction (SPME) using cross-linked polymeric ionic liquid (PIL)-based sorbent coatings was used to extract volatile aroma-related compounds from coffee samples. Several PIL-based coatings were screened alongside a commercial poly(acrylate) (PA) SPME coating. The best performing PIL-based SPME fiber, poly(1-vinyl-3-hexadecylimidazolium bis[(trifluoromethyl)sulfonylimide]) with 50% (w/w) 1,12-di(3-vinylbenzylimidazolium)dodecane dibis[(trifluoromethyl)sulfonyl]imide incorporated cross-linker, was used to isolate the volatile fraction of Arabica coffee. To illustrate the importance of trace analyte isolation, a method for the detection and quantification of coffee adulteration is described. Chromatographic profiles obtained by gas chromatography/mass spectrometry (GC/MS) were used to create the chemometric model. Partial least squares (PLS) regression was employed to correlate the aroma-related chemical fingerprint to the degree of adulteration. The proposed method successfully detected fraud down to 1% (w/w) of adulterant and accurately determined the degree of coffee adulteration (i.e, root mean square error of calibration and prediction of 0.54% and 0.83% (w/w), respectively). Finally, important aroma-related compounds including furans, methoxyphenols, pyrazines, and ketones were identified.

Quantitative analysis of biodiesel in blends of biodiesel and conventional diesel by comprehensive two-dimensional gas chromatography and multivariate curve resolution.

In this paper, a method to determine the composition of blends of biodiesel with mineral diesel (BXX) by multivariate curve resolution with Alternating Least Squares (MRC-ALS) combined to comprehensive two-dimensional gas chromatography with Flame Ionization Detection (GC×GC-FID) is presented. Chromatographic profiles of BXX blends produced with biodiesels from different sources were used as input data. An initial evaluation carried out after multiway principal component analysis (MPCA) was used to reveal regions of the chromatograms were the signal was likely to be dependent on the concentration of biodiesel, regardless its vegetable source. After this preliminary step MCR-ALS modeling was carried out only using relevant parts of the chromatograms. The resulting procedure was able to predict accurately the concentration of biodiesel in the BXX samples regardless of its origin.