The absolute need to improve the separating power of liquid chromatography, especially for multi-constituent biological samples, is becoming increasingly evident. In response, over the past few years, there has been a great deal of interest in the development of two-dimensional liquid chromatography (2DLC). Just as 1DLC is preferred to 1DGC based on its compatibility with biological materials we believe that ultimately 2DLC will be preferred to the much more highly developed 2DGC for such samples. The huge advantage of 2D chromatographic techniques over 1D methods is inherent in the tremendous potential increase in peak capacity (resolving power). This is especially true of comprehensive 2D chromatography wherein it is possible, under ideal conditions, to obtain a total peak capacity equal to the product of the peak capacities of the first and second dimension separations. However, the very long timescale (typically several hours to tens of hours) of comprehensive 2DLC is clearly its chief drawback. Recent advances in the use of higher temperatures to speed up isocratic and gradient elution liquid chromatography have been used to decrease the time needed to do the second dimension LC separation of 2DLC to about 20s for a full gradient elution run. Thus, fast, high temperature LC is becoming a very promising technique. Peak capacities of over 2000 and rates of peak capacity production of nearly 1 peak/s have been achieved. In consequence, many real samples showing more than 200 peaks with signal to noise ratios of better than 10:1 have been run in total times of under 30 min. This report is not intended to be a comprehensive review of 2DLC, but is deliberately focused on the issues involved in doing fast 2DLC by means of elevating the column temperature; however, many issues of broader applicability will be discussed.

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Two-dimensional liquid chromatography (2D-LC) is rapidly gaining popularity for the analysis of very complex mixtures, including proteomic and metabolomic samples. It provides an effective strategy for separating such samples, because the resolving power of 2D-LC is far superior to that of traditional single-dimension separations. The present work focuses on the development of data analysis methods for the extremely large data sets, on the order of 10 million data points, generated by 2D-LC with diode-array detection (DAD). Specifically, we have applied and adapted chemometric methods to the analysis of maize seedling digests, focusing on compounds related to the biosynthetic pathways of indole-3-acetic acid, the primary growth regulator in plants. The chemometric techniques of window target testing factor analysis (WTTFA), along with parallel factor analysis - alternating least squares (PARAFAC-ALS) were used to analyze 2D-LC-DAD chromatograms of a sample composed of 26 indolic standards, 2 extracts of mutant orange pericarp maize seedlings, 2 extracts of wild-type maize seedlings, and a blank sample. The indolic compounds studied belonged to six spectrally unique groups, and WTTFA was able to specifically identify the presence or absence of any of the 26 indolic standards in the mutant and wild-type samples. A PARAFAC-ALS algorithm and an ALS algorithm with flexible constraints were successfully applied to resolve the spectrally rank deficient data and to demonstrate the quantitative potential of multivariate curve resolution methods. Using this procedure, 95 total peaks were resolved in the data set analyzed. Of those 95 peaks, 45 were found in both the mutant and wild-type maize samples, 16 peaks were unique to the mutant maize samples, 13 peaks were unique to the wild-type maize samples, and 15 peaks were unique to the standard chromatograms. Of the 26 standards included in the data set, several indole acetic acid conjugates were identified and quantified in the maize samples at levels of approximately 0.3-2 microg/g plant material.

The solvatochromic comparison method has been used to probe the interactions of solutes with binary solvent mixtures of methanol-water and acetonitrile-water. The solute spectra recorded in these mixtures are composed of the additive spectral contributions of the different solvated species of the solute, i.e., the water-solvated species, the cosolvent-solvated species, and the species solvated by water-solvent complexes. Multivariate curve resolution-alternating least squares has been used to model the solvation of the solutes as a function of the composition of the binary solvent mixture. Spectra and concentration profiles of the dye surrounded by the different solvation environments have been isolated. For the first time, solute spectra solvated exclusively by methanol-water and acetonitrile-water complexes have been obtained, and the solvatochromic parameters of dipolarity/polarizability and hydrogen-bonding acidity have been estimated for these complex species.

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A series of solvatochromic dyes has been used to probe the solid/solution interface of Cis bonded silica in mobile-phase mixtures consisting of methanol and water and acetonitrile and water. Chromatographic capacity factors (k) were measured in order to determine the fraction of dye sorbed at the surface. An adaptive Kalman filter has been used to resolve the spectrum of the surface-phase dye from that due to dye in the adjacent solution. Values for the Kamlet-Taft dipolarity/ polarizability x* parameter for octadecylsilica in contact with the methanol/water mobile phase ranged from 0.72 to 0.75, indicating that the stationary phase is considerably more polar than bulk alkane solutions. The interfacial values for x* and a (the Kamlet-Taft hydrogen bond acidity parameter) support the hypothesis that the chemistry and solvation of the interphase region is strongly influenced by the presence of residual surface silanol groups.Reversed-phase liquid chromatography (RPLC) is a commonly used method for the separation of a wide variety of analytes. The application of RPLC involves the use of a relatively nonpolar stationary phase such as octadecyl silica, and a more polar mobile phase, such as water mixed with various organic solvents. From a practical viewpoint, RPLC is an extremely valuable technique. At the same time, the chemistry of the stationary phase (the interphase region)* 1 23456is complex and has not been completely characterized.The characterization of the interphase region using spectroscopic probes has, thus far, been limited to the use of fluorescent probe molecules. These methods have revealed information regarding the polarity of the solvated surface2,3 and have provided some of the first evidence that the chemistry and properties of the stationary phase are dependent upon interactions with mobile-phase components.2-6 Some common fluorescent probes that have been used are pyrene, n-propanedansylamide, and n-decanedansylamide.2-6 One limitation of these fluorescent probes is that they are relatively nonpolar and may only sorb to specific regions of the stationary phase. In addition, they do not allow specific interactions, such as hydrogen bonding, dipolar, and dispersion, to be identified and only give an indication of the overall

The retention properties of eight alkyl, aromatic and fluorinated reversed-HPLC bonded phases were characterized through the use of Linear Solvation Energy Relationships (LSERs). The stationary phases were investigated in a series of methanol-water mobile phases. LSER results show that solute molecular size under all conditions and hydrogen bond acceptor basicity are the two dominant retention controlling factors and that these two factors are linearly correlated when either different stationary phases at a fixed mobile phase composition or different mobile phase compositions at a fixed stationary phase are considered.The large variation in the dependence of retention on solute molecular volume as only the stationary phase is changed indicate that the dispersive interactions between nonpolar solutes and the stationary phase are quite significant relative to the energy of the mobile phase cavity formation process.Principal Component Analysis (PCA) results indicate that one PCA factor is required to explain the data when stationary phases of the same chemical nature (alkyl, aromatic and fluoroalkyl phases) are individually considered. However, three PCA factors are not quite sufficient to explain the whole data set for the three classes of stationary phases. In spite of this, the average standard deviation obtained by the use of these principal components factors are significantly smaller than the average standard deviation obtained by the LSER approach. In addition, selectivities predicted through the LSER equation are not in complete agreement with experimental results.These results show that the LSER model does not properly account for all molecular interactions involved in RP-HPLC. The failure could reside in the V 2 solute parameter used to account for both dispersive and cohesive interactions since "shape selectivity" predictions for a pair of structural isomers are very bad.

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