The advantage of mixed-mode separation in the first dimension of comprehensive two-dimensional liquid-chromatography.

Comprehensive two-dimension liquid chromatography (LC×LC) has exhibited its powerful ability to separate complex samples. However, the use of a single chromatographic mode in 1st dimension has been limited to the separation of components by their individual characteristics, such as hydrophobicity, ionic properties etc. The use of mixed-mode stationary phases has revealed opportunities to combine different retention mechanisms. In this respect, stationary phases featuring both RP-like hydrophobic and ion-exchange interactive sites promise great versatility in retaining both polar and more apolar ionic and non-ionic compounds. We have therefore developed an LC×LC system based on mixed-mode (strong anion exchange and reversed phase) in the first dimension and a C18 phase in the second dimension. The system has been evaluated with standard compounds and applied for the separation of white wine and Chinese Herbal Medicine (CHM). The mixed-mode system SAX-PFP×C18 results in a better separation than a single mode system such as SAX×C18 or PFP×C18. Although little improvement in orthogonality (0.91 instead 0.86) is achieved with SAX×C18, the mixed-mode SAX-PFP×C18 gives a much larger effective peak distribution area in the analysis of e. g. white wine. But the analysis of aqueous extracts of CHM (Hdyotis diffusa and Scutellaria barbata) with SAX-PFP×RP leads to a very long analysis time because of strong hydrophobic interactions with the PFP column. Thus, the system was changed by using a cyano phase instead of a PFP phase. The improved SAX-CN×C18 system shows a better peak distribution and more importantly a reasonable analysis time.

High-performance liquid chromatography-mass spectrometry profiling of phenolic compounds for evaluation of olive oil bitterness and pungency.

Bitterness and pungency are important parameters for olive oil quality. Therefore, two instrumental methods for evaluation of these taste attributes were developed. The first one is based on the photometric measurement of total phenolic compounds content, whereas the second one is based on the semiquantitative evaluation of hydrophilic compounds by high-performance liquid chromatography-mass spectrometry (HPLC-MS). Evaluation of total phenolic compounds content was performed by a modified method for the determination of the K(225) value using a more specific detection based on the pH value dependency of absorbance coefficients of phenols at λ = 274 nm. The latter method was not suitable for correct prediction, because no significant correlation between bitterness/pungency and total phenolic compounds content could be found. For the second method, areas of 25 peaks detected in 54 olive oil samples by a HPLC-MS profiling method were correlated with the bitterness and pungency by partial least-squares regression. Six compounds (oleuropein aglycon, ligstroside aglycon, decarboxymethyl oleuropein aglycon, decarboxymethyl ligstroside aglycon, elenolic acid, and elenolic acid methyl ester) show high correlations to bitterness and pungency. The computed model using these six compounds was able to predict bitterness and pungency of olive oil in the error margin of the sensory evaluation (±0.5) for most of the samples.

A simple method for the determination of peak distribution in comprehensive two-dimensional liquid chromatography.

In LC × LC the peak capacity (2D)n and the orthogonality O are often used as parameters of resolving power. Unfortunately, these parameters are not easily accessible from chromatograms. In this work we will present a novel method, based on the description as vectors of experimentally easily accessible data. This approach makes it possible to calculate separation space (peak distribution) in parallelograms and other more complex geometric patterns by describing a two dimensional area by vectors. The calculated separation space allows a comparison between several column combinations and is a useful tool in optimization of LC × LC analysis.

Combination of chemical and electron-impact ionisation with GC x GC-qMS for characterization of fatty alcohol alkoxylate polymers in the low-molecular-weight range up to 700 Da.

The class of fatty alcohol alkoxylates describes surfactants that are synthesised by reaction of fatty alcohols with alkoxides such as ethylene oxide or propylene oxide or a combination of both as copolymers. Such alkoxylates are used, for example, as nonionic surfactants in home and industrial cleaning and washing agents. Chemical characteristics of such alkoxylate copolymers, for example the degree of alkoxylation, the arrangement of building blocks (random or block polymerisation), the type of the starter, and endcapping, play an important role in application behaviour. The analysis of these characteristics is challenging because in many cases such copolymers have high polydispersity and a large number of constitutional isomers depending on the degree of alkoxylation. Furthermore, the alkoxylates often occur in a complex multicomponent matrix. Here we present a method for characterization of silylated fatty alcohol alkoxylates in the low-molecular-weight range by means of comprehensive two-dimensional gas chromatography-mass spectrometry with electron impact and chemical ionisation. This method also enables detailed analysis of the alkoxylates in a complex matrix such as modern detergents.