Simulation of elution profiles in liquid chromatography – IV: Experimental characterization and modeling of solute injection profiles from a modulation valve used in two-dimensional liquid chromatography

Detailed numerical study of the peak shapes of neutral analytes injected at high solvent strength in short reversed-phase liquid chromatography columns and comparison with experimental observations

“…Characteristic for the elution of these compounds is that, under the selected experimental injection conditions, they do not elute as a single peak but have a part eluting near the t0time of the column (so-called breakthrough fraction), followed by a long tail connecting to a second peak eluting near the expected retention time of the analyte (retained part of the peak). Similar peak shapes have very recently also been reported by Weatherbee et al [35], who found the exact peak shape to be strongly depending on the shape of the injection profile.…”

“…Whereas this profile has been obtained using Eq. ( 9), it should be remarked it is very similar to the profiles observed in [35] (appears backwards, because Figure S-7 is shown on the distance axis, and the profiles shown in [35] are shown on a time axis).…”

“…Given the short length of the investigated column, the eventually recorded peak shape not only depends strongly on the volume but also on the exact shape of the injected sample band, as was also observed by Weatherbee et al [35]. The degree of band broadening experienced by the analytes and the sample solvent (which are in general different from each other) contributes significantly to the eventual peak shape as well.…”

Untangling comprehensive two-dimensional liquid chromatography data sets using regions of interest and multivariate curve resolution approaches

“…In order to calculate retention parameters, statistical screening tests are useful as an input for the design of the experiments, optimal retention and chemometric modeling. Preliminary predictions of the retention times and simulation of elution profiles of the different analytes will reduce experimental effort and speed up the whole optimization process [29], especially due to the usually long LC Â LC runs. Besides, automated multicolumn LC Â LC workflows can accelerate method development, as they allow fast identification of the best combinations of columns and mobile phases compositions, for both targeted and untargeted analysis [30,31].…”

Recent advances in modelling and control of liquid chromatography

“…Owing to this additional complexity (or to bad habits), the incorrectly assumed rectangular injection profiles still prevail. There are exceptions, which use either experimentally determined injection profiles [46] or surrogate models derived by convoluting Gaussian, square and exponential residence time profiles, that can account for variable sample volumes and flow rates after parameter estimation [51 ]. Additional complexity arises from solvent mismatch between the sample and the mobile phase, which is more relevant to preparative chromatography [46].…”