Dataset Information

High-pressure open-channel on-chip electroosmotic pump for nanoflow high performance liquid chromatography.

ABSTRACT: Here, we construct an open-channel on-chip electroosmotic pump capable of generating pressures up to ∼170 bar and flow rates up to ∼500 nL/min, adequate for high performance liquid chromatographic (HPLC) separations. A great feature of this pump is that a number of its basic pump units can be connected in series to enhance its pumping power; the output pressure is directly proportional to the number of pump units connected. This additive nature is excellent and useful, and no other pumps can work in this fashion. We demonstrate the feasibility of using this pump to perform nanoflow HPLC separations; tryptic digests of bovine serum albumin (BSA), transferrin factor (TF), and human immunoglobulins (IgG) are utilized as exemplary samples. We also compare the performance of our electroosmotic (EO)-driven HPLC with Agilent 1200 HPLC; comparable efficiencies, resolutions, and peak capacities are obtained. Since the pump is based on electroosmosis, it has no moving parts. The common material and process also allow this pump to be integrated with other microfabricated functional components. Development of this high-pressure on-chip pump will have a profound impact on the advancement of lab-on-a-chip devices.

SUBMITTER: Wang W

PROVIDER: S-EPMC3982979 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:The general limitations on liquid chromatographic performance in isocratic and gradient elution are now well understood. Many workers have contributed to this understanding and to developing graphical methods, or plots, to illustrate the capabilities of chromatographic systems over a wide range of values of operational parameters. These have been invaluable in getting a picture, in broad strokes, about the value of changing an operational parameter or the value of one separation approach over another. Here we present a plotting approach more appropriate for determining how to use chromatography most efficiently in one's own laboratory. The axes are linear: column length vertical and mobile phase velocity horizontal. In this coordinate system, straight lines with intercept zero correspond to different values of t0. Hyperbolas correspond to values of pressure as the product of length and velocity is proportional to pressure. For a given relationship between theoretical plate height and velocity (e.g., van Deemter), the number of theoretical plates as a function of column length and mobile phase velocity is a surface (z direction) to the x and y of velocity and length. By representing the surface as contours, a two-dimensional plot results. Any point along a constant pressure hyperbola represents the best one can do given the particle diameter, solute diffusion coefficient, and temperature. The user can quickly see how to use the pressure for speed or for more theoretical plates. Sets of such plots allow for comparisons among particle diameters or temperatures. Analogous plots of peak capacity for gradient elution are equally revealing. The plots lead instantly to understanding liquid chromatographic optimization at a practical level. They neatly illustrate the value (or not) of changing pump pressure, particle diameter, or temperature for fast or slow separations in either isocratic or gradient elution. They are illustrated with a focus on maximizing plate count with a given analysis time (isocratic), the effect of volume overload (isocratic), and separations of a limited number of peptides with a peak capacity coming from statistical peak overlap theory (gradient).

Project description:Gradient retention times are difficult to project from the underlying retention factor (k) vs. solvent composition (?) relationships. A major reason for this difficulty is that gradients produced by HPLC pumps are imperfect - gradient delay, gradient dispersion, and solvent mis-proportioning are all difficult to account for in calculations. However, we recently showed that a gradient "back-calculation" methodology can measure these imperfections and take them into account. In RPLC, when the back-calculation methodology was used, error in projected gradient retention times is as low as could be expected based on repeatability in the k vs. ? relationships. HILIC, however, presents a new challenge: the selectivity of HILIC columns drift strongly over time. Retention is repeatable in short time, but selectivity frequently drifts over the course of weeks. In this study, we set out to understand if the issue of selectivity drift can be avoid by doing our experiments quickly, and if there any other factors that make it difficult to predict gradient retention times from isocratic k vs. ? relationships when gradient imperfections are taken into account with the back-calculation methodology. While in past reports, the accuracy of retention projections was >5%, the back-calculation methodology brought our error down to ?1%. This result was 6-43 times more accurate than projections made using ideal gradients and 3-5 times more accurate than the same retention projections made using offset gradients (i.e., gradients that only took gradient delay into account). Still, the error remained higher in our HILIC projections than in RPLC. Based on the shape of the back-calculated gradients, we suspect the higher error is a result of prominent gradient distortion caused by strong, preferential water uptake from the mobile phase into the stationary phase during the gradient - a factor our model did not properly take into account. It appears that, at least with the stationary phase we used, column distortion is an important factor to take into account in retention projection in HILIC that is not usually important in RPLC.

Dataset Information

High-pressure open-channel on-chip electroosmotic pump for nanoflow high performance liquid chromatography.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets