Chromatographic modeling as a tool in optimizing reversed-phase separation methods
| Authors | |
|---|---|
| Year of publication | 2022 |
| Type | Conference abstract |
| MU Faculty or unit | |
| Citation | |
| Description | Gradient elution can significantly enhance the separation in terms of the run time and peaks’ shape in HPLC. However, optimizing a gradient elution method can be a laborious process, especially if a larger number of compounds, significantly differing in the chromatographic behavior, needs to be separated. Multiple approaches are employed in order to obtain an ideal gradient composition over time – ranging from the “trial and error” methods to complex mathematical models. These models often rely on the Snyder’s equation and its modifications. In a typical setup, two or more separations are initially performed, and the results are fed to a software analysis tool, which tries to predict ideal conditions for the current system. Up to date available software tools for gradient run optimization lack either financial affordability or a feature-rich interface. A software tool developed in Python was developed, tested, and will be presented. |
| Related projects: |