The ?PAC???capLC column serves those who are looking for increased robustness and throughput without losing sensitivity.
A flow rate versatility between 1 and 15 ?L/min at moderate pressures enables short gradient separations. The ?PAC? technology ensures an exceptionally high reproducibility over time and across laboratories. This makes the ?PAC? capLC column ideally suited for applications such as (clinical) proteomics, metabolomics and biopharmaceutical analyses.
The column is compatible with all commercially available capillary LC systems, and can be integrated smoothly in any experimental set-up.
Must be used in combination with a grounding cable (included).
Imported from the EU exclusively by ESI Source Solutions.
This column offers:
Optimal separation performance
Introducing perfect order in the chromatographic separation bed guarantees minimal peak dispersion resulting in high peak capacities and increased proteome coverage. Discover the results in our application note about peptide mapping.
Easy to implement
Plug and play connectivity by introducing commonly used 1/16? fittings from both sides, makes the column compatible with any third party LC vendor.
Each column has been manufactured by etching channels and arrays of pillars out of a solid silicon wafer. The column offers a high permeability and contains no particles or frits. This prevents blockages and retention time variation over multiple runs. Run your entire project on a single column.
Increased column to column reproducibility
The microfabrication production process, using the same lithographic mask, ensures that every column is identical. Replace ?PAC? capLC columns without shifts in retention time or differences in performance. Obtain results over time and across laboratories, sufficiently consistent for big data analysis.
High flow rate flexibility
The capLC column can be operated at moderate LC pump pressures up to 350 bar over a wide range of flow rates between 1 and 15 ?L/min. The entire capillary flow segment is covered with a single column as demonstrated in this webinar.