Agilent | 6850 |
Stationary phase | |
Gas mobile phase | Helium (most common) / Nitrogen (moving towards) / Hydrogen |
Temperature range | 30 – 300 °C |
Detector | Flame ionization (FID) |
Gas chromatography with flame ionization detection (GC-FID) is a widely used analytical technique that allows for the separation, identification, and quantification of volatile and semi-volatile compounds in a sample. Sample is injected into a heated inlet, vaporizing the sample at ca. 350 °C. The vaporized material is then pulled into the column by the carrier gas (i.e., gas mobile phase). Typically, this carrier gas is helium; however, with the current helium shortage, most labs/systems are transitioning to nitrogen or hydrogen carrier gases, with nitrogen being the safer and cheaper option. Columns are generally capillary tubing filled with a thin film of thermally stable polymer material. Different components interact with the stationary phase to varying degrees and elution from the column can be aided by a temperature ramp. Sample-column interaction ultimately results in (ideally) isolated components at different retention times. The FI detector consists of a hydrogen-air flame, which combusts and ionizes the separately eluting components. The ionized compounds generate an electric current that can be measured, providing a signal proportional to concentration. By comparing the retention time to known standards, it is possible to identify and quantify the compounds present in the sample.
As with liquid chromatography (LC), GC can be applied to purity analysis. Or, more commonly, for polymer characterization, to pyrolysis analysis. Pyrolysis uses the high vaporization temperature, perhaps applied for longer time periods prior to loading onto the column, to decompose the polymer. This application yields quantitative evaluation of polymer structure, monomer composition, stereochemistry, tacticity, and molecular arrangements in homo and copolymers. In conjunction with techniques such as DSC or TGA(-MS), GC can provided complimentary data, especially for decomposition events that are close in temperature and/or complex product distribution (i.e., several decomposition products produced in a single decomposition event and producing a complex and difficult to evaluate EI-MS spectrum).