In-Line Dopant Generation for Atmospheric Pressure Ionization Mass Spectrometry

Atmospheric pressure photoionization (APPI) has been successfully demonstrated to provide high sensitivity to LC-MS analysis. A vacuum-ultraviolet lamp designed for photoionization detection in gas chromatography is used as a source of 10-eV photons. The mixture of samples and solvent eluting from an HPLC is fully evaporated prior to introduction into the photoionization region. In the new method, large quantities of an ionizable dopant are added to the vapor generated from the LC eluant, allowing for a great abundance of dopant photoions to be produced. Because the ion source is at atmospheric pressure, and the collision rate is high, the dopant photoions react to completion with solvent and analyte molecules present in the ion source. Using APPI, at an LC flow rate of 200 microL/min, it is possible to obtain analyte signal intensities 8 times as high as those obtainable with a commercially available corona discharge-atmospheric pressure chemical ionization source.

The most widely used ionization techniques in liquid chromatography-mass spectrometry (LC-MS) are electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI) and atmospheric pressure photoionization (APPI). All three provide user friendly coupling of LC to MS. Achieving optimal LC-MS conditions is not always easy, however, owing to the complexity of ionization processes and the many parameters affecting mass spectrometric sensitivity and chromatographic performance. The selection of eluent composition requires particular attention since a solvent that is optimal for analyte ionization often does not provide acceptable retention and resolution in LC. Compromises must then be made between ionization and chromatographic separation efficiencies. The review presents an overview of studies concerning the effect of eluent composition on the ionization efficiency of ESI, APCI and APPI in LC-MS. Solvent characteristics are discussed in the light of ionization theories, and selected analytical applications are described. The aim is to provide practical background information for the development and optimization of LC-MS methods.