A Combination MAI and MALDI Vacuum Source Operational from Atmospheric Pressure for Fast, Robust, and Sensitive Analyses

Previously, vacuum matrix-assisted ionization (vMAI) was employed with matrix/analyte sample introduction into the vacuum of a mass spectrometer on a probe sample introduction device. Low attomole detection was achieved, while no carryover was observed even for concentrated samples. Here, we report a new vacuum ionization source designed to duplicate the sensitivity and robustness of probe device while providing fast multisample introduction to vacuum and rapid sequential ionization. Exposure of a sample to the vacuum of the mass spectrometer provides spontaneous ionization of volatile as well as nonvolatile analytes without the need for external energy input. However, the novel source design described herein, in addition to vMAI, can employ a laser to obtain vacuum matrix-assisted laser desorption/ ionization (vMALDI). In particular, ionization by vMAI or vMALDI is achieved by using the appropriate matrix. Switching between ionization modes is accomplished in a few seconds. We present results demonstrating the utility of the two ionization methods in combination to improve the molecular analyses of sample composition. In both ionization modes, multiple samples can be sequentially and rapidly acquired to increase throughput in MS. With the prototype source, samples were acquired in as little as 1 s per sample. Exchanging multisample plates can be accomplished in as little as 2 s, suggesting low-cost high-throughput automation when properly developed. [Graphics]

Automated summary

A new vacuum ionization source has been developed to provide fast multisample introduction to vacuum and rapid sequential ionization, duplicating the sensitivity and robustness of probe device. This source design allows for ionization using either vMAI or vMALDI, with the ability to switch between ionization modes in seconds. The combination of these two ionization methods improves molecular analyses of sample composition, with the potential for low-cost high-throughput automation.