Issue 19, 2019

Characterisation and optimisation of ion discrimination in a mini ion funnel for a miniature mass spectrometer

Abstract

Ion funnels have been miniaturised and integrated into miniature ion trap mass spectrometers to improve instrument sensitivity. However, the ion discrimination effect of the ion funnel constrains its application. Previous research has generally reported that the ion discrimination is related mainly to the mass of the ions. In this paper, the Runge–Kutta algorithm was used to characterise the trajectories of ions in the funnel under collisions with gas molecules. It is theoretically and empirically proved that, in a continuous atmospheric-pressure-interfaced miniature mass spectrometer, ion discrimination in the funnel shows two aspects: mass discrimination and collision cross-section discrimination. It was found that DC gradient, RF amplitude and operating pressure of the ion funnel will affect ion transmission. Among these parameters, RF amplitude is the key parameter controlling ion discrimination. To weaken the ion discrimination, RF amplitude scanning method was introduced in the injection section of the ion trap to improve ion transmission efficiency over the entire mass range. After optimisation of the ion funnel, the dynamic range of the instrument concentration reached four orders of magnitude. The detection limit of roxithromycin reached a low level of 1 ng mL−1. The results of this study increase the theoretical understanding of the ion funnel, providing guidance for applying ion funnels in improving the sensitivity of miniature mass spectrometers and expanding their actual applicability.

Graphical abstract: Characterisation and optimisation of ion discrimination in a mini ion funnel for a miniature mass spectrometer

Supplementary files

Article information

Article type
Paper
Submitted
01 Apr 2019
Accepted
15 Apr 2019
First published
27 Apr 2019

Anal. Methods, 2019,11, 2551-2558

Characterisation and optimisation of ion discrimination in a mini ion funnel for a miniature mass spectrometer

X. Zhang, X. Huo, F. Tang, Z. Zha, F. Yang, Y. Ni, Y. Wang, M. Zhou and X. Wang, Anal. Methods, 2019, 11, 2551 DOI: 10.1039/C9AY00677J

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