Genetic algorithm parallel optimization of a new high mass resolution planar electrostatic ion trap mass analyzer

Abstract

The study and design of high-resolution mass analyzers is a very important task in mass spectrometry. A planar electrostatic ion trap (PEIT) mass analyzer with image charge detection and FT-based data processing has been developed, theoretically simulated, and experimentally validated. However, the 10 ring electrode configuration (PEIT-10) is difficult for mechanical construction and voltage tuning; moreover, few methods have been reported for optimizing the performance of multi-electrode mass analyzers. In this article, a simplified PEIT-7 mass analyzer was designed, and a genetic algorithm parallel optimization (GAPO) method was developed for optimizing multiple voltage settings of the new PEIT-7 mass analyzer to achieve spatial and energy isochronicity as well as iso-coordinate property. The automatic voltage optimization processes for the reduction of time aberration and spatial aberration showed that the developed GAPO method can significantly improve the optimization efficiency (the optimal voltage set being found within 5 hours with a maximum time aberration of 15 ps and a maximum z aberration of 0.10 μm). Based on the results obtained from the GAPO method, the resolving power of the PEIT-7 mass analyzer for six groups of ions with closely packed masses (m/z = 117.000 Th to 117.010 Th) was demonstrated, and a mass resolution of 171k was achieved at an acquisition time of 200 ms. The established GAPO method facilitates the design and optimization of high-resolution mass analyzers and may be useful for the design of other multi-electrode ion optical devices.