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HUANG Qi, REN Yi, CHEN Zheng-ge, CHEN Jian-song, HONG Yi, LIANG Xin, LI Mei, HUANG Zheng-xu, ZHOU Zhen. Voltage Optimization of Multiple Reflection Time of Flight Mass Analyzer Based on Particle Swarm Optimization Algorithm[J]. Journal of Chinese Mass Spectrometry Society, 2023, 44(5): 667-675. DOI: 10.7538/zpxb.2023.0024
Citation: HUANG Qi, REN Yi, CHEN Zheng-ge, CHEN Jian-song, HONG Yi, LIANG Xin, LI Mei, HUANG Zheng-xu, ZHOU Zhen. Voltage Optimization of Multiple Reflection Time of Flight Mass Analyzer Based on Particle Swarm Optimization Algorithm[J]. Journal of Chinese Mass Spectrometry Society, 2023, 44(5): 667-675. DOI: 10.7538/zpxb.2023.0024
shu

Voltage Optimization of Multiple Reflection Time of Flight Mass Analyzer Based on Particle Swarm Optimization Algorithm

  • 1.

    Institute of Mass Spectrometry and Atmospheric Environment, Jinan University, Guangzhou 510632, China

  • 2.

    Guangzhou Hexin Instrument Co., Ltd, Guangzhou 510530, China

  • 3.

    Guangzhou MS Institute of Scientific Instrument Innovation, Guangzhou 510700, China

  • 4.

    Guangdong Provincial Engineering Research Center for Online Source Apportionment System of Air Pollution, Guangzhou 510632, China

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    • Abstract
  • Time-of-flight mass spectrometry is a commonly mass spectrometry technique that is widely used in biomedicine, environmental science and food science. The multiple reflection time-of-flight (MR-TOF) mass analyzer is a new type of mass analyzer with ultra-high mass resolution and has been used at institutions, such as Helmholtz Centre for Heavy Ion Research (GSI), European Organization for Nuclear Research (CERN) and High Energy Accelerator Research Organization (KEK) to measure short-lived ion masses, separate isobar and store ions. As the demand for use increasing, it is becoming important to improve the resolving power of MR-TOF mass analyzers. However, the optimization of the voltage parameters of MR-TOF mass analyzers is a high-dimensional, highly refined and non-linear problem, which is difficult to solve optimally by analytical method. In this study, a particle swarm optimization (PSO) algorithm-based method for optimizing the voltage parameters of MR-TOF mass analyzers was proposed. The method used an improved particle swarm optimization (IPSO) approach with a inertia weight decay strategy. The optimization method was tested on the SIMION ion optics simulation platform. Considering 133Cs+ ion with E=1.5 keV, δE=8.5 eV, δx=δy=1 mm, δα=δβ=1.5 mrad, a mass resolving power over 8.1×105 was achieved when Δt=0 ns and a mass resolving power over 5.0×105 was achieved when Δt=20 ns. IPSO optimized the best results to achieve the 2nd order focus of time with respect to energy for the MR-TOF mass analyzer, and the deviation of the ion′s half-turn time of flight was within 1.3×10-6. In 20 times experiments, IPSO improved the maximum results by 33%, the average results by 35% and the standard deviation by 29% compared with PSO optimization, providing better solution quality and stability. IPSO′s linear decay strategy effectively controlled the reduction of the voltage update step size and was able to meet the global search and refinement of the MR-TOF mass analyzer voltage parameter optimization problem. It had good convergence and convergence speed. This work provided a fast and effective method for optimizing the voltage parameters of the MR-TOF mass analyzer and helped to improve the performance of this analyzer. The results showed that the IPSO is able to obtain a limiting mass resolution of more than 810 000, which has better performance compared with the PSO. The method has the advantages of simple operation, fast optimization and better solution, which can provide a method reference for voltage optimization of MR-TOF mass analyzer and thus improve the development efficiency of MR-TOF mass analyzer.
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    • References (29)
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