4.7 Article

Coulombic effects on resolution of ion mobility spectrometry and its application in online qualitative analysis

Journal

ANALYTICA CHIMICA ACTA
Volume 1183, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.aca.2021.338969

Keywords

Peak deconvolution; Asymmetric peak model; Improved ion mobility resolution; Ion diffusion modeling

Funding

  1. National Key Research and Develop-ment Project [2018YFC0809301]
  2. State Key Laboratory of NBC Protection for Civilian [sklnbc2019-07]

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This study presents an asymmetric peak model for processing ion mobility peaks to extract characteristic analyte peaks and achieve online qualitative analysis. By focusing on the Coulombic effects, a new hypothesis of ion cloud shape was proposed, and a formula for calculating the standard deviation was derived. The proposed method successfully decomposed overlapping peaks into individual peaks and outperformed other available methods in terms of execution time.
Ion mobility spectrometry is an important gas analysis method used in the rapid detection field. How-ever, due to a lacking of explicit mathematical model of ion peak, it is difficult to extract characteristic analyte peaks from a spectrum containing overlapping peaks to achieve online qualitative analysis. Here, we present an asymmetric peak model for processing ion mobility peaks. For the asymmetric peak model, the key is to accurately estimate the standard deviation of the peak model and the fitting function of the tailing edge. We focused on the Coulombic effects on resolution of ion mobility spectrometry based on a new hypothesis of ion cloud shape and derived a formula for calculating the standard de-viation taking the initial pulse width, diffusion and Coulomb repulsion factors into account. The proposed asymmetric peak model combines the advantages of optimal physical and chemical interpretation and explicit mathematical meaning. A fast decomposition method based on the peak model was developed to decompose overlapping peaks. Two overlapping simulated data sets and one real data set (a mixture of acetone and methyl salicylate) were used to test the method. The results indicated that our proposed method successfully decomposed the overlapping spectrum into individual peaks and performed markedly better than other three available methods in terms of the execution time. The proposed method meets the requirements for online qualitative analysis. (c) 2021 Elsevier B.V. All rights reserved.

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