Simulation study of inverse diffusion counterbalance method for super-resolution ion mobility spectrometry

Abstract

Ion mobility spectrometer (IMS) is a powerful chemical composition analysis tool working at atmospheric pressure that can be used to separate complex samples and study molecular structures. Resolution is a key parameter for evaluating the performance of IMS. However, for the pulsed sampling technique used by drift tube IMS, there is an upper limit to the resolution due to the diffusion between ions and the drift gas. In this work, an inverse diffusion counterbalance method is proposed to break the resolution limit. The method is inspired by the stimulated emission depletion (STED). In optical microscopy systems, STED is used to break the optical diffraction limit by a ring of depleted light to counteract diffraction effects of the excited light. We modified this strategy and applied it to an IMS system for counteracting the diffusion effect of the pulsed ion packet. The method can increase the resolution up to 1.55 times through theoretical analysis, and the improvement is verified by simulations. The simulation results find that the initial width of the ion packet has an influence on the effectiveness of the method, and the narrower the initial width, the better the effect. The proposed inverse counterbalance strategy may also be applied to other spectral analysis instruments to break the resolution limit.

Publication
Frontiers in Chemistry
Kaitai Guo
Kaitai Guo
Assistant Professor

My research interests include broad-spectrum substance identification, microwave and infrared imaging, and system simulation and evaluation.

Yang Zheng
Yang Zheng
Assistant Professor

My research interests include human behaviour analysis for intelligent diagnosis of developmental coordination disorder, aritifical intelligence, and computer vision.

Haihong Hu
Haihong Hu
Associate Professor

My research interests include signal and image processing and computer vision.

Jimin Liang
Jimin Liang
Professor of Electronic Engineering

My research interests include artificial intelligence and computer vision.