Ren Gao1,2, Junhui Li1,2, Wenqing Gao2,3, Lei Li2,3, Xinkai Wang1,2, Bing Wu1,2, Yong Wu2,3, Jiancheng Yu1,2. 1. Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, 315211, China. 2. Institute of Mass Spectrometry, Ningbo University, Ningbo, 315211, China. 3. School of Material Science and Chemical Engineering, Ningbo University, Ningbo, 315211, China.
Abstract
RATIONALE: Ion mobility spectrometry (IMS) is a powerful analytical tool extensively applied in numerous domains. However, there still exists the phenomenon of peaks overlapping in the analysis of isomers with similar structures due to the limited resolution of IMS. In this paper, a dynamic inertia weight particle swarm optimization (DIWPSO) algorithm combined with second-order differentiation is proposed to separate the IMS overlapping peaks efficiently and precisely. METHODS: It can identify the component number of overlapping peaks and limit those parameters (ion mobility, intensity, and full-width at half maximum of each single peak) of the peak model in a small range using second-order differentiation. Based on this, DIWPSO that has been set the best operating parameters is capable of accurately separating IMS overlapping peaks to identify the compound within a short time. RESULTS: A comparison between the performance of DIWPSO and the improved particle swarm optimization (IPSO) found that DIWPSO with separation errors less than 2.34% overall outperforms IPSO whose maximum error is up to 5.58%. Moreover, the running time of DIWPSO is 30-80 times less than that of IPSO, and DIWPSO exhibits stronger robustness. CONCLUSIONS: This method can automatically identify the component number of IMS overlapping peaks and resolve them with muticomponents and different overlapped degrees rapidly and accurately, which further improves the structural resolution of IMS.
RATIONALE: Ion mobility spectrometry (IMS) is a powerful analytical tool extensively applied in numerous domains. However, there still exists the phenomenon of peaks overlapping in the analysis of isomers with similar structures due to the limited resolution of IMS. In this paper, a dynamic inertia weight particle swarm optimization (DIWPSO) algorithm combined with second-order differentiation is proposed to separate the IMS overlapping peaks efficiently and precisely. METHODS: It can identify the component number of overlapping peaks and limit those parameters (ion mobility, intensity, and full-width at half maximum of each single peak) of the peak model in a small range using second-order differentiation. Based on this, DIWPSO that has been set the best operating parameters is capable of accurately separating IMS overlapping peaks to identify the compound within a short time. RESULTS: A comparison between the performance of DIWPSO and the improved particle swarm optimization (IPSO) found that DIWPSO with separation errors less than 2.34% overall outperforms IPSO whose maximum error is up to 5.58%. Moreover, the running time of DIWPSO is 30-80 times less than that of IPSO, and DIWPSO exhibits stronger robustness. CONCLUSIONS: This method can automatically identify the component number of IMS overlapping peaks and resolve them with muticomponents and different overlapped degrees rapidly and accurately, which further improves the structural resolution of IMS.