Possible strategy to use differential mobility spectrometry in real time applications

Osmo Anttalainen,Zahra Safaei,Jaroslaw Puton,Markus Karjalainen,Niku Oksala,Antti Roine,Anton Kontunen,Pekka Kumpulainen

doi:10.1007/s12127-019-00251-1

Abstract

Differential Mobility Spectrometry (DMS), also called as FAIMS is a variation of atmospheric pressure ion mobility measurement techniques and is capable of providing information about the electric field - mobility dependence of ions. In this method, a combined electric field is used. This field consists of asymmetric oscillating electric field of high intensity and low static field component. Analytical information in DMS is 2-dimensional dependence of ionic current on oscillating field amplitude and the value of static field intensity. The measurement of DMS signal for whole ranges of both variables is time consuming and also generates lot of data. It is a disadvantage of DMS method, which limits the use of this otherwise powerful technology in real time applications that require a response time of few seconds. This paper presents a way to limit measurement time by heuristic knowledge of the properties of the data space and another method based on the concept of Shannon Entropy to find operating parameters satisfying both separation and signal to noise ratio requirements.

Highlights

The purpose of spectrometric methods is to produce knowledge about the object under study by separating the sample matrix into the informative prime components
This paper introduces one possible strategy to reduce the measurement time in order to enable applications such as real time detection of biomarkers in surgical smoke
The measurement results from Differential Mobility Spectrometry (DMS) can be displayed as a heat map, where x-axis represents the compensation voltage UCV, y-axis the separation voltage USV and the intensity of the signal is colour coded

Summary

Introduction

The purpose of spectrometric methods is to produce knowledge about the object under study by separating the sample matrix into the informative prime components. The measurement results from DMS can be displayed as a heat map, where x-axis represents the compensation voltage UCV, y-axis the separation voltage USV and the intensity of the signal is colour coded. This type of data presentation is visually appealing, informative for the user and is an outcome of the natural way of parameter scanning in DMS. In case of uniform distribution, the probability of finding signal in each interval is pi

N and thus the formula for calculation the entropy becomes

Discussion