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.

A model to quantitatively predict ion abundances from atmospheric pressure chemical ionization (APCI) between hydrated protons and a volatile organic compound (VOC) was extended to binary mixtures of VOCs. The model includes differences in vapor concentrations, rate coefficients, and reaction times and is enhanced with cross reactions between neutral vapors and protonated monomers. In this model, two specific VOCs were considered, a ketone, 6-methyl-5-hepten-2-one (M, and an amine, 2,6-di-tert-butyl-pyridine (N), with measured "conditional rate coefficients" (in cm³·s^-1) of k_M = 1.11 × 10^-9 and k_N = 9.17 × 10^-10, respectively. The cross reaction of MH⁺(H₂O)_x to NH⁺(H₂O)_y was measured as k_cr = 1.31 × 10^-12 at 60 °C. Cross reactions showed an impact on ion abundances at t > 30 ms for equal vapor concentrations of 100 ppb for M and N. In contrast, this impact was negligible for vapor concentrations of 1 ppb and did not exceed 5% change in product ion abundance up to 1000 ms reaction times. The model was validated with laboratory measurements to within ∼10% using an ion mobility spectrometer and effective reaction time obtained from computational fitting of experimental findings. This was necessitated by complex flow patterns in the ion source volume and was determined as ∼10.5 ms. The model has interpretative and predictive value for quantitative analysis of responses with ambient pressure ion sources for mass spectrometry and ion mobility spectrometry.

Classification of volatile organic compounds (VOCs) is of interest in many fields. Examples include but are not limited to medicine, detection of explosives, and food quality control. Measurements collected with so-called electronic noses can be used for classification and analysis of VOCs. One type of electronic noses that has seen considerable development in recent years is Differential Mobility Spectrometry (DMS). DMS yields measurements that are visualized as dispersion plots that contain traces, also known as alpha curves. Current methods used for analyzing DMS dispersion plots do not usually utilize the information stored in the continuity of these traces, which suggests that alternative approaches should be investigated. In this work, for the first time, dispersion plots were interpreted as a series of measurements evolving sequentially. Thus, it was hypothesized that time-series classification algorithms can be effective for classification and analysis of dispersion plots. An extensive dataset of 900 dispersion plots for five chemicals measured at five flow rates and two concentrations was collected. The data was used to analyze the classification performance of six algorithms. The highest classification accuracy of 88% was achieved by a Long-Short Term Memory neural network, which supports the hypothesis that interpreting DMS measurements as sequential data is beneficial and outperformed classification algorithms traditionally used for DMS-based VOC identification.

The abundance of ions is an essential parameter for ion mobility and mass spectrometry instrument design and for the control or optimization of chemical reactions with reactant ions. This information also advances the study of atmospheric pressure ion kinetics under continuous ionization, which has a role in developing trace level chemical analyzers. In this study, an ionization chamber is described to measure the abundance of ions produced by a 4.9 keV, model L12535, soft x-ray source from Hamamatsu Corporation. Ions of positive and negative polarity were measured independently in an 8 × 30 mm² cross section at distances of 12–136 mm at ambient air from an uncollimated beam. Ions were collected using electric fields and 16 sets of plates. The ion current decreased exponentially with distance from the source, and the calculated ion concentration varied between 1.0 × 10⁸ and 3.8 × 10⁵ ions cm⁻³ on plates. A 2D-COMSOL model including losses by recombination and diffusion was favorably matched to changes in ion current intensity in the ionization chamber. Although the ionization chamber was built to characterize a commercial ion source, the design may be considered generally applicable to other x-ray sources.