Interactive Self-Modeling Mixture Analysis of Ion Mobility Spectra

Abstract

Ion mobility spectrometry (IMS) has been successfully developed to yield an advanced portable instrument. However, the formation of pure or heterogeneous cluster ions introduces nonlinear variances into the data. Cluster ions may arise from the sample in addition, and competition to the standard anticipated product ions and may deleteriously affect quantitative determinations. The SIMPLISMA (simple-to-use interactive self-modeling mixture analysis) method is demonstrated for detecting and modeling these nonlinear variances in IMS data, which is especially useful when vapor mixtures are encountered. Furthermore, SIMPLISMA may assist in the resolution of overlapping peaks that are characteristic of low-resolution IMS drift tubes. The synergistic combination of IMS and SIMPLISMA is shown for the detection of heterogeneous cluster ions produced from vapor mixtures of 1-pentanol and 1-octanol.