Interactive Self-Modeling Mixture Analysis of Ion Mobility Spectra
- 1 June 1997
- journal article
- research article
- Published by SAGE Publications in Applied Spectroscopy
- Vol. 51 (6) , 808-816
- https://doi.org/10.1366/00037029760563499
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.Keywords
This publication has 10 references indexed in Scilit:
- Application of Eigenstructure Tracking Analysis and SIMPLISMA to the Study of the Protonation Equilibria of cCMP and Several PolynucleotidesAnalytical Chemistry, 1996
- Diffuse Reflectance Spectroscopy of Dehydrated Cobalt-Exchanged Faujasite-Type Zeolites: A New Method for Co2+ SitingThe Journal of Physical Chemistry, 1995
- Application of SIMPLISMA for the assessment of peak purity in liquid chromatography with diode array detectionAnalytica Chimica Acta, 1994
- The use of second-derivative spectra for pure-variable based self-modeling mixture analysis techniquesChemometrics and Intelligent Laboratory Systems, 1994
- Infrared Chemical Micro-Imaging Assisted by Interactive Self-Modeling Multivariate AnalysisApplied Spectroscopy, 1994
- Simple-to-use interactive self-modeling mixture analysis of FTIR microscopy dataJournal of Molecular Structure, 1993
- Pure Component Analysis of Chain Length Distributions from Solid-State Polymerization of FormaldehydeApplied Spectroscopy, 1992
- Self-modeling mixture analysis of second-derivative near-infrared spectral data using the SIMPLISMA approachAnalytical Chemistry, 1992
- Self-modeling mixture analysis of categorized pyrolysis mass spectral data with the SIMPLISMA approachChemometrics and Intelligent Laboratory Systems, 1992
- Interactive self-modeling mixture analysisAnalytical Chemistry, 1991