Skip to main navigation Skip to search Skip to main content

A non-linear asymmetric error function-based least mean square approach for the analysis of multicomponent mass spectra measured by membrane inlet mass spectrometry

  • Raimo Ketola
  • , Marja Ojala
  • , Veikko Komppa
  • , Tapio Kotiaho*
  • , Jouni Juujärvi
  • , Jukka Heikkonen
  • *Corresponding author for this work
  • VTT (former employee or external)
  • Helsinki University of Technology

Research output: Contribution to journalArticleScientificpeer-review

Abstract

A nonlinear asymmetric error function‐based least mean square method (NALMS) for the deconvolution of identity and quantity of individual compounds based on the multicomponent mass spectra measured by membrane inlet mass spectrometry (MIMS) was developed and detailed testing results are presented. The method utilizes the complete mass spectra of the compounds present in a reference library during the calculation of a solution for an unknown multicomponent mass spectrum. The results presented here and in our previous publications in which the NALMS method was utilized show that the method can be used to separate complex multicomponent electron ionization mass spectra into their individual constituents, thus considerably improving the selectivity of MIMS.
Original languageEnglish
Pages (from-to)654-662
JournalRapid Communications in Mass Spectrometry
Volume13
Issue number8
DOIs
Publication statusPublished - 1999
MoE publication typeA1 Journal article-refereed

Fingerprint

Dive into the research topics of 'A non-linear asymmetric error function-based least mean square approach for the analysis of multicomponent mass spectra measured by membrane inlet mass spectrometry'. Together they form a unique fingerprint.

Cite this