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Rapid Analysis of Complex Mixtures by Means of Resonant Laser Ionization Mass Spectrometry

  • Christian Weickhardt
  • Karen Tönnies
Chapter

Abstract

Unlike any other field of instrumental analysis, mass spectrometry is in a phase of highly dynamic development, in which new areas of applications and technical or methodical innovations stimulate one another. Its popularity arises from its universal applicability, its high sensitivity, the quickness of its measurements and their high information content. On the instrumental side, besides the continuous improvement of the conventional types of mass spectrometers, the development of novel ones on the basis of magnetic and electrodynamic ion traps (March and Todd 1995) has to be mentioned. However, the most important improvements in the field of mass spectrometry within the last decade are probably due to the development of new ionization techniques. These are, on the one hand side methods which allow the intact ionization of large, in particular biologically and medically relevant, molecules (e.g. Electrospray Ionization (Gaskell 1997) and Matrix Assisted Laser Desorption/Ionization (Karas et al. 1991) and on the other side techniques which involve a certain degree of selectivity in the ionization step. Selectivity is imperative for the analysis of complex mixtures and is usually added to a mass spectrometric measurement in form of chromatographic preseparation. However, chromatographic techniques eliminate one of the major advantages of mass spectrometry: the quickness of the measurement. Furthermore, they require a considerable effort for the sample preparation, which as far as time consumption is concerned in many cases exceeds that for the instrumental analysis step by far. Finally, sample preparation and clean-up are a major source of quantitative errors.

Keywords

Laser Desorption Laser Shot Multiphoton Ionization Nanosecond Laser Pulse Technical Paper Series 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Christian Weickhardt
  • Karen Tönnies

There are no affiliations available

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