Previous Topic Back Forward Next Topic
Print Page Frank Dieterle
Ph. D. ThesisPh. D. Thesis 5. Results – Kinetic Measurements5. Results – Kinetic Measurements
About Me
Ph. D. Thesis
  Table of Contents
  1. Introduction
  2. Theory – Fundamentals of the Multivariate Data Analysis
  3. Theory – Quantification of the Refrigerants R22 and R134a: Part I
  4. Experiments, Setups and Data Sets
  5. Results – Kinetic Measurements
    5.1. Static Sensor Measurements
    5.2. Time-resolved Sensor Measurements
    5.3. Makrolon – A Polymer for Time-resolved Measurements
    5.4. Conclusions
  6. Results – Multivariate Calibrations
  7. Results – Genetic Algorithm Framework
  8. Results – Growing Neural Network Framework
  9. Results – All Data Sets
  10. Results – Various Aspects of the Frameworks and Measurements
  11. Summary and Outlook
  12. References
  13. Acknowledgements
Research Tutorials
Downloads and Links
Site Map
Print this Page Print this Page

5.   Results – Kinetic Measurements

In this chapter, the principle of the time-resolved measurements is introduced. In contrast to the common principles of static measurements and static feature extractions, this approach allows the simultaneous quantification of a virtually unlimited number of analytes. Although some sporadic reports of time-resolved measurements in chemical sensing can be found in literature, no systematic investigations of time-resolved measurements, no systematic exploi­tations of the time domain and no transfers to different setups and measurement principles have been reported for chemical sensing up to now. Although the approach of the time-resolved measurements can be used for many different transduction and interaction principles, this study focuses on the application of one specific polymer for the time-resolved measure­ments. Thus, after an explanation of the static and the time-resolved sensor measurements this polymer is introduced. Then different properties of the polymer and different interactions of the polymer with analyte molecules are investigated as the understanding of these properties and interactions allows tweaking the sensors for different analytical tasks. This tuning is demonstrated in the last sections of this chapter.

Page 78 © Frank Dieterle, 03.03.2019 Navigation