3. Theory Quantification of the Refrigerants R22
and R134a: Part I
chapter, an example of a multivariate calibration in chemical sensing is shown
whereby the focus of this example is the demonstration of the methods, which
are widely accepted and which can be found in literature over and over again.
This allows an easy comparison with the new approaches proposed in this study,
which are going far beyond the widespread techniques in the areas of multivariate
calibration and measurement principles. Furthermore, this data set will be examined
later again (section 9.5) using the new approaches proposed
in this work. Although the recording of the data set was not optimized for these
approaches, the new methods of data analysis show better results. Additionally
some concepts and theories of chemical sensing of vapors by polymer-based sensors
are introduced in this chapter.
of this example is the quantitative detection of the ozone depleting R22 (chlorodifluoromethan)
in the vapor of its harmless substitute R134a (1,1,1,2-tetrafluoroethan) and
in air for preliminary studies of on-line measurements in recycling stations.
More details of the environmental background of these refrigerants can be found
in section 4.5.1. First, the sorption characteristics
of 6 different polymers, which are exposed to different concentrations of the
refrigerants R22 and R134a, are investigated with a sensor array setup in respect
to sensitivities, sensitivity patterns, and calibration curves. Based on these
investigations two polymers are selected for the application in a miniaturized
low-cost 4l sensor setup, which
complies best with the conditions for on-site measurements at recycling stations.
Finally, different binary mixtures of R22 and R134a are measured by both setups
and a multivariate calibration is performed by the use of neural networks.