setups, which are based on the reflectometric interference spectroscopy, are
described in detail in section 4.3 (Array set-up) and
in section 4.4 (4l setup). For the sensor
array setup, 6 sensitive polymer layers were prepared using the polymers Polyetherurethane
(PUT), Polydimethylsiloxane (PDMS), a hyperbranched polyester (HBP), Ultrason
(UE 2010) and Makrolon (M 2400). Besides of measurements of single analyte vapors
for a sensitivity analysis, two data sets of binary mixtures were measured based
on an equidistant 6-level full factorial design .
Thereby the relative saturation pressures and thus the concentrations of the
analytes R22 and R134a were varied between 0 and 0.1 with synthetic air as ambient
gas. The first data set was generated by measuring the experimental design 4
times with the sensor array RIfS setup and the second data set was produced
by measuring the experimental design twice with the miniaturized 4l RIfS setup. The sensor
signals were recorded after 10 minutes of exposure to analyte and a recovery
time of 2 hours was chosen.
random subsampling procedure described in section 2.4
was used for splitting the data into a calibration data set (75%) and a test
data set (25%) with the confinement that all repeated measurements of a concentration
combination went into one subset to prevent overoptimistic predictions .
The neural networks implemented for this example had a topology of 1 output
neuron, 4 neurons in 1 hidden layer and 6 respectively 2 input neurons with
all features and parameters described in section 2.7.3