In
this chapter, the principle of time-resolved measurements has been introduced
as a new approach in chemical sensing. Thereby the time-resolved measurements
performed in this work are based on Makrolon as sensitive polymer layer. The
microporous structure of this polymer allows the discrimination of different
analytes based on the size of the molecules. The combination of the polymer and
a time-resolved recording of the sensor responses during sorption and
desorption of the analytes allows a simultaneous quantification of a virtually
unlimited number of analytes. The analytes to be quantified are only limited by
too similar kinetics and by too slow kinetics whereby the kinetics can be
modified by the type of carrier gas and by the thickness of the sensitive
layer. The new time-resolved approach allows reducing the number of sensors to
be used for an analytical problem. In this work, several analytical tasks are
solved by the use of a single sensor setup rendering sensor arrays unnecessary,
which would have been used for these analytical problems in the common approaches.
Additional
research on other microporous polymers should allow the application of this
approach to a broader spectrum of analytes. Yet, the time-resolved measurements
are not limited to a size sensitive detection but can also be applied to other
interaction principles. The time-resolved approach with a discrimination of
the analytes based on exploiting the different shapes of the time-resolved sensor
responses also dramatically changes the search for suitable sensitive layers
for an analytical problem. Optimal sensitive layers of the common static sensor
evaluation show most different sensitivity patterns for the analytes (like in
section 3.3) whereas an optimal sensitive layer for the
time-resolved sensor evaluation shows different shapes of the sensor responses
for the different analytes.
In
contrast to the sparse reports of time-resolved measurements in chemical
sensing found in literature, the properties and interactions of the sensitive
layer with the analytes is systematically investigated in this study allowing
the tweaking of the kinetics described above. In the next chapters additional
systematic investigations follow, which concern the exposure time, the
recording speed of the of the sensor responses, the parallelization of the
sensors and last but not least the multivariate data analysis rendering this
work unique in respect to time-resolved measurements in chemical sensing.
Ph. D. Thesis