Fluorescence measurements use a variety of parameters (eg, fluorescence intensity, anisotropy, lifetime, propagation and excitation spectra, fluorescence decay, and quantum performance) to analyze the data, thus providing considerable flexibility to this method. In general, fluorescence techniques can be divided into three main classes: intrinsic fluorescence, external fluorescence, and differential fluorescent probes [79, 143]. Bolse et al. Reported a fluorescent optoelectronic nose using aerosol jet printing for highly sensitive and highly selective detection of nitrobenzene, 1, 3-dinitrobenzene and DNT, which printed an array of sensors six different commercially available on a glass substrate. In addition, they were able to establish a low detection range of about 1 to 3ppb close to the detection range of trained dogs. most importantly, the sensor arrays using classifiers calculated from the LDA demonstrated excellent differentiation ability for nitroaromatic explosive. In addition to excellent statistics, these classifiers were shown to be suitable for optimal separation. This approach can pave the way for high-volume optoelectronic nose applications that can be understood with digital printing techniques [144, 145].
Fluorescence measurements
use
a variety of parameters (
eg
, fluorescence intensity,
anisotropy
, lifetime, propagation and excitation spectra, fluorescence decay, and quantum performance) to analyze the data,
thus
providing considerable flexibility to this method.
In general
, fluorescence techniques can
be divided
into three main classes: intrinsic fluorescence, external fluorescence, and differential fluorescent probes [79, 143].
Bolse
et al. Reported a fluorescent
optoelectronic
nose using aerosol jet printing for
highly
sensitive and
highly
selective detection of nitrobenzene, 1, 3-dinitrobenzene and DNT, which printed an array of sensors six
different
commercially
available on a glass substrate.
In addition
, they were able to establish a low detection range of about 1 to 3ppb close to the detection range of trained dogs.
most
importantly
, the sensor arrays using classifiers calculated from the LDA demonstrated excellent differentiation ability for
nitroaromatic
explosive.
In addition
to excellent statistics, these classifiers
were shown
to be suitable for optimal separation. This approach can pave the way for high-volume
optoelectronic
nose applications that can
be understood
with digital printing techniques [144, 145].