TY - GEN
T1 - Temperature-centric evaluation of sensor transients
AU - Ayhan, Tuba
AU - Muezzinoglu, Kerem
AU - Vergara, Alexander
AU - Yalcin, Mustak
PY - 2011
Y1 - 2011
N2 - Controllable sensing conditions provide the means for diversifying sensor response and achieving better selectivity. Modulating the sensing layer temperature of metal-oxide sensors is a popular method for multiplexing the limited number of sensing elements that can be employed in a practical array. Time limitations in many applications, however, cannot tolerate an ad-hoc, one-size-fits-all modulation pattern. When the response pattern is itself non-stationary, as in the transient phase, a temperature program also becomes infeasible. We consider the problem of determining and tuning into a fixed optimum temperature in a sensor array. For this purpose, we present an empirical analysis of the temperature's role on the performance of a metal-oxide gas sensor array in the identification of odorants along the response transient. We show that the optimal temperature in this sense depends heavily on the selection of (i) the set of candidate analytes, (ii) the time-window of the analysis, (iii) the feature extracted from the sensor response, and (iv) the computational identification method used.
AB - Controllable sensing conditions provide the means for diversifying sensor response and achieving better selectivity. Modulating the sensing layer temperature of metal-oxide sensors is a popular method for multiplexing the limited number of sensing elements that can be employed in a practical array. Time limitations in many applications, however, cannot tolerate an ad-hoc, one-size-fits-all modulation pattern. When the response pattern is itself non-stationary, as in the transient phase, a temperature program also becomes infeasible. We consider the problem of determining and tuning into a fixed optimum temperature in a sensor array. For this purpose, we present an empirical analysis of the temperature's role on the performance of a metal-oxide gas sensor array in the identification of odorants along the response transient. We show that the optimal temperature in this sense depends heavily on the selection of (i) the set of candidate analytes, (ii) the time-window of the analysis, (iii) the feature extracted from the sensor response, and (iv) the computational identification method used.
KW - MOX sensors
KW - Operating temperature
KW - Sensor transient
UR - http://www.scopus.com/inward/record.url?scp=80053285732&partnerID=8YFLogxK
U2 - 10.1063/1.3626373
DO - 10.1063/1.3626373
M3 - Conference contribution
AN - SCOPUS:80053285732
SN - 9780735409200
T3 - AIP Conference Proceedings
SP - 236
EP - 238
BT - Olfaction and Electronic Nose
T2 - 14th International Symposium on Olfaction and Electronic Nose, ISOEN 2011
Y2 - 2 May 2011 through 5 May 2011
ER -