MLS based temperature modulation of micro-hotplates

Even if a great deal of work has been done with temperature-modulated micro-hotplate gas sensors, the selection of the modulating frequencies remains an obscure and non-systematic method Here we introduce a method, borrowed from the field of system identification, to systematically select modulation frequencies to enhance sensor selectivity. We report for the first time that maximum length pseudorandom binary sequences (MLS) can be used to modulate the working temperature of metal oxide micro-hotplate gas sensors, in a wide frequency range. The impulse response of a pair sensor-gas is computed from the circular crosscorrelation of the MLS temperature-modulating sequence and sensor response sequence. This method enables each system sensor-gas to be identified and to find, in a systematic way, those modulation frequencies that are important to discriminate between different gases and to estimate gas concentration. This is demonstrated by obtaining the impulse response of integrated microarrays of either sputtered or screen-printed WO/sub 3/ in the presence of pollutant gases.