Optimization of Perovskite Gas Sensor Performance: Characterization, Measurement and Experimental Design

Eight different types of nanostructured perovskites based on YCoO [Formula: see text] with different chemical compositions are prepared as gas sensor materials, and they are studied with two target gases NO [Formula: see text] and CO. Moreover, a statistical approach is adopted to optimize their performance. The innovative contribution is carried out through a split-plot design planning and modeling, also involving random effects, for studying Metal Oxide Semiconductors (MOX) sensors in a robust design context. The statistical results prove the validity of the proposed approach; in fact, for each material type, the variation of the electrical resistance achieves a satisfactory optimized value conditional to the working temperature and by controlling for the gas concentration variability. Just to mention some results, the sensing material YCo [Formula: see text] Pd [Formula: see text] O [Formula: see text] (Mt1) achieved excellent solutions during the optimization procedure. In particular, Mt1 resulted in being useful and feasible for the detection of both gases, with optimal response equal to +10.23% and working temperature at [Formula: see text] C for CO (284 ppm, from design) and response equal to −14.17% at [Formula: see text] C for NO [Formula: see text] (16 ppm, from design). Analogously, for NO [Formula: see text] (16 ppm, from design), the material type YCo [Formula: see text] O [Formula: see text] Pd (Mt8) allows for optimizing the response value at [Formula: see text] with a working temperature at [Formula: see text] C, whereas for YCo [Formula: see text] Pd [Formula: see text] O [Formula: see text] (Mt3), the best response value is achieved at [Formula: see text] with the temperature equal to [Formula: see text] C.