Investigating the selective behaviour of CuO in gas sensing applications
This contribution revisits recent results regarding the selective detection of the trace gases hydrogen sulfide, nitrogen oxide, and nitrogen dioxide using cupric oxide (CuO). It demonstrates how the variation of the surface temperature may be used to learn about basic material parameters as well as control the surface reactions. In contrast to commonly employed modulation schemes that continuously vary the temperature we use a steady-state approach in order to extract information about gas matrices. Our results highlight the potential for incorporating laboratory results regarding surface processes in pattern recognition schemes to improve the performance of these algorithms. We propose to implement the findings into temperature modulation schemes in order to allow for adding highly gas specific elements to the algorithms deployed.