Transition metal oxides are attractive candidates for gas sensing thanks to their interesting semiconductive properties [1,2]. In particular, tin oxide (SnO2) is the most utilized n-type metal oxide semiconductor, as it typically provides high sensitivity to a large variety of gas analytes. In this study, we are using the versatility of solution-based approaches to prepare MOS materials at the nanoscale and to control critical film morphology parameters for gas sensing such as crystallinity, grain size, film thickness, as well as surface area (through porosity) – the focus of this paper. In the literature, methods of preparing porous SnO2 have been reported many times. However, they are either i) simple but yield SnO2 with small, hard to access pores (sol-gel), potentially non-contiguous films (nanoparticles packing), or ii) they are more complex and in turn more costly (use of porogen, electrochemical processes etc.). Here, we report on a simple, template-free, one-step process that, if deposited in the right conditions, inherently yields highly porous films with large pores (Fig. 1b). The morphology of the macropores was unanticipated with the pores being self-organized, and completely open to the surface. An important parameter to obtain these pores is to deposit the solution at an optimal aging time, as illustrated in Figure 1. Additionally, other factors such as solution concentration and pH, or the nature of the solvent can also impact the macropores formation. The role played by these factors will be discussed, and hypotheses on the macropores formation mechanism will be proposed. The presence of these macropores led to a two-fold increase in sensitivity in our gas sensing measurements (Fig. 1e, 1f) [3]. Altogether, these results suggest that solution-based processes are very powerful to prepare highly sensitive metal oxide gas sensors. The unique morphologies achieved could be highly advantageous in the context of an electronic nose. References K. Lionti et.al., TechConnect Briefs 2017, Chap. 7, p.219A. Fasoli et.al., IEEE International Symposium on Olfaction and Electronic Nose 2017, p.978K. Lionti et al., 2017, US10020199B1. Figure 1
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