Morphological effects in SnO2 chemiresistors for ethanol detection: a systematic statistical analysis of results published in the last 5 years

SnO2 is one of the most studied materials in gas sensing and is often used as benchmark for other metal oxide based gas sensors. Among the many strategies adopted to optimize its sensing properties, the fine tuning of the morphology in nanoparticles, nanowires, nanosheets and their eventual hierarchical organization has become an active field of research in the last years.

In this work, with the aim to have a more general and reliable picture of the state of the art, results published in literature in the last five years are systematically analyzed focusing on response intensities recorded with chemiresistors based on pure SnO2 for ethanol detection in dry air.

The statistics is discussed on the basis of descriptive morphological parameters such as the crystallite shape, which may be in the form of nanoparticles, nanowires, nanosheets, and their eventual hierarchical assembly, including fibers, spheres, hollow spheres.

Results indicate that no morphology clearly outperforms others, while a few individual sensors emerge as remarkable outliers with respect to the whole dataset. Interestingly, an appreciable number of outliers feature the morphology of the thick film traditionally employed in the field, i.e. a thick, random network of SnO2 nanoparticles. This result is interpreted in terms of the longer tradition of the thick film approach with respect those of nanowires/nanosheets and hierarchical structures. Such a longer experience may reasonably imply a more developed capability to effectively combine the many parameters underlying the sensing mechanism, which may counterbalance the advantages arising from the fine morphological tuning inherent in the more recent nanostructures.