The electrical properties of reduced graphene oxide (rGO) have been previously shown to be very sensitive to surface adsorbates, thus making rGO a very promising platform for highly sensitive gas sensors. However, poor selectivity of rGO-based gas sensors remains a major problem for their practical use. In this paper, we address the selectivity problem by employing an array of rGO-based integrated sensors instead of focusing on the performance of a single sensing element. Each rGO-based device in such an array has a unique sensor response due to the irregular structure of rGO films at different levels of organization, ranging from nanoscale to macroscale. The resulting rGO-based gas sensing system could reliably recognize analytes of nearly the same chemical nature. In our experiments rGO-based sensor arrays demonstrated a high selectivity that was sufficient to discriminate between different alcohols, such as methanol, ethanol and isopropanol, at a 100% success rate. We also discuss a possible sensing mechanism that provides the basis for analyte differentiation.

We discuss the fabrication of gas-analytical multisensor arrays based on ZnO nanorods grown via a hydrothermal route directly on a multielectrode chip. The protocol to deposit the nanorods over the chip includes the primary formation of ZnO nano-clusters over the surface and secondly the oxide hydrothermal growth in a solution that facilitates the appearance of ZnO nanorods in the high aspect ratio which comprise a network. We have tested the proof-of-concept prototype of the ZnO nanorod network-based chip heated up to 400 °C versus three alcohol vapors, ethanol, isopropanol and butanol, at approx. 0.2–5 ppm concentrations when mixed with dry air. The results indicate that the developed chip is highly sensitive to these analytes with a detection limit down to the sub-ppm range. Due to the pristine differences in ZnO nanorod network density the chip yields a vector signal which enables the discrimination of various alcohols at a reasonable degree via processing by linear discriminant analysis even at a sub-ppm concentration range suitable for practical applications.

Bottom-up synthesized quasi-2D Co₃O₄ nanoflakes demonstrate a remarkable chemiresistive response towards chemically akin alcohol vapors in a mixture with air.

Arrays of nearly identical graphene devices on Si/SiO₂ exhibit a substantial device-to-device variation, even in case of a high-quality chemical vapor deposition (CVD) or mechanically exfoliated graphene. We propose that such device-to-device variation could provide a platform for highly selective multisensor electronic olfactory systems. We fabricated a multielectrode array of CVD graphene devices on a Si/SiO₂ substrate and demonstrated that the diversity of these devices is sufficient to reliably discriminate different short-chain alcohols: methanol, ethanol, and isopropanol. The diversity of graphene devices on Si/SiO₂ could possibly be used to construct similar multisensor systems trained to recognize other analytes as well.