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Resistive-based gas sensors have been considered as the most favorable gas sensors for detection of toxic gases and volatile organic compounds (VOCs) because of their simple structure, low cost, high sensitivity, ease of use, and high stability. Unfortunately, wide application of resistive-based gas sensors is limited by their low selectivity. In this article, we present the fabrication of ultrahigh selective NH3 gas sensor based on tin–titanium dioxide/reduced graphene/carbon nanotube (Sn–TiO2@rGO/CNT) nanocomposites. The Sn–TiO2@rGO/CNT nanocomposites with different molar ratios of Sn/Ti (1:10, 3:10, and 5:10) were synthesized via the solvothermal method. Characterizations by scanning electron microscopy, transmission electron microscopy, and X-ray photoelectron spectroscopy confirmed the decoration of Sn–TiO2 nanoparticles on rGO/CNT nanocomposite surfaces. The Sn–TiO2@rGO/CNT nanocomposite gas sensor exhibited high response and ultrahigh selectivity to NH3 against toluene, dimethylformamide, acetone, ethanol, methanol, isopropanol, formaldehyde, hydrogen, carbon dioxide, acetylene, and VOCs in paint thinners at room temperature. The Sn–TiO2@rGO/CNT nanocomposite gas sensor with molar ratio of Sn/Ti = 1:10 showed the highest response to NH3 over other molar ratios of Sn/Ti as well as pure rGO/CNT and Sn–TiO2 gas sensors. The ammonia-sensing mechanisms of the Sn–TiO2@rGO/CNT gas sensor were proposed based on the formation of p–n heterojunctions of p-type rGO/CNT and n-type Sn–TiO2 nanoparticles via a low-temperature oxidizing reaction process.

An electronic nose (E-nose) has been designed and equipped with software that can detect and classify human armpit body odor. An array of metal oxide sensors was used for detecting volatile organic compounds. The measurement circuit employs a voltage divider resistor to measure the sensitivity of each sensor. This E-nose was controlled by in-house developed software through a portable USB data acquisition card with a principle component analysis (PCA) algorithm implemented for pattern recognition and classification. Because gas sensor sensitivity in the detection of armpit odor samples is affected by humidity, we propose a new method and algorithms combining hardware/software for the correction of the humidity noise. After the humidity correction, the E-nose showed the capability of detecting human body odor and distinguishing the body odors from two persons in a relative manner. The E-nose is still able to recognize people, even after application of deodorant. In conclusion, this is the first report of the application of an E-nose for armpit odor recognition.

A shape diagram of ZnO nanostructures grown by thermal evaporation of a ZnO:C powder (carbothermal method) was derived by varying the powder source temperature (T p) and the substrate temperature (T s). All other growth parameters including (1) the carrier gas composition, pressure, and flow, (2) the substrate and catalyst type, and (3) the system geometry were kept constant. Comparative selected growth experiments utilizing a laser ablation system were performed to establish the general nature of the results. The roles of T s and T p in the evolution of the ZnO morphology and the mechanisms leading to the different morphologies were highlighted.

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