Nickel oxide nanoflowers based resistive sensors for detecting methyl salicylate and linalool

Crop health monitoring is crucial for early detection of biotic stress, which can significantly impact crop yield and quality. This work reports detection of two volatile organic compounds (VOCs) - methyl salicylate and linalool which have promising utility in agriculture including indication of biotic stresses in crops. NiO nanoflowers were synthesized using a solvothermal method. The polycrystalline nature of the metal oxide was confirmed using X-ray diffractometer pattern and crystallite size was found to be 16.8 nm. The bandgap of the NiO nanoflowers were found to be 3.47 eV when using UV-Visible spectrometer. The morphology of the nanomaterial was confirmed using field emission scanning electron microscope. Brunauer-Emmett-Teller confirmed the surface area of NiO to be 39.6 m² g⁻¹. X-ray photoelectron spectroscopy confirms the successful synthesis of nickel oxide (NiO) with distinct Ni 2p peaks at 855.5 eV and 873.3 eV, along with O 1s lattice oxygen at 529.6 eV. Satellite peaks at 861 eV and 879 eV further validate the Ni(II) oxidation state, indicating a well-defined crystalline structure. The NiO nanoflower was seen to exhibit temperature modulated dual selectivity as it exhibited the highest response to linalool at 300 °C whereas for methyl salicylate the optimum sensing temperature was found to be 250 °C. The response of NiO was found to be varying from 5.2-40% towards 5-40 ppm of linalool at 300 °C and between 2.5-13.5% towards 10-40 ppm of methyl salicylate at 250 °C. The response times and recovery times of the sensor varied from 260 s to 160 s and 170 s to 650 s, respectively for 5 to 40 ppm of linalool. For 10 to 40 ppm methyl salicylate, the response times and recovery times ranged from 280 s to 230 s and 220 s to 1203 s, respectively. The sensor was found to be highly selective towards linalool at 300 °C but the response of NiO was found to be comparable for both methyl salicylate and linalool at 250 °C. A simple algorithm based on steady state responses of the sensor at 250 and 300 °C could be developed for accurate prediction of both the VOCs.