Green synthesis of carbon and nitrogen-containing tin oxide hierarchical nanostructures using apricot tree gum extract for selective isopropanol vapor sensing

In this work, carbon and nitrogen-containing tin oxide (C, N-SnO₂) hierarchical nanostructures were synthesized using apricot tree gum extract and was used for construction a resistive-type gas sensor for the selective detection of isopropanol vapor. Structural and compositional analyses confirmed the formation of phase-pure tetragonal SnO₂ with no detectable secondary phases. Field emission scanning electron microscopy (FESEM) revealed a hierarchical morphology consisting of tubular microstructures decorated with spherical nanoparticles, creating enhanced surface accessibility. Energy-dispersive X-ray spectroscopy (EDX) detected the presence of carbon and nitrogen, suggesting dopant incorporation. Fourier transform infrared spectroscopy (FTIR) analysis confirmed the tetragonal SnO₂ structure and identified vibrational bands associated with Sn–O bonds and carbon- and nitrogen-related functional groups, providing evidence for dopant- derived species within the nanostructure. The vapor sensing performance of the fabricated sensor was systematically evaluated toward isopropanol vapor under varying operating temperatures, with an optimal temperature of 350 °C yielding the highest response. At this condition, the sensor exhibited a maximum response of 32.4 toward 0.1095 mol% isopropanol, with a response time of 24.34 s and a recovery time of 11.19 s, indicating fast and largely reversible sensing behavior. The effect of humidity on the sensor response also was investigated. Repeatable behavior was observed over ten consecutive dynamic injection-recovery cycles with negligible signal fluctuation, indicating good short-term operational stability. Furthermore, the sensor response showed a strong linear relationship with the logarithm of isopropanol concentration over a detection range of 0.0073–1.46 mol%, enabling reliable quantitative analysis. Based on the baseline variation and extrapolation of the calibration relationship, an estimated limit of detection (LOD) of approximately 3.6 ppm was obtained. Preliminary selectivity tests against individually tested interfering gases revealed lower responses compared to isopropanol, indicating favorable cross-sensitivity under the tested conditions. The enhanced sensing performance is proposed to be associated with the presence of carbon and nitrogen-containing species, which may modify the surface and electronic properties of SnO₂ and promote surface reaction kinetics, together with the hierarchical tubular–nanoparticle morphology that increases the active surface area available for gas adsorption. These results indicate that C, N-SnO₂ hierarchical nanostructures are a promising platform for selective isopropanol gas detection.