In the present work, the structural and morphological of 5, 10, 15, 20 tetratoloylphenylporphyrinato Zinc (II) (ZnTTP) thin films prepared by spin coating on low cost glass substrate have been investigated using X-ray photoelectron spectroscopy (XPS) and atomic force microscopy (AFM). At room temperature, the electrical responses of ZnTTP thin films were measured under five reducing volatile organic compounds, including toluene, acetone, methanol, ethanol, and isopropanol. The obtained results indicate that the ZnTTP behaves as a p-type semiconductor. The developed sensor exhibits the highest linear response with methanol vapor. The selective methanol sensor based on ZnTTP thin film reveals a good reproducibility, great stability for more than 28 days, and a limit of detection as low as 2 ppm. At 260 ppm, it has fast response and recovery times of 51 s and 92 s, respectively. The principal component analysis (PCA) treatment was successfully used to discriminate methanol vapor.

In this work, an innovative approach based on the combination of hierarchical ascending classification (HAC) and principal component analysis (PCA) is proposed to discriminate individual vapors such as methanol, toluene, acetone, isopropanol, and ethanol using dynamic responses of one single sensor based on 5, 10, 15, 20 tetratoloylphenylporphyrinato Zn (II) (ZnTTP) at room temperature. Experimental data of 20 measurements as individuals (i.e., four different concentrations of each vapor) and extraction of new mathematical features associated with dynamic behavior were the basis of two subsets entered into the gas identification method. With PCA, four distinct groups were observed for each subset. The first three principal components have been added as data features for each previous corresponding subset of the HAC process. The classification becomes clearer and unambiguously separates the different clusters in good compliance with PCA. The obtained results have demonstrated the possibility to recognize the studied vapors by exploiting a single gas sensor with an opportunity to apply the developed PCA/HAC-based platform in cost-effective and highly selective gas monitoring systems.

The green synthesis of zinc oxide nanoparticles (ZnO NPs) using Retama raetam leaf extract via microwave irradiation was investigated. The biosynthesized NPs were characterized using scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and UV-Vis spectrophotometry. An XRD pattern confirmed the formation of a hexagonal wurtzite structure. An FTIR analysis indicated the interactions of the NPs with bioactive molecules involved in their synthesis. SEM and STEM imaging determined the morphology of the NPs with an average size of 14 nm. Furthermore, the biosynthesized ZnO NPs were used as a sensitive layer for detecting volatile organic compounds (VOCs) at low concentrations ranging from 0.5 to 5 ppm. The response sensor measured at an optimum operating temperature of 250 °C and 50% relative humidity (RH). The sensor exhibited a strong response to 5 ppm ethanol (325%), a detection limit as low as 4 ppb and an excellent stability across varying humidity levels.