Журнал химической инженерии и технологических процессов
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Modeling of Cu Doped Cobalt Oxide Nanocrystal Gas Sensor for Methane Detection: ANFIS Approach

M. Esfandyari, M. Koolivand-Salooki, Z. Sheikhi Mehrabadi and A. Ahmadpour

In this paper, Nano-sized copper-cobalt compound oxide powders have been prepared by sol-gel technique with different mole ratios of Cu/Co (from 0.00 to 0.15); Detection of the methane gas, the most chemically stable hydrocarbon, is done. The structural properties and morphology of powders were studied by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and Transmission electron microscopy (TEM). XRD analysis confirms that Co₃O₄ and (CuO_0.3CO_0.7) Co₂O₄ phases have been formed and mean grain size were decreased with increasing dopant (from 28 to 24nm). According to TEM images it was found that the particles have cubic morphologies with nearly uniform distribution. Then an adaptive neuro-fuzzy inference system (ANFIS) models have been utilized for prediction of sensitivity values of the corresponded sensor. The results of ANFIS model show that the independent predicted Sensitivity values (S) compared to the measured target values have a good agreement. And also, high coefficient were found (R² > 0.98) for the response.