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Modeling of Cu Doped Cobalt Oxide Nanocrystal Gas Sensor for Methane Detection: ANFIS Approach | Abstract
Journal of Chemical Engineering & Process Technology

Journal of Chemical Engineering & Process Technology
Open Access

ISSN: 2157-7048

Abstract

Modeling of Cu Doped Cobalt Oxide Nanocrystal Gas Sensor for Methane Detection: ANFIS Approach

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

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 (CuO0.3CO0.7) 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.