DFT Based Simulation for Predicting Alcohol Adsorption on Oxygenated Functional Group Containing GO and rGO Based Gas Sensor Devices

This paper predicts the adsorption probability (sensitivity performance) of various alcohol vapors in graphene oxide (GO) and reduced graphene oxide (rGO) based gas sensor devices, where the role of oxygen containing functional groups of GO and rGO like, epoxy, carbonyl, carboxyl, hydroxyl (sp2 hybridized) and hydroxyl (sp3 hybridized) were investigated for physisorption of methanol and ethanol with the help of first principle calculation (density functional theory (DFT)) employing Atomistix Toolkit QuantumATK (version: P_2019.03-SP1). Among the above mentioned oxygenated functional groups, carbonyl, carboxyl and sp2 hybridized hydroxyl groups were placed at the edges of the GO and rGO basal plane, however epoxy and sp3 hybridized hydroxyl groups were placed vertically to that basal plane. For the considered test species (methanol and ethanol), the optimal positions for gas adsorption onto the oxygenated functional groups, favorable adsorption energy value and charge transfer capacity were calculated for the above stated two planes, separately. It was observed that among the other functional groups, edge carbonyl group showed better adsorption probability with respect to minimum adsorption distance, favorable adsorption energy and charge transfer efficiency towards methanol and ethanol. However, the better sensitivity and selectivity performance was found towards methanol compared to that of ethanol in GO and rGO based gas sensor devices.