Selectivity Tuning of Graphene Oxide Based Reliable Gas Sensor Devices by Tailoring the Oxygen Functional Groups: A DFT Study Based Approach

Abstract

This paper concerns the selectivity tuning of graphene oxide based gas sensor devices, where the role of oxygen functional groups like, carboxyl, carbonyl, hydroxyl (sp <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ), epoxy, and hydroxyl (sp <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> ) were investigated for physisorption of NO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> , NH <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> , CO, and H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> O using first principle calculation (density functional theory) incorporating Atomistix Toolkit (v2015.1). Among the five functional groups under consideration, carboxyl, carbonyl, and hydroxyl (sp <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) were considered at the edges on the basal plane, while epoxy and hydroxyl (sp <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> ) groups were considered in the plane perpendicular to that. For all the species, the optimum positions for adsorption, adsorption energy and charge transfer efficiency were investigated for the above two planes. It was found that edge carboxyl group is the most favorable in terms of adsorption energy and charge transfer efficiency targeting NH <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> , CO, and H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> O. On the contrary, for NO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> , hydroxyl functionalization was found to be the most efficient one.