Shedding light on the mechanism of graphene oxide thermal decomposition: A kinetic study using isoconversional method and artificial neural network

Abstract

This work investigates the kinetics of Graphene Oxide (GO) thermal decomposition in mild temperatures (<550 K) using non-isothermal thermogravimetric data of freeze-dried GO. We employed the isoconvertional method and an artificial neural network to determine the multiple mechanistic kinetic models involved. Two distinct steps were clearly observed, both with high contribution of first-order kinetic model due to the dependence on the concentration of oxygen functionalities. Moreover, the first step of decomposition showed significant contribution of 3D diffusion model, likely related to the diffusion of produced gases in the 3D stacked-layered structure. The second step does not show dependence on 3D diffusion anymore, suggesting the layered structure was exfoliated during the first step. The second step showed high contribution of 2D nucleation models, which imply the formation of holes and cracks in the GO carbon skeleton. Therefore, this work clarifies the mechanism of preparation of reduced GO (rGO).