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Modeling and simulation of graphene-oxide-based RRAM

Research paper by Ee Wah Lim, Mohammad Taghi Ahmadi, Razali Ismail

Indexed on: 18 Mar '16Published on: 17 Mar '16Published in: Journal of Computational Electronics



Abstract

We propose a conduction model for resistive random-access memory (RRAM) based on graphene oxide (GO). We associate the electron transport mechanism with a multiphonon trap-assisted tunneling (MTAT) model. Pristine GO is electrically insulating due to the presence of \(sp^{3}\)-hybridized oxygen functional groups, e.g., hydroxyl, epoxide, carbonyl, and carboxyl groups. Electrically driven reduction of these oxygen groups triggers formation of nanoscale \(sp^{2}\) islands across the oxide layers. These graphene-like islands act as intermediate trap sites and assist electrons to tunnel from the cathode toward the anode despite being isolated by the disordered \(sp^{3}\)-bonded matrix. The presence of vertically aligned trap sites leads to the formation of percolation paths that allow a steady flow of electrons. The resistance state of the RRAM device can then be reversibly switched by electrically modulating the concentration of \(sp^{2}\) islands. This model shows good agreement with experimental data; therefore, we regard MTAT as an admissible explanation for the conduction mechanism in GO-based RRAM.