Nhảy đến nội dung

Analytical modeling of graphene oxide based memristor


Mohammad Taghi Ahmadi, Banafsheh Alizadeh Arashloo, Truong Khang Nguyen

Source title: 
Ain Shams Engineering Journal, 12: 1741-1748, 2021 (ISI)
Academic year of acceptance: 

Nowadays, carbon–based materials like graphene and its derivatives consume great nano-technological applications worldwide. Graphene, due to its attractive properties such as its unusual charge transport, mechanical and thermal capabilities, is in the nano-scaling research spotlight. Additionally, to overcome the scaling limitations of large-scale charge-storage-based memories, the Memristor is focused upon as a nonvolatile memory. In the present work, the modeling of a Memristor based on graphene oxide as an active layer is considered. The drift-diffusion formalism as an electron transport mechanism, derived from ion immigration, is explored. It is concluded that by increasing the voltage between two metalelectrodes, the carrier concentration is increased, and the carrier mobility on the sandwiched layer (graphene oxide) is decreased. The conductive path by the redox of graphene oxide (GO) atoms, due to the conversion of sp3 to sp2 oxygen functionalities, is formed, which can be modeled by degenerate mode (the low resistance switching or ON state). This path is ruptured by decreasing the voltage into the reset voltage, which is modeled by the non-degenerate mode (the high resistance switching or OFF state). Finally, the model in comparison with the experimental data numerically is simulated, and acceptable results for metal and graphene–like path formation are observed.