Model for 2-D materials based RRAM found

Graphene and related two dimensional (2D) materials have raised massive interest and investment during the last years. However, the amount of 2D-materials-based commercial devices available in the market is still very low.

This image shows resistive random access memory made of graphene electrodes and hexagonal boron nitride dielectric. Credit: American Institute of Physics 2017.

This image shows resistive random access memory made of graphene electrodes and hexagonal boron nitride dielectric. Credit: American Institute of Physics 2017.

The research group led by Dr. Mario Lanza, a Young 1000 Talent Professor born in Barcelona (Spain) and based in Soochow University (China), is leading a global effort to investigate the properties of layered dielectrics. In their recent investigation, published in the journal 2D Materials, Prof. Lanza and co-workers synthesized a resistive random access memory (RRAM) using graphene/hexagonal-boron-nitride/graphene (G/h-BN/G) van der Waals structures. Furthermore, they developed a compact model to accurately describe its functioning. The model is based on the nonlinear Landauer approach for mesoscopic conductors, in this case atomic-sized filaments formed within the 2D materials system. Besides providing excellent overall fitting results (which have been corroborated in log-log, log-linear and linear-linear plots), the model is able to explain the dispersion of the data obtained from cycle-to-cycle in terms of the particular features of the filamentary paths, mainly their confinement potential barrier height.

The development of theoretical models to describe the functioning of electronic devices is one essential step enabling device/systems simulation, which is essential before device mass production. The device selected in this case, the RRAM device, is the most promising technology for future high-density information storage.

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