The research team claims the amount of 2D-materials-based commercial devices available in the market is ‘preoccupyingly’ low and analytical tools capable of describing and predicting the behaviour of the devices – which are necessary before facing mass production – are scarce.
To counter these issues, the team developed a RRAM device with graphene electrodes and hexagonal boron nitride dielectric. They used scalable methods, such as chemical vapour deposition for material growth and shadow mask for electrode patterning. The device is said to show reproducible resistive switching.
The team also developed a model to accurately describe the device’s 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 accurate results which have been corroborated in log-log, log-linear and linear-linear plots, the model can 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.
According to the researchers, the device selected in this case, the RRAM device, is the most promising technology for future high density information storage.