A computational study of AlScN-based ferroelectric tunnel junction

Ferroelectric (FE) AlScN materials have been experimentally explored for memory and neuromorphic computing device applications. Here a computational study is performed to simulate the device characteristics and assess the performance potential of a ferroelectric tunnel junction (FTJ) based on AlScN. We parameterize an efficient k$\cdot$p Hamiltonian from the complex band structure of AlScN from ab initio density-functional theory calculations to enable efficient quantum transport simulations of the FTJ device. Using a metal–FE–graphene structure enhances the barrier height modulation and the tunneling electroresistance (TER) ratio, compared to a metal–FE–semiconductor FTJ device structure. The barrier height modulation between ON and OFF states can reach $\sim$ 0.7eV with a FE polarization of 25 $\mu$C/cm². Reducing the AlScN tunnel layer thickness is important for increasing the device ON current and reducing the read latency. The results indicate the importance of contact designs and FE layer thickness in the design of AlScN-based FTJ devices, and highlight the potential of AlScN FTJ for future memory device technology applications.