HfO_x-Based Conductive Bridge Random Access Memory with Al₂O₃ Sandglass Nanostructures via Glancing Angle Deposition Technology toward Neuromorphic Applications

Conductive bridge random access memory (CBRAM) is one of the promising nonvolatile memories for next-generation technology owing to its high density, low power consumption, and fast switching speed, which is also a potential candidate for implementation of neuromorphic computing. However, CBRAMs suffer from stochastically growing conducting filaments in the insulator layer. Herein, we demonstrated Al₂O₃ sandglass nanostructures (SNGSs) embedded into HfO_x-based CBRAMs via glancing angle deposition technology with the AlN thermal enhanced layer to prevent the overinjection of cations and localize the growth of conducting filaments in the HfO_x switching layer. With the assistance of Al₂O₃ SNGSs and the AlN layer, the Cu/Al₂O₃ SNGSs/HfO_x/AlN/TiN device exhibited a stable on/off ratio of >10 for more than 6000 cycles. Furthermore, with a Te top electrode, the Te/Al₂O₃ SNGSs/HfO_x/AlN/TiN device shows a multilevel cell characteristic by controlling compliance currents. In addition, it possesses excellent potentiation and depression nonlinearities of 1.28 and 0.4, respectively, which is beneficial for future applications in neuromorphic computing.