HfOx-based nano-wedge structured resistive switching memory device operating at sub-mu A current for neuromorphic computing application

Abstract

We fabricated a silicon based nano-wedge resistive switching memory device with the stack of Ti/HfOx/p(+)-Si. By using 25% tetra-methyl-ammonium hydroxide (TMAH) aqueous solution, the anisotropic wet etching process is carried out to minimize the tip structure of the silicon bottom electrode to a width of 4 nm, and the structure was validated through TEM analysis. Due to the minimized device area, low read current levels (mu A) were obtained in the nano-wedge RRAM while the opposites were measured in large size RRAM devices. In addition, the fabricated nano-wedge RRAM exhibited low power consumption during the DC switching process. Additionally, pulse measurement and retention tests were performed to demonstrate the synaptic behaviors of long-term potentiation and depression. Software neural network simulation was followed to test the feasibility of nano-wedge RRAM's array implementation. These results demonstrate the fabricated nano-wedge RRAM devices' potential usage as a synaptic device in neuromorphic computing systems.