Neuromorphic computing has the capacity to emulate the neural structure and the operation of the human brain with energyefficient and flexible processing. [1] When implementing a neuromorphic system on the hardware level, an array of memristors can be used as adaptive synapses. [2,3] In particular, vector matrix multiplication in a memristor has the advantage of greatly reducing the computational burden of the graphics processing unit. Basically, long-term retention is preferred for hardware-based neuromorphic systems in terms of energy efficiency. On the other hand, short-term memory (STM) is suitable for temporal/sequential data processing, which can be emulated by the loss of retention in a memristor. [4,5] Until now, the artificial synaptic devices of memristor type have been reported from a lot of materials to implement the bio-inspired computing. [6-13] SiN x is one of the core materials in the complementary metal oxide semiconductor (CMOS) process, where it is used as a passivating, buffer, masking, and chemical mechanical polishing stopper layer. It has also been used in nonvolatile memory applications, such as in NAND flash [14] and memristor devices. [15-24] The SiN x layer has a different form in flash memory as in charge trapping. The SiN x layer in a memristor acts as a resistive switching layer by controlling conductance with the applied electric