Dynamic and Static Switching in ITO/SnOx/ITO and Its Synaptic Application

Abstract

The attempts to devise networks that resemble human minds are steadily progressing through the development and diversification of neural networks (NN), such as artificial NN (ANN), convolution NN (CNN), and recurrent NN (RNN). Meanwhile, memory devices applied on the networks are also being studied together, and RRAM is the one of the most promising candidates. The fabricated ITO/SnOX/TaN device showed two forms of current–voltage (I-V) curves, classified as dynamic and static. It was triggered from the forming process, and the difference between the two curves resulted from the data retention measured at room temperature for 103 s. The dynamic curve shows a time-dependent change in the data, and the cause of the data preservation period was considered through X-ray photoelectron spectroscopy (XPS) and linear fitting in conduction mechanisms. To confirm whether the memory performance of the device may be implemented on the synapse, the change in the plasticity was confirmed using a rectangular-shaped pulse. Paired-pulse facilitation (PPF) was implemented, and the change from short-term potentiation (STP) to long-term potentiation (LTP) was achieved.