Abstract
Learning by human beings is achieved by changing the synaptic weights of a neural network in the brain. Low frequency stimulation temporarily increases a synaptic weight, which then decreases to the initial low state in the interval after each stimulation. Conversely, high frequency stimulation keeps a synaptic weight at an elevated level, even after the stimulation ends. These phenomena are termed short‐term plasticity (STP) and long‐term potentiation (LTP), respectively. These functions have been emulated by various nonvolatile devices, with the aim of developing hardware‐based artificial intelligent (AI) systems. In order to use the functions in actual AI systems with other conventional devices, control of the operating characteristics, such as matching a decay constant in STP, is indispensable. This paper reports an electrochemical method for controlling the characteristics of time‐dependent neuromorphic operations of molecular gap atomic switches. Pre‐doping of Ag+ cations into an ionic transfer layer (Ta2O5) changes the amount of shift in an electrochemical potential in the time‐dependent operation, which drastically improves the decaying characteristics in STP mode.
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