Synaptic behaviors of electromigrated Au nanogaps

• Published in: AIP advances Vol. 9; no. 5; pp. 055317 - 055317-5
• Main Authors: Sakai, Keita, Sato, Tomomi, Tani, Soki, Ito, Mitsuki, Yagi, Mamiko, Shirakashi, Jun-ichi
• Format: Journal Article
• Language: English
• Published: Melville American Institute of Physics 01-05-2019; AIP Publishing LLC
• Subjects: Activation; Biological effects; Brain; Computation; Control methods; Electric potential; Electromigration; Electronic devices; Plastic properties; Synapses; Voltage pulses
• ISSN: 2158-3226; 2158-3226
• DOI: 10.1063/1.5096817

Artificial electronic synapses or synaptic devices, which are capable of mimicking the functions of biological synapses in the human brain, are considered the basic building blocks for brain-inspired computing. Therefore, we investigated the emulation of synaptic functions in a simple Au nanogap. The synaptic functionality of neuromorphic hardware originates from a gradually modulated resistance. Previously, we investigated simple electromigration-based methods for controlling the tunnel resistance of nanogaps, called activation. In this study, a new type of artificial synaptic device based on planar Au nanogaps is demonstrated using a newly investigated activation procedure with voltage pulses. In the activation method with specific voltage pulses, the change in tunnel resistance of the Au nanogaps can be gradually controlled depending on the interval and amplitude of input voltage pulses. Moreover, Au inorganic synapses can emulate the synaptic functions of both short-term plasticity (STP) and long-term plasticity (LTP) characteristics. After the applied pulse is removed, the current decays rapidly at the beginning, followed by a gradual fade to a stable level. In addition, with repeated stimulations, the forgetting rate becomes decreases and the memory retention increases. Therefore, we observe an effect analogous to a memory transition from STP to LTP in biological systems. Our results may contribute to the development of highly functional artificial synapses and the further construction of neuromorphic computing architecture.