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Inverse paired-pulse facilitation in neuroplasticity based on interface-boosted charge trapping layered electronics
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Inverse paired-pulse facilitation in neuroplasticity based on interface-boosted charge trapping layered electronics

Ko-Chun Lee, Mengjiao Li, Yu-Hsiang Chang, Shih-Hsien Yang, Che-Yi Lin, Yuan-Ming Chang, Feng-Shou Yang, Kenji Watanabe, Takashi Taniguchi, Ching-Hwa Ho, …
Nano Energy, 卷.77, 105258
11/2020

摘要

Charge-trap electronics InSe Inverse PPF Paired-pulse facilitation (PPF) Synapse Renewable Energy Sustainability and the Environment Materials Science (all) Electrical and Electronic Engineering
Modern technology allows us to mimic biological functions with artificial devices. The human brain, including numerous neural cells that connect via synapses, enables us to handle complex tasks with ultra-low power consumption, which is one of the most important biological components that eager to emulate. Here, we propose and build a simple indium selenide (InSe)-based photonic synaptic device with unique gate tunable behaviours such as time-varying output current, auto-depression rate, and paired-pulse facilitation (PPF). A new inverse PPF behaviour is observed, characterized by the positive correlations to the time interval, which is opposite of those negative ones in previous studies. To unveil the origin of this new finding, both the substrate-dependent persistent photocurrent examination and low-frequency noise (LFN) measurements are performed to investigate the electric-controlled charge trapping/detrapping processes between the InSe and SiO 2 interface. Furthermore, we systematically demonstrate such the specific evolution of the flexible plasticity within a low-operation voltage and a wide range of visible spectra. Interestingly, the inverse PPF can be employed to emulate more detailed characteristics of a biological brain such as the age-related changes of synaptic plasticity in real human brains. Thus, we believed that our findings provide a proof-of-concept for systematically mimicking the brain plasticity and advancing the development of energy-efficient artificial brains.

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