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Low-energy and tunable LIF neuron using SiGe bandgap-engineered resistive switching transistor SCIE SCOPUS

Title
Low-energy and tunable LIF neuron using SiGe bandgap-engineered resistive switching transistor
Authors
KIM, YI JOONKIM, HYANGWOOOH, KYOUNGHWANPARK, JUHONGKONG, BYOUNG DONBAEK, CHANG KI
Date Issued
2024-08
Publisher
SPRINGER
Abstract
We have proposed leaky integrate-and-fire (LIF) neuron having low-energy consumption and tunable functionality without external circuit components. Our LIF neuron has a simple configuration consisting of only three components: one bandgap-engineered resistive switching transistor (BE-RST), one capacitor, and one resistor. Here, the crucial point is that BE-RST with a silicon-germanium heterojunction possesses an amplified hysteric current switching with a low latch-up voltage due to improved hole storage capability and impact ionization coefficient. Therefore, the proposed neuron utilizing BE-RST requires an energy consumption of 0.36 pJ/spike, which is approximately six times lower than 2.08 pJ/spike of pure silicon-RST based neuron. In addition, the spiking properties can be tuned by modulating the leakage rate and threshold through gate bias, which contributes to energy-efficient sparse-activity and high learning accuracy. As a result, our proposed neuron can be a promising candidate for executing various spiking neural network applications.
URI
https://oasis.postech.ac.kr/handle/2014.oak/124156
DOI
10.1186/s11671-024-04079-5
ISSN
2731-9229
Article Type
Article
Citation
Discover Nano, vol. 19, no. 1, 2024-08
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백창기BAEK, CHANG KI
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