A charge trap device based on field-effect transistors (FET) is a promising candidate for artificial synapses because of its high reliability and mature fabrication technology. However, conventional MOSFET-based charge trap synapses require a strong stimulus for synaptic update because of their inefficient hot-carrier injection into the charge trapping layer, consequently causing a slow speed operation and large power consumption. Here, we propose a highly efficient charge trap synapse using III-V materials-based tunnel field-effect transistor (TFET). Our synaptic TFETs present superior subthreshold swing and improved charge trapping ability utilizing both carriers as charge trapping sources: hot holes created by impact ionization in the narrow bandgap InGaAs after being provided from the p+-source, and band-to-band tunneling hot electrons (BBHEs) generated at the abrupt p+n junctions in the TFETs. Thanks to these advances, our devices achieved outstanding efficiency in synaptic characteristics with a 5750 times faster synaptic update speed and 51 times lower sub-fJ/um2energy consumption per single synaptic update in comparison to the MOSFET-based synapse. An artificial neural network (ANN) simulation also confirmed a high recognition accuracy of handwritten digits up to ∼90% in a multilayer perceptron neural network based on our synaptic devices.
Bibliographical noteFunding Information:
This work was supported in part by the Institutional Program (2E31532 and 2E31550) funded by the Korea Institute of Science and Technology (KIST), and in part by the National Research Foundation of Korea (NRF) Grant funded by the Korean Government Ministry of Science and ICT (Grants 2019M3F3A1A0207206912 and 2021M3F3A2A01037814).
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- charge trap synapse
- hot carrier
- tunneling field-effect transistors
ASJC Scopus subject areas
- General Materials Science