电解质
对偶(语法数字)
材料科学
突触
可塑性
纳米技术
离子
金属
光电子学
化学
复合材料
电极
冶金
神经科学
心理学
物理化学
艺术
文学类
有机化学
作者
Reetwik Bhadra,Ramesh Kumar,Amitesh Kumar
标识
DOI:10.1109/ted.2024.3367663
摘要
An energy-efficient artificial neuron can be developed with synaptic transistors using the electric double-layer (EDL) effect in the transistor's oxide layer. This work proposes a dual metal gate (DMG) engineered indium-gallium-zinc-oxide (IGZO) transistor utilizing a novel Al2O3-based ion conducting electrolyte for tunable synaptic performance based on the ion drift-diffusion model. The simulation has been carried out at an ultralow voltage of 0.5 V employing two connection schemes. The results show accurate simulations of synaptic activities like paired-pulse facilitation, excitatory postsynaptic current (EPSC), memory transition from short-term to long-term, depression, and dynamic filtering characteristics. To validate the device's performance, voltage, frequency, and pulse interval modulation have been carried out to determine the synaptic strength of the device. The dual metal assists in a higher ON/OFF ratio, leading to more robust potentiation and depression characteristics. The results imply that the DMG-based EDL device proposed provides a physical understanding and helps to relate the artificial synaptic transistors with a biological neuron.
科研通智能强力驱动
Strongly Powered by AbleSci AI