The self-powered artificial synapse mechanotactile sensing system by integrating triboelectric plasma and gas-ionic-gated graphene transistor

摩擦电效应 材料科学 晶体管 石墨烯 突触 纳米技术 光电子学 离子键合 等离子体 电气工程 电压 离子 神经科学 物理 量子力学 生物 工程类 复合材料
作者
Song Zhang,Junmeng Guo,Liangliang Liu,Haoran Ruan,Chuiyun Kong,Xiaobo Yuan,Bao Zhang,Guangqin Gu,Peng Cui,Gang Cheng,Zuliang Du
出处
期刊:Nano Energy [Elsevier BV]
卷期号:91: 106660-106660 被引量:56
标识
DOI:10.1016/j.nanoen.2021.106660
摘要

The emulation of biological nerves to develop artificial synapse tactile sensing system has great application potentials in the fields of Internet of Things and artificial intelligence. Novel sensing strategies to achieve low power consumption, low cost, low complexity and high efficiency still face challenges. Here, a self-powered tactile sensing system has been developed by integrating a triboelectric plasma and a gas-ions-gated (GIG) graphene transistor, in which the GIG transistor is served as the artificial synapse, and the triboelectric plasma is served as both a tactile sensor and the driving signals of the GIG transistor. The N 2 + ions in the triboelectric plasma are directly adsorbed on the graphene surface, acting as a floating gate of the GIG transistor to regulate its electrical transport characteristics. The adsorption density of N 2 + ions reach up to 3.96 × 10 12 cm −2 with a measured desorption energy of 196 meV. The theoretical simulation shows that the N 2 + ion is adsorbed at the site of carbon vacancy on the graphene surface. By regulating the number, frequency and polarization of the discharge pulse, various synaptic behaviors are achieved, such as short-term depression, long-term depression, long-term potentiation, paired-pulse facilitation, etc. Also, the neural functions of learning and temporal decoding have been demonstrated in experiments. By combining triboelectric plasma and GIG transistor, a facile experimental scheme for a self-powered, integrated, and simple structured intelligent tactile sensing system has been proposed, which is highly expected to promote the development of intelligent sensing fields in the future. A facile self-powered artificial synapse tactile sensing system was first constructed by integrating triboelectric plasma and gas-ionic-gated graphene transistor, where the GIG transistor is served as the artificial synapse, and the triboelectric plasma is served as both a tactile sensor and the driving signals of the GIG transistor. The short-term depression, long-term depression, long-term potentiation, and paired-pulse facilitation etc. synaptic behaviors have been achieved by varying the density of N 2 + ions adsorbed on the surface of single layer graphene. The nonlinear response with the increment of discharge pulses stimuli demonstrates the learning and temporal decoding functions of this mechanotactile sensing system. This is highly expected to promote the development of intelligent sensing fields in the future. • We designed a novel self-powered artificial synapse sensing system by integrating triboelectric plasma and GIG transistors. • The N 2 + ions serve as floating gates to regulate the electrical transport of single layer graphene. • The STD, LTD, STP, PPF etc. synaptic behaviors have been realized by varying the density of N 2 + on the surface of graphene. • The nonlinear response demonstrates the learning and temporal decoding functions of this sensing system.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
2秒前
嘿嘿发布了新的文献求助10
2秒前
Ferry完成签到,获得积分10
3秒前
GuGuGuee完成签到,获得积分20
5秒前
科研白发布了新的文献求助10
5秒前
贤者完成签到 ,获得积分10
5秒前
拼搏梦寒发布了新的文献求助10
5秒前
听闻韬声依旧完成签到 ,获得积分10
6秒前
hailiangzheng发布了新的文献求助10
7秒前
8秒前
duola完成签到,获得积分10
8秒前
多喝水发布了新的文献求助10
9秒前
nino完成签到,获得积分10
9秒前
天天乐完成签到,获得积分10
11秒前
11秒前
11秒前
12秒前
Ju1es完成签到,获得积分10
12秒前
13秒前
yiheng完成签到,获得积分10
13秒前
所所应助promise采纳,获得30
14秒前
14秒前
ding应助泽锦臻采纳,获得10
14秒前
15秒前
诺wang完成签到,获得积分10
15秒前
16秒前
Artorias完成签到,获得积分10
17秒前
18秒前
南山的云和你完成签到,获得积分10
18秒前
heab完成签到 ,获得积分10
20秒前
hhh发布了新的文献求助10
20秒前
善良丸子完成签到,获得积分10
21秒前
bkagyin应助美丽的半芹采纳,获得10
22秒前
多喝水完成签到,获得积分10
25秒前
科研通AI6.1应助羽化采纳,获得10
26秒前
善良丸子发布了新的文献求助10
26秒前
李爱国应助火星上如柏采纳,获得10
26秒前
ztww发布了新的文献求助10
28秒前
NexusExplorer应助李壮壮采纳,获得10
30秒前
高分求助中
Introduction to Helicopter and Tiltrotor Flight Simulation, Second Edition 2000
Overcoming Stigma and Bias in Obesity Management 1200
Malcolm Fraser : a biography 700
Signals, Systems, and Signal Processing 610
Bounds for Statistical Estimation in Semiparametric Models 500
Forced degradation and stability indicating LC method for Letrozole: A stress testing guide 500
Ideology and Meaning-Making under the Putin Regime 450
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6488935
求助须知:如何正确求助?哪些是违规求助? 8287408
关于积分的说明 17679883
捐赠科研通 5578848
什么是DOI,文献DOI怎么找? 2914156
邀请新用户注册赠送积分活动 1891280
关于科研通互助平台的介绍 1748846