A general strategy for manufacturing flexible synaptic transistors with high mechanical stability

神经形态工程学 材料科学 兴奋性突触后电位 突触后电流 弯曲 计算机科学 晶体管 人工神经网络 光电子学 人工智能 神经科学 复合材料 电压 抑制性突触后电位 电气工程 生物 工程类
作者
Bingyong Zhuang,Xiumei Wang,Chuanbin An,Congyong Wang,Lujian Liu,Huipeng Chen,Tailiang Guo,Wenping Hu
出处
期刊:Science China. Materials [Springer Science+Business Media]
卷期号:66 (7): 2812-2821 被引量:1
标识
DOI:10.1007/s40843-022-2408-7
摘要

Flexible organic synaptic transistors (FOSTs) have attracted considerable attention owing to their flexibility, biocompatibility, ease of processing, and reduced complexity. However, FOSTs rarely maintain the mechanical stability of their synaptic properties while meeting the device deformation requirements. Here, we experimentally found that bending deformation had a greater influence on the synaptic performance (i.e., the excitatory postsynaptic current (EPSC) value) of FOSTs than on the on-state current. Moreover, through formula derivation, we proved that the density of bending-induced defect states generated near the channel considerably influences the synaptic performance. We propose a general approach to tune the stable segment of the device using an encapsulation layer. The EPSC value of the ordinary FOSTs without a regulated stable segment decreased by nearly 1.5–2 orders of magnitude after bending. In contrast, the designed flexible synaptic device exhibited relatively stable EPSC. Moreover, the designed FOST exhibited stable paired-pulse facilitation, long-term potentiation, and optical synaptic performance. Furthermore, neuromorphic computational simulations based on our device before and after 500 bending cycles were performed using a handwritten artificial neural network. The device showed stable recognition accuracy after 50 learning cycles (91.55% in the initial state and 90.43% after 500 bending cycles). The successful application of a stable segment in flexible synaptic transistors provides a convenient and simple idea for fabricating flexible neuromorphic electronics with mechanical stability.

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
领导范儿应助予青采纳,获得10
刚刚
完美世界应助阿耒采纳,获得10
1秒前
YangLi发布了新的文献求助10
1秒前
Orange应助嘻嘻滑呀采纳,获得10
1秒前
2秒前
zzz发布了新的文献求助10
3秒前
3秒前
桐桐应助CDong采纳,获得10
3秒前
hh完成签到 ,获得积分10
3秒前
4秒前
香蕉觅云应助dildil采纳,获得10
4秒前
余慵慵完成签到 ,获得积分10
4秒前
幽默代丝发布了新的文献求助10
4秒前
小白小王发布了新的文献求助10
4秒前
wanci应助Xhhhhhh采纳,获得10
5秒前
5秒前
小马甲应助随心所欲采纳,获得10
5秒前
鲸鱼发布了新的文献求助10
6秒前
老实醉冬完成签到,获得积分10
8秒前
8秒前
8秒前
wlgxd完成签到,获得积分10
9秒前
hob发布了新的文献求助10
9秒前
迅速柚子完成签到 ,获得积分10
9秒前
10秒前
CALCULATING完成签到,获得积分10
10秒前
wangzw完成签到,获得积分20
10秒前
11秒前
共享精神应助质谱仪采纳,获得10
11秒前
橘子汽水完成签到,获得积分10
12秒前
13秒前
13秒前
13秒前
xuxuxuxuxu发布了新的文献求助10
13秒前
rong杏完成签到,获得积分10
14秒前
zheng关注了科研通微信公众号
14秒前
圆缘园完成签到,获得积分10
14秒前
OnlyHarbour完成签到,获得积分10
15秒前
15秒前
16秒前
高分求助中
Markov Chain Monte Carlo 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 5000
Advanced Weaponeering Fourth Edition, Volume 2 1000
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 700
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
Data book on fatigue strength of metallic materials 500
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 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7560676
求助须知:如何正确求助?哪些是违规求助? 9141613
关于积分的说明 19542501
捐赠科研通 7148980
什么是DOI,文献DOI怎么找? 3261754
关于科研通互助平台的介绍 2428213
邀请新用户注册赠送积分活动 2251184