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 Nature]
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
fhbsdufh发布了新的文献求助10
刚刚
华仔应助lizhiqian2024采纳,获得10
1秒前
shenyu完成签到 ,获得积分10
1秒前
默默海露发布了新的文献求助10
1秒前
1+1发布了新的文献求助10
1秒前
听话的萤完成签到,获得积分10
2秒前
2秒前
着急的天奇关注了科研通微信公众号
2秒前
沉着的芦丁完成签到 ,获得积分10
3秒前
乐乐应助cy采纳,获得10
3秒前
3秒前
可宝想当富婆完成签到,获得积分10
3秒前
dyc0222应助端庄千山采纳,获得30
3秒前
正直的念梦完成签到,获得积分10
4秒前
4秒前
乔木发布了新的文献求助10
5秒前
YZJing完成签到,获得积分10
5秒前
I_won_t完成签到,获得积分10
5秒前
5秒前
元元元完成签到,获得积分10
6秒前
173678完成签到,获得积分20
7秒前
醒醒完成签到,获得积分10
7秒前
7秒前
狗狗耳完成签到 ,获得积分10
7秒前
琳科研_文献完成签到,获得积分10
7秒前
8秒前
香蕉觅云应助HHZ采纳,获得10
8秒前
宋嬴一发布了新的文献求助10
8秒前
8秒前
以前完成签到,获得积分10
9秒前
9秒前
慕薯殿焚完成签到,获得积分10
9秒前
隐形曼青应助金皮卡采纳,获得10
10秒前
自信的鹭洋完成签到,获得积分10
10秒前
狒狒爱学习完成签到,获得积分10
11秒前
11秒前
11秒前
健壮羊青发布了新的文献求助10
11秒前
lst完成签到,获得积分10
11秒前
Barry完成签到,获得积分10
11秒前
高分求助中
(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
Binary Alloy Phase Diagrams, 2nd Edition 8000
Building Quantum Computers 800
Translanguaging in Action in English-Medium Classrooms: A Resource Book for Teachers 700
Natural Product Extraction: Principles and Applications 500
Exosomes Pipeline Insight, 2025 500
Qualitative Data Analysis with NVivo By Jenine Beekhuyzen, Pat Bazeley · 2024 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5665118
求助须知:如何正确求助?哪些是违规求助? 4875227
关于积分的说明 15112135
捐赠科研通 4824320
什么是DOI,文献DOI怎么找? 2582694
邀请新用户注册赠送积分活动 1536665
关于科研通互助平台的介绍 1495279