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
小马甲应助成就的橘子采纳,获得10
1秒前
中杯西瓜冰完成签到,获得积分10
2秒前
饥饿面包发布了新的文献求助10
2秒前
Superxx完成签到,获得积分10
3秒前
安鹏完成签到 ,获得积分10
3秒前
4秒前
suicone完成签到,获得积分10
4秒前
ray完成签到,获得积分20
4秒前
5秒前
ikutovaya完成签到,获得积分10
5秒前
叶颤发布了新的文献求助10
5秒前
小马甲应助陈吉止采纳,获得30
6秒前
6秒前
百川发布了新的文献求助20
7秒前
领导范儿应助彭于晏女友采纳,获得10
7秒前
7秒前
8秒前
上官若男应助1024采纳,获得10
9秒前
10秒前
满意诗霜发布了新的文献求助10
11秒前
阳光中道完成签到,获得积分10
11秒前
我是老大应助123晨+采纳,获得10
12秒前
愉快的牛氓完成签到,获得积分10
12秒前
12秒前
烨笙发布了新的文献求助10
12秒前
Yancy发布了新的文献求助10
13秒前
13秒前
14秒前
深情安青应助留胡子的火采纳,获得10
14秒前
百川完成签到,获得积分10
15秒前
STEAM发布了新的文献求助10
15秒前
盼芙发布了新的文献求助10
15秒前
Copyright应助阳光中道采纳,获得10
16秒前
叶秋寒发布了新的文献求助10
18秒前
花花123发布了新的文献求助10
18秒前
19秒前
19秒前
徐风拂海棠完成签到 ,获得积分10
20秒前
Yancy完成签到,获得积分10
21秒前
22秒前
高分求助中
Cronologia da história de Macau 5000
Matrix Methods in Data Mining and Pattern Recognition 510
C语言程序设计(微课版) 500
Interactions of Vowel Quality and Prosody in East Slavic 500
Vander's Renal Physiology第10版 500
Forensic Science An Introduction to Scientific and Investigative Techniques 6th Edition 400
Reaction of 3-Methylenedihydro-(3H)furan-2-one with Diazoalkanes. Syntheses and Crystal Structures of Spiranic Cyclopropyl Compounds 400
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 7096855
求助须知:如何正确求助?哪些是违规求助? 8753378
关于积分的说明 18513861
捐赠科研通 6651732
什么是DOI,文献DOI怎么找? 3138313
关于科研通互助平台的介绍 2247074
邀请新用户注册赠送积分活动 2113085