Highly sensitive, wide-pressure and low-frequency characterized pressure sensor based on piezoresistive-piezoelectric coupling effects in porous wood

压阻效应 压电 材料科学 压力传感器 灵敏度(控制系统) 复合材料 多孔性 压缩性 联轴节(管道) 声学 光电子学 电子工程 机械工程 机械 物理 工程类
作者
Jingjing Luo,Feihua Liu,Ao Yin,Xue Qi,Jiang Liu,Zhongqi Ren,Shiqiang Zhou,Yuxin Wang,Yang Ye,Qingzhi Ma,Junjun Zhu,Kang Li,Chen Zhang,Weiwei Zhao,Suzhu Yu,Jun Wei
出处
期刊:Carbohydrate Polymers [Elsevier]
卷期号:315: 120983-120983 被引量:18
标识
DOI:10.1016/j.carbpol.2023.120983
摘要

Lightweight and highly compressible materials have received considerable attention in flexible pressure sensing devices. In this study, a series of porous woods (PWs) are produced by chemical removal of lignin and hemicellulose from natural wood by tuning treatment time from 0 to 15 h and extra oxidation through H2O2. The prepared PWs with apparent densities varying from 95.9 to 46.16 mg/cm3 tend to form a wave-shaped interwoven structure with improved compressibility (up to 91.89 % strain under 100 kPa). The sensor assembled from PW with treatment time of 12 h (PW-12) exhibits the optimal piezoresistive-piezoelectric coupling sensing properties. For the piezoresistive properties, it has high stress sensitivity of 15.14 kPa-1, covering a wide linear working pressure range of 0.06-100 kPa. For its piezoelectric potential, PW-12 shows a sensitivity of 0.443 V·kPa-1 with ultralow frequency detection as low as 0.0028 Hz, and good cyclability over 60,000 cycles under 0.41 Hz. The nature-derived all-wood pressure sensor shows obvious superiority in the flexibility for power supply requirement. More importantly, it presents fully decoupled signals without cross-talks in the dual-sensing functionality. Sensor like this is capable of monitoring various dynamic human motions, making it an extremely promising candidate for the next generation artificial intelligence products.
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
666星爷留下了新的社区评论
刚刚
风吹似夏完成签到,获得积分10
刚刚
刚刚
李健应助crr采纳,获得10
刚刚
tao完成签到,获得积分20
1秒前
淡淡的雪完成签到,获得积分10
1秒前
1秒前
1秒前
yitang发布了新的文献求助10
2秒前
涛浪发布了新的文献求助10
2秒前
3秒前
3秒前
乔治韦斯莱完成签到 ,获得积分10
4秒前
Jenny应助圈圈采纳,获得10
4秒前
4秒前
呆萌完成签到 ,获得积分10
4秒前
啾啾完成签到,获得积分10
4秒前
脑洞疼应助hhy采纳,获得10
5秒前
Zhong发布了新的文献求助10
7秒前
7秒前
神仙也抠脚丫完成签到,获得积分10
7秒前
7秒前
8秒前
岩中花树完成签到,获得积分10
8秒前
8秒前
科研小白完成签到,获得积分10
9秒前
9秒前
追梦发布了新的文献求助10
9秒前
9秒前
豆包完成签到,获得积分10
9秒前
怕孤单的耳机完成签到,获得积分10
9秒前
成就梦松发布了新的文献求助10
9秒前
Donnie发布了新的文献求助10
10秒前
scc完成签到,获得积分10
10秒前
呼叫554发布了新的文献求助30
10秒前
Ava应助向北游采纳,获得10
10秒前
CodeCraft应助科研通管家采纳,获得10
11秒前
SciGPT应助科研通管家采纳,获得10
11秒前
科研通AI5应助MRCHONG采纳,获得10
11秒前
Simon应助科研通管家采纳,获得10
11秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527304
求助须知:如何正确求助?哪些是违规求助? 3107454
关于积分的说明 9285518
捐赠科研通 2805269
什么是DOI,文献DOI怎么找? 1539827
邀请新用户注册赠送积分活动 716708
科研通“疑难数据库(出版商)”最低求助积分说明 709672