刚度
夹紧
材料科学
灵敏度(控制系统)
分层(地质)
机器人
压力(语言学)
纳米技术
声学
机械工程
复合材料
结构工程
计算机科学
工程类
人工智能
电子工程
地质学
物理
古生物学
哲学
语言学
构造学
俯冲
作者
Fuhua Xue,Haowen Zheng,Qingyu Peng,Ying Hu,Xiaojian Zhao,Liangliang Xu,Pengyang Li,Yue Zhu,Zonglin Liu,Xiaodong He
出处
期刊:Materials horizons
[The Royal Society of Chemistry]
日期:2021-01-01
卷期号:8 (8): 2260-2272
被引量:25
摘要
The question of how to make artificial intelligence robots perceive the power of "light as a feather" and "heavy as a mountain" at the same time has always been a goal that people are striving to achieve. However, pressure sensors, the key components of electronic equipment, are often unable to incorporate high sensitivity and wide range performance. Here, we proposed a "gradient stiffness design" strategy to prepare a kind of carbon nanotube sponge with a stiffness difference of up to 254 times between different layers, but still maintaining an integral conductive network without delamination. This gradient stiffness structure sponge shows prominent sensing properties with ultra-broad range (from 0.0022 MPa to 5.47 MPa) and high sensitivity. The low stiffness layer can detect low stress (0.0022 MPa) with high sensitivity of 0.765 MPa-1, and the high stiffness layer can greatly extend the sensing range to an unprecedentedly high value (5.47 MPa). It can concisely detect various motions with different stress, from slight clamping of fragile fries by the robot fingers to heavily stomping motions by a 90 kg person. Moreover, a series of human movements from small-scale to large-scale can be also monitored, revealing the great potential of this gradient stiffness structure in future sensing research.
科研通智能强力驱动
Strongly Powered by AbleSci AI