解耦(概率)
热电效应
塞贝克系数
材料科学
佩多:嘘
压力传感器
灵敏度(控制系统)
光电子学
聚合物
电压
信号(编程语言)
气凝胶
电子工程
纳米技术
计算机科学
电气工程
复合材料
物理
控制工程
工程类
机械工程
热力学
热导率
程序设计语言
作者
Zubin Wang,Saihua Jiang,Yubin Huang,Tao Song,Chaokang Liufu,Yaofeng Huang,Gang Zhou,Qi Zhang,Xiaodong Qian,Yang Lan,Nour F. Attia
标识
DOI:10.1002/admt.202400096
摘要
Abstract The capability to emulate skin‐like temperature and pressure sensing is fundamental for next‐generation artificial intelligence products. However, detecting temperature and pressure simultaneously with a single sensor without signal interference is challenging. Herein, a novel PCC aerogel sensor composed of PEDOT:PSS, CNTs, and CNF via directional freezing technology is developed. The PCC sensor can decouple temperature and pressure stimuli into individual voltage and resistance signals. It exhibits high‐precision temperature sensing capabilities, boasting an exceptionally high Seebeck coefficient of 30.4 µV K‐1 and the ability to detect temperature variations as low as 0.1 K. PCC sensors show excellent sensitivity and fast response times for detecting static and dynamic pressures, as well as high stability after 1000 cycles. Its maximum pressure sensitivity can reach 159.1% kPa −1 , and the lowest detection limit is 10 Pa. Additionally, its excellent thermoelectric properties also enable to generating thermopower from human skin for self‐powered pressure sensing. A 3×3 PCC sensor array has been proposed to simulate the unique features of human skin in temperature and pressure recognition. This work provides a scalable manufacturing strategy for multi‐functional tactile sensors.
科研通智能强力驱动
Strongly Powered by AbleSci AI