Multifunctional Sensor Based on Porous Carbon Derived from Metal-Organic Frameworks for Real Time Health Monitoring

Xin Hua Zhao, Sai Nan Ma, Hui Long, Huiyu Yuan, Chun Yin Tang, Ping Kwong Cheng, Yuen Hong Tsang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

138 Citations (Scopus)

Abstract

Flexible and sensitive sensors that can detect external stimuli such as pressure, temperature, and strain are essential components for applications in health diagnosis and artificial intelligence. Multifunctional sensors with the capabilities of sensing pressure and temperature simultaneously are highly desirable for health monitoring. Here, we have successfully fabricated a flexible and simply structured bimodal sensor based on metal-organic frameworks (MOFs) derived porous carbon (PC) and polydimethylsiloxane (PDMS) composite. Attributed to the porous structure of PC/PDMS composite, the fabricated sensor exhibits high sensitivity (15.63 kPa-1), fast response time (<65 ms), and high durability (∼2000 cycles) for pressure sensing. Additionally, its application in detecting human motions such as subtle wrist pulses in real time has been demonstrated. Furthermore, the as-prepared device based on the PC/PDMS composite exhibits a good sensitivity (>0.11 °C-1) and fast response time (∼100 ms), indicating its potential application in sensing temperature. All of these capabilities indicate its great potential in the applications of health monitoring and artificial skin for artificial intelligence system.
Original languageEnglish
Pages (from-to)3986-3993
Number of pages8
JournalACS Applied Materials and Interfaces
Volume10
Issue number4
DOIs
Publication statusPublished - 31 Jan 2018

Keywords

  • metal-organic frameworks (MOFs)
  • porous carbon
  • pressure sensor
  • real time health monitoring
  • temperature sensor

ASJC Scopus subject areas

  • General Materials Science

Fingerprint

Dive into the research topics of 'Multifunctional Sensor Based on Porous Carbon Derived from Metal-Organic Frameworks for Real Time Health Monitoring'. Together they form a unique fingerprint.

Cite this