Quantitative description of Ag nanoparticles-graphene hybrids with optimized morphology on sensing performance

  • Hui Song
  • , Shaochong Lei
  • , Xin Li
  • , Shixi Guo
  • , Ping Cui
  • , Xianqi Wei
  • , Weihua Liu
  • , Hongzhong Liu

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Due to their synergistic effect, metal nanoparticles (NPs)-graphene hybrids exhibit better catalytic activity and sensing performance in bio application, chemical sensors and Surface-enhanced Raman spectroscopy substrate than most of other hybrids. To give quantitative description of gas sensing performance depending on metal NPs morphology, we have experimentally acquired NH3 sensing profiles of Ag NPs-graphene hybrids with different morphology, and extracted adsorption heat according to the Langmuir adsorption theory. The relation between sensing performance and catalytic activity of Ag NPs-graphene hybrids has been established. The optimized morphology as size, coverage and degree of dispersion of Ag NPs on graphene results in higher catalytic activity, which is the key point of enhanced sensing performance. The maximum response of Ag NPs-graphene hybrids with optimized morphology is about 2 times the average response of the others. The quantitative description of gas sensing performance depending on surface morphology of Ag NPs-graphene hybrids should pave a way for other sensing areas.

Original languageEnglish
Pages (from-to)53-59
Number of pages7
JournalSensors and Actuators A: Physical
Volume271
DOIs
StatePublished - 1 Mar 2018

Keywords

  • Adsorption heat
  • Ag nanoparticles
  • Catalytic activity
  • Gas sensor
  • Graphene
  • Quantitative description

Fingerprint

Dive into the research topics of 'Quantitative description of Ag nanoparticles-graphene hybrids with optimized morphology on sensing performance'. Together they form a unique fingerprint.

Cite this