Recent advances in carbon material-based NO2 gas sensors

Sang Won Lee, Wonseok Lee, Yoochan Hong, Gyudo Lee, Dae Sung Yoon

Research output: Contribution to journalReview articlepeer-review

177 Citations (Scopus)

Abstract

Nitrogen dioxide (NO2) detection is critical because NO2 is a typical toxic gas that is harmful to humans as well as the environment. Over the last few decades, various nanomaterials such as nanowires, nanoparticles, carbon nanotubes, and graphene have been widely utilized to construct the platform (i.e., supporting material) of NO2 gas sensors. Among these materials, carbon nanomaterials (e.g., graphene and carbon nanotubes) have received increasing attention owing to their outstanding physical and electrical properties required for NO2 detection. Recently, many attempts have been made to blend the carbon nanomaterials with other materials, resulting in the creation of composite materials with enhanced electrical conductivity and physical properties for highly sensitive and selective detection of NO2 gas. As such, blended or stacked carbon composite materials offer higher efficiency (i.e., improved sensitivity and response/recovery time) for detecting NO2 gas in comparison with pristine carbon nanomaterials. In this review, we consider state-of-the-art amperometric NO2 gas sensors based on carbon nanomaterials with respect to their dimensionalities, and we discuss the enhanced gas-sensing performance achieved by using composite materials.

Original languageEnglish
Pages (from-to)1788-1804
Number of pages17
JournalSensors and Actuators, B: Chemical
Volume255
DOIs
Publication statusPublished - 2018 Feb

Keywords

  • Carbon nanotube
  • Electrical gas sensor
  • Nanomaterial
  • Nitrogen dioxide (NO)
  • Reduced graphene oxide
  • Response/recovery time

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Instrumentation
  • Condensed Matter Physics
  • Surfaces, Coatings and Films
  • Metals and Alloys
  • Electrical and Electronic Engineering
  • Materials Chemistry

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