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The sensing mechanism of HCHO gas sensor based on transition metal doped graphene: Insights from DFT study

  • Yuanchao Li
  • , Yanling Xu
  • , Xin Li*
  • *Corresponding author for this work
  • School of Chemistry and Chemical Engineering, Harbin Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

Formaldehyde (HCHO), as primary chemical feedstock, is widely used in various fields. Unfortunately, it can cause harmful impacts on human health due to its high toxicity. Therefore, effective monitoring and detection of HCHO is significant. HCHO gas sensor based on doped graphene was extensively investigated in recent years. However, the relationship between gas-sensing performance and electronegativity of doped atoms has not been clarified. In this research, Ni, Pd and Pt are used as dopants, and the adsorption behaviors, energies, electronic and optical properties of HCHO molecule on doped graphene were systematically investigated by density functional theory (DFT) method to explore the effect of electronegativity of doped atoms on the sensing property. The calculated results show that graphene doped with higher electronegativity atoms is beneficial to cause a recordable electric signal due to larger change of energy gap. The adsorption energy increases steadily with an enhancement in the electronegativity of doped atoms. It is clear that there is an obvious linear relationship between gas-sensing performance and electronegativity of doped atoms. In other words, specific sensitivities (e.g., adsorption energy, electrical conductivity, recovery time, chemical reactivity parameters and so on) of gas sensor can be adjusted by embedding different electronegativity atoms in graphene, which provide meaningful information to design highly sensitive graphene-based gas sensors. Besides, the adsorption and desorption performance of HCHO can be controlled by applying positive or negative electric field.

Original languageEnglish
Article number113460
JournalSensors and Actuators A: Physical
Volume338
DOIs
StatePublished - 1 May 2022
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Density functional theory
  • Doped graphene
  • Electronegativity
  • Gas sensor
  • Sensing mechanism

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