Effects of graphene defects on gas sensing properties towards NO 2 detection

Journal Article (2017)
Author(s)

Filiberto Ricciardella (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Sten Vollebregt (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Tiziana Polichetti (ENEA Research Center)

Mario Miscuglio (Università degli Studi di Genova, Italian Institute of Technology)

Brigida Alfano (Università degli Studi di Napoli Federico II, ENEA Research Center)

Maria L Miglietta (ENEA Research Center)

Ettore Massera (ENEA Research Center)

Girolamo Di Francia (ENEA Research Center)

Pasqualina M Sarro (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Research Group
Electronic Components, Technology and Materials
DOI related publication
https://doi.org/10.1039/c7nr01120b Final published version
More Info
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Publication Year
2017
Language
English
Research Group
Electronic Components, Technology and Materials
Journal title
Nanoscale
Issue number
18
Volume number
9
Pages (from-to)
6085-6093
Downloads counter
317
Collections
Institutional Repository
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Abstract

The crystal structure of graphene flakes is expected to significantly affect their sensing properties. Here we report an experimental investigation on the crystalline structure of graphene aimed at exploring the effects on the gas sensing properties. The morphology of graphene, prepared via Chemical Vapor Deposition (CVD), Liquid Phase Exfoliation (LPE) and Mechanical Exfoliation (ME), is inspected through Raman spectroscopy, Atomic Force Microscopy (AFM) and Scanning Electron Microscopy (SEM). CVD and LPE-graphene structures are found to be more defective with respect to ME-graphene. The defects are due to the jagged morphology of the films rather than originating from intrinsic disorder. The flatness of ME-graphene flakes, instead, explains the absence of defects. Chemiresistors based on the three different graphene preparation methods are subsequently exposed to NO2 in the concentration range 0.1–1.5 ppm (parts per million). The device performance is demonstrated to be strongly and unambiguously affected by the material structure: the less defective the material is, the higher the response rate is. In terms of signal variation, at 1.5 ppm, for instance, ME-graphene shows the highest value (5%) among the three materials. This study, comparing simultaneously graphene and sensors prepared via different routes, provides the first experimental evidence of the role played by the graphene level of defectiveness in the interaction with analytes. Moreover, these findings can pave the path for tailoring the sensor behavior as a function of graphene morphology.