| Literature DB >> 35112565 |
Bitnuri Kwon1, Hyeonhu Bae2, Hoonkyung Lee2, Seunghyun Kim3, Jinhyun Hwang1, Hyungsub Lim3, Jung Hun Lee4, Kilwon Cho3, Jongpil Ye5, Seungae Lee6, Wi Hyoung Lee1,6.
Abstract
Sensitive and selective detection of target gases is the ultimate goal for commercialization of graphene gas sensors. Here, ultrasensitive n-channel graphene gas sensors were developed by using n-doped graphene with ethylene amines. The exposure of the n-doped graphene to oxidizing gases such as NO2 leads to a current decrease that depends strongly on the number of amine functional groups in various types of ethylene amines. Graphene doped with diethylenetriamine (DETA) exhibits the highest response, recovery, and long-term sensing stability to NO2, with an average detection limit of 0.83 parts per quadrillion (ppq, 10-15), due to the attractive electrostatic interaction between electron-rich graphene and electron-deficient NO2. Our first-principles calculation supported a preferential adsorption of NO2 on n-doped graphene. In addition, gas molecules on the n-channel graphene provide charged impurities, thereby intensifying the current decrease for an excellent response to oxidizing gases such as NO2 or SO2. On the contrary, absence of such a strong interaction between NH3 and DETA-doped graphene and combined effects of current increase by n-doping and mobility decrease by charged impurities result in a completely no response to NH3. Because the n-channel is easily induced by a top-molecular dopant, a flexible graphene sensor with outstanding NO2 detection capability was successfully fabricated on plastic without vertical stacks of gate-electrode and gate-dielectric. Our gate-free graphene gas sensors enabled by nondestructive molecular n-doping could be used for the selective detection of subppq-level NO2 in a gas mixture with reducing gases.Entities:
Keywords: gas sensor; gate-free; graphene; molecular doping; n-channel; sensitivity
Year: 2022 PMID: 35112565 DOI: 10.1021/acsnano.1c08186
Source DB: PubMed Journal: ACS Nano ISSN: 1936-0851 Impact factor: 15.881