Laterally extended atomically precise graphene nanoribbons with improved electrical conductivity for efficient gas sensing

Mohammad Mehdi Pour, Andrey Lashkov, Adrian Radocea, Ximeng Liu, Tao Sun, Alexey Lipatov, Rafal A. Korlacki, Mikhail Shekhirev, Narayana R. Aluru, Joseph W. Lyding, Victor Sysoev, Alexander Sinitskii

Research output: Contribution to journalArticlepeer-review

Abstract

Narrow atomically precise graphene nanoribbons hold great promise for electronic and optoelectronic applications, but the previously demonstrated nanoribbon-based devices typically suffer from low currents and mobilities. In this study, we explored the idea of lateral extension of graphene nanoribbons for improving their electrical conductivity. We started with a conventional chevron graphene nanoribbon, and designed its laterally extended variant. We synthesized these new graphene nanoribbons in solution and found that the lateral extension results in decrease of their electronic bandgap and improvement in the electrical conductivity of nanoribbon-based thin films. These films were employed in gas sensors and an electronic nose system, which showed improved responsivities to low molecular weight alcohols compared to similar sensors based on benchmark graphitic materials, such as graphene and reduced graphene oxide, and a reliable analyte recognition. This study shows the methodology for designing new atomically precise graphene nanoribbons with improved properties, their bottom-up synthesis, characterization, processing and implementation in electronic devices.

Original languageEnglish (US)
Article number820
JournalNature communications
Volume8
Issue number1
DOIs
StatePublished - Dec 1 2017

ASJC Scopus subject areas

  • General Chemistry
  • General Biochemistry, Genetics and Molecular Biology
  • General Physics and Astronomy

Fingerprint

Dive into the research topics of 'Laterally extended atomically precise graphene nanoribbons with improved electrical conductivity for efficient gas sensing'. Together they form a unique fingerprint.

Cite this