| Literature DB >> 34493951 |
Luis Antonio Panes-Ruiz1, Leif Riemenschneider1, Mohamad Moner Al Chawa2, Markus Löffler3, Bernd Rellinghaus3, Ronald Tetzlaff2, Viktor Bezugly1,4,5, Bergoi Ibarlucea1,5, Gianaurelio Cuniberti1,5.
Abstract
We demonstrate the selective detection of hydrogen sulfide at breath concentration levels under humid airflow, using a self-validating 64-channel sensor array based on semiconducting single-walled carbon nanotubes (sc-SWCNTs). The reproducible sensor fabrication process is based on a multiplexed and controlled dielectrophoretic deposition of sc-SWCNTs. The sensing area is functionalized with gold nanoparticles to address the detection at room temperature by exploiting the affinity between gold and sulfur atoms of the gas. Sensing devices functionalized with an optimized distribution of nanoparticles show a sensitivity of 0.122%/part per billion (ppb) and a calculated limit of detection (LOD) of 3 ppb. Beyond the self-validation, our sensors show increased stability and higher response levels compared to some commercially available electrochemical sensors. The cross-sensitivity to breath gases NH3 and NO is addressed demonstrating the high selectivity to H2S. Finally, mathematical models of sensors' electrical characteristics and sensing responses are developed to enhance the differentiation capabilities of the platform to be used in breath analysis applications. Electronic Supplementary Material: Supplementary material (details on the dielectrophoretic deposition, AuNP functionalization optimization, full range of experimental and model H2S sensing response up to 820 ppb, and sensing response to NO gas) is available in the online version of this article at 10.1007/s12274-021-3771-7.Entities:
Keywords: chemiresistive gas sensors; chemiresistor mathematical model; gold nanoparticles; hydrogen sulfide detection; semiconducting carbon nanotubes
Year: 2021 PMID: 34493951 PMCID: PMC8412394 DOI: 10.1007/s12274-021-3771-7
Source DB: PubMed Journal: Nano Res ISSN: 1998-0000 Impact factor: 10.269