Rationalizing Graphene–ZnO Composites for Gas Sensing via Functionalization with Amines

Author:

Rabchinskii Maxim K.1ORCID,Sysoev Victor V.2ORCID,Brzhezinskaya Maria3,Solomatin Maksim A.2,Gabrelian Vladimir S.1,Kirilenko Demid A.1ORCID,Stolyarova Dina Yu.4,Saveliev Sviatoslav D.12,Shvidchenko Alexander V.1,Cherviakova Polina D.1,Varezhnikov Alexey S.2ORCID,Pavlov Sergey I.1ORCID,Ryzhkov Sergei A.12,Khalturin Boris G.1,Prasolov Nikita D.1ORCID,Brunkov Pavel N.1ORCID

Affiliation:

1. Ioffe Institute, Politekhnicheskaya St. 26, Saint Petersburg 194021, Russia

2. Department of Physics, Yuri Gagarin State Technical University of Saratov, 77 Polytechnicheskaya St., Saratov 410054, Russia

3. Helmholtz-Zentrum Berlin für Materialien und Energie, Hahn-Meitner-Platz 1, 14109 Berlin, Germany

4. NRC “Kurchatov Institute”, Akademika Kurchatova pl. 1, Moscow 123182, Russia

Abstract

The rational design of composites based on graphene/metal oxides is one of the pillars for advancing their application in various practical fields, particularly gas sensing. In this study, a uniform distribution of ZnO nanoparticles (NPs) through the graphene layer was achieved, taking advantage of amine functionalization. The beneficial effect of amine groups on the arrangement of ZnO NPs and the efficiency of their immobilization was revealed by core-level spectroscopy, pointing out strong ionic bonding between the aminated graphene (AmG) and ZnO. The stability of the resulting Am-ZnO nanocomposite was confirmed by demonstrating that its morphology remains unchanged even after prolonged heating up to 350 °C, as observed by electron microscopy. On-chip multisensor arrays composed of both AmG and Am-ZnO were fabricated and thoroughly tested, showing almost tenfold enhancement of the chemiresistive response upon decorating the AmG layer with ZnO nanoparticles, due to the formation of p-n heterojunctions. Operating at room temperature, the fabricated multisensor chips exhibited high robustness and a detection limit of 3.6 ppm and 5.1 ppm for ammonia and ethanol, respectively. Precise identification of the studied analytes was achieved by employing the pattern recognition technique based on linear discriminant analysis to process the acquired multisensor response.

Funder

Russian Science Foundation

Ministry of Science and Higher Education of the Russian Federation

Publisher

MDPI AG

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