Amplified sensing of nitrogen dioxide with a phosphate-doped reduced graphene oxide powder

abstract

Surface chemistry plays an essential role in gas-sensing applications, enabling significant improvements in the sensing performance. This study investigates the influence of the graphene oxide (GO) synthesis route on the sensitivity to NO 2 gas at room temperature (25 degrees C) and 100 degrees C in a dry and humid atmosphere. GO powders were synthesized using both the classical Hummers ' method (HGO), and an improved version of the Hummers ' method (IGO) using a mixture of phosphoric and sulfuric acids. The subsequent reduction (resulting in rHGO and rIGO, respectively) aimed to enhance the electrical properties and procure nanomaterials sensitive to surface adsorbates. In contrast to the HGO, both IGO and rIGO samples exhibited a transient sensor response and an outstanding recovery performance, which was attributed to the existence of phosphate groups in the latter samples. Notably, the rIGO sample achieved a 23 -fold increase in response to NO 2 compared to rHGO. Additionally, the limit of detection (LOD) was calculated to be 0.98 ppb at 100 degrees C. Computational studies considering models of GO and of GO with phosphorus-containing species demonstrate that the presence of the latter, either at the surface or below the surface, leads to a four-fold increase in the NO 2 adsorption energies, hence accounting for the significant enhancement in the sensing performance observed experimentally. This underscores the importance of tailoring the structure and chemical properties of GO/rGO materials for optimal performance in gas sensing applications.

keywords

INITIO MOLECULAR-DYNAMICS; OXYGEN REDUCTION REACTION; TOTAL-ENERGY CALCULATIONS; GAS SENSOR; PERFORMANCE; GRAPHITE; SENSITIVITY; EFFICIENCY; AREA

subject category

Chemistry; Materials Science

authors

Hasanov, BE; Casanova-Chafer, J; Deokar, G; Gouveia, JD; Nematulloev, S; Gomes, JRB; Llobet, E; Costa, PMFJ

Groups

G6 - Virtual Materials and Artificial Intelligence

Projects

CICECO - Aveiro Institute of Materials (UIDB/50011/2020)

CICECO - Aveiro Institute of Materials (UIDP/50011/2020)

Associated Laboratory CICECO-Aveiro Institute of Materials (LA/P/0006/2020)

Collaboratory for Emerging Technologies, CoLab (EMERGING TECHNOLOGIES)

acknowledgements

This work was financially supported by KAUST (BAS/1/1346-01-01) , MICINN and FEDER grant no. PDC2022-133967-I00 and AGAUR grant no. 2017 SGR 418, and by FCT/MEC (PIDDAC) through project CICECO-Aveiro Institute of Materials, with refs. UIDB/50011/2020, UIDP/50011/2020 and LA/P/0006/2020. We thank the Core Labs scientists for their technical assistance at KAUST. J.C.-C. is supported by the Marie Sklodowska-Curie grant agreement No. 101066282-GREBOS. E.L. is supported by the Catalan Institute for Advanced Studies (ICREA) via the 2023 Edition of the ICREA Academia Award. JDG and JRBG thank the Portuguese Foundation for Science and Technology (FCT) I.P. for the computational resources granted in the framework of project Ref. 2022.15802.CPCA.A2 by the FCT/CPCA/2022/01 Call for Advanced Computing Projects. JDG thanks FCT through the grants Refs.2022.00719.CEECIND and 2023.06511.CEECIND, in the scope of the Individual Call to Scientific Employment Stimulus - 5th and 6th Editions.