Highly sensitive and selective SO2 MOF sensor: the integration of MFM-300 MOF as a sensitive layer on a capacitive interdigitated electrode
KAUST DepartmentPhysical Sciences and Engineering (PSE) Division
Chemical Science Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Advanced Membranes and Porous Materials Research Center
Electrical Engineering Program
Functional Materials Design, Discovery and Development (FMD3)
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AbstractWe report on the fabrication of an advanced chemical capacitive sensor for the detection of sulfur dioxide (SO2) at room temperature. The sensing layer based on an indium metal–organic framework (MOF), namely MFM-300, is coated solvothermally on a functionalized capacitive interdigitated electrode. The fabricated sensor exhibits significant detection sensitivity to SO2 at concentrations down to 75 ppb, with the lower detection limit estimated to be around 5 ppb. The MFM-300 MOF sensor demonstrates highly desirable detection selectivity towards SO2 vs. CH4, CO2, NO2 and H2, as well as an outstanding SO2 sensing stability.
CitationChernikova V, Yassine O, Shekhah O, Eddaoudi M, Salama KN (2018) Highly sensitive and selective SO2 MOF sensor: the integration of MFM-300 MOF as a sensitive layer on a capacitive interdigitated electrode. Journal of Materials Chemistry A. Available: http://dx.doi.org/10.1039/c7ta10538j.
SponsorsThe research reported in this publication was supported by funding from King Abdullah University of Science and Technology (KAUST). We also thank Dr Y. Belmabkhout for valuable discussions and Dr P. Bhatt for sorption experiments.
PublisherRoyal Society of Chemistry (RSC)
JournalJournal of Materials Chemistry A
CollectionsArticles; Advanced Membranes and Porous Materials Research Center; Physical Sciences and Engineering (PSE) Division; Functional Materials Design, Discovery and Development (FMD3); Electrical Engineering Program; Chemical Science Program; Sensors Lab; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
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