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Sensitive and Reversible Detection of Methanol and Water Vapor by In Situ Electrochemically Grown CuBTC MOFs on Interdigitated Electrodes
- Source :
- Small 13 (2017) 29, Small, 13(29)
- Publication Year :
- 2017
-
Abstract
- The in situ electrochemical growth of Cu benzene-1,3,5-tricarboxylate (CuBTC) metal-organic frameworks, as an affinity layer, directly on custom-fabricated Cu interdigitated electrodes (IDEs) is described, acting as a transducer. Crystalline 5-7 μm thick CuBTC layers are grown on IDEs consisting of 100 electrodes with a width and a gap of both 50 μm and a height of 6-8 μm. These capacitive sensors are exposed to methanol and water vapor at 30 °C. The affinities show to be completely reversible with higher affinity toward water compared to methanol. For exposure to 1000 ppm methanol, a fast response is observed with a capacitance change of 5.57 pF at equilibrium. The capacitance increases in time followed diffusion-controlled kinetics (k = 2.9 mmol s-0.5 g-1 CuBTC). The observed capacitance change with methanol concentration follows a Langmuir adsorption isotherm, with a value for the equilibrium affinity Ke = 174.8 bar-1. A volume fraction fMeOH = 0.038 is occupied upon exposure to 1000 ppm of methanol. The thin CuBTC affinity layer on the Cu-IDEs shows fast, reversible, and sensitive responses to methanol and water vapor, enabling quantitative detection in the range of 100-8000 ppm.
- Subjects :
- Inorganic chemistry
Analytical chemistry
02 engineering and technology
Interdigitated electrodes
010402 general chemistry
Electrochemistry
01 natural sciences
Capacitance
Biomaterials
symbols.namesake
chemistry.chemical_compound
General Materials Science
Capacitive sensing
Chemistry
Organic Chemistry
Electrochemical synthesis
Langmuir adsorption model
General Chemistry
Metal-organic frameworks
021001 nanoscience & nanotechnology
Organische Chemie
0104 chemical sciences
Volume fraction
Electrode
symbols
Metal-organic framework
Methanol
0210 nano-technology
Water vapor
Biotechnology
Subjects
Details
- Language :
- English
- ISSN :
- 16136810
- Database :
- OpenAIRE
- Journal :
- Small 13 (2017) 29, Small, 13(29)
- Accession number :
- edsair.doi.dedup.....15c48a9a365fe65480b9f76e693b2b46