Modeling the Conductivity Response to NO<sub>2</sub> Gas of Films Based on MWCNT Networks
Ada Fort,
Marco Mugnaini,
Enza Panzardi,
Anna Lo Grasso,
Ammar Al Hamry,
Anurag Adiraju,
Valerio Vignoli,
Olfa Kanoun
Affiliations
Ada Fort
Department of Information Engineering and Mathematical Sciences, University of Siena, Via Roma 56, 53100 Siena, Italy
Marco Mugnaini
Department of Information Engineering and Mathematical Sciences, University of Siena, Via Roma 56, 53100 Siena, Italy
Enza Panzardi
Department of Information Engineering and Mathematical Sciences, University of Siena, Via Roma 56, 53100 Siena, Italy
Anna Lo Grasso
Department of Information Engineering and Mathematical Sciences, University of Siena, Via Roma 56, 53100 Siena, Italy
Ammar Al Hamry
Chair Measurement and Sensor Technology, Department of Electrical Engineering and Information, Technology, Chemnitz University of Technology, 09107 Chemnitz, Germany
Anurag Adiraju
Chair Measurement and Sensor Technology, Department of Electrical Engineering and Information, Technology, Chemnitz University of Technology, 09107 Chemnitz, Germany
Valerio Vignoli
Department of Information Engineering and Mathematical Sciences, University of Siena, Via Roma 56, 53100 Siena, Italy
Olfa Kanoun
Chair Measurement and Sensor Technology, Department of Electrical Engineering and Information, Technology, Chemnitz University of Technology, 09107 Chemnitz, Germany
This work proposes a model describing the dynamic behavior of sensing films based on functionalized MWCNT networks in terms of conductivity when exposed to time-variable concentrations of NO2 and operating with variable working temperatures. To test the proposed model, disordered networks of MWCNTs functionalized with COOH and Au nanoparticles were exploited. The model is derived from theoretical descriptions of the electronic transport in the nanotube network, of the NO2 chemisorption reaction and of the interaction of these two phenomena. The model is numerically implemented and then identified by estimating all the chemical/physical quantities involved and acting as parameters, through a model fitting procedure. Satisfactory results were obtained in the fitting process, and the identified model was used to further the analysis of the MWCNT sensing in dynamical conditions.
