Modeling the Conductivity Response to NO2 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

doi:10.3390/s21144723

Modeling the Conductivity Response to NO₂ Gas of Films Based on MWCNT Networks

Sensors (Basel). 2021 Jul 10;21(14):4723. doi: 10.3390/s21144723.

Authors

Ada Fort¹, Marco Mugnaini¹, Enza Panzardi¹, Anna Lo Grasso¹, Ammar Al Hamry², Anurag Adiraju², Valerio Vignoli¹, Olfa Kanoun²

Affiliations

¹ Department of Information Engineering and Mathematical Sciences, University of Siena, Via Roma 56, 53100 Siena, Italy.
² Chair Measurement and Sensor Technology, Department of Electrical Engineering and Information, Technology, Chemnitz University of Technology, 09107 Chemnitz, Germany.

Abstract

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.

Keywords: Au nanoparticles; CNT gas sensing analytical model; MWCNT NO2 sensing; functionalized MWCNT; gas sensing conductivity model.