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 concen-trations 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 net-work, 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.
Fort, A., Mugnaini, M., Panzardi, E., Lo Grasso, A., Al Hamry, A., Adiraju, A., et al. (2021). Modeling the conductivity response to NO2 gas of films based on MWCNT networks. SENSORS, 21(14) [10.3390/s21144723].
Modeling the conductivity response to NO2 gas of films based on MWCNT networks
Fort A.
;Mugnaini M.;Panzardi E.;Vignoli V.;
2021-01-01
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 concen-trations 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 net-work, 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.File | Dimensione | Formato | |
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https://hdl.handle.net/11365/1173264