Sensors 2012, 12(7), 9146-9160; doi:10.3390/s120709146
Article

Modelling Carbon Nanotubes-Based Mediatorless Biosensor

1 Faculty of Mathematics and Informatics, Vilnius University, Naugarduko 24, LT-03225 Vilnius, Lithuania 2 Institute of Biochemistry, Vilnius University, Mokslininku 12, LT-08662 Vilnius, Lithuania
* Author to whom correspondence should be addressed.
Received: 16 April 2012; in revised form: 1 June 2012 / Accepted: 6 June 2012 / Published: 3 July 2012
(This article belongs to the Section Biosensors)
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Abstract: This paper presents a mathematical model of carbon nanotubes-based mediatorless biosensor. The developed model is based on nonlinear non-stationary reaction-diffusion equations. The model involves four layers (compartments): a layer of enzyme solution entrapped on a terylene membrane, a layer of the single walled carbon nanotubes deposited on a perforated membrane, and an outer diffusion layer. The biosensor response and sensitivity are investigated by changing the model parameters with a special emphasis on the mediatorless transfer of the electrons in the layer of the enzyme-loaded carbon nanotubes. The numerical simulation at transient and steady state conditions was carried out using the finite difference technique. The mathematical model and the numerical solution were validated by experimental data. The obtained agreement between the simulation results and the experimental data was admissible at different concentrations of the substrate.
Keywords: modelling; simulation; reaction-diffusion; biosensor; mediatorless; SWCNT

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MDPI and ACS Style

Baronas, R.; Kulys, J.; Petrauskas, K.; Razumiene, J. Modelling Carbon Nanotubes-Based Mediatorless Biosensor. Sensors 2012, 12, 9146-9160.

AMA Style

Baronas R, Kulys J, Petrauskas K, Razumiene J. Modelling Carbon Nanotubes-Based Mediatorless Biosensor. Sensors. 2012; 12(7):9146-9160.

Chicago/Turabian Style

Baronas, Romas; Kulys, Juozas; Petrauskas, Karolis; Razumiene, Julija. 2012. "Modelling Carbon Nanotubes-Based Mediatorless Biosensor." Sensors 12, no. 7: 9146-9160.

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