A numerical modelling of an amperometric-enzymatic based uric acid biosensor for GOUT arthritis diseases. (2019) - Parthasarathy, P.; Vivekanandan, S.
Abstract: A numerical model of an amperometric-enzymatic uric acid biosensor for a non-relentless condition has been developed. This model depends on the arrangement of nonlinear reaction diffusion equations for Michaelis-Menten formalism that depicts the concentrations of substrate and product. The new rough scientific articulations for the concentration of substrate (uricase enzyme) and product and the corresponding current response have been derived for all estimations of parameters utilizing the new perturbation technique. The non-dimensional numerical model of the amperometric biosensor can be effectively used to examine the responses. Moreover, the relative impact of these parameters is chosen by the Damkohler number and the impact of current density on this number likewise contemplated. All the analytical results are compared with simulation results using MATLAB program and the numerical outcomes concur with fitting hypotheses. Notwithstanding, strikingly the model likewise proposed that the choice of substrate and product for uric acid biosensor for the application of kidney disease and GOUT arthritis diseases.