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Titlebook: Mathematical Modeling of Biosensors; Romas Baronas,Feliksas Ivanauskas,Juozas Kulys Book 2021Latest edition Springer Nature Switzerland AG

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https://doi.org/10.1007/978-3-030-65505-1carbon nanotube based biosensors; optimal design of biosensors; Enzymatic Kinetic; Nernst diffusion lay
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Introduction to Modeling of Biosensors,at some critical concentrations of the substrate when analytical solution of the governing equations is performed. Using numerical simulation, the influence of the model parameters on the biosensor response is investigated. The simulation of the biosensor operation particularly showed a non-monotono
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Effects of Diffusion Limitations on the Response and Sensitivity of Biosensors,re considered. The mathematical models are based on the reaction–diffusion equations containing a nonlinear term related to Michaelis–Menten kinetics. The computer simulation was carried out using the finite difference technique.
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Biosensors Response Amplification with Cyclic Substrates Conversion,nd analysed computationally, too. The simulated response of the biosensors acting in two trigger schemes is compared with the response of a single enzyme biosensor utilizing Michaelis–Menten kinetics. The numerical experiments demonstrated significant gain in the biosensor sensitivity when the biose
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Biosensors Utilizing Synergistic Substrates Conversion,e of the kinetic constants and reagents concentrations on the synergy of the simultaneous substrates conversion. The digital simulation of the system confirmed that the high sensitivity of the bioelectrode achieved in the presence of organic mediators is due to the synergistic substrates conversion
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Chemically Modified Enzyme and Biomimetic Catalysts Electrodes,sensors based on biomimetic catalysts utilizing a combination of two kinds of redox interaction—a simple chemical second-order reaction and Michaelis-type redox reaction scheme. By applying these two types of reactions the influence of the physical and the kinetic parameters on the biosensor respons
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