Mathematical Modeling of Biosensors An Introduction for Chemists and Mathematicians /

This book presents biosensor development and modeling from both a chemical and a mathematical point of view. It contains unique modeling methods for catalytical (amperometric, potentiometer and optical) biosensors. It examines processes that occur in the sensors' layers and at their interface,...

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Bibliographic Details
Main Authors: Baronas, Romas. (Author), Ivanauskas, Feliksas. (Author), Kulys, Juozas. (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic
Language:English
Published: Dordrecht : Springer Netherlands, 2010.
Series:Springer Series on Chemical Sensors and Biosensors, Methods and Applications, 9
Subjects:
Online Access:https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-90-481-3243-0
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505 0 # |a Introduction -- Part I Analytical Modeling of Biosensors -- 1 Biosensor Action -- 2 Modeling Biosensors at Steady State and Internal Diffusion Limitations -- 3 Modeling Biosensors at Steady State and External Diffusion Limitations -- 4 Modeling Biosensors Utilizing Microbial cells -- 5 Modeling Nonstationary State of Biosensors -- Part II Numerical Modeling of Biosensors -- 6 Mono-Layer Mono-Enzyme Models of Biosensors -- 7 One-Layer Multi-Enzyme Models of Biosensors -- 8 Multi-Layer Models of Biosensors -- 9 Modeling Biosensors of Complex Geometry -- Part III Numerical Methods for Reaction-Diffusion Equations -- 10 The Difference Schemes for the Diffusion Equation -- 11 The Difference Schemes for the Reaction-Diffusion Equations -- References -- Index. 
520 # # |a This book presents biosensor development and modeling from both a chemical and a mathematical point of view. It contains unique modeling methods for catalytical (amperometric, potentiometer and optical) biosensors. It examines processes that occur in the sensors' layers and at their interface, and it provides analytical and numerical methods to solve enzymatic kinetic and diffusion equations. The action of single enzyme as well as polyenzyme biosensors is studied, and the modeling of biosensors that contain perforated membranes and multipart mass transport profiles is critically investigated. Furthermore, it is fully described how signals can be biochemically amplified, how cascades of enzymatic substrate conversion are triggered, and how signals are processed via a chemometric approach and artificial neuronal networks. The results of digital modeling are compared with both proximal analytical solutions and experimental data. 
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