Name: Mathematical Modeling of Biosensors (en Inglés)
Price: 261.21 EUR
Availability: InStock
Author: Baronas, Romas ; Ivanauskas, Feliksas ; Kulys, Juozas
ISBN: 9783030655044

portada Mathematical Modeling of Biosensors (en Inglés)

Formato

Libro Físico

Autor

Editorial

Idioma

Inglés

N° páginas

456

Encuadernación

Tapa Dura

Dimensiones

23.4 x 15.6 x 2.7 cm

Peso

0.84 kg.

ISBN13

9783030655044

N° edición

0002

Categorías

Ingeniería biomédica
Química
Biotecnología
Química industrial e ingeniería química

Mathematical Modeling of Biosensors (en Inglés)

Romas Baronas (Autor) · Feliksas Ivanauskas (Autor) · Juozas Kulys (Autor) · Springer · Tapa Dura

Libro Nuevo

261,21 €

274,96 €

Ahorras: 13,75 €

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Origen: Estados Unidos (Costos de importación incluídos en el precio)

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Reseña del libro "Mathematical Modeling of Biosensors (en Inglés)"

This newly designed and enlarged edition offers an up-to-date presentation of biosensor development and modeling from both a chemical and a mathematical point of view. An entire new chapter in particular is dedicated to optimal design of biosensors. Two more new chapters discuss biosensors which utilize microbial cells and are based on carbon nanotubes respectively. All the other chapters have been revised and updated. The book contains unique modeling methods for amperometric, potentiometric and optical biosensors based mainly on biocatalysts . It examines processes that occur in the sensors' layers and at their interface, and it provides analytical and numerical methods to solve equations of conjugated enzymatic (chemical) and diffusion processes. The action of single enzyme as well as polyenzyme biosensors and biosensors based on chemically modified electrodes is studied. 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.