Mathematical Modeling and Scale-Up of Liquid Chromatography (2nd Ed., 2nd ed. 2015)
With Application Examples

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Language: Anglais

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Mathematical Modeling and Scale-Up of Liquid Chromatography
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Mathematical Modeling and Scale-Up of Liquid Chromatography. With Application Examples (2nd Ed.)
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207 p. · 15.5x23.5 cm · Hardback
This new edition provides a comprehensive set of nonlinear multicomponent liquid chromatography (LC) models for various forms of LC, such as adsorption, size exclusion, ion-exchange, reversed-phase, affinity, isocratic/gradient elution and axial/radial flow LC. Much has advanced since the first edition of this book and the author's software, described here, is now used for teaching and research in 32 different countries. This book comes together with a complete software package with graphical user interface for personal computers, offered free for academic applications. Additionally, this book provides detailed methods for parameter estimation of mass transfer coefficients, bed voidage, particle porosity and isotherms. The author gives examples of how to use the software for predicitons and scale-up. In contrast to the first edition, authors do not need to deal with complicated math. Instead, they focus on how to obtain a few parameters for simulation and how to compare simulation results with experimental data. After reading the detailed descriptions in the book, a reader is able to use the simulation software to investigate chromatographic behavior without doing actual experiments. This book is aimed at readers who are interested in learning about LC behaviors and at those who want to scale up LC for preparative- and large-scale applications. Both academic personnel and industrial practitioners can benefit from the use of the book. This new edition includes:
- New models and software for pellicular (cored) beads in liquid chromatography
- Introduction of user-friendly software (with graphical user interface)
- Detailed descriptions on how to use the software
- Step-by-step instructions on parameter estimation for the models
- New mass-transfer correlations for parameter estimation
- Experimental methods for parameter estimation
- Several actual examples using the model for product development and scale-up
- Updated literature review
Introduction. Literature Review. General Multicomponent Rate Models for Column Liquid Chromatography. Numerical Solutions and Computer Software with Graphical User Interface. Mass Transfer Effects. Interference Effects in Multicomponent Chromatography. System Peaks In Multicomponent Elution. Multicomponent Adsorption with Uneven Saturation Capacities. Modeling of Size Exclusion Chromatography. Modeling of Ion-Exchange Chromatography with Steric Mass-Action Isotherm. Modeling of Chromatography with Cored Beads – Advantages and Limitations. Modeling of Affinity Chromatography. Modeling of Multicomponent Gradient Elution. Multicomponent Radial Flow Chromatography. Parameter Estimation and Parameter Sensitivity Analysis. Scale-Up Methods and Examples.

Dr. Tingyue Gu is a professor in the Department of Chemical & Biomolecular Engineering at Ohio University. He obtained his PhD degree in chemical engineering from Purdue University in 1990. His PhD work was devoted to liquid chromatography (LC) theories and modeling. Dr. Gu has solved a series of LC models numerically for various forms of LC and developed a comprehensive software package with graphical user interface. His software has been used in over 34 countries by numerous people. The software is offered for free for academic applications. It has also been commercially licensed by major companies including leading biotech and pharmaceutical companies. The software has been successfully used for product development with huge savings in time through simulation. Apart from LC, his current research also encompasses bioenergy, biofilm electrochemistry, biocorrosion, and microbial fuel cells.

Introduces user-friendly software (with graphical user interface) and detailed descriptions on how to use the software

Outlines step-by-step instructions on parameter estimation for the models

Includes an updated literature review