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Microelectrofluidic Systems: Modeling and Simulation by Tainhao Zhang β€” book cover

Microelectrofluidic Systems: Modeling and Simulation

by Tainhao Zhang, Richard B. Fair, Krishnendu Chakrabarty, Sergey Edward Lyshevsky
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Overview

Composite systems that integrate microelectromechanical and microelectrofluidic (MEF) components with electronics are emerging as the next generation of system-on-a-chip (SOC) designs. However, there remains a pressing need for a structured methodology for MEFS design automation, including modeling techniques and simulation and optimization tools.

Integrating top-down and bottom-up design philosophies, Microelectrofluidic Systems presents the first comprehensive design strategy for MEFS. This strategy supports hierarchical modeling and simulation from the component level to the system level. It leads to multi-objective optimization tools valuable in all phases of the design process, from conceptualization to final manufacturing. The authors begin by defining the basic variables and elements needed to describe MEFS behavior, then model that behavior across three layers of abstraction: the low-level component, high-level reconfigurable architecture, and bio/chemical application layers. They have developed a hierarchical integrated design environment with SystemC and present its architecture and associated functional packages.

Microelectrofluidic Systems is visionary in its leverage of electronic design principles for microsystem design and heralds a new era of automated SOC design. The strategy it presents holds the potential for significant reductions in design time and life-cycle maintenance costs, and its techniques and tools for robust design and application flexibility can lead to the high-volume production needed for the inevitably growing product market.

Composite systems that integrate microelectromechanical and microelectrofluidic (MEF) components with electronics are emerging as the next generation of system-on-a-chip (SOC) designs. However, there remains a pressing need for a structured methodology for MEFS design automation, including modeling techniques and simulation and optimization tools.Integrating top-down and bottom-up design philosophies, Microelectrofluidic Systems presents the first comprehensive design strategy for MEFS. This strategy supports hierarchical modeling and simulation from the component level to the system level. It leads to multi-objective optimization tools valuable in all phases of the design process, from conceptualization to final manufacturing. The authors begin by defining the basic variables and elements needed to describe MEFS behavior, then model that behavior across three layers of abstraction: the low-level component, high-level reconfigurable architecture, and bio/chemical application layers. They have developed a hierarchical integrated design environment with SystemC and present its architecture and associated functional packages.Microelectrofluidic Systems is visionary in its leverage of electronic design principles for microsystem design and heralds a new era of automated SOC design. The strategy it presents holds the potential for significant reductions in design time and life-cycle maintenance costs, and its techniques and tools for robust design and application flexibility can lead to the high-volume production needed for the inevitably growing product market.

Synopsis

Composite systems that integrate microelectromechanical and microelectrofluidic (MEF) components with electronics are emerging as the next generation of system-on-a-chip (SOC) designs. However, there remains a pressing need for a structured methodology for MEFS design automation, including modeling techniques and simulation and optimization tools.

Integrating top-down and bottom-up design philosophies, Microelectrofluidic Systems presents the first comprehensive design strategy for MEFS. This strategy supports hierarchical modeling and simulation from the component level to the system level. It leads to multi-objective optimization tools valuable in all phases of the design process, from conceptualization to final manufacturing. The authors begin by defining the basic variables and elements needed to describe MEFS behavior, then model that behavior across three layers of abstraction: the low-level component, high-level reconfigurable architecture, and bio/chemical application layers. They have developed a hierarchical integrated design environment with SystemC and present its architecture and associated functional packages.

Microelectrofluidic Systems is visionary in its leverage of electronic design principles for microsystem design and heralds a new era of automated SOC design. The strategy it presents holds the potential for significant reductions in design time and life-cycle maintenance costs, and its techniques and tools for robust design and application flexibility can lead to the high-volume production needed for the inevitably growing product market.

Booknews

Based on a research project at Duke University, this monograph presents an integrated approach to the hierarchical modeling, simulation, and design of microelectrofluidic systems (MEFS) used for automated drug dispensing and microchemical analysis. The simulation methodology combines a high-level stochastic queuing network approach with low-level nodal conservative differential equations. The design optimization algorithms utilize the Taguchi robust design method and the statistical response analysis method. The final chapter compares the performance of continuous-flow systems and droplet-based systems for performing polymerase chain reactions. Annotation c. Book News, Inc., Portland, OR (booknews.com)

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From The Critics

Based on a research project at Duke University, this monograph presents an integrated approach to the hierarchical modeling, simulation, and design of microelectrofluidic systems (MEFS) used for automated drug dispensing and microchemical analysis. The simulation methodology combines a high-level stochastic queuing network approach with low-level nodal conservative differential equations. The design optimization algorithms utilize the Taguchi robust design method and the statistical response analysis method. The final chapter compares the performance of continuous-flow systems and droplet-based systems for performing polymerase chain reactions. Annotation c. Book News, Inc., Portland, OR (booknews.com)

Book Details

Published
May 1, 2002
Publisher
CRC Press
Pages
288
Format
Hardcover
ISBN
9780849312762

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