Get Microelectrofluidic Systems: Modeling and Simulation PDF

By Tianhao Zhang

Composite structures that combine microelectromechanical and microelectrofluidic (MEF) elements with electronics are rising because the subsequent iteration of system-on-a-chip (SOC) designs. despite the fact that, there continues to be a urgent desire for a dependent technique for MEFS layout automation, together with modeling concepts and simulation and optimization tools.Integrating top-down and bottom-up layout philosophies, Microelectrofluidic structures offers the 1st accomplished layout procedure for MEFS. This procedure helps hierarchical modeling and simulation from the part point to the approach point. It results in multi-objective optimization instruments important in all levels of the layout strategy, from conceptualization to ultimate production. The authors commence via defining the elemental variables and components had to describe MEFS habit, then version that habit throughout 3 layers of abstraction: the low-level part, high-level reconfigurable structure, and bio/chemical program layers. they've got constructed a hierarchical built-in layout surroundings with SystemC and current its structure and linked practical packages.Microelectrofluidic platforms is visionary in its leverage of digital layout rules for microsystem layout and heralds a brand new period of automatic SOC layout. the method it provides holds the potential of major rate reductions in layout time and life-cycle upkeep expenditures, and its concepts and instruments for strong layout and alertness flexibility may end up in the high-volume creation wanted for the unavoidably transforming into product industry.

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Extra info for Microelectrofluidic Systems: Modeling and Simulation

Sample text

These factors are necessary to describe the system-level bio/chemical application behavior and MEFS architecture. They are also critical parts of a MEFS modeling and simulation language. 1, which consists of multiple system description perspectives, objectoriented and dynamic data structures, and the system specification capacity. 2, factors reflecting the system-level simulation are presented. They include the time-advanced mechanism [43] which is useful for keeping track of the simulated time, and system design scalability.

Is the output vector, is the output matrix, and is the direct transmission matrix. The system dynamical modeling using bond graphs typically generates state-space equilibrium equations. Kirchhoffian network theory is not the only approach to formulating a set of equilibrium equations. For instance, Hamilton’s principle using energy and coenergy form the basis for an alternate formulation, called Lagrangian equations.

1 Computational Architectures for MEFS The limitation of present designs is that devices tend to be application/analysis specific. There is no one system capable of performing a collection of differing analyses or procedures. In addition, in a number of systems, only the analysis device is microfluidic in nature. The remaining pre-/postprocessing is performed by normal macroscopic, possibly automated, methods. It is easy to recognize the potential of a universal architecture, one in which multiple, differing procedures may be performed with simple reconfiguration, and possibly in parallel.

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