Design Automation Methods And Tools for Microfluidics-based Biochips

by Chakrabarty, Krishnendu; Zeng, Jun

• ISBN13: 9781402051227
• ISBN10: 1402051220
• Format: Hardcover
• Copyright: 2006-09-15
• Publisher: Springer Verlag

Summary

Microfluidics-based biochips, also known as lab-on-a-chip or bio-MEMS, are becoming increasingly popular for DNA analysis, clinical diagnostics, and the detection/manipulation of bio-molecules. These systems automate highly repetitive laboratory tasks by replacing cumbersome equipment with miniaturized and integrated systems, and they enable the handling of small amounts, e.g., nanoliters, of fluids. Thus they are able to provide ultra-sensitive detection at significantly lower costs per assay than traditional methods. As the use of microfluidics-based biochips increases, their complexity is expected to become significant due to the need for multiple and concurrent assays on the chip, as well as more sophisticated control mechanisms for resource management. Time-to-market and fault tolerance are also expected to emerge as design considerations. As a result, current full-custom design techniques will not scale well for larger designs. There is a need to deliver the same level of CAD support to the biochip designer that the semiconductor industry now takes for granted. Design Automation Methods and Tools for Microfluidics-Based Biochips deals with all aspects of design automation for microfluidics-based biochips. Experts have contributed chapters on various aspects of biochip design automation. Topics that are covered include device modeling; adaptation of bioassays for on-chip implementations; numerical methods and simulation tools; architectural synthesis, scheduling and binding of assay operations; physical design and module placement; fault modeling and testing; reconfiguration methods.

Table of Contents

Preface	vii
1. Microfluidics-based Biochips: Technology Issues, Implementation Platforms, and Design Automation Challenges
F. Su, K. Chakrabarty and R.B. Fair	1	(30)
2. Modeling and Simulation of Electrified Droplets and Its Application to Computer-Aided Design of Digital Microfluidics
Jun Zeng	31	(22)
3. Modelling, Simulation and Optimization of Electrowetting
Jan Lienemann, Andreas Greiner, and Jan G. Korvink	53	(32)
4. Algorithms in FastStokes and its Application to Micromachined Device Simulation
Xin Wang, Joe Kanapka, Wenjing Ye, Narayan Aluru Jacob White	85	(24)
5. Composable Behavioral Models and Schematic-Based Simulation of Electrokinetic Lab-on-a-Chip Systems
Yi Wang, Qiao Lin, Tamal Mukherjee	109	(34)
6. FFTSVD: A Fast Multiscale Boundary Element Method Solver Suitable for Bio-MEMS and Biomolecule Simulation
Michael D. Altman, Jaydeep P. Bardhan, Bruce Tidor, Jacob K. White	143	(26)
7. Macromodel Generation for BioMEMS Components Using a Stabilized Balanced Truncation Plus Trajectory Piecewise Linear Approach
Dmitry Vasilyev, Michal Rewienski, Jacob White	169	(20)
8. System-level Simulation of Flow Induced Dispersion in Lab-on-a-chip Systems
A.S. Bedekar, Y. Wang, S. Krishnamoorthy, S.S. Siddhaye, and S. Sundaram	189	(26)
9. Microfluidic Injector Models Based On Artificial Neural Networks
R. Magargle, J.F. Hoburg, T. Mukherjee	215	(20)
10. Computer-Aided Optimization of DNA Array Design and Manufacturing
A.B. Kahng, LL Mandoiu, S. Reda, X Xu, and A.Z. Zelikovsky	235	(36)
11. Synthesis of Multiplexed Biofluidic Microchips
Anton J. Pfeiffer, Tamal Mukherjee, and Steinar Hauan	271	(30)
12. Modeling and Controlling Parallel Tasks in Droplet-Based Microfluidic Systems
Karl F. Böhringer	301	(28)
13. Performance Characterization of a Reconfigurable Planar Array Digital Microfluidic System
Eric J. Griffith, Srinivas Akella, Mark Goldberg	329	(28)
14. A Pattern Mining Method for High-throughput Lab-on-a-chip Data Analysis
Sungroh Yoon, Luca Benini, Giovanni De Michell	357	(44)
Index	401