Automatic volume management for programmable microfluidics

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Automatic volume management for programmable microfluidics

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Conference on Programming Language Design and Implementation archive
Proceedings of the 2008 ACM SIGPLAN conference on Programming language design and implementation table of contents

Tucson, AZ, USA

SESSION: Session III table of contents

Pages 56-67

Year of Publication: 2008

ISBN:978-1-59593-860-2

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Authors

Ahmed M. Amin	Purdue University, W. Lafayette, IN, USA
Mithuna Thottethodi	Purdue University, W. Lafayette, IN, USA
T. N. Vijaykumar	Purdue University, W. Lafayette, IN, USA
Steven Wereley	Purdue University, W. Lafayette, IN, USA
Stephen C. Jacobson	Indiana University, Bloomington, IN, USA

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ACM: Association for Computing Machinery
SIGPLAN: ACM Special Interest Group on Programming Languages

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ACM New York, NY, USA

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ABSTRACT

Microfluidics has enabled lab-on-a-chip technology to miniaturize and integrate biological and chemical analyses to a single chip comprising channels, valves, mixers, heaters, separators, and sensors. Recent papers have proposed programmable labs-on-a-chip as an alternative to traditional application-specific chips to reduce design effort, time, and cost. While these previous papers provide the basic support for programmability, this paper identifies and addresses a practical issue, namely, fluid volume management. Volume management addresses the problem that the use of a fluid depletes it and unless the given volume of a fluid is distributed carefully among all its uses, execution may run out of the fluid before all its uses are complete. Additionally, fluid volumes should not overflow (i.e., exceed hardware capacity) or underflow (i.e., fall below hardware resolution). We show that the problem can be formulated as a linear programming problem (LP). Because LP's complexity and slow execution times in practice may be a concern, we propose another approach, called DAGSolve, which over-constrains the problem to achieve linear complexity while maintaining good solution quality. We also propose two optimizations, called cascading and static replication, to handle cases involving extreme mix ratios and numerous fluid uses which may defeat both LP and DAGSolve. Using some real-world assays, we show that our techniques produce good solutions while being faster than LP.

REFERENCES

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	1	MILP LP_Solve 5.5, http://sourceforge.net/project/showfiles.php?group_id=145213.
	2	Ahmed M. Amin , Mithuna Thottethodi , T. N. Vijaykumar , Steven Wereley , Stephen C. Jacobson, Aquacore: a programmable architecture for microfluidics, Proceedings of the 34th annual international symposium on Computer architecture, June 09-13, 2007, San Diego, California, USA
	3	R. Go' mez, R. Bashir, A. Sarikaya, M. Ladisch, J. Sturgis, J. Robinson, T. Geng, A. Bhunia, H. Apple, and S. Wereley. Microfluidic Biochip for Impedance Spectroscopy of Biological Species. Biomedical Microdevices, 3(3):201--209, 2001.
	4	C. C. Gonzaga, An algorithm for solving linear programming programs in O(n3L) operations, Progress in Mathematical Programming Interior-point and related methods, Springer-Verlag New York, Inc., New York, NY, 1988
	5	A. Hadd, D. Raymond, J. Halliwell, S. Jacobson, and J. Ramsey. Microchip Device for Performing Enzyme Assays. Analytical Chemistry, 69(17):3407--3412, 1997.
	6	Johan Janssen , Henk Corporaal, Partitioned register file for TTAs, Proceedings of the 28th annual international symposium on Microarchitecture, p.303-312, November 29-December 01, 1995, Ann Arbor, Michigan, United States
	7	Y. Mechref and M. Novotny. Structural Investigations of Glycoconjugates at High Sensitivity. Chemical Reviews, 102(2):321--370, 2002.
	8	N. Nguyen and S. Wereley. Fundamentals and Applications of Microfluidics. Artech House, 2002.
	9	V. Srinivasan, V. Pamula, M. Pollack, and R. Fair. A digital microfluidic biosensor for multianalyte detection. In Proceedings of the 16th Annual IEEE International Conference on Micro Electro Mechanical Systems, pages 327--330, 2003.
	10	William Thies , John Paul Urbanski , Todd Thorsen , Saman Amarasinghe, Abstraction layers for scalable microfluidic biocomputing, Natural Computing: an international journal, v.7 n.2, p.255-275, June 2008 [doi>10.1007/s11047-006-9032-6]
	11	F. Tip. A survey of program slicing techniques. Journal of programming languages, 3:121--189, 1995.
	12	M. A. Unger, H.-P. Chou, T. Thorsen, A. Scherer, and S. R. Quake. Monolithic Microfabricated Valves and Pumps by Multilayer Soft Lithography. Science, 288(5463):113--116, 2000.
	13	J. P. Urbanski, W. Thies, C. Rhodes, S. Amarasinghe, and T. Thorsen. Digital microfluidics using soft lithography. Lab on a Chip, 6(1):96--104, Jan 2006.
	14	Y. Zhang. Solving largescale linear programs by interiorpoint methods under the MATLAB environment. Technical Report 9601, Baltimore, MD 21228--5398, USA, 1996.