1. Synthesis of Reliable Digital Microfluidic Biochips using Monte Carlo Simulation Elena Maftei, Paul Pop, Florin Popenţiu Vlădicescu Technical University of Denmark

2. 2 Background & Motivation Test tubes Robotics Microfluidics Automation Integration Miniaturization Automation Integration Miniaturization Automation Integration Miniaturization Slide soruce: Krish Chakrabarty, Duke University

3. 3 Microfluidics (University of Michigan) 1998 (Duke University) 2002 Slide soruce: Krish Chakrabarty, Duke University Continuous-flow biochips Droplet-based biochips

4. 4 Biochip Architecture

5. 5 Electrowetting on Dielectric

6. 6 Synthesis: Main Design Tasks Scheduling Binding Placement Allocation

7. 7 Fault Model  Types of faults:  Permanent  Parametric  Causes:  Particle contamination  Excessive voltage  Coating failure  Assumption:  Same probability for all cells

8. 8 Fault Tolerance

9. 9 Design Automation  ILP-based syntehsis  Constraints:  Scheduling and precedence  Resource  Placement  Optimization objective:  Minimize the completion time of the application  Evaluation of a design alternative using MCS  Generate a set of faulty cells  Try to reconfigure the biochip such that the execution time remains the same as for the case with no faults  Reconfiguration done using ILP-based synthesis

10. 10 Experimental Evaluation  Real-life application  Mixing stage of polymerase chain reaction (PCR) ‏  Assay completion time: 13 s  Experimental setup  ILP: GAMS 21.5, CPLEX 9.130  SunFire v440 4, UltraSPARC IIIi CPUs, 1,062 MHz and 8 GB RAM  MCS: 5,000 runs with a cell failure probability of 0.999

11. 11 Contributions and Message  Contributions  ILP-based synthesis of digital microfluidic biochips  Considered permanent cell faults  Message  Labs-on-a-chip can be implemented with digital microfluidics  CAD tools are essential for the design of such biochips