BioScript: programming safe chemistry on laboratories-on-a-chip

This paper introduces BioScript, a domain-specific language (DSL) for programmable biochemistry which executes on emerging microfluidic platforms. The goal of this research is to provide a simple, intuitive, and type-safe DSL that is accessible to life science practitioners. The novel feature of the language is its syntax, which aims to optimize human readability; the technical contributions of the paper include the BioScript type system and relevant portions of its compiler. The type system ensures that certain types of errors, specific to biochemistry, do not occur, including the interaction of chemicals that may be unsafe. The compiler includes novel optimizations that place biochemical operations to execute concurrently on a spatial 2D array platform on the granularity of a control flow graph, as opposed to individual basic blocks. Results are obtained using both a cycle-accurate microfluidic simulator and a software interface to a real-world platform

Strategic Optimization Techniques For FRTU Deployment and Chip Physical Design

Combinatorial optimization is a complex engineering subject. Although formulation often depends on the nature of problems that differs from their setup, design, constraints, and implications, establishing a unifying framework is essential. This dissertation investigates the unique features of three important optimization problems that can span from small-scale design automation to large-scale power system planning: (1) Feeder remote terminal unit (FRTU) planning strategy by considering the cybersecurity of secondary distribution network in electrical distribution grid, (2) physical-level synthesis for microfluidic lab-on-a-chip, and (3) discrete gate sizing in very-large-scale integration (VLSI) circuit. First, an optimization technique by cross entropy is proposed to handle FRTU deployment in primary network considering cybersecurity of secondary distribution network. While it is constrained by monetary budget on the number of deployed FRTUs, the proposed algorithm identi?es pivotal locations of a distribution feeder to install the FRTUs in different time horizons. Then, multi-scale optimization techniques are proposed for digital micro?uidic lab-on-a-chip physical level synthesis. The proposed techniques handle the variation-aware lab-on-a-chip placement and routing co-design while satisfying all constraints, and considering contamination and defect. Last, the first fully polynomial time approximation scheme (FPTAS) is proposed for the delay driven discrete gate sizing problem, which explores the theoretical view since the existing works are heuristics with no performance guarantee. The intellectual contribution of the proposed methods establishes a novel paradigm bridging the gaps between professional communities

A Framework for Automated Correctness Checking of Biochemical Protocol Realizations on Digital Microfluidic Biochips

Recent advances in digital microfluidic (DMF) technologies offer a promising platform for a wide variety of biochemical applications, such as DNA analysis, automated drug discovery, and toxicity monitoring. For on-chip implementation of complex bioassays, automated synthesis tools have been developed to meet the design challenges. Currently, the synthesis tools pass through a number of complex design steps to realize a given biochemical protocol on a target DMF architecture. Thus, design errors can arise during the synthesis steps. Before deploying a DMF biochip on a safety critical system, it is necessary to ensure that the desired biochemical protocol has been correctly implemented, i.e., the synthesized output (actuation sequences for the biochip) is free from any design or realization errors. We propose a symbolic constraint-based analysis framework for checking the correctness of a synthesized biochemical protocol with respect to the original design specification. The verification scheme based on this framework can detect several post-synthesis fluidic violations and realization errors in 2D-array based or pin-constrained biochips as well as in cyberphysical systems. It further generates diagnostic feedback for error localization. We present experimental results on the polymerase chain reaction (PCR) and in-vitro multiplexed bioassays to demonstrate the proposed verification approach

Microfluidic very large-scale integration for biochips: Technology, testing and fault-tolerant design

Microfluidic biochips are replacing the conventional biochemical analyzers by integrating all the necessary functions for biochemical analysis using microfluidics. Biochips are used in many application areas, such as, in vitro diagnostics, drug discovery, biotech and ecology. The focus of this paper is on continuous-flow biochips, where the basic building block is a microvalve. By combining these microvalves, more complex units such as mixers, switches, multiplexers can be built, hence the name of the technology, “microfluidic Very Large-Scale Integration” (mVLSI). A roadblock in the deployment of microfluidic biochips is their low reliability and lack of test techniques to screen defective devices before they are used for biochemical analysis. Defective chips lead to repetition of experiments, which is undesirable due to high reagent cost and limited availability of samples. This paper presents the state-of-the-art in the mVLSI platforms and emerging research challenges in the area of continuous-flow microfluidics, focusing on testing techniques and fault-tolerant design

Placement and routing for cross-referencing digital microfluidic biochips.

Xiao, Zigang."October 2010."Thesis (M.Phil.)--Chinese University of Hong Kong, 2011.Includes bibliographical references (leaves 62-66).Abstracts in English and Chinese.Abstract --- p.iAcknowledgement --- p.viChapter 1 --- Introduction --- p.1Chapter 1.1 --- Microfluidic Technology --- p.2Chapter 1.1.1 --- Continuous Flow Microfluidic System --- p.2Chapter 1.1.2 --- Digital Microfluidic System --- p.2Chapter 1.2 --- Pin-Constrained Biochips --- p.4Chapter 1.2.1 --- Droplet-Trace-Based Array Partitioning Method --- p.5Chapter 1.2.2 --- Broadcast-addressing Method --- p.5Chapter 1.2.3 --- Cross-Referencing Method --- p.6Chapter 1.2.3.1 --- Electrode Interference in Cross-Referencing Biochips --- p.7Chapter 1.3 --- Computer-Aided Design Techniques for Biochip --- p.8Chapter 1.4 --- Placement Problem in Biochips --- p.8Chapter 1.5 --- Droplet Routing Problem in Cross-Referencing Biochips --- p.11Chapter 1.6 --- Our Contributions --- p.14Chapter 1.7 --- Thesis Organization --- p.15Chapter 2 --- Literature Review --- p.16Chapter 2.1 --- Introduction --- p.16Chapter 2.2 --- Previous Works on Placement --- p.17Chapter 2.2.1 --- Basic Simulated Annealing --- p.17Chapter 2.2.2 --- Unified Synthesis Approach --- p.18Chapter 2.2.3 --- Droplet-Routing-Aware Unified Synthesis Approach --- p.19Chapter 2.2.4 --- Simulated Annealing Using T-tree Representation --- p.20Chapter 2.3 --- Previous Works on Routing --- p.21Chapter 2.3.1 --- Direct-Addressing Droplet Routing --- p.22Chapter 2.3.1.1 --- A* Search Method --- p.22Chapter 2.3.1.2 --- Open Shortest Path First Method --- p.23Chapter 2.3.1.3 --- A Two Phase Algorithm --- p.24Chapter 2.3.1.4 --- Network-Flow Based Method --- p.25Chapter 2.3.1.5 --- Bypassibility and Concession Method --- p.26Chapter 2.3.2 --- Cross-Referencing Droplet Routing --- p.28Chapter 2.3.2.1 --- Graph Coloring Method --- p.28Chapter 2.3.2.2 --- Clique Partitioning Method --- p.30Chapter 2.3.2.3 --- Progressive-ILP Method --- p.31Chapter 2.4 --- Conclusion --- p.32Chapter 3 --- CrossRouter for Cross-Referencing Biochip --- p.33Chapter 3.1 --- Introduction --- p.33Chapter 3.2 --- Problem Formulation --- p.34Chapter 3.3 --- Overview of Our Method --- p.35Chapter 3.4 --- Net Order Computation --- p.35Chapter 3.5 --- Propagation Stage --- p.36Chapter 3.5.1 --- Fluidic Constraint Check --- p.38Chapter 3.5.2 --- Electrode Constraint Check --- p.38Chapter 3.5.3 --- Handling 3-pin net --- p.44Chapter 3.5.4 --- Waste Reservoir --- p.45Chapter 3.6 --- Backtracking Stage --- p.45Chapter 3.7 --- Rip-up and Re-route Nets --- p.45Chapter 3.8 --- Experimental Results --- p.46Chapter 3.9 --- Conclusion --- p.47Chapter 4 --- Placement in Cross-Referencing Biochip --- p.49Chapter 4.1 --- Introduction --- p.49Chapter 4.2 --- Problem Formulation --- p.50Chapter 4.3 --- Overview of the method --- p.50Chapter 4.4 --- Dispenser and Reservoir Location Generation --- p.51Chapter 4.5 --- Solving Placement Problem Using ILP --- p.51Chapter 4.5.1 --- Constraints --- p.53Chapter 4.5.1.1 --- Validity of modules --- p.53Chapter 4.5.1.2 --- Non-overlapping and separation of Modules --- p.53Chapter 4.5.1.3 --- Droplet-Routing length constraint --- p.54Chapter 4.5.1.4 --- Optical detector resource constraint --- p.55Chapter 4.5.2 --- Objective --- p.55Chapter 4.5.3 --- Problem Partition --- p.56Chapter 4.6 --- Pin Assignment --- p.56Chapter 4.7 --- Experimental Results --- p.57Chapter 4.8 --- Conclusion --- p.59Chapter 5 --- Conclusion --- p.60Bibliography --- p.6