Fast online synthesis of generally programmable digital microfluidic biochips

Abstract

We introduce an online synthesis flow for digital microfluidic biochips, which will enable real-time response to errors and control flow. The objective of this flow is to facilitate fast assay synthesis while minimally compromising the quality of results. In particular, we show that a virtual topology, which constrains the allowable locations of assay operations such as mixing, dilution, sensing, etc., in lieu of traditional placement, can significantly speed up the synthesis process without significantly lengthening assay execution time.

A Low-Cost Field-Programmable Pin-Constrained Digital Microfluidic Biochip

“…The FPPC-DMFB contains a vertical column of mixing modules on the left (blue/orange electrodes, Pins [10][11][12][13][14][15][16][17][18][19][20] and a vertical column of modules on the right (orange electrodes, Pins 31-36) that perform splitting, storage, and detection (which requires an external detector affixed above the module); we call these modules SSD modules.…”

A digital microfluidic biochip synthesis framework

“…Placement determines the specific location on the DMFB where each assay operation will start, at the times computed by the scheduler [6][15] [16]. The placer annotates each node in the DAG with the location of the module, and outputs a .dot file, as shown in Fig.…”

“…The light red cells depict the interference region (IR) [6][15] [17] of the mixing operations. Any droplet that inadvertently enters the interference region of an operation will mix with the droplet(s) engaged in the operation, which could result in contamination.…”

“…The framework has also been used to produce new research results, including two new scheduling algorithms [7][10] and a fast online DMFB synthesis flow that is intended for dynamic interpretation, rather than static compilation [6].…”

“…Assays are specified as directed acyclic graphs (DAGs). Synthesis involves three steps: scheduling the operations [7][9] [10][12] [14], placing modules onto the device [6][15] [16], and routing droplets [13] [19]; algorithms that perform multiple steps at once, to synergize cross-boundary optimization, have also been proposed [16].…”