IEEE transactions on computer-aided design of integrated circuits and systems : a publication of the IEEE Circuits and Systems Society

Droplet-based microfluidics is a colloidal and interfacial system that has rapidly progressed in the past decade because of the advantages of low fabrication costs, small sample volumes, reduced analysis durations, high-throughput analysis with exceptional sensitivity, enhanced operational flexibility, and facile automation. This technology has emerged as a new tool for many recently used applications in molecular detection, imaging, drug delivery, diagnostics, cell biology and other fields. Herein, we review recent applications of droplet microfluidics proposed since 2013.

Recent Advances in Applications of Droplet Microfluidics

An open-source compiler and PCB synthesis tool for digital microfluidic biochips

Digital (droplet-based) microfluidic technology offers an attractive platform for implementing a wide variety of biochemical laboratory protocols, such as point-of-care diagnosis, DNA analysis, target detection, and drug discovery. A digital microfluidic biochip consists of a patterned array of electrodes on which tiny fluid droplets are manipulated by electrical actuation sequences to perform various fluidic operations, for example, dispense, transport, mix, or split. However, because of the inherent uncertainty of fluidic operations, the outcome of biochemical experiments performed on-chip can be erroneous even if the chip is tested a priori and deemed to be defect-free. In this article, we address an important error recoverability problem in the context of sample preparation. We assume a cyberphysical environment, in which the physical errors, when detected online at selected checkpoints with integrated sensors, can be corrected through recovery techniques. However, almost all prior work on error recoverability used checkpointing-based rollback approach, that is, re-execution of certain portions of the protocol starting from the previous checkpoint. Unfortunately, such techniques are expensive both in terms of assay completion time and reagent cost, and can never ensure full error-recovery in deterministic sense. We consider imprecise droplet mix-split operations and present a novel roll-forward approach where the erroneous droplets, thus produced, are used in the error-recovery process, instead of being discarded or remixed. All erroneous droplets participate in the dilution process and they mutually cancel or reduce the concentration-error when the target droplet is reached. We also present a rigorous analysis that reveals the role of volumetric-error on the concentration of a sample to be prepared, and we describe the layout of a lab-on-chip that can execute the proposed cyberphysical dilution algorithm. Our analysis reveals that fluidic errors caused by unbalanced droplet splitting can be classified as being either critical or non-critical, and only those of the former type require correction to achieve error-free sample dilution. Simulation experiments on various sample preparation test cases demonstrate the effectiveness of the proposed method.

Error-Correcting Sample Preparation with Cyberphysical Digital Microfluidic Lab-on-Chip

In many biochemical protocols, sample preparation is an extremely important step for mixing multiple reagents in a given ratio. Dilution of a biochemical sample/reagent is the special case of mixing or solution preparation where only two fluids (sample and buffer) are mixed at a certain ratio corresponding to the desired concentration factor. Many bioassays often require multiple concentration values of the same sample/reagent, and implementing them efficiently on a digital microfluidic biochip is a challenge. In this paper, we present an algorithmic solution for the problem of producing a set of different target droplets in a minimum number of mix-split steps, and satisfying a given upper bound in concentration error. Unlike prior methods, this approach does not require any intermediate storage. We represent the underlying search space using a binary de Brujin graph and show that a shortest mix-split sequence can be obtained by solving an asymmetric traveling salesman problem therein. Simulation results over a large data set reveal that the proposed technique outperforms existing methods in terms of the number of mix-split steps, waste droplets, and reactant usage. The method is applicable in general scenarios of either one mixer or more mixers on the chip. A digital microfluidic platform can be easily designed to implement such a technique for rapid on-chip sample preparation.

On-Chip Sample Preparation for Multiple Targets Using Digital Microfluidics

Sample preparation is one of essential processes in biochemical reactions. Raw reactants are diluted in this process to achieve given target concentrations. A bioassay may require several different target concentrations of a reactant. Both the dilution operation count and the reactant usage can be minimized if multiple target concentrations are considered simultaneously during sample preparation. Hence, in this paper, we propose a multitarget sample preparation algorithm that extensively exploits the ideas of waste recycling and intermediate droplet sharing to reduce both reactant usage and waste amount for digital microfluidic biochips. Experimental results show that our waste recycling algorithm can reduce the waste and operation count by 48% and 37%, respectively, as compared to an existing state-of-the-art multitarget sample preparation method if the number of target concentrations is ten. The reduction can be up to 97% and 73% when the number of target concentrations goes even higher.

Huei-Shan Lin

Papers

Reactant and Waste Minimization in Multitarget Sample Preparation on Digital Microfluidic Biochips