Hybrid Digital-Droplet Microfluidic Chip for Applications in Droplet Digital Nucleic Acid Amplification: Design, Fabrication and Characterization.

Microfluidic-based platforms have become a hallmark for chemical and biological assays, empowering micro- and nano-reaction vessels. The fusion of microfluidic technologies (digital microfluidics, continuous-flow microfluidics, and droplet microfluidics, just to name a few) presents great potential for overcoming the inherent limitations of each approach, while also elevating their respective strengths. This work exploits the combination of digital microfluidics (DMF) and droplet microfluidics (DrMF) on a single substrate, where DMF enables droplet mixing and further acts as a controlled liquid supplier for a high-throughput nano-liter droplet generator. Droplet generation is performed at a flow-focusing region, operating on dual pressure: negative pressure applied to the aqueous phase and positive pressure applied to the oil phase. We evaluate the droplets produced with our hybrid DMF-DrMF devices in terms of droplet volume, speed, and production frequency and further compare them with standalone DrMF devices. Both types of devices enable customizable droplet production (various volumes and circulation speeds), yet hybrid DMF-DrMF devices yield more controlled droplet production while achieving throughputs that are similar to standalone DrMF devices. These hybrid devices enable the production of up to four droplets per second, which reach a maximum circulation speed close to 1540 µm/s and volumes as low as 0.5 nL.

Open-source tool for real-time and automated analysis of droplet-based microfluidic.

Droplet-based microfluidic technology is a powerful tool for generating large numbers of monodispersed nanoliter-sized droplets for ultra-high throughput screening of molecules or single cells. Yet further progress in the development of methods for the real-time detection and measurement of passing droplets is needed for achieving fully automated systems and ultimately scalability. Existing droplet monitoring technologies are either difficult to implement by non-experts or require complex experimentation setups. Moreover, commercially available monitoring equipment is expensive and therefore limited to a few laboratories worldwide. In this work, we validated for the first time an easy-to-use, open-source Bonsai visual programming language to accurately measure in real-time droplets generated in a microfluidic device. With this method, droplets are found and characterized from bright-field images with high processing speed. We used off-the-shelf components to achieve an optical system that allows sensitive image-based, label-free, and cost-effective monitoring. As a test of its use we present the results, in terms of droplet radius, circulation speed and production frequency, of our method and compared its performance with that of the widely-used ImageJ software. Moreover, we show that similar results are obtained regardless of the degree of expertise. Finally, our goal is to provide a robust, simple to integrate, and user-friendly tool for monitoring droplets, capable of helping researchers to get started in the laboratory immediately, even without programming experience, enabling analysis and reporting of droplet data in real-time and closed-loop experiments.