Facile and Low-Waste Self-Digitization of Samples by Oil-Triggered, Template-Confined Dewetting on a Networked Microwell Array

semanticscholar(2022)

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摘要
In this work, we present a simple, straightforward, and robust method for spontaneously digitizing samples into an array of dis-crete volumes. The method is based on an oil-triggered, template-confined dewetting phenomenon. To realize the dewetting-induced sample digitization, an aqueous sample is firstly infused into a networked microwell array (NMA) through a predegassing-based self-pumping mechanism, and then an immiscible oil phase is applied over the surface of NMA chip to induce the templated dewetting. Due to a periodic interfacial tension heterogeneity, such dewetting ruptures the sample at the thinnest parts (i.e., con-nection channels) and spontaneously splits the sample into droplets in individual microwells. Without requiring any complex pump-ing or valving systems, this method can discretize a sample into tens of thousands of addressable droplets in a matter of minutes with nearly 98% usage. To demonstrate the utility and universality of this self-digitization method, we exploited it to discretize samples into 40,233 wells for digital PCR assay, digital quantification of bacteria, and self-assembly of spherical colloidal photonic crystals. We believe this facile technique will be useful in a broad range of applications where partitioning of samples into a large number of small individual volumes is required.
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