While droplet-based microfluidics is a powerful technique with transformative applications, most devices are passively operated and thus have limited real-time control over droplet contents. In this report, an automated droplet-based microfluidic device with pneumatic pumps and salt water electrodes was developed to generate and coalesce up to six aqueous-in-oil droplets (2.77 nL each). Custom control software combined six droplets drawn from any of four inlet reservoirs. Using our μChopper method for lock-in fluorescence detection, we first accomplished continuous linear calibration and quantified an unknown sample. Analyte-independent signal drifts and even an abrupt decrease in excitation light intensity were corrected in real-time. The system was then validated with homogeneous insulin immunoassays that showed a nonlinear response. On-chip droplet merging with antibody-oligonucleotide (Ab-oligo) probes, insulin standards, and buffer permitted the real-time calibration and correction of large signal drifts. Full calibrations (LOD_conc = 2 ng mL⁻¹ = 300 pM; LOD_amt = 5 amol) required <1 min with merely 13.85 nL of Ab-oligo reagents, giving cost-savings 160-fold over the standard well-plate format while also automating the workflow. This proof-of-concept device—effectively a microfluidic digital-to-analog converter—is readily scalable to more droplets, and it is well-suited for the real-time automation of bioassays that call for expensive reagents.

中文翻译：

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具有片上液滴合并功能的可编程µChopper设备，用于连续测定校准。

尽管基于液滴的微流体技术在转化应用中是一项强大的技术，但是大多数设备都是被动运行的，因此对液滴含量的实时控制有限。在本报告中，开发了一种具有气动泵和盐水电极的基于液滴的自动微流控设备，以产生和凝聚多达六个油包水液滴（每个为2.77 nL）。定制控制软件结合了从四个入口容器中抽取的六个液滴。使用我们的μChopper方法进行锁定荧光检测，我们首先完成了连续线性校准并量化了未知样品。实时校正与分析物无关的信号漂移，甚至激发光强度的突然下降。然后用显示出非线性响应的均相胰岛素免疫分析验证该系统。芯片上的液滴与抗体-寡核苷酸（Ab-oligo）探针，胰岛素标准品和缓冲液合并，可以实时校准和校正大信号漂移。全面校准（LOD_浓度= 2 ng mL ^-1 = 300 pM; LOD _amt = 5 amol）仅需13.5 nL Ab-oligo试剂即可在1分钟内完成，与标准孔板相比可节省160倍的成本，同时还可以实现工作流程的自动化。这种概念验证装置-有效地是微流体数模转换器-可以轻松扩展到更多液滴，并且非常适合需要昂贵试剂的生物测定的实时自动化。