论文标题
跳过边界层：使用雷利声流的高速基于液滴的免疫测定
Skipping the boundary layer: high-speed droplet-based immunoassay using Rayleigh acoustic streaming
论文作者
论文摘要
液滴的声学混合是实现结合高速和最少试剂消耗的生物传感器的一种有希望的方法。迄今为止，这种类型的液滴混合是由大部分流体中高频声波吸收引起的体积力驱动的。在这里，我们表明这些传感器的速度受到分析物对传感器表面的缓慢对流的限制，这是由于水动力边界层的形成。我们通过使用较低的超声频率激发液滴来消除这种流体动力边界层，从而驱动雷利流媒体的行为基本上像滑动速度一样。三维模拟表明，与ECKART流相比，这提供了三倍的速度。在实验上，我们将SARS-COV-2抗体免疫测定从20分钟缩短到40 s。
Acoustic mixing of droplets is a promising way to implement biosensors that combine high speed and minimal reagent consumption. To date, this type of droplet mixing is driven by a volume force resulting from the absorption of high-frequency acoustic waves in the bulk of the fluid. Here, we show that the speed of these sensors is limited by the slow advection of analyte to the sensor surface due to the formation of a hydrodynamic boundary layer. We eliminate this hydrodynamic boundary layer by using much lower ultrasonic frequencies to excite the droplet, which drives a Rayleigh streaming that behaves essentially like a slip velocity. Three-dimensional simulations show that this provides a threefold speedup compared to Eckart streaming. Experimentally, we shorten a SARS-CoV-2 antibody immunoassay from 20 min to 40 s.
