Campbell Kyle, Groisman Alex
Department of Physics, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA.
Lab Chip. 2007 Feb;7(2):264-72. doi: 10.1039/b610011b. Epub 2006 Nov 27.
We describe the principles of design and the architecture of planar microfluidic networks producing concentration gradients with the shape of any given monotonic function. Each microfluidic network is fed by two separate source solutions and delivers to its outlet a set of N solutions that all differ in concentration. Inside the network, the source solutions flow through a series of k = log(2)(N-1) stages, where they are repeatedly split and mixed. Streams of the solutions emerging from the network are combined to create a single stream with the desired shape of the concentration profile across the direction of flow. To demonstrate the functionality of the proposed architecture, we have built and tested three networks with k = 4 and N = 17 that generate an exponential concentration profile, a linear profile, and a profile with a shape of two fused branches of a parabola.
我们描述了平面微流体网络的设计原理和架构,该网络可产生具有任何给定单调函数形状的浓度梯度。每个微流体网络由两种单独的源溶液供料,并向其出口输送一组浓度各不相同的N种溶液。在网络内部,源溶液流经一系列k = log(2)(N - 1)个阶段,在这些阶段中它们被反复分流和混合。从网络中流出的溶液流被合并,以创建一个具有沿流动方向所需浓度分布形状的单一流。为了证明所提出架构的功能,我们构建并测试了三个k = 4且N = 17的网络,它们分别产生指数浓度分布、线性分布以及具有抛物线两个融合分支形状的分布。