Lee Kangsun, Kim Choong, Oh Kwang W
SMALL (Sensors and MicroActuators Learning Lab), Department of Electrical Engineering, The State University of New York at Buffalo, Buffalo, NY 14260, USA.
Sensor Solution Laboratory, LG Electronics, LG Science Park, Seoul 07796, Korea.
Micromachines (Basel). 2018 Sep 25;9(10):489. doi: 10.3390/mi9100489.
In this paper, we presented a straightforward strategy to generate 15 combinations of three samples based on an experimental simplex lattice design using a single-layer microfluidic network. First, we investigated the performances of the plain structural and the groove structural combinatorial devices by computational simulation (CFD-ACE+). The simulated output concentrations were extremely close to the desirable values within an absolute error of less than 1%. Based on the simulated designs, polydimethylsiloxane (PDMS) devices were fabricated with soft lithography and tested with fluorescent dye (sodium salt). The mixing results for 15 combinations showed good performance, with an absolute error of less than 4%. We also investigated two liquid handling methods (bottom⁻up and top⁻down) for high-throughput screening and assay. The liquid-handling methods were successfully accomplished by adding the systematic structured groove sets on the mixing channels.
在本文中，我们提出了一种简单的策略，基于使用单层微流体网络的实验单纯形格子设计来生成三个样本的15种组合。首先，我们通过计算模拟（CFD-ACE+）研究了普通结构和凹槽结构组合装置的性能。模拟输出浓度与理想值极为接近，绝对误差小于1%。基于模拟设计，采用软光刻技术制造了聚二甲基硅氧烷（PDMS）装置，并用荧光染料（钠盐）进行了测试。15种组合的混合结果显示出良好的性能，绝对误差小于4%。我们还研究了用于高通量筛选和测定的两种液体处理方法（自下而上和自上而下）。通过在混合通道上添加系统的结构化凹槽组，成功实现了液体处理方法。
