Optimization and development of a universal flow‐based microfluidic gradient generator

The preparation of concentration gradients of reactive molecules is fundamentally important for many research fields including biology, pharmaceutical and chemical engineering (Kim et al. 2010; Lin and Levchenko 2015; Sackmann et al. 2014; Sant et al. 2010; Wu et al. 2010). To generate concentration gradients, microfluidic gradient generators (MGGs), including flow based and (Abe et al. 2015; Chen et al. 2012; Friedrich et al. 2012; Lin et al. 2004; Wang et al. 2015; Yang et al. 2011) diffusion based (Brett et al. 2012; Saadi et al. 2007; Sahai et al. 2011), and active MGGs (Ahmed et al. 2013; Destgeer et al. 2014; Jain et al. 2010) have recently emerged as a powerful tool to produce the desired concentration gradients in a controlled manner. Among these studies, a flowbased “universal MGG”, which is able to produce arbitrary monotonic gradients from two input concentrations, has attracted considerable attention (Irimia et al. 2006). Compared to other flow-based MGG devices such as “Christmas tree” (Lin et al. 2004) and radical-structured (Wang et al. 2015) designs which need to design separate channels to control the flows, universal MGG only needs to place a set of flow dividers along the flow direction in one single channel, so as to split and remix the flows of different concentrations. Such strategy to manipulate the flow behaviour renders universal MGG devices simple and cost efficient. Recently, increasing numbers of experimental researches (Xu et al. 2012) and numerical simulations (Hu et al. 2011) have been conducted on design and applications of universal MGGs, which have shown agreement with the original Abstract Generation of concentration gradients of reactive molecules is of fundamental importance for many applications including biology, pharmaceutical and chemical engineering. By numerically simulating the flow behaviour, we reveal the possible factors that cause significant error in the gradients generated by the conventional universal microfluidic gradient generator (MGG) device reported previously. Based on these computational analyses, we optimize the geometrical design of the conventional 2-inlet MGG devices and improve the accuracy of the generated gradients. Moreover, we innovatively propose a 3-inlet MGG design showing desirable accuracy and versatility on creating various gradient profiles using the one single device. We further demonstrate our numerical simulation by fabricating the MGG devices by soft lithography and experimentally produce concentration gradients of diverse power functions. In general, the current study substantially improves the performance of universal MGG devices, which can serve as powerful tools for widespread applications in biology and chemistry.