Synthesizing microfluidic networks of one-step-dilution gradient generators with arbitrary concentration profiles

This paper presents a methodology for synthesizing concentration gradient generators (CGGs) with arbitrary concentration profiles. The synthesized CGGs employ the design of a one-step-dilution microfluidic network, and utilize inexpensive multi-barrel syringe pumps for reducing the complexity of the flow manifold. The proposed design potentially exhibits high throughput with a wide range of input flowrates. The core of the proposed methodology is a CGG-synthesizing algorithm and a set of parametrized standard microfluidic components. The algorithm calculates the equivalent channel flow resistances, which control the volumetric mixing ratios of the CGG mixing channels to generate predefined concentration gradient profiles. Using a computational fluid dynamics (CFD) solver, the synthesized CGG microfluidic networks, including the linear, Gaussian, and logarithmic concentration profiles, were simulated and validated. The logarithmic profiles include profiles over 2-fold and 10-fold concentration increases. The maximum discrepancies between the simulated concentration profiles and the target profiles for these cases were less than 5 %. These synthesized CGGs were fabricated and implemented. The performance of the concentration profile generation was measured by dye visualization. The results show that the CGGs produce precise concentration gradients for the designs of the linear, Gaussian, and logarithmic profiles. The maximum discrepancy between the measurement results and the target profiles is approximately 1–8 %, which indicates that the diluted solution of the given concentration profiles can be generated consistently. The CGGs synthesized by the proposed algorithm are ready for applications such as drug screening and toxicity evaluation. In addition, by using a simple microfluidic outlet chip, the outputs of a linear CGG can be combined into a single flow with a monotonic concentration profile, which is suitable for the applications of chemotaxis studies. [Display omitted] •An algorithm for synthesizing customized concentration gradient generators (CGGs).•One-step-dilution design with high throughput, easy scale-up and small footprint.•Automatic generation of simple CGG layouts with standard microfluidic components.•Performance validation conducted for the CGGs with huge concentration variations.