This website provides users with access to the database of 10,513 random microfluidic chip designs described in "Random Design of Microfluidics" by Junchao Wang, Philip Brisk and William H. Grover.

In this work we created functional microfluidic chips without actually designing them. We accomplished this by first generating a library of thousands of random microfluidic chip designs, then simulating the behavior of each design using finite element analysis. The simulation results were then saved to a database which a user can then query via a website to find specific chip designs suitable for a given task. Our proof-of-concept library can provide chip designs that generate any three desired concentrations of a solute. We also fabricated and tested 16 chips from the library and confirmed that they function as predicted. Using this approach, individuals with no training in microfluidics can obtain chip designs for their specific needs in just a few seconds.

Please cite the following paper if you find random microfluidic mixers are helpful.

  1. Wang, J., Brisk, P., & Grover, W. H. (2016). Random design of microfluidics. Lab on a Chip, 16(21), 4212-4219.
  2. Ji, W., Ho, T. Y., Wang, J., & Yao, H. (2019). Microfluidic design for concentration gradient generation using artificial neural network. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 39(10), 2544-2557.
  3. Wang, J., Zhang, N., Chen, J., Su, G., Yao, H., Ho, T. Y., & Sun, L. (2021). Predicting the fluid behavior of random microfluidic mixers using convolutional neural networks. Lab on a Chip, 21(2), 296-309. (Cover)
  4. Zhang, N., Zha, K., & Wang, J. (2021). Exploring the Design Efficiency of Random Microfluidic Mixers. IEEE Access, 9, 9864-9872.

Find a random microfluidic chip for any three desired concentration

Outlet 1
(0.5 - 1.0)
Outlet 2
(0 - 1.0)
Outlet 3
(0 - 0.5)
Diffusion Coefficient (m^2/s)

  • Concentration unit is proportion concentration of inlet 1. Ex. For 100%, please input 1; For 84%, please input 0.84.
  • The input specifications should also comply with the following rule: Outlet 1 concentration > Outlet 2 concentration > Outlet 3 concentration.
  • Sodium ion (Na+) is suitable for simulating ions.
  • Fluorescein is suitable for small molecules.
  • Bovine serum albumin (BSA) is suitable for simulating large protein.

  • Recent chips found by users

    Outlet 1 Outlet 2 Outlet 3 Diffusion Coefficient[m^2/s]
    100fluoresceinCheck it! serum albuminCheck it! it!
    10.50.3fluoresceinCheck it! it!