Congratulations to Matt, Tuo, and to our collaborators in Prof. Al Faruque lab at the University of California, Irvine!
Our work that pioneers the use of Artificial Intelligence to automatically characterize the frequencies used to attract and repel microbeads to/from the electrodes is published in the Micromachines journal. This technology is a necessary precursor for the development of the automation (based on the Artificial Intelligence algorithms) of electrokinetic micro- and nano-assembly processes.
Michaels, M.; Yu, S.-Y.; Zhou, T.; Du, F.; Al Faruque, M.A.; Kulinsky, L. Artificial Intelligence Algorithms Enable Automated Characterization of the Positive and Negative Dielectrophoretic Ranges of Applied Frequency. Micromachines 2022, 13, 399. https://doi.org/10.3390/mi13030399
