UCLA

Sorting engineered cells with unique properties or functions from a larger population represents the future for personalized cell therapy and diagnostics. High- throughput and high-content single-cell sorting methods enable selecting specific desirable cell subpopulations from a heterogeneous mixture and facilitate extracting wealthy information of medically relevant biomarkers. This thesis explores programmable microfluidic and multiferroic methods for cell sorting and analysis. Microcavity flow was used to passively separate cancer cells from blood in high-throughput. Cavity flow physics was explored for size-based capture of cells. To expand cell sorting automation and artificial intelligence integration in microfluidic devices, suspended micromotor system was developed and controlled with computer-assisted image analysis software to enable modular sorting of cells, cells encapsulated in droplets, cell clusters, and organoids of any size. Next section, programmable magnetoelastic microstructures were coupled with microfluidic devices for single-cell manipulation. Magnetoelastic materials with controllable intrinsic magnetic properties were used for single-cell capture/release in highly parallel arrays. Microfluidic and multiferroic cell sorting technologies will potentially enhance single-cell profiling across diverse cancer cells for personalized medicine and support cell engineering technologies through a precise selection of high-performing cells.