Our research group employs theoretical tools of applied mathematics, computer modeling and simulations, machine learning as well as various experimental tools to investigate fundamental and application problems in fluid mechanics, biophysics and smart materials. Our research focus includes active matter, microfluidics, liquid manipulation, microswimmers and biological adaptation.
Surfaces patterned with properly designed microstructures leverage liquid-solid interfacial energy for directional liquid transport, providing a new dimension for on-demand, smart liquid manipulation in 3D. This technology has tremendous potential in microfluidics, green energy, biochemistry and biomedical applications. Based on fluid dynamics and bioinspiration, our research group designs novel structured surfaces to establish universal platforms for triggering versatile liquid behaviors. We also explore how such smart liquid manipulation technology can be applied to different application domains.
Swimming microorganisms exhibit a variety of intricate behaviors and taxis strategies to achieve navigational tasks in response to environmental stimuli such as chemicals, light, electric fields and fluid flows. These adaptation behaviors of swimming microorganisms affects many biological processes, including biosynthesis, cell-cell communication, reproduction, infection and marine ecology. Our research group develops general biophysical principles to explain how biological microswimmers coordinate and optimize their short-term responses in order to accomplish more complex, long-term taxis strategies.
We discover a striking phototactic behavior of the microswimmer Euglena gracilis, where these eukaryotic cells swim in polygonal trajectories due to a sudden increase in light intensity.
For more details, refer to our paper: A. C. H. Tsang, A. T. Lam and I. H. Riedel-Kruse. Nature Physics, 14, 1216-1222, 2018. (pdf) (journal)
Euglena cells exposed to a spatial light gradient switch between spinning, polygonal motion and helical swimming in a light-intensity dependent manner, performing a biased ‘run-and-tumble’ towards darker regions.
For more details, refer to our paper: A. C. H. Tsang, A. T. Lam and I. H. Riedel-Kruse. Nature Physics, 14, 1216-1222, 2018. (pdf) (journal)
Smart artificial microswimmers with self-learning and adaptive capabilities offer exciting opportunities for the next generation biomedical applications such as microsurgery and targeted drug delivery. Our research group develops the artificial intelligence framework to design and manipulate smart artificial microswimmers that can behave similar to biological cells.
Microswimmers generate complex fluid flows to self-organize into large-scale dynamic patterns (e.g., swirls, swarms, aggregates, circulation, density shocks, and traveling waves). For biological microswimmers, these collective behaviors encode synergetic functions for the coordination, survival and growth of the swimmers. For artificial microswimmers, the accurate control of their collective behaviors is crucial for cooperative tasks such as cargo transport and assembly of microstructures. Our research group develops multi-scale hydrodynamic models and experimental systems to harness the collective behaviors of microswimmers.