Date of Award
Doctor of Philosophy (PhD)
Miniaturization of on-board actuation and powering engenders the proliferation of biohybrid microrobots, which integrate motile bacteria or cells with synthetic functional components to achieve micron-scale actuations. Flagellated bacteria like S. marcescens are among the leading candidates for the actuators of swimming microrobots. However, the high intrinsic stochasticity in bacteria-driven microrobots severely limits their potential applications, such as targeted drug delivery. Taxis behaviors (e.g., chemotaxis), which help free-swimming bacteria to navigate towards favorable environments and away from hazardous ones, may offer an elegant means to control the motion of bacteria-driven microrobots. Therefore, this thesis focuses on: (a) addressing the motion guiding of bacteria-driven microrobots using common bacterial taxis behaviors, specifically chemotaxis and pH-taxis, (b) explaining the physical mechanisms associated with the tactic motions in bacteria-driven microrobots, and (c) developing a biophysical model to describe the bacterial propulsion and the chemotaxis in bacteria-driven microrobots. In order to produce considerable chemotactic motion in bacteria-driven microrobots, an appropriate chemical concentration profile needs to be determined, which requires the knowledge of the chemotaxis response of the integrated bacterial species. Thus, we first propose an experimental and modeling framework to characterize bacterial chemotaxis. The chemotaxis response of a species against a chemoattractant is experimentally quantified under a linear concentration gradient of the attractant. A signaling pathway model is fitted to the experimental measurements over a series of gradients to determine the species-specific parameters in the model, thereby fulfilling an analytical characterization of the chemotaxis. Subsequently, in a multi-bacteria-driven microrobotic system, we quantify the chemotactic drift of the microrobotic swarms towards a potent chemoattractant L-serine and elucidate the physical mechanisms associated with the drift motion by statistical trajectory analysis. It shows that the microrobots have an apparent heading preference for moving up the gradient, which constitutes the major factor that produces the chemotactic drift. The apparent heading bias is caused by a higher persistence in the heading direction when a microrobot moves up the the L-serine gradient compared to traveling down the gradient. Besides chemotaxis, we explore the potential of utilizing ambient pH to guide the motion of the bacteria-driven microrobots. Under three different pH gradients, we demonstrate that the microrobots exhibit both unidirectional and bidirectional pH-tactic behaviors. Two factors, a swimming heading bias and a speed bias, are found to be responsible for the pH-tactic motion while the heading bias contributes more. Like in chemotaxis, the heading directions of the microrobots are also significantly more persistent when they move towards favored pH regions. Finally, a biophysical model is developed to describe the bacterial propulsion and the chemotaxis in an extensively adopted design of bacteria-driven microrobots. The model traces helical trajectories and chemotactic motion that resemble those observed from experiments, which validates the basic correctness of the model. The model simulation also suggests that the seemingly collective chemotaxis among the multiple bacteria attached to a microrobot could be explained by a synchronized signaling pathway response among these bacteria. Furthermore, we investigate the dependencies of the microrobots’ per
Zhuang, Jiang, "Taxis-Based Motion Control of Biohybrid Microrobots" (2017). Dissertations. 798.