NSF Award
2324195
Non-technical Description: Biological cells exhibit remarkable functionalities, such as motility, division, and self-healing. Reproducing these life-like behaviors in synthetic materials would both revolutionize engineering and advance fundamental science. Active fluids, which are composed of motile energy-consuming microscopic units, are a promising platform for achieving these ambitious goals. In contrast to widely studied conventional passive materials, active fluids generate internal forces that drive persistent autonomous motion, an alluring life-like feature. On their own, however, bulk active fluids exhibit chaotic flows. Thus, they are unable to perform useful functions such as generating work or driving net material transport. By seamlessly merging experiments, theory and machine learning methods, this project aims to harness the chaotic dynamics of active fluids to achieve functional behaviors. In particular, the project will measure the instantaneous configuration of a light-responsive active fluid and use model-dependent theory and/or model-independent machine-learning methods to forecast its evolving dynamics. This information will impose theory-guided external signals that steer the system toward a targeted state such as a persistent rotation of an inclusion or cell-like persistent crawling of a deformable droplet that encapsulates an active fluid. The project will also pursue several tightly integrated education and outreach activities focused on (1) providing rigorous training and mentoring in interdisciplinary sciences to graduate and undergraduate students, (2) encouraging underrepresented groups to pursue work in STEM-related fields, (3) and raising general awareness of the importance of scientific research to broader communities. <br/><br/>Technical Description: By controlling interactions between the force-generating cytoskeleton and the surrounding deformable lipid membrane, biological cells achieve remarkable functionalities. Inspired by this observation, this project will pursue two complementary aims that use light-responsive microtubule-based active fluids to control the dynamics and motions of rigid and deformable interfaces and inclusions. This represents a first step toward creating synthetic life-like materials and machines. The first aim will embed an isolated rigid inclusion into a photo-responsive active nematic liquid crystal. The stresses generated by the active fluid exert stochastic forces on the inclusion, driving its dynamics. The aim is to implement hybrid theory-experiment feedback to drive the targeted inclusion dynamics by imposing spatiotemporal patterns of active stress. The second aim will encapsulate light-responsive active fluids within deformable droplets created by conventional liquid-liquid phase separation. Under uniform illumination (thus uniform activity), active droplets exhibit life-like morphological shape changes and activity-induced spreading, but unlike biological cells have no directional motion. The implemented feedback scheme will control the formation, motility, fusion, and breakup of the active droplets. The project will develop unique responsive and adaptive materials as envisioned by the DMREF program, by implementing iterative theory/experiment feedback cycles during a single experiment on timescales of seconds to minutes.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
