(4eq) Programming Structural Transition in Dynamic Systems
AIChE Annual Meeting
Sunday, November 7, 2021 - 1:00pm to 3:00pm
My work has also been inspired by the recent momentum in the biophysical understanding of emergent phenomena in the context of physical interactions. The development is spurred by the advances in synthetic biology, additive manufacturing, and artificial intelligence, making supramolecular structure routinely available and providing the analytical infrastructure to interpret the resulting data streams. Whereas biological systems are adaptive, man-made materials are typically static. Three primary thrusts of my research will be to (1) develop high throughput suites of tools to characterize system dynamics, (2) construct reduced settings to distill rules about complex, multicomponent systems, (3) develop strategies to control, calibrate or actuate material properties. I propose to use my expertise in complex fluids and dynamic systems to advance the understanding of far-from-equilibrium phenomena. I will seek rules from soft matter physics, topology, and topography to guide structure formation, using an integrated approach combining material engineering, high-throughput experiment design, and data analytics.
Microscopy as a high-throughput characterization tool. While a variety of tools are available to characterize static systems, recent years have witness a burgeoning interest to monitor dynamic, adaptable, and out-of-equilibrium systems. Structure of a colloidal suspension under shear, for instance, can be examined by neutron scattering. In comparison, microscopy is more ubiquitous. While microscopy has historically been used for direct visualization and obtaining qualitative information, the view is shifting towards quantitative analysis. Modern microscopes, equipped with the latest automation capabilities, can measure samples from mesoscale down to nanometer length scale, collecting data from several different channels in parallel, vertical z-stacks, time-lapse sequences, etc, and generate TB of data in a single experimental setting. During my postdoc, I spearheaded an effort to develop a workflow that combine a fully automated, high precision optical microscope stage with statistical methods for rapid material characterization. The high throughput infrastructure paves the way for rapid screening upstream, integration with addition machine learning algorithm downstream, and serves as a critical link for the inverse design problem in material discovery.
Active colloids in liquid crystals. Cytoskeleton contains filamentous structures that manifest characteristics akin to nematic liquid crystals (NLCs), which promote physiological processes at micro- and meso-scales. These local and global organizations are constrained by boundary and elasticity, which can be harnessed for cargo transport and tissue engineering purposes. Particle inclusions interact with their surrounding networks in a complex fashion, so much so that the particle shape determines its fate: actin filaments must be mobilized into the correct configuration to accommodate the local curvatures to prompt phagocytosis. Using a model NLC system, I designed boundary conditions that defined the orientation of these molecules, known as the âdirector fieldâ. NLC molecules tend to align with their neighbors and conform to boundary cues to minimize the overall distortion. In this way, they also control the assembly of the inclusions embedded in them. By tuning the geometry of the particles and bounding surfaces, I demonstrated the ability to position particles, plan trajectories, control defects and template assemblies. A single particle allows us to understand the rules of highly specific microscopic interaction, nevertheless, to accomplish meaningful tasks at the microscale, such as a switchable photonic material, we must understand the collective behaviors of many particles subject to the interplay of thermal, elastic, and hydrodynamic forces. This goal will be achieved in a series of systematic investigations, by defining precise boundary conditions and applying a data-driven approaches to analyze the resulting configurations.
Cell-substrate interactions, a fundamentally important biological phenomenon, is also critical to medicine and material science applications such as tissue scaffolding and wound healing. This process is highly reciprocal: extracellular matrix (ECM) composition affects the motility and the protein production of cells, in return, cells also remodel the ECM. However, most engineered substrates have static properties. Furthermore, it is difficult to quantify how cells dynamically remodel their environment locally by traditional bulk characterization techniques. Structured fluids such as liquid crystals (LCs) are ubiquitous in nature and widely used in display industry owing to their sensitive optical response, yet their tunability and interaction with cells are underexplored. I have recently been awarded the Otis Williams Postdoctoral Fellowship for my own proposed work to harness the responsiveness of LC as a dynamic substrate to control cell behaviors. The fellowship will fully support my work in the coming year to develop a platform which will allow us to track cellsâ adaptive response to substrate ordering, and explore its applications in fundamental science and biomedicine.
Teaching interests. My teaching philosophy is based on my belief in the role of the instructor both as a source of knowledge and a facilitator for learning. Furthermore, I value the power of clear communication of highly technical knowledge. Therefore, I seek to create a classroom that promotes peer-learning, active learning, communication and learning beyond classroom. Learning outcomes results from a combination of stimulation and perception personal control, thus I will adopt my course assignment to learner types. My goal for graduate education is to learn and evolve the projects with the graduate studentsâ input, so the project can develop in a direction for which my students feel a sense of ownership. I am well-prepared teach a wide range of courses offered in the undergraduate and graduate curriculum. Due to my research interests in soft matter and especially colloid science, I believe I can be most effective in teaching Fluid Transport, Thermodynamics, Heat and Mass Transport. I am also interested in developing a course in Self-Assembly and Liquid crystals.
1. Gu*, Y. Luo*, Y. He, M. E. Helgeson, M. T. Valentine, "Uncertainty quantification and estimation in differential dynamic microscopy", Phys. Rev. E, 2021, in revision. arXiv: 2105.01200.
2. Luo, Y. -F. Lee, K. A. Dennis, C. Velez, S. C. Brown, E. M. Furst, and N. J. Wagner, "One-step, in-situ jamming point measurements by immobilization cell rheometry", Rheol. Acta, 2020, 59, 209â225.
3. Luo, T. Yao, F. Serra, D. A. Beller, and K. J. Stebe, âDeck the walls with anisotropic colloids in nematic liquid crystals", Langmuir, 2019, DOI: 10.1021/acs.langmuir.9b01811
4. Luo, D. A. Beller, F. Serra, and K. J. Stebe, âTunable colloid trajectories in nematic liquid crystals near wavy walls", Nat. Comm., 2018, 3841.
5. Luo, F. Serra, and K. J. Stebe, âExperimental realization of the `lock-and-key' mechanism in liquid crystals", Soft Matter, 2016, 12, 6027-6032. (Front Cover: Soft Matter, 2016, 12, 6007-6008.)
6. Luo, F. Serra, D. A. Beller, M. A. Gharbi, N. Li, S. Yang, R. D. Kamien, and K. J. Stebe, âAround the corner: Colloidal assembly and wiring in groovy nematic cells", Phys. Rev. E, 2016, 93, 032705.