2D Dipole Lattices in Apolar Nematic Liquid Crystals via Geometrical Confinement

About This Grant

Non-Technical Abstract: This project will study a special kind of material called a liquid crystal (LC). It flows like a liquid but has some internal structure and is already used in everyday items like phone and TV screens. In this research, scientists will place LCs on tiny, patterned surfaces and gently move drops of water or other fluids across them. As the fluid moves, it changes how the LC molecules line up, and the LC can “remember” the direction the fluid moved, even after the motion stops. This could lead to new ways to store and use information without electronics, such as fluid-based memory that works like a read-only chip. It could also help track how bacteria or cells move on surfaces or detect tiny changes in fluid flow. The project will also give college and high school students hands-on lab experience, helping them build skills for future careers in science, technology, and manufacturing. Technical Abstract: This project will investigate how confinement and interfacial shear induce polar order and reconfigurable dipole lattices in apolar nematic LCs. Unlike ferroelectric systems that rely on intrinsic molecular dipoles, nematic LCs are typically nonpolar and symmetric, with no preferred direction. This research investigates how symmetry breaking through geometric confinement and fluid interfaces can lead to the emergence of stable elastic dipoles, i.e., pairs formed between topological point defects and fixed geometric anchors. These dipoles exhibit discrete orientations that can be switched by fluid motion, forming two-dimensional dipole lattices with programmable states. The work will combine experiment and theory. This project will fabricate patterned microstructures, introduce nematic LCs, and apply immiscible fluid droplets to induce reorientation. Observations will be made using polarized light microscopy. Theoretically, the project will use Landau–de Gennes Q-tensor modeling and hydrodynamic simulations to predict defect configurations and dynamic responses under shear. Three main research thrusts will be pursued: (1) establishing control over defect orientation through confinement and flow, (2) developing predictive models of defect behavior in various geometries and LC mesophases, and (3) exploring multistate memory behavior and flow detection applications. The outcomes will expand understanding of defect-driven order in soft materials, demonstrate how polar textures can be induced in apolar systems, and provide a basis for novel technologies such as fluid-responsive sensors and passive, read-only memory elements based on liquid materials. The project will also help train students in experimental and computational techniques relevant to future scientific and engineering careers. 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.