TUESDAY, February 20, 2007
Time: 4:30 PM
OCNPS 200

Title: Computational materials science of liquid crystals

Alejandro D. Rey
Department of Chemical Engineering
McGill University

Liquid crystals are orientationally ordered soft phase materials with many functional and structural applications. Understanding and optimizing the functionality and processability of these anisotropic, textured, viscoelastic materials requires the integrated use of optics, rheology interfacial science, phase transitions, defect physics and topology. Computational materials science is a methodology based on the integration of all these disciplines. I will discuss several challenges in liquid crystal research in which computational materials science has helped to elucidate structure and dynamics relevant to functionality and processability. Processing of liquid crystalline polymers to produce fibers involves flow-induced texturing, pattern formation, and texture transformation through defect nucleation and annihilation. I will discuss how computational rheooptics together with defect physics and bifurcation theory yield quantitative information on orientation field symmetry, defect density, and rheological functions, as well as inverse problems, such as extracting heterogeneous orientation information from optical signals. Carbonaceous mesophases are discotic liquid crystals used as precursors for carbon super-fibers, composites, foams, and nanofibers. Mesophase orientation and self-assembly under non-planar confinement invariably leads to characteristic heterogeneous textures and defect lattice structures. I will discuss the use of phase ordering models, computational reflection polarized microscopy, and differential geometry to develop an understanding of how defect lattices and orientation heterogeneities arise under confinement. Texturing by chemical, electrical, and geometrical heterogeneities of substrates in contact with liquid crystals can be detected by transmitted optical microscopy, an optoelastic process known as liquid crystal vision. I will present progress and challenges in computational polarized optical microscopy of textured liquid crystals based on Maxwell equations and device models based on liquid crystal vision.