(5ay) Nanoscience of Liquid Crystals and Porous Materials: Insights from Computational Modeling

Computational modeling and simulation, and their interplay with experiments, have proven to be valuable tools in providing a fundamental understanding of key aspects of many emerging technologies. In this poster, I present two examples from my recent research in two different areas: the phase behavior of molecules confined in ordered nanoporous materials, and the driven assembly of nanoparticles immersed in liquid crystalline solvents.

Materials with nanopores of regular and tunable morphology are finding emerging applications in different fields, besides their traditional uses in separations and catalysis. As an example, templated mesoporous silicas MCM-41 and SBA-15 are being used in microelectronics as low dielectric constant materials to insulate integrated circuits and microchips, and as templates for fabrication of opto-electronic nanodevices, ordered carbon materials and nanowires. Advances in applications involving these materials are directly linked to understanding the physical properties of guest molecules inside the pores. Gas adsorption is a standard measurement in the characterization of porous materials; moreover, the incorporation of guest molecules can be used to further modify the physical properties of the porous materials. The interpretation of experimental results is complicated by issues such as metastability and an incomplete characterization of the pore morphology. As a result, molecular simulations have been invaluable in the study of confined systems. Here we present Monte Carlo simulation results for capillary condensation and freezing of fluids inside realistic models of carbon nanotubes, MCM-41 and SBA-15. A rich phase behavior with multiple transition temperatures and different phases was observed for these confined systems. Our results show that intermolecular interactions and pore morphology have a profound influence on the gas-liquid and freezing transitions in confinement.

Our second research topic is based on the driven assembly of nanoparticles immersed in liquid crystals (LC). These systems have attracted great attention for their potential uses in optical sensors. Recent experiments have demonstrated that the binding of chemicals, biomolecules and viruses at solid-LC and liquid-LC functionalized interfaces can be detected by simply using a microscope and polarized light. Systems of particles in liquid crystals also have potential applications for development of new composites and colloidal crystals. The inclusion of colloids induces elastic distortions in the liquid crystal, giving rise to long-range interparticle interactions that are absent when isotropic solvents are used. Optimization of these applications Increases in selectivity and sensitivity of these sensors, as well as controlled colloidal assemblies, can be obtained by tuning the size and shape of the particles, by engineering their surfaces, or by manipulating the physical properties of the liquid crystal. Optimization of these applications requires a theoretical formalism linking macroscopic measurements (collective optical properties) with events occurring at smaller length scales (particle aggregation, liquid crystal reordering and binding events at the surface of the particles). Here we present numerical simulations for systems of spherical colloids dispersed in a liquid crystal. We have adopted a hybrid strategy that includes particle-based modeling of the colloids and a continuous field treatment of the liquid crystal. The effect of several physical variables is analyzed and discussed. We also show results for anisotropic, spherocylindrical particles immersed in liquid crystals, for which it was found that the interparticle energies were up to three times stronger than those observed for spherical colloids of comparable diameters.