INVESTIGATION OF THE ASSEMBLY OF SURFACTANTS AT THE SOLID-LIQID INTERFACE FOR ADSORPTION AND MATERIALS APPLICATIONS

This dissertation addresses two topics associated with the assembly of surfactants at the solid-liquid interface for adsorption and materials synthesis. The first is the adsorption of an anionic fluorinated surfactant, tetraethylammonium perfluorooctylsulfonate (TEA-FOS), at the solid/liquid interface. Attenuated total reflection Fourier transform infrared spectroscopy is used to study the adsorption kinetics and average orientation of surfactants at the hydroxylated germanium surface. Atomic force microscopy provides complementary images of the adsorbed layer structure on mica. The adsorption follows unusual three-stage kinetics in which the rate of adsorption starts fast, slows as the surface becomes crowded, and then (surprisingly) accelerates due to nucleation of a heterogeneous multilayer structure. These fast-slow-fast three stage adsorption kinetics are observed for a wide range of concentrations at pH 6, and the rates of the three stages are modulated by pH and salt by tuning electrostatic interactions among surfactants, counterions, and the surface. The results suggest that tetraethylammonium mediates interactions between surfactants and with negatively charged surfaces. The dichroism measurements and AFM are consistent with a mechanism in which TEA-FOS first forms an incomplete layer with chains oriented randomly or somewhat parallel to the surface, followed by formation of flattened multilayer clusters with the chains oriented somewhat normal to the substrate. The second topic is the sol-gel synthesis of mesoporous silica materials using dual surfactant templates. Studies of templating with mixed cetyltrimethylammonium bromide and octyl-beta-D-glucopyranoside surfactants shows that the ternary phase diagram of surfactants in water can be used to predict mesoporous materials structure, and that vapor-phase ammonia treatments can either stabilize the structure or induce swelling by the Maillard reaction. Studies of sol-gel reaction-induced precipitation with demixed hydrocarbon and fluorocarbon cationic surfactant micelles show a wide variety of pore structures. A number of synthesis parameters are adjusted to tune the pore structure, for instance to adjust the size and populations of bimodal mesopores. Selective swelling of the two surfactants by liphophilic and fluorophilic solvents is observed. Finally, proteinaccessible hollow spherical silica particles with mesoporous shells are reported. The methods for engineering mesoporous materials reported here have potential applications in adsorption, controlled drug delivery and for catalysis

A nondominated sorting genetic algorithm for bi-objective network coding based multicast routing problems

Network coding is a new communication technique that generalizes routing, where, instead of simply forwarding the packets they receive, intermediate nodes are allowed to recombine (code) together some of the data packets received from different incoming links if necessary. By doing so, the maximum information flow in a network can always be achieved. However, performing coding operations (i.e. recombining data packets) incur computational overhead and delay of data processing at the corresponding nodes. In this paper, we investigate the optimization of the network coding based multicast routing problem with respect to two widely considered objectives, i.e. the cost and the delay. In general, reducing cost can result into a cheaper multicast solution for network service providers, while decreasing delay improves the service quality for users. Hence we model the problem as a bi-objective optimization problem to minimize the total cost and the maximum transmission delay of a multicast. This bi-objective optimization problem has not been considered in the literature. We adapt the Elitist Nondominated Sorting Genetic Algorithm (NSGA-II) for the new problem by introducing two adjustments. As there are many infeasible solutions in the search space, the first adjustment is an initialization scheme to generate a population of feasible and diversified solutions. These initial solutions help to guide the search towards the Pareto-optimal front. In addition, the original NSGA-II is very likely to produce a number of solutions with identical objective values at each generation, which may seriously deteriorate the level of diversity and the optimization performance. The second adjustment is an individual delegate scheme where, among those solutions with identical objective values, only one of them is retained in the population while the others are deleted. Experimental results reveal that each adopted adjustment contributes to the adaptation of NSGA-II for the problem concerned. Moreover, the adjusted NSGA-II outperforms a number of state-of-the-art multiobjective evolutionary algorithms with respect to the quality of the obtained nondominated solutions in the conducted experiments