(8f) Self-Assembly of Specific Nanostructures on Catalyst Supports Using Reverse Micelles as Nano-Vehicle

Employing catalysts, especially heterogeneous catalysts, in process reactions has always been one of the ways to enhance the efficiency of the reactions along with increased product selectivity. Since the inception of the idea of nanotechnology in catalysis, extensive research has been carried out in nanocatalysis, which has showed several advantages such as extremely high activity and selectivity, high yield, and high surface to volume ratio. Though several methods of catalyst synthesis techniques are available, scientists and engineers have been working to develop newer and more efficient synthesis techniques. One of which being the reverse micelle technique that allows for highly controlled particle sizes and the ability to deposit multiple metals onto a desired catalyst support surface. The reason to include the support (i.e. porous inorganic oxide) is mainly to maintain nanometer size catalyst metal dispersions even under severe processing conditions.

The size of these catalyst sites on the support is influenced by various synthesis conditions (i.e. water to surfactant molar ratio, reaction time, surfactant concentration, solvent, and surfactant type). These parameters can be adjusted to tune the size of the catalyst site on a metal-oxide support. From an exhaustive literature search, the size of the catalytic sites was compiled against their respective synthesis conditions. A multiple regression analysis using least squares, including response surface models, was performed to correlate the relationship between the dependent variable (i.e. size of the catalyst site) and independent variables (i.e. synthesis conditions). Laboratory tests were conducted using the regression results to develop nano-nickel sites deposited onto TiO₂ support material. The model developed depicts the variation of the size of the catalyst site against specific surfactant/solvent combinations (i.e. Triton-X/cyclohexane). The model also predicts the variation of the size of the catalyst site with combinations of other mentioned synthesis conditions. Finally, the size of the synthesized nano-nickel sites were obtained from SEM which fell in the range of sizes of the catalyst sites obtained from the regression analysis. This work aids in finding the confluence between computational catalysis and catalyst synthesis techniques along with parameter optimization, which, unlike computational approaches, have physical and chemical constraints.