College Park, Maryland      June 6 - 10 , 2004

MP7: Structure Dete4rmination of Subcolloidal Zeolite Precursor Nanoparticles

J. M. Fedeyko, D. Vlachos, R. F. Lobo (Center for Catalytic Science and Technology, Department of Chemical Engineering, University of Delaware, Newark, DE 19713 USA)

Upon mixing a solution of tetrapropylammonium hydroxide (TPAOH) and tetraethylorthosilicate (TEOS) at room temperature, a segregation of the solution into two metastable phases is observed. A continuous water-rich phase is formed containing most of the water and a small amount of SiO2 and TPAOH. At the same time, the silica is microsegregated into nanoparticles (~ 4 nm) that contain most of the silica, a large fraction of the TPAOH and a small amount of water. It has been shown that the rate of growth of zeolites is controlled by the addition of these subcolloidal silica nanoparticles to the growing surface. However, many important aspects of these particles remain unresolved. For instance, the particle shape, particle size distribution, and fundamental properties such as the average composition, internal structure and charge are completely unknown. We have started a comprehensive investigation of this system in an attempt to resolve these issues and will use the information gathered to develop a zeolite growth model that describes the system as a function of intensive variables such as temperature, pressure and composition.

We have conducted contrast matching small-angle neutron scattering experiments in the dilute limit in combination with small-angle x-ray scattering and in-situ NMR spectroscopy. Analysis of the SANS patterns of particles prepared in D2O revealed that the particles are ellipsoidal shaped. Our study of the contrast matching and SAXS experiments indicates that the core of these particles is composed primarily of silica. In-situ 29Si NMR gives information about the connectivity of the silica core. We find that about 78% of the silica groups are Q3(SiO3/2–OH) and 22% of Q2(SiO2/2–(OH)2). All this information is being used as input to a simulated annealing code that generates models of the nanoparticles with atomic detail. We will present a summary of our results and analysis.

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