Awl t~tuQ STI AbstractRecent investigations have implicated cage-liie precursors in the unusually high gelation conversion (W 82Yo) of acid-catalyzed tetraethoxysilane. However, the statistical models used so far cannot capture kinetic or composition-dependent features of alkoxysilane polycondensation.Here we take a first step towards unified modeling of the kinetics and structure of silica gelation.Dynamic Monte Carlo simulations [J. Somv&rsky and K. DuSek, Polym. BuJ1. 1994 33:369] are developed which permit competition between extensive cyclization and growth. The model includes well-established kinetic trends (hydrolysis pre-equilibrium and first shell substitution effects). As a first approximation, unimolecular-like terms for cyclization reactivity follow the experimental pattern of bimolecular rate coefficients. The present simulations allow unlimited formation of 3-site rings, giving rise to many structures which are not those of real silicates (where 4-site rings dominate). However, the level of cyclization (both cycles per molecule and per site) is consistent with that of real silicates, and is enough to delay gelation to 82% conversion or higher. These simulations also display a broader range of gelation behavior than prior kinetic models. At high to moderate monomer concentrations, competition between cyclization and growth causes the expected delay of gelation. Upon further dilution, we discover a third regime, absent from prior kinetic gelation models but important for siloxanes: formation of a distribution of polycyclic precursors which still rettin enough functionalisty to gel.

This article presents a novel method for tuning the reactivity of nanoenergetic materials by coating a strong oxidizer nanoparticle (potassium permanganate; approximately 150 nm) with a layer of a relatively mild oxidizer (iron oxide). The measured reactivity for a nano-Al/composite oxidizer could be varied by more than a factor of 10, as measured by the pressurization rate in a closed vessel (psl/micros), by changing the coating thickness of the iron oxide. The composite oxidizer nanoparticles were synthesized by a new aerosol approach in which the nonwetting interaction between iron oxide and molten potassium permanganate aids the phase segregation of a nanocomposite droplet into a core-shell structure.

Interest in developing an oxidizer matrix for reaction with nano-aluminum for energy-intensive applications involving explosives and propellants have led to the development of an aerosol-based sol−gel method (Aero-sol−gel) for preparing nanoporous iron-oxide nanoparticles with high internal surface area. We have employed sol−gel reactions in the aerosol phase using an iron(III) salt with an epoxide in a volatile solvent (ethanol), to generate nanoporous oxidizer nanoparticles. Porosity of the particles results from the nature of the sol−gel chemistry implemented. Energy-dispersive spectrometry (EDS) results indicate that the aerosol-based chemistry is qualitatively similar to that occurring in bulk sol−gel synthesis. The oxidizer particles obtained from the aero-sol−gel experiment are in the 100−250-nm size range as evidenced by SEM and differential mobility analysis (DMA). Porosity of particles is observed qualitatively in the TEM micrographs and quantitatively determined with BET surface area measurements which indicate that these particles have total surface area that is enhanced by a factor of 200 over the geometric surface area. The aero-sol−gel derived iron oxide has also been mixed with nano-aluminum and preliminary ignition tests have been performed to show the effectiveness of the oxidizer particles.

We compare two approaches in modeling first shell substitution effects (FSSE) coupled with cyclization in acid-catalyzed sol−gel polymerization. First, an approximate, statistically based, kinetic-recursive model (KR) is developed that is computationally inexpensive for investigating trends in the polymerization. Second, an exact Monte-Carlo model (MC) that tracks a finite pool of growing polymer clusters is constructed for comparison to the KR model. The two models agree well prior to gelation when using rate constants typical of sol−gel polymerization. However, near the gel point, discrepancies between the two models arise because of the KR model's inability to account for correlations in the growing structure beyond the site distribution. We show that both FSSE and cyclization cause the polymer's structure distribution to be history dependent. We also show that the inclusion of both FSSE and cyclization in the model is capable of increasing gel conversions above the 0.50 limit of previous exclusive FSSE models. We show that FSSE aids cyclization by increasing the concentrations of oligomers that are candidates for intramolecular reaction and that a strong FSSE with cyclization causes a local maximum to occur in the polydispersity index as a function of conversion. Both models fall short of predicting experimentally observed gel conversions; indicating that, in addition to the small cycles allowed in the present work, cage formation may also be significant.