Many important catalysts begin as molecular precursors that react with hydroxyls on the surface of amorphous silica.  The result is an ensemble of isolated catalyst sites, each with different local silica environments and different properties.  Standard computational methods and experimental characterization tools are not applicable to these quenched and disordered catalysts, so their active sites and mechanisms are often poorly understood.  For a simple model of the Phillips catalyst, we combine machine learning tools and rare events methods to efficiently identify the most likely grafting sites on the starting support material.  We use the predicted ensemble of non-uniform sites to predict site-averaged activation energies and activities.   We demonstrate that these tools provide 1000-fold acceleration in the calculation of site-averaged kinetic properties.  Finally, we systematically create an ensemble of cluster models using graph-theoretic tools.  In this talk, we present ab initio calculations to understand the grafting reactions in the preparation of a Ti/SiO<sub>2</sub> expoxidation catalyst.

Modeling single-site catalysts on amorphous supports: Important learning algorithm

Macromolecular Chemistry: The Second Century

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ACS Spring 2020 National Meeting & Expo

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.