Metal-support interactions typically control the stability of supported metal nanoparticle (NP) catalysts. Moreover, metal-support interactions may also dramatically impact catalytic activity of the NPs. Therefore, an accurate description of the metal NP-support interactions is crucial for successful design and optimization of supported NP catalysts. Atomistic computational modeling of metal NP-support interactions has typically utilized crystalline supports. Current state-of-the-art modeling includes effects of step edges, vicinal surfaces and even some level of defects.  However, modeling amorphous surfaces is considerably less common. This is because the computational tool of choice for modeling NP-support interactions, periodic density functional theory (DFT), cannot truly model amorphous materials. However, one of the most common and versatile oxide supports used is amorphous silica, and many other amorphous metal oxides are widely used. We have developed a formalism for generating models of amorphous silica from atomistic simulations. We have tested the validity of our generated models by comparing with experimental data not used to develop the model and have used the model surfaces to explore NP-support interactions. We have used discrete element method (DEM) simulations to sample the NP-support interface at various NP adsorption locations on model amorphous silica surface structures. Our DFT calculations revealed that, for various metals, both NP stability and the charge on the NP depend linearly on the number of NP-silica bonds, which is determined by the surface hydroxyl content, and hence the silica pretreatment temperature. These correlations are independent of NP geometry and size, enabling very efficient simulations using only DEM simulations for predicting catalyst-support effects for various NP geometries and sizes. Preliminary experimental results validate our prediction relating NP stability to silica pretreatment temperature. We also examine the influence of the amorphous support on the structure and energetics of single-site catalysts. We have found that simple cluster models of the surface are not able to capture the rich heterogeneity of an extended surface model containing hundreds of atoms. As a result, trends that appear in the cluster models do not appear in the larger extended models.<br/>

Accurate modeling of amorphous silica catalyst supports

2019 Fall National Meeting

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