Surface Acidity Characterization of Metal-Doped Amorphous Silicates via Py-FTIR and 15N NMR Simulations

Abstract

Metal-doped amorphous silicates are effective acidic catalysts for numerous industrial applications, including dehydration of alcohols, hydrodeoxygenation of biomass, and metathesis of olefins. The acidity of these catalysts is derived from the metal dopant and is experimentally characterized using a number of techniques, such as ammonia temperature-programmed desorption (NH3-TPD), pyridine Fourier transform infrared (Py-FTIR), and 15N nuclear magnetic resonance (NMR) spectroscopy of either probe molecule. Although these measurements provide information regarding the amount and strength of the acid sites, they alone do not provide any detail about the local structure around the metal center, which hampers the ability to systematically design better catalysts. In this study, we present density functional theory (DFT) simulations of Py-FTIR and 15N NMR spectra to characterize the local structure and acidity strength of metal-doped silicate clusters. We perform calculations on the model structures compiled in the METal-doped Amorphous SIlicate Library (METASIL), which aims at providing realistic amorphous structures for Zr-, Nb-, and W-doped silicates. By matching the calculated normal mode frequencies with experimental IR spectra, we reproduce the differentiation between Lewis and strong Brønsted acid sites. However, our simulations show that the coordination of Py to weak Brønsted acids is indistinguishable from that to metal sites, as they elicit similar frequency shifts. On the other hand, 15N NMR can distinguish between Py interacting with metal centers, weak and strong Brønsted acid sites, and it may be able to identify the structure of metal dopants. Therefore, these results can be used to provide theoretical support for the design of new catalytic materials.