Abstract
The initial mechanistic steps underlying heterogeneous chemical catalysis can be described in a framework where the composition, structure, and orientation of molecules adsorbed to reactive interfaces are known. However, extracting this vital information is the limiting step in most cases due in part to challenges in probing the interfacial monolayer with enough chemical specificity to characterize the surface molecular constituents. These challenges are exacerbated at complex or spatially heterogeneous interfaces where competing processes and a distribution of local environments can uniquely drive chemistry. To address these limitations, this work presents a distinctive combination of materials synthesis, surface-specific optical experiments, and theory to probe and understand molecular structure at catalytic interfaces. Specifically, isopropanol was adsorbed to surfaces of the model CeO2 catalyst that were synthesized with only the (100) facet exposed. Vibrational sum-frequency generation was used to probe the molecular monolayer and, with the guidance of density functional theory calculations, was used to extract the structure and absolute molecular orientation of isopropanol at the CeO2(100) surface. Our results show that isopropanol is readily deprotonated at the surface, and through the measured absolute molecular orientation of isopropanol, we obtain new insight into the selectivity of the (100) surface to form propylene. Our findings reveal key insight into the chemical and physical phenomena taking place at pristine interfaces, thereby pointing to intuitive structural arguments to describe catalytic selectivity in more complex systems. (Graph Presented).
Original language | English |
---|---|
Pages (from-to) | 14137-14146 |
Number of pages | 10 |
Journal | Journal of Physical Chemistry C |
Volume | 121 |
Issue number | 26 |
DOIs | |
State | Published - Jul 6 2017 |
Funding
This work was supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Chemical Sciences, Geosciences, and Biosciences Division (B.D., Y.-Z.M., and D.A.L.), Materials Sciences and Engineering Division (D.L. and H. N. L.), and the Critical Materials Institute, an Energy Innovation Hub funded by the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Advanced Manufacturing Office (S.G.S. and V.S.B.). This research used computational resources at the Orcinus computing facility of WestGrid/Compute Canada and the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, supported by the Office of Science of the U.S. Department of Energy under contract No. DE-AC05-00OR22725.