Abstract
Abstract: We demonstrate the use of gas phase metal hydroxide clusters to identify descriptors and generate scaling relationships for predicting catalytic performances of porphyrin-supported metal hydroxide catalysts. Using the gas phase clusters for these purposes takes just 5 % of the time that would have been required if the porphyrin-supported models had been used. Graphical Abstract: [Figure not available: see fulltext.]
| Original language | English (US) |
|---|---|
| Pages (from-to) | 2566-2573 |
| Number of pages | 8 |
| Journal | Catalysis Letters |
| Volume | 146 |
| Issue number | 12 |
| DOIs | |
| State | Published - Dec 1 2016 |
Funding
This work was supported as part of the Inorganometallic Catalyst Design Center, an Energy Frontier Research Center funded by the U.S. Department of Energy (DOE), Office of Science, Basic Energy Sciences (BES), under Award DE-SC0012702. Simulations were performed on the Palmetto Supercomputer Cluster, which is maintained by the Cyberinfrastructure Technology Integration Group at Clemson University. We thank Andrew Samstag, who is an undergraduate research assistant in our group, for his help in setting up the simulations for the porphyrin supported catalysts. We would also like to thank Pere Miró (University of North Florida) for helpful discussions about setting up the QM/QM ONIOM model for the porphyrin supported catalysts.
Keywords
- Computational catalysis
- Heterogeneous catalysis
- Kinetic modeling
- Nanocluster catalysts
ASJC Scopus subject areas
- Catalysis
- General Chemistry