October 23, 2024
Journal Article
Distribution Tendencies of Noble Metals on Fe(100) Using Lattice Gas Cluster Expansions.
Abstract
Fe-based catalysts have been shown to be highly selective for hydrodeoxygenation of biomass derived oxygenates but are prone to oxidative deactivation. Promotion with a noble metal has been shown to improve oxidative resistance. The chemical properties of such bimetallic systems depend critically on the surface geometry and spatial configuration of surface atoms in addition to their coverage (i.e., noble metal loading), and so these aspects must be accounted for in order to develop reliable models for such complex systems. This requires sampling a vast configurational space which is rather impractical using density functional theory (DFT) calculations alone. Moreover, “DFT-based” models are limited to length-scales that are often too small for experimental relevance. Here, we circumvent this challenge by constructing DFT-parameterized lattice gas cluster expansions (LG CEs), which can describe these types of systems at significantly larger length-scales. Here, we apply this strategy to Fe(100) promoted with four technologically relevant precious metals: Pd, Pt, Rh, and Ru. The resultant LG CEs have remarkable predictive accuracy, with predictive errors below 10 meV/site over a coverage range of 0 to 2 monolayers. The ground state configurations for each noble metal were identified, and the analysis of the cluster energies reveal a significant disparity in their dispersion tendency. The work was primarily funded by the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Chemical Sciences, Biosciences and Geosciences within the Catalysis Science program, under award number DE-SC0014560. Y.W. would like to acknowledge the support from the U.S. Department of Energy (DOE), Office of Science (SC), Basic Energy Sciences (BES), Division of Chemical Sciences, Geosciences, and Biosciences within the Catalysis Science program (DE-AC05-RL01830, FWP-47319). This research used resources from the Center for Institutional Research Computing at Washington State University. This work was partially funded by the Joint Center for Deployment and Research in Earth Abundant Materials (JCDREAM) in Washington State. We also acknowledge fruitful discussions with Mr. Jacob Bray. PNNL is a multi-program national laboratory operated for the U.S. DOE by Battelle.Published: October 23, 2024