Deducing subnanometer cluster size and shape distributions of heterogeneous supported catalysts
| Author(s) | Liao, Vinson | |
| Author(s) | Cohen, Maximilian | |
| Author(s) | Wang, Yifan | |
| Author(s) | Vlachos, Dionisios G. | |
| Date Accessioned | 2023-06-22T20:03:29Z | |
| Date Available | 2023-06-22T20:03:29Z | |
| Publication Date | 2023-04-08 | |
| Description | This article was originally published in Nature Communications. The version of record is available at: https://doi.org/10.1038/s41467-023-37664-w. © The Author(s) 2023 | |
| Abstract | Infrared (IR) spectra of adsorbate vibrational modes are sensitive to adsorbate/metal interactions, accurate, and easily obtainable in-situ or operando. While they are the gold standards for characterizing single-crystals and large nanoparticles, analogous spectra for highly dispersed heterogeneous catalysts consisting of single-atoms and ultra-small clusters are lacking. Here, we combine data-based approaches with physics-driven surrogate models to generate synthetic IR spectra from first-principles. We bypass the vast combinatorial space of clusters by determining viable, low-energy structures using machine-learned Hamiltonians, genetic algorithm optimization, and grand canonical Monte Carlo calculations. We obtain first-principles vibrations on this tractable ensemble and generate single-cluster primary spectra analogous to pure component gas-phase IR spectra. With such spectra as standards, we predict cluster size distributions from computational and experimental data, demonstrated in the case of CO adsorption on Pd/CeO2(111) catalysts, and quantify uncertainty using Bayesian Inference. We discuss extensions for characterizing complex materials towards closing the materials gap. | |
| Sponsor | This work was financially supported by the RAPID manufacturing institute, supported by the Department of Energy (DOE) Advanced Manufacturing Office (AMO), award number DE-EE0007888-9.5 [DGV]. RAPID projects at the University of Delaware are also made possible, in part, by funding provided by the State of Delaware. The Delaware Energy Institute acknowledges the support and partnership of the State of Delaware in furthering the essential scientific research being conducted through the RAPID projects. This research was supported in part through the use of Information Technologies (IT) resources at the University of Delaware, specifically the high-performance computing resources. | |
| Citation | Liao, V., Cohen, M., Wang, Y. et al. Deducing subnanometer cluster size and shape distributions of heterogeneous supported catalysts. Nat Commun 14, 1965 (2023). https://doi.org/10.1038/s41467-023-37664-w | |
| ISSN | 2041-1723 | |
| URL | https://udspace.udel.edu/handle/19716/32943 | |
| Language | en_US | |
| Publisher | Nature Communications | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| Title | Deducing subnanometer cluster size and shape distributions of heterogeneous supported catalysts | |
| Type | Article |
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