Identification of stable adsorption sites and diffusion paths on nanocluster surfaces: an automated scanning algorithm
Abstract
The diverse coordination environments on the surfaces of discrete, three-dimensional (3D) nanoclusters contribute significantly to their unique catalytic properties. Identifying the numerous adsorption sites and diffusion paths on these clusters is however tedious and time-consuming, especially for large, asymmetric nanoclusters. Here, we present a simple, automated method for constructing approximate 2D potential energy surfaces for the adsorption of atomic species on the surfaces of 3D nanoclusters with minimal human intervention. These potential energy surfaces fully characterize the important adsorption sites and diffusion paths on the nanocluster surfaces with accuracies similar to current approaches and at comparable computational cost. Our method can treat complex nanoclusters, such as alloy nanoclusters, and accounts for cluster relaxation and adsorbate-induced reconstruction, important for obtaining accurate energetics. Moreover, its highly parallelizable nature is ideal for modern supercomputer architectures. We showcase our method using two clusters: Au18 and Pt55. For Au18, diffusion of atomic hydrogen between the most stable sites occurs via non-intuitive paths, underlining the necessity of exploring the complete potential energy surface. By enabling the rapid and unbiased assessment of adsorption and diffusion on large, complex nanoclusters, which are particularly difficult to handle manually, our method will help advance materials discovery and the rational designmore »
- Publication Date:
- Research Org.:
- Univ. of Wisconsin, Madison, WI (United States); University of California, Berkeley, CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Basic Energy Sciences (BES). Chemical Sciences, Geosciences, and Biosciences Division; Agency for Science, Technology, and Research (A*STAR) Singapore
- OSTI Identifier:
- 1616952
- Grant/Contract Number:
- FG02-05ER15731; AC02-05CH11231
- Resource Type:
- Accepted Manuscript
- Journal Name:
- npj Computational Materials
- Additional Journal Information:
- Journal Volume: 5; Journal Issue: 1; Journal ID: ISSN 2057-3960
- Publisher:
- Nature Publishing Group
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 36 MATERIALS SCIENCE
Citation Formats
Szilvási, Tibor, Chen, Benjamin W. J., and Mavrikakis, Manos. Identification of stable adsorption sites and diffusion paths on nanocluster surfaces: an automated scanning algorithm. United States: N. p., 2019.
Web. doi:10.1038/s41524-019-0240-x.
Szilvási, Tibor, Chen, Benjamin W. J., & Mavrikakis, Manos. Identification of stable adsorption sites and diffusion paths on nanocluster surfaces: an automated scanning algorithm. United States. https://doi.org/10.1038/s41524-019-0240-x
Szilvási, Tibor, Chen, Benjamin W. J., and Mavrikakis, Manos. Fri .
"Identification of stable adsorption sites and diffusion paths on nanocluster surfaces: an automated scanning algorithm". United States. https://doi.org/10.1038/s41524-019-0240-x. https://www.osti.gov/servlets/purl/1616952.
@article{osti_1616952,
title = {Identification of stable adsorption sites and diffusion paths on nanocluster surfaces: an automated scanning algorithm},
author = {Szilvási, Tibor and Chen, Benjamin W. J. and Mavrikakis, Manos},
abstractNote = {The diverse coordination environments on the surfaces of discrete, three-dimensional (3D) nanoclusters contribute significantly to their unique catalytic properties. Identifying the numerous adsorption sites and diffusion paths on these clusters is however tedious and time-consuming, especially for large, asymmetric nanoclusters. Here, we present a simple, automated method for constructing approximate 2D potential energy surfaces for the adsorption of atomic species on the surfaces of 3D nanoclusters with minimal human intervention. These potential energy surfaces fully characterize the important adsorption sites and diffusion paths on the nanocluster surfaces with accuracies similar to current approaches and at comparable computational cost. Our method can treat complex nanoclusters, such as alloy nanoclusters, and accounts for cluster relaxation and adsorbate-induced reconstruction, important for obtaining accurate energetics. Moreover, its highly parallelizable nature is ideal for modern supercomputer architectures. We showcase our method using two clusters: Au18 and Pt55. For Au18, diffusion of atomic hydrogen between the most stable sites occurs via non-intuitive paths, underlining the necessity of exploring the complete potential energy surface. By enabling the rapid and unbiased assessment of adsorption and diffusion on large, complex nanoclusters, which are particularly difficult to handle manually, our method will help advance materials discovery and the rational design of catalysts.},
doi = {10.1038/s41524-019-0240-x},
journal = {npj Computational Materials},
number = 1,
volume = 5,
place = {United States},
year = {Fri Oct 25 00:00:00 EDT 2019},
month = {Fri Oct 25 00:00:00 EDT 2019}
}
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