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Complex oscillatory decrease with size in diffusivity of {100}-epitaxially supported 3D fcc metal nanoclusters.

King C Lai1, James W Evans1

  • 1Division of Chemical & Biological Sciences, Ames Laboratory, USDOE and Department of Physics & Astronomy, Iowa State University, Ames IA 50011, USA. kclai@iastate.edu evans@ameslab.gov.

Nanoscale
|September 19, 2019
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Summary
This summary is machine-generated.

Smoluchowski Ripening (SR) degrades catalysts. New simulations reveal metal nanocluster (NC) diffusion coefficients oscillate with size, challenging traditional models and offering insights into catalyst stability.

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Area of Science:

  • Materials Science
  • Surface Science
  • Nanotechnology

Background:

  • Supported 3D metal nanoclusters (NCs) undergo diffusion and coalescence, leading to Smoluchowski Ripening (SR), a primary mechanism for catalyst degradation.
  • The kinetics of SR are governed by the variation of the NC diffusion coefficient (DN) with size (N).
  • Previous studies assumed a simple power-law relationship (DN∼N-β) based on mean-field analysis.

Purpose of the Study:

  • To investigate the size-dependent diffusion coefficient (DN) of supported fcc metal nanoclusters using a stochastic model.
  • To elucidate the relationship between nanocluster shape, surface diffusion energetics, and diffusion kinetics.
  • To provide a more accurate understanding of Smoluchowski Ripening and catalyst degradation pathways.

Main Methods:

  • Kinetic Monte Carlo (KMC) simulations of a stochastic model for nanocluster diffusion on {100}-epitaxial surfaces.
  • Incorporation of realistic surface diffusion barriers for metal atoms, considering facet, step edge, and inter-facet diffusion.
  • Analytic characterization of energetics along the nanocluster diffusion pathway.

Main Results:

  • The nanocluster diffusion coefficient (DN) exhibits a complex, oscillatory decrease with size (N), deviating from the traditional power-law assumption.
  • For strongly adhered nanoclusters (truncated pyramids), local minima in DN correlate with, but do not always coincide with, closed-shell structures.
  • For weakly adhered nanoclusters (truncated octahedra), local minima in DN are observed near specific closed-shell sizes.

Conclusions:

  • The study reveals a nuanced, size-dependent behavior of nanocluster diffusion, crucial for understanding Smoluchowski Ripening.
  • Realistic modeling of surface diffusion energetics is essential for accurately predicting nanocluster dynamics and catalyst stability.
  • The findings challenge existing models and provide fundamental insights into the factors governing catalyst degradation.