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Multi-scale Simulation of Equilibrium Step Fluctuations on Cu(111) Surfaces
Harry Handoko Halim1, Septia Eka Marsha Putra1, Fahdzi Muttaqien2,3
1Department of Precision Engineering, Graduate School of Engineering, Osaka University, 2-1, Yamada-oka, Suita, Osaka 565-0871, Japan.
ACS Omega
|March 8, 2021
Summary
Investigating copper (Cu) surface diffusion using density functional theory-kinetic Monte Carlo (DFT-KMC) reveals step edge diffusion as the primary mass transport mechanism. This study clarifies catalyst reconstruction dynamics under reaction conditions.
Area of Science:
- Materials Science
- Surface Science
- Computational Chemistry
Background:
- Understanding catalyst active site dynamics is crucial but challenging due to sensitivity to reaction conditions.
- Catalyst reconstruction involves complex processes, with surface diffusion being a key elementary step.
Purpose of the Study:
- To investigate the microscopic mechanisms of copper (Cu) surface diffusion, particularly in the presence of defects like steps and kinks.
- To elucidate the dominant mass transport pathways during catalyst evolution under reaction conditions.
Main Methods:
- Density Functional Theory-Kinetic Monte Carlo (DFT-KMC) simulations were employed.
- Cluster Expansion (CE) was utilized in conjunction with DFT-KMC.
- Analysis of surface diffusion events, energetics, and time correlation functions at various temperatures (300 K, 400 K, 500 K).
Main Results:
- Energetics derived from CE showed good agreement with DFT calculations.
- Diffusion along the step edge was identified as the dominant mass transport mechanism due to the lowest activation energy.
- Time correlation functions were calculated, though power law behavior was limited by finite step length and kink density variation.
Conclusions:
- The study provides insights into the microscopic mechanisms governing Cu surface diffusion and catalyst reconstruction.
- Step edge diffusion is highlighted as a critical pathway for mass transport in defective Cu surfaces.
- The findings contribute to a better understanding of catalyst behavior under dynamic reaction environments.
