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Halide-induced Step Faceting and Dissolution Energetics from Atomistic Machine Learned Potentials on Cu(100).
Mitchell C Groenenboom1, Thomas P Moffat1, Kathleen A Schwarz1
1Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD 20899-8520 USA.
Chlorine adsorbates on copper surfaces alter step structures and reactivity. This study uses density functional theory (DFT) and neural networks to reveal how chlorine influences copper’s dissolution and deposition behavior at the atomic level.
Area of Science:
- Surface Science
- Computational Materials Science
- Electrochemistry
Background:
- Adsorbates significantly influence the surface stability and reactivity of metallic electrodes.
- Understanding these effects is crucial for controlling corrosion, dissolution, and deposition processes.
Purpose of the Study:
- To investigate the geometric and energetic properties of stepped and kinked Cu(100) surfaces with a c(2×2) Cl adlayer.
- To determine the impact of chlorine adsorption on surface stability and atom removal energies.
Main Methods:
- Density Functional Theory (DFT) calculations were employed to study surface structures and energies.
- DFT-based Behler-Parrinello neural networks (BPNN) were developed and validated against DFT results for accurate energy calculations.
- Scanning tunneling microscopy (STM) observations were used for comparison with theoretical predictions.
Main Results:
- Adsorbate-free surfaces favor <110> step orientations, while chlorine adsorption induces <100> step facets, consistent with STM data.
- BPNN calculations achieved high accuracy (1.3 meV/atom RMSE) compared to DFT.
- Chlorine atoms occupy three-fold hollow sites at <100> step edges, and halide overlayer disruptions lead to long-range step-step interactions.
Conclusions:
- Chlorine adsorption significantly alters copper surface structures and energetics, favoring <100> step facets.
- Long-range interactions between steps and anisotropic dissolution/deposition energetics are driven by the halide adlayer.
- The combined DFT-BPNN approach provides an effective method for large-scale surface science studies with atomic precision.
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