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Scaling behavior of cyclical surface growth
1Department of Physics and Astronomy, University of Rochester, Rochester, New York 14627, USA.
Physical Review Letters
|October 6, 2000
Summary
Surface roughness in cyclical growth, like deposition and desorption, follows predictable scaling laws. The dominant process dictates the asymptotic behavior, while both processes influence the overall amplitude, confirmed by simulations and silver electrodeposition experiments.
Area of Science:
- Surface science
- Materials science
- Condensed matter physics
Background:
- Cyclical surface growth processes, such as deposition and desorption, are fundamental in various scientific and industrial applications.
- Understanding the scaling behavior of surface roughness is crucial for controlling material properties and predicting film morphology.
Purpose of the Study:
- To investigate the scaling behavior of surface roughness during cyclical growth as a function of the number of cycles, n.
- To determine how linear primary processes and their nonlinear effects influence surface scaling exponents and amplitudes.
- To validate theoretical predictions with numerical simulations and experimental data.
Main Methods:
- Theoretical analysis of scaling behavior for surfaces grown by two linear primary processes.
- Numerical simulations of generic primary process pairs to confirm theoretical conclusions.
- Experimental measurement of surface roughness during cyclical electrodeposition/dissolution of silver.
Main Results:
- Surface roughness exhibits scaling behavior with the number of cycles, n.
- Asymptotic exponents are inherited from the dominant linear process, while effective amplitudes depend on both processes.
- Numerical simulations and experimental results for silver electrodeposition confirm the power-law dependence on n and the scaling description.
Conclusions:
- The scaling description accurately characterizes cyclical surface growth.
- The interplay between dominant and secondary processes dictates the surface morphology evolution.
- The findings are consistent across theoretical models, numerical simulations, and experimental observations.
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