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Mechanistic Insights into Nanostructure Formation via Phase-Field Modeling and Experimental Validation of Metal-Assisted Chemical Etching
Kun-Dar Li a and David T.W. Lin a
aProfessor, Department of Materials Science, National University of Tainan, Tainan, Taiwan 70005, ROC.
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Abstract:
Metal-assisted chemical etching (MACE) is crucial for modifying semiconductor surface morphol¬ogy, especially in fabricating extremely high aspect ratio structures for silicon. This study combines phase-field modeling and experiments to explore MACE mechanisms. Numerical simulations show that metal catalyst characteristics, especially particle size, signif¬icantly affect surface evolution. Larger particles create deeper cavities and rougher surfaces while maintain¬ing etching rates. Particle distribution patterns have minimal impact. Experiments with Au-coated GaAs substrates validate the model, showing strong agree¬ment between simulations and actual morphologies. Under the conditions of high oxidant concentrations, the etching reactions and surface morphological features are enhanced due to the accelerated rate of chemical reactions. This work provides a computa¬tional framework for optimizing MACE, offering insights for nanoelectronics, photovoltaics, and sensors. The phase-field modeling approach is a pow¬erful tool for nanoscale surface engineering.
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Keywords: metal-assisted chemical etching, phase-field modeling, nanostructure fabrication surface morphology, numerical simulation
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©
2026
CSME , ISSN 0257-9731
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