Metasurface Optic Features Using Metal-Assisted Chemical Etching (MACE)
Authors: St John Christopher , Arrington Christian L. , Coleman Jonathan , Risley Mason , Burckel David Bruce 
Published: December 2024

Metal-assisted chemical etching (MACE or MacEtch) is a versatile method for fabricating nano and micro-structured silicon (Si), which has garnered significant attention due to its potential applications in photovoltaics, sensors, and nanoelectronics. The process involves the oxidation of Si in the presence of a metal catalyst (typically noble metals like Au, Ag, or Pt) and a wet etch solution, usually comprising hydrofluoric acid (HF) and an oxidizing agent such as hydrogen peroxide (H2O2).
Impressive work has already been completed in the two decades following the introduction of this method through the field of stain etching [1]. Researchers have reported anisotropic structures in silicon as high as 10,000:1 aspect ratio [2] and studied the impact of catalyst thickness [3], geometry [4], chemical ratios [5][6], and level of doping [7].
In this work, we systematically tune the selectivity of the MACE process based on the geometry of desired structures, chemical ratios of HF, H2O2 and ethanol, silicon doping types, and characteristics of the metal catalyst targeting our desired metasurface optic features. We use statistical analysis such as ensemble machine learning algorithms to create an informed understanding and importance matrix for each of these variables, toward the purpose of creating refractive optical features in silicon. The important parameters in the desired final product are vertical sidewalls, 10:1 aspect ratio, minimized surface roughness in the field, an optimized geometry, and a target depth.
This comprehensive statistical analysis contributes to a deeper understanding of the MACE process, offering valuable guidelines for optimizing etching conditions to achieve desired micron to nanometer structures in silicon. The findings hold promise for advancing the fabrication of silicon-based nano-devices, paving the way for novel applications in various technological fields.

SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525

SAND2024-04791A
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Figure 1