A statistical method to optimize the chemical etching process of Zinc Oxide thin films
Cite this dataset
Chandrahalim, Hengky et al. (2021). A statistical method to optimize the chemical etching process of Zinc Oxide thin films [Dataset]. Dryad. https://doi.org/10.5061/dryad.73n5tb2xx
Zinc Oxide (ZnO) is an attractive material for micro and nanoscale devices. Its desirable semiconductor, piezoelectric, and optical properties make it useful in applications ranging from microphones to missile warning systems to biometric sensors. This work introduces a demonstration of blending statistics and chemical etching of thin films to identify the dominant factors, and interaction between factors, and develop statistically enhanced models on etch rate and selectivity of ZnO thin films. Over other mineral acids, ammonium chloride (NH4Cl) solutions have commonly been used to wet etch microscale ZnO devices because of their controllable etch rate and near-linear behavior. Etchant concentration and temperature were found to have a significant effect on etch rate. Moreover, this is the first demonstration that has identified multifactor interactions between temperature and concentration and between temperature and agitation. A linear model was developed relating etch rate and its variance against these significant factors and multifactor interactions. An average selectivity of 73:1 was measured with none of the experimental factors having a significant effect on the selectivity. This statistical study captures the significant variance observed by other researchers. Furthermore, it enables statistically enhanced microfabrication processes for other materials.
Air Force Institute of Technology
United States Air Force Research Laboratory