A statistical method to optimize the chemical etching process of Zinc Oxide thin films

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.