Combination of a global-search method with model selection criteria for the ellipsometric data evaluation of DLC coatings

A method for the evaluation of experimental data from spectroscopic ellipsometry is proposed which combines the global-search optimization algorithm with statistical model selection criteria. The hybrid geneticgradient search algorithm (HGGA) is applied to find the optical parameters and thickness of a diamond-like carbon (DLC) coating deposited on SW7M stainless steel. Akaike and Bayesian information criteria are used to evaluate the different dielectric function models. The method is able to find optical model parameters even in case of a limited initial knowledge about the material optical constants. At the same time, the optimal dielectric function model for the description of the material optical properties can be selected unambiguously from the set of candidate models.

Automated summary

A new method for evaluating experimental data from spectroscopic ellipsometry is proposed, which combines the global-search optimization algorithm with statistical model selection criteria. This method is able to find the optical model parameters and select the optimal dielectric function model for describing the optical properties of materials even with limited initial knowledge.