Hybrid GA-gradient method for thin films ellipsometric data evaluation

•A global-search method is proposed for the ellipsometry data analysis.•Concept of genetic algorithm (GA) with gradient-based optimizer is proposed.•The method is applied to evaluate the ellipsometry data.•Samples with different structure complexity are evaluated.•Material parameters can be found even for limited a priori knowledge. A global-search method which applies the concept of genetic algorithm (GA) with gradient-based optimizer is proposed for the problem of experimental data analysis from spectroscopic ellipsometry on thin films. The method is applied to evaluate the data obtained for samples with different structure complexity, starting with transparent monolayers (SiO2, HfO2) on a substrate, through absorbing film (diamond-like carbon) and multilayer structures. We demonstrate that by using this method we are able to find material parameters even for limited a priori knowledge about the sample properties, where classical methods fail.