In order to obtain accurate nano-film characteristic parameters in the ellipsometry measurement process, an optimization algorithm for solving the thickness and complex refractive index of nano films by spectroscopic ellipsometry is proposed. An improved adaptive genetic algorithm (IAGA) has been proposed to process nano-film data, this method combines the evolutionary algebraic attenuation factor with the adaptive genetic algorithm. It can solve the problem that the genetic algorithm is premature and easy to fall into the local optimization. The algorithm is used to calculate the film parameters of silicon dioxide nano film thickness standard template with standard value of 49.7±0.4 nm in this paper. The results show that the relative error of the calculation results of the film thickness is less than 3%, and the error of refractive index is less than 0.1. At the same time, it is verified by experiments that the IAGA algorithm model can effectively optimize the number of iterations, and has the advantages of fast convergence speed and high measurement efficiency.
A method for solving bimetallic film coefficients using surface plasmon resonance (SPR) phase difference experimental data with fixed wavelength and multiple incident angles is presented to simplify and quickly solve the thickness and optical constants of metal films in this paper. The purpose is to extract unknown parameters from the phase difference between P- and S- polarizations of the reflected light occurred at the metal/dielectric interface. The results of bimetallic layer film’s thickness and optical constants obtained by our method are in better agreement with that of spectroscopic ellipsometer (SE) measurement method. Therefore, the approach reveals the possibility of retrieving the thickness and optical constants from the measurement results of the phase difference for multilayers, and makes it be a much better option to be employed for further film’s parameter analysis applications
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