Extracting film thickness and optical constants from spectrophotometric data by evolutionary optimization.

Autor: Dutta R; Institute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore., Tian SIP; Low Energy Electronic Systems (LEES), Singapore-MIT Alliance for Research and Technology (SMART), Singapore, Singapore.; Solar Energy Research Institute of Singapore (SERIS), National University of Singapore, Singapore, Singapore., Liu Z; Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States of America., Lakshminarayanan M; Institute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore., Venkataraj S; Solar Energy Research Institute of Singapore (SERIS), National University of Singapore, Singapore, Singapore., Cheng Y; Solar Energy Research Institute of Singapore (SERIS), National University of Singapore, Singapore, Singapore., Bash D; Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore., Chellappan V; Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore., Buonassisi T; Low Energy Electronic Systems (LEES), Singapore-MIT Alliance for Research and Technology (SMART), Singapore, Singapore.; Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States of America., Jayavelu S; Institute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.; Artificial Intelligence, Analytics And Informatics (AI3), A*STAR, Singapore, Singapore.
Jazyk: angličtina
Zdroj: PloS one [PLoS One] 2022 Nov 30; Vol. 17 (11), pp. e0276555. Date of Electronic Publication: 2022 Nov 30 (Print Publication: 2022).
DOI: 10.1371/journal.pone.0276555
Abstrakt: In this paper, we propose a simple and elegant method to extract the thickness and the optical constants of various films from the reflectance and transmittance spectra in the wavelength range of 350 - 1000 nm. The underlying inverse problem is posed here as an optimization problem. To find unique solutions to this problem, we adopt an evolutionary optimization approach that drives a population of candidate solutions towards the global optimum. An ensemble of Tauc-Lorentz Oscillators (TLOs) and an ensemble of Gaussian Oscillators (GOs), are leveraged to compute the reflectance and transmittance spectra for different candidate thickness values and refractive index profiles. This model-based optimization is solved using two efficient evolutionary algorithms (EAs), namely genetic algorithm (GA) and covariance matrix adaptation evolution strategy (CMAES), such that the resulting spectra simultaneously fit all the given data points in the admissible wavelength range. Numerical results validate the effectiveness of the proposed approach in estimating the optical parameters of interest.
Competing Interests: The authors have declared that no competing interests exist.
(Copyright: © 2022 Dutta et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Databáze: MEDLINE
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