Extracting film thickness and optical constants from spectrophotometric data by evolutionary optimization
Name
journal.pone.0276555.pdf
Description
Published version
Size
2.27 MB
Format
Adobe PDF
Checksum (MD5)
17e81143b47a14d84a248b7bbdffb021
Author(s)
Dutta, Rajdeep
Tian, Siyu Isaac Parker
Liu, Zhe
Lakshminarayanan, Madhavkrishnan
Venkataraj, Selvaraj
Cheng, Yuanhang
Bash, Daniil
Chellappan, Vijila
Buonassisi, Tonio
Jayavelu, Senthilnath
Date Issued
2022
Journal
PLoS ONE
Publisher
Public Library of Science (PLoS)
Citation
Dutta, Rajdeep, Tian, Siyu Isaac Parker, Liu, Zhe, Lakshminarayanan, Madhavkrishnan, Venkataraj, Selvaraj et al. 2022. "Extracting film thickness and optical constants from spectrophotometric data by evolutionary optimization." PLoS ONE, 17 (11).
Version
Final published version
Abstract
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.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1371/JOURNAL.PONE.0276555
