Extracting film thickness and optical constants from spectrophotometric data by evolutionary optimization
<jats:p>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...
| Main Authors: | , , , , , , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2023
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| Online Access: | https://hdl.handle.net/1721.1/150807 |
| _version_ | 1826217605302583296 |
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| author | Dutta, Rajdeep Tian, Siyu Isaac Parker Liu, Zhe Lakshminarayanan, Madhavkrishnan Venkataraj, Selvaraj Cheng, Yuanhang Bash, Daniil Chellappan, Vijila Buonassisi, Tonio Jayavelu, Senthilnath |
| author2 | Massachusetts Institute of Technology. Department of Mechanical Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Mechanical Engineering Dutta, Rajdeep Tian, Siyu Isaac Parker Liu, Zhe Lakshminarayanan, Madhavkrishnan Venkataraj, Selvaraj Cheng, Yuanhang Bash, Daniil Chellappan, Vijila Buonassisi, Tonio Jayavelu, Senthilnath |
| author_sort | Dutta, Rajdeep |
| collection | MIT |
| description | <jats:p>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.</jats:p> |
| first_indexed | 2024-09-23T17:06:20Z |
| format | Article |
| id | mit-1721.1/150807 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T17:06:20Z |
| publishDate | 2023 |
| publisher | Public Library of Science (PLoS) |
| record_format | dspace |
| spelling | mit-1721.1/1508072023-05-25T03:00:48Z Extracting film thickness and optical constants from spectrophotometric data by evolutionary optimization Dutta, Rajdeep Tian, Siyu Isaac Parker Liu, Zhe Lakshminarayanan, Madhavkrishnan Venkataraj, Selvaraj Cheng, Yuanhang Bash, Daniil Chellappan, Vijila Buonassisi, Tonio Jayavelu, Senthilnath Massachusetts Institute of Technology. Department of Mechanical Engineering <jats:p>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.</jats:p> 2023-05-24T18:45:42Z 2023-05-24T18:45:42Z 2022 2023-05-24T18:43:37Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/150807 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). en 10.1371/JOURNAL.PONE.0276555 PLoS ONE Creative Commons Attribution http://creativecommons.org/licenses/by/4.0/ application/pdf Public Library of Science (PLoS) PLOS |
| spellingShingle | Dutta, Rajdeep Tian, Siyu Isaac Parker Liu, Zhe Lakshminarayanan, Madhavkrishnan Venkataraj, Selvaraj Cheng, Yuanhang Bash, Daniil Chellappan, Vijila Buonassisi, Tonio Jayavelu, Senthilnath Extracting film thickness and optical constants from spectrophotometric data by evolutionary optimization |
| title | Extracting film thickness and optical constants from spectrophotometric data by evolutionary optimization |
| title_full | Extracting film thickness and optical constants from spectrophotometric data by evolutionary optimization |
| title_fullStr | Extracting film thickness and optical constants from spectrophotometric data by evolutionary optimization |
| title_full_unstemmed | Extracting film thickness and optical constants from spectrophotometric data by evolutionary optimization |
| title_short | Extracting film thickness and optical constants from spectrophotometric data by evolutionary optimization |
| title_sort | extracting film thickness and optical constants from spectrophotometric data by evolutionary optimization |
| url | https://hdl.handle.net/1721.1/150807 |
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