Color Simulation of Multilayered Thin Films Using Python

Physical insight into a material can be first gained by its color, as the reflectance spectrum of an object reflects its microstructure and complex refractive indices. Here, we present a comprehensive overview of electrodynamics and optics related to reflectance spectra and color. We provide an open-source Python code for simulating reflectance spectra and extracting color values. The validity and applicability of the code are demonstrated through a comparative analysis with both the literature and experimental data. For SnO2 and ZnO thin films deposited on SiO2/Si substrates using rf sputtering, the Python code and simulation predict color variations with the film thickness and effectively capture their angular dependence. This code will help in understanding and making use of color-related phenomena. It can be further used and developed for various purposes, particularly machine learning, which requires extensive spectral and color data for model training.

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Publication Details

Journal
Applied Sciences
Published
2025-04-26
DOI
https://doi.org/10.3390/app15094814
Citations
1
Primary Topic
Photonic Crystals and Applications
Type
article
Field-Weighted Citation Impact
1.25

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article

Color Simulation of Multilayered Thin Films Using Python

Dongik Lee, Seunghun Lee
1 citations
Applied Sciences
Photonic Crystals and Applications
1.25
article

Color Simulation of Multilayered Thin Films Using Python

Dongik Lee, Seunghun Lee
article en
1 citations

Abstract

Physical insight into a material can be first gained by its color, as the reflectance spectrum of an object reflects its microstructure and complex refractive indices. Here, we present a comprehensive overview of electrodynamics and optics related to reflectance spectra and color. We provide an open-source Python code for simulating reflectance spectra and extracting color values. The validity and applicability of the code are demonstrated through a comparative analysis with both the literature and experimental data. For SnO2 and ZnO thin films deposited on SiO2/Si substrates using rf sputtering, the Python code and simulation predict color variations with the film thickness and effectively capture their angular dependence. This code will help in understanding and making use of color-related phenomena. It can be further used and developed for various purposes, particularly machine learning, which requires extensive spectral and color data for model training.

Applied SciencesVol. 15(9)
Pukyong National University (KR)
National Research Foundation, National Research Foundation of Korea, Ministry of Education, India
Openalex Percentile: Top 22%
Photonic Crystals and Applications
1.25
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Color Simulation of Multilayered Thin Films Using Python — Dongik Lee, Seunghun Lee · Applied Sciences (2025) | TGRS Research Map | TGRS