Visible-near-infrared reflectance spectra of Cr2O3-based biomimetic leaves: A combined spectroscopic ellipsometry and first-principles study

The quest for biomimetic materials that emulate the solar spectral response of green plants has garnered substantial attention. Herein, we combined density-functional theory with on-site Coulomb corrections and spectroscopic ellipsometry to obtain the complex dielectric functions of chromium oxide (Cr 2 O 3 ) pigment and polyurethane (PU) binder, respectively. Based on the Lorenz-Mie scattering theory and two-flux method considering anisotropic scattering, we systematically studied the regulatory mechanism of particle structural parameters on the reflectance spectrum of the biomimetic coating. The results show that optimizing the structural parameters of Cr 2 O 3 particles reproduces the canonical vegetation features in the visible-near-infrared region. Coating reflectance decreases monotonically with both increasing particle volume fraction and larger mean radius. Additionally, the slope of red edge can be independently tuned by the particle size distribution, i.e. a larger proportion of small particles steepens the red-edge slope. This study provides a theoretical basis and data support for further optimizing the similarity between biomimetic coatings and natural vegetation in terms of their hyperspectral images in the visible-near infrared spectral range. • Multiscale simulation of spectral characteristics for Cr 2 O 3 biomimetic leaves. • Increasing the particle volume fraction lowers the overall reflectance. • Reducing the average radius causes CIE chromaticity closer to natural leaves. • A higher proportion of small-radius particles yields a steeper red-edge slope.

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Publication Details

Journal
Materials Science in Semiconductor Processing
Published
2025-12-05
DOI
https://doi.org/10.1016/j.mssp.2025.110325
Primary Topic
Remote Sensing in Agriculture
Type
article
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article

Visible-near-infrared reflectance spectra of Cr2O3-based biomimetic leaves: A combined spectroscopic ellipsometry and first-principles study

Linhua Liu, Zhiming Liu, Zhongbo Su, Jia‐Yue Yang et al.
Materials Science in Semiconductor Processing
Remote Sensing in Agriculture
article

Visible-near-infrared reflectance spectra of Cr2O3-based biomimetic leaves: A combined spectroscopic ellipsometry and first-principles study

Linhua Liu, Zhiming Liu, Zhongbo Su, Jia‐Yue Yang, Tianbao Zhao, Jiayi Zheng, Tao Cheng, Meng Zhao
article en

Abstract

The quest for biomimetic materials that emulate the solar spectral response of green plants has garnered substantial attention. Herein, we combined density-functional theory with on-site Coulomb corrections and spectroscopic ellipsometry to obtain the complex dielectric functions of chromium oxide (Cr 2 O 3 ) pigment and polyurethane (PU) binder, respectively. Based on the Lorenz-Mie scattering theory and two-flux method considering anisotropic scattering, we systematically studied the regulatory mechanism of particle structural parameters on the reflectance spectrum of the biomimetic coating. The results show that optimizing the structural parameters of Cr 2 O 3 particles reproduces the canonical vegetation features in the visible-near-infrared region. Coating reflectance decreases monotonically with both increasing particle volume fraction and larger mean radius. Additionally, the slope of red edge can be independently tuned by the particle size distribution, i.e. a larger proportion of small particles steepens the red-edge slope. This study provides a theoretical basis and data support for further optimizing the similarity between biomimetic coatings and natural vegetation in terms of their hyperspectral images in the visible-near infrared spectral range. • Multiscale simulation of spectral characteristics for Cr 2 O 3 biomimetic leaves. • Increasing the particle volume fraction lowers the overall reflectance. • Reducing the average radius causes CIE chromaticity closer to natural leaves. • A higher proportion of small-radius particles yields a steeper red-edge slope.

Materials Science in Semiconductor ProcessingVol. 204
Shandong University (CN), Beijing Chemical Industry Research Institute (China) (CN)
Openalex Percentile: Top 62%
Remote Sensing in Agriculture
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