Accurate Determination of the Molar Absorption Spectra of Unstable Organic Redox-State Species in Thin-Layer Electrolysis

Precise knowledge of the molar absorption spectra of redox (ionic) states is fundamental to understanding their electronic structures and to advancing quantitative models of charge-transfer and excitation processes. However, many redox species are intrinsically unstable, spontaneously reverting to their initial forms, thereby preventing direct spectroscopic isolation and challenging accurate determination of their molar absorption coefficients. Here, we develop a quantitative spectroelectrochemical framework that combines constraint-based multivariate curve resolution (MCR) with finite-difference simulations of thin-layer electrolysis coupled to nonlinear homogeneous back reactions. This integrated approach defines the physically feasible spectral domain, enables yield-corrected extraction of pure ionic spectra, and provides a self-consistent route to absolute molar absorption coefficients for otherwise inaccessible redox states. Validation through numerical simulations and experimentally measured thin-layer spectra demonstrates that the method achieves high quantitative accuracy in systems where conventional spectroelectrochemical or MCR approaches fail. Beyond improving data reliability, the framework supplies benchmark optical constants that strengthen connections between experiment and electronic-structure theory and support rational design in electrochromic, conducting-polymer, and energy-conversion systems.

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Publication Details

Journal
Analytical Chemistry
Published
2026-04-06
DOI
https://doi.org/10.1021/acs.analchem.5c07341
Primary Topic
Electrocatalysts for Energy Conversion
Type
article
Field-Weighted Citation Impact
0.00

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article

Accurate Determination of the Molar Absorption Spectra of Unstable Organic Redox-State Species in Thin-Layer Electrolysis

Yao Yu, Min Sun, Changhao Ruan, Yuguang Ma et al.
Analytical Chemistry
Electrocatalysts for Energy Conversion
article

Accurate Determination of the Molar Absorption Spectra of Unstable Organic Redox-State Species in Thin-Layer Electrolysis

Yao Yu, Min Sun, Changhao Ruan, Yuguang Ma, Bohan Wang
article en

Abstract

Precise knowledge of the molar absorption spectra of redox (ionic) states is fundamental to understanding their electronic structures and to advancing quantitative models of charge-transfer and excitation processes. However, many redox species are intrinsically unstable, spontaneously reverting to their initial forms, thereby preventing direct spectroscopic isolation and challenging accurate determination of their molar absorption coefficients. Here, we develop a quantitative spectroelectrochemical framework that combines constraint-based multivariate curve resolution (MCR) with finite-difference simulations of thin-layer electrolysis coupled to nonlinear homogeneous back reactions. This integrated approach defines the physically feasible spectral domain, enables yield-corrected extraction of pure ionic spectra, and provides a self-consistent route to absolute molar absorption coefficients for otherwise inaccessible redox states. Validation through numerical simulations and experimentally measured thin-layer spectra demonstrates that the method achieves high quantitative accuracy in systems where conventional spectroelectrochemical or MCR approaches fail. Beyond improving data reliability, the framework supplies benchmark optical constants that strengthen connections between experiment and electronic-structure theory and support rational design in electrochromic, conducting-polymer, and energy-conversion systems.

Analytical ChemistryVol. 98(15)
Advanced Materials and Devices (United States) (US), State Key Laboratory of Luminescent Materials and Devices, South China University of Technology (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China, Guangdong Provincial Key Laboratory of Luminescence from Molecular Aggregates, South China University of Technology
Affordable and clean energy
Openalex Percentile: Top 28%
Electrocatalysts for Energy Conversion
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