Video Colorimetry of Single-Chromophore Systems based on Vector Analysis in the 3D Color Space: Unexpected Hysteresis Loops in Oscillating Chemical Reactions
Abstract
Colorimetry, the quantitative determination of color, usually of a digital image, has useful applications in diverse areas of research. Many methods have been proposed for translating the RGB data of an image to obtain concentration information. Among the many methods for RGB analysis, we focus on the vector projection method (VP), which is based on a vector analysis in 3D RGB color space. This method has the major advantages of being conceptually intelligible and generalizable to various systems. For solutions with variable concentrations of one chromophore, we will show that the analysis of the trace in RGB color space allows for a judgment about the reliability of the linear concentration dependence of the chromapostasi parameter. We discuss the theoretical underpinnings of the method in two test cases, a simple dye solution and a titration of an organic acid with phenolphthalein indicator. The VP method was then applied to the Ce-catalyzed Belousov-Zhabotinsky reaction with the expectation that the colorimetry would quantify [Ce4+] oscillations. Surprisingly, the 3D color space analysis revealed hysteresis loops and the origin and implications of this observation are discussed.
Recommended Citation
J. Schell et al., "Video Colorimetry of Single-Chromophore Systems based on Vector Analysis in the 3D Color Space: Unexpected Hysteresis Loops in Oscillating Chemical Reactions," Talanta, vol. 220, Elsevier, Dec 2020.
The definitive version is available at https://doi.org/10.1016/j.talanta.2020.121303
Department(s)
Chemistry
Research Center/Lab(s)
Center for High Performance Computing Research
Keywords and Phrases
Belousov-Zhabotinsky oscillating reaction; Colorimetry; Hysteresis loops; RGB Color space; Vector projection; Video-based kinetics
International Standard Serial Number (ISSN)
0039-9140
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2020 Elsevier, All rights reserved.
Publication Date
01 Dec 2020
PubMed ID
32928377
Comments
Missouri University of Science and Technology, Grant 1665487