Resolving Peak Overlap in HPLC Analysis of Glycerol Oxidation Products by Utilizing Various Detectors: Application to BiVO<sub>4</sub> Photoanodes

Glycerol, often considered a waste byproduct of biodiesel production, holds the potential for conversion into chemicals of varying economic value, such as dihydroxyacetone (DHA) and formic acid (FA). Hence, accurate identification and quantification of glycerol oxidation reaction (GOR) products are crucial for glycerol valorization research and practical deployment. High-performance liquid chromatography (HPLC) is the preferred analytical method for these purposes due to its proficiency in separating and quantifying components in liquid mixtures, even in the presence of diluted solutes. On the other hand, peak overlap in chromatograms, especially among glycerol, DHA, and FA, poses a notable challenge in the analysis of GOR products. This study introduces a quantification method aimed at resolving peak overlaps in HPLC analysis of GOR products. Initially, we examine the optical properties of glycerol and GOR products to identify optimal wavelengths for spectrophotometric HPLC analysis and detection. Subsequently, we propose an algebraic approach to resolve the peak overlap of glycerol, DHA, and FA using various detectors, including the refractive index detector (RID) and the variable wavelength detector (VWD). This method is applied to analyze the GOR products of undoped, nonco-catalyzed nanoporous BiVO<sub>4</sub> photoanodes, which have shown an intrinsic catalytic activity toward GOR products in previous studies.

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Publication Details

Journal
ACS Omega
Published
2025-03-18
DOI
https://doi.org/10.1021/acsomega.4c07497
Citations
3
Primary Topic
Gas Sensing Nanomaterials and Sensors
Type
article
Field-Weighted Citation Impact
2.19
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article

Resolving Peak Overlap in HPLC Analysis of Glycerol Oxidation Products by Utilizing Various Detectors: Application to BiVO4 Photoanodes

Camilo Arturo Mesa, Eva Ng, Fatwa F. Abdi, Sixto Giménez et al.
3 citations
ACS Omega
Gas Sensing Nanomaterials and Sensors
2.19
article

Resolving Peak Overlap in HPLC Analysis of Glycerol Oxidation Products by Utilizing Various Detectors: Application to BiVO4 Photoanodes

Camilo Arturo Mesa, Eva Ng, Fatwa F. Abdi, Sixto Giménez, Heejung Kong, Marco Favaro, Siddharth Gupta, Roel van de Krol, Matthew T. Mayer
article en
3 citations

Abstract

Glycerol, often considered a waste byproduct of biodiesel production, holds the potential for conversion into chemicals of varying economic value, such as dihydroxyacetone (DHA) and formic acid (FA). Hence, accurate identification and quantification of glycerol oxidation reaction (GOR) products are crucial for glycerol valorization research and practical deployment. High-performance liquid chromatography (HPLC) is the preferred analytical method for these purposes due to its proficiency in separating and quantifying components in liquid mixtures, even in the presence of diluted solutes. On the other hand, peak overlap in chromatograms, especially among glycerol, DHA, and FA, poses a notable challenge in the analysis of GOR products. This study introduces a quantification method aimed at resolving peak overlaps in HPLC analysis of GOR products. Initially, we examine the optical properties of glycerol and GOR products to identify optimal wavelengths for spectrophotometric HPLC analysis and detection. Subsequently, we propose an algebraic approach to resolve the peak overlap of glycerol, DHA, and FA using various detectors, including the refractive index detector (RID) and the variable wavelength detector (VWD). This method is applied to analyze the GOR products of undoped, nonco-catalyzed nanoporous BiVO<sub>4</sub> photoanodes, which have shown an intrinsic catalytic activity toward GOR products in previous studies.

ACS OmegaVol. 10(12)
Universitat Jaume I (ES), City University of Hong Kong (HK), Helmholtz-Zentrum Berlin für Materialien und Energie (DE), Institute of Chemistry (CN), Technische Universität Berlin (DE), Freie Universität Berlin (DE)
Openalex Percentile: Top 13%
Gas Sensing Nanomaterials and Sensors
2.19
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