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Determination of Peak Purity in HPLC by Coupling Coulometric Array Detection and Two-Dimensional Correlation Analysis
Julio Enrique Oney-Montalvo1, Ksenia Morozova2, Manuel Octavio Ramírez-Sucre1
1Centro de Investigación y Asistencia en Tecnología y Diseño del Estado de Jalisco, A.C. Sede Sureste, Tablaje Catastral No. 31264, km 5.5 Carretera Sierra Papacal-Chuburna Puerto, Interior del Parque Científico y Tecnológico Yucatán, Mérida 97302, Yucatán, Mexico.
Two-dimensional correlation (2D-corr) analysis effectively verifies chromatographic peak purity by identifying overlapping compounds. This method enhances the analysis of complex mixtures, such as Capsicum chili extracts, ensuring accurate results.
Area of Science:
- Analytical Chemistry
- Chromatography
- Spectroscopy
Background:
- Chromatographic peak purity is crucial for accurate compound identification and quantification.
- Overlapping peaks can lead to misinterpretation of results in complex sample analyses.
Purpose of the Study:
- To evaluate the utility of two-dimensional correlation (2D-corr) analysis for assessing chromatographic peak purity.
- To demonstrate the capability of 2D-corr analysis in detecting coeluting species within chromatographic peaks.
Main Methods:
- Two-dimensional correlation (2D-corr) analysis was applied to chromatographic data.
- High-performance liquid chromatography (HPLC) coupled with a 16-detector coulometric array was used.
- Mass spectrometry (MS) was employed for coeluting species identification.
Main Results:
- 2D-corr analysis successfully identified the number of peaks and revealed overlapping species.
- Analysis of Capsicum chili extracts showed at least three overlapping species on a single peak.
- Coeluting species were identified as quinic acid, ascorbic acid, and phenylalanine.
Conclusions:
- 2D-corr analysis is a valuable tool for verifying chromatographic signal purity.
- The method effectively detects and helps resolve overlapping compounds in complex mixtures.
- This approach enhances the reliability of chromatographic analyses.
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