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Application of Clustering Methods for Interpretation of Petroleum Spectra from Negative-Mode ESI FT-ICR MS

  • Yeo, In-Joon (Kyungpook National University, Department of Chemistry) ;
  • Lee, Jae-Won (Korea University, Department of Statistics) ;
  • Kim, Sung-Hwan (Kyungpook National University, Department of Chemistry)
  • Received : 2010.08.14
  • Accepted : 2010.09.30
  • Published : 2010.11.20

Abstract

This study was performed to develop analytical methods to better understand the properties and reactivity of petroleum, which is a highly complex organic mixture, using high-resolution mass spectrometry and statistical analysis. Ten crude oil samples were analyzed using negative-mode electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI FT-ICR MS). Clustering methods, including principle component analysis (PCA), hierarchical clustering analysis (HCA), and k-means clustering, were used to comparatively interpret the spectra. All the methods were consistent and showed that oxygen and sulfur-containing heteroatom species played important roles in clustering samples or peaks. The oxygen-containing samples had higher acidity than the other samples, and the clustering results were linked to properties of the crude oils. This study demonstrated that clustering methods provide a simple and effective way to interpret complex petroleomic data.

Keywords

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