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

Authors
Yeo, InjoonLee, Jae WonKim, Sunghwan
Issue Date
20-Nov-2010
Publisher
WILEY-V C H VERLAG GMBH
Keywords
Petroleomics; FT-ICR MS; Clustering analysis; ESI
Citation
BULLETIN OF THE KOREAN CHEMICAL SOCIETY, v.31, no.11, pp.3151 - 3155
Indexed
SCIE
SCOPUS
KCI
Journal Title
BULLETIN OF THE KOREAN CHEMICAL SOCIETY
Volume
31
Number
11
Start Page
3151
End Page
3155
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/115313
DOI
10.5012/bkcs.2010.31.11.3151
ISSN
0253-2964
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
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