Semi-quantitative analysis of molecular composition for petroleum fractions using electrospray ionization high-resolution mass spectrometry. (1st March 2023)

• Record Type: Journal Article
• Authors: Li, Shuofan; Wu, Jianxun; Wang, Yidi; Li, Yunyun; Zhang, Weilai; Zhang, Yahe; He, Kaiyuan; Cai, Chuxuan; Bian, Gangyue; Wang, Hangzhou; Ji, Ye; Shi, Quan
• Is Part Of: Fuel. Volume 335(2023)
• Publication Date: 2023-03-01
• Subjects: Molecular composition -- Semi-quantitative analysis -- Electrospray ionization -- High-resolution mass spectrometry; Fuel -- Periodicals; Coal -- Periodicals; Coal; Fuel; Periodicals; 662.6
• DOI: 10.1016/j.fuel.2022.127049
• Languages: English
• ISSNs: 0016-2361

Abstract

Graphical abstract: Highlights: Semi-quantitative analysis of molecular composition for heavy petroleum fractions was carried out. All compounds were characterized by only ESI coupled with high-resolution MS. Molecular composition was calculated and integrated quantitatively based on bulk chemical composition. Four heavy petroleum fractions were comprehensively characterized. More than 5000 molecules of 16 compound classes were semi-quantitatively characterized from VGOs. Abstract: The developments of high-resolution mass spectrometry and soft ionization technologies have enabled the molecular characterization of petroleum fractions. However, quantitative analysis of molecular composition for petroleum is far from being achieved. In this study, semi-quantitative analysis of molecular composition for the whole compounds in heavy petroleum fractions was carried out. Hydrocarbons and various heteroatoms in the heavy petroleum fractions were characterized by only electrospray ionization coupled with high-resolution mass spectrometry. The molecular composition of various types of compounds were calculated and integrated quantitatively based on bulk chemical composition. The semi-quantitative molecular compositions of four heavy petroleum fractions with largely different bulk properties were comprehensively characterized in multiple dimensions such as carbon number distribution, condensation degree, molecular weight, mass fraction, and molecule number. More than 5, 000 molecules, which classified into 16 compound classes of seven groups were quantitatively characterized from the four fractions. The accuracy of the analysis seems acceptable according the H/C ratio comparation between that derived from element analysis and the semi-quantitative molecular composition. Representative molecule set containing structural information was also proposed based on the semi-quantitative results.