Classification Method and Rational Adjustment of Asphalt Four Component Molecules Based on Quantum Chemical Calculation
ABSTRACT Asphalt is composed of four main components, with over 50 different molecules identified to characterize asphaltenes, resins, aromatics, and saturates. However, there has been a lack of sufficient quantitative demonstration to determine the rationality of these molecules representing their respective components. In this investigation, 64 types of molecules representing the four components of asphalt were collected to develop a more realistic molecular model. Quantum chemical calculations were performed to determine the Mayer bond order, HOMO–LUMO gap, molecular mass, sp 2 hybrid carbon atom proportion, atomic charge, electrostatic potential, dipole moment, and molecular polarity index of the asphalt four‐component molecules. Based on the statistical analysis of the aforementioned indicators, the rationality of the classification was demonstrated, and appropriate adjustments were made. The results indicated that saturates could be classified by Mayer bond order; Asphaltenes could be classified by the HOMO–LUMO gap and molecular mass; Resins and aromatics could be classified by molecular polarity index, average Mayer bond order, and sp 2 hybrid carbon atom proportion. This investigation provided a feasible method for classifying the four components of asphalt at the nanoscale and was expected to provide theoretical guidance for multi‐scale investigation on asphalt performance.
Authors
- Shitong Yang (ORCID: https://orcid.org/0000-0002-8373-4813)
- Jie Zhu (ORCID: https://orcid.org/0000-0002-7620-8233)
- Shengxing Wu
- Dejian Shen (ORCID: https://orcid.org/0000-0002-0283-6835)
- Yufan Zhang (ORCID: https://orcid.org/0000-0002-3104-1070)
- Rongji Cao
- Chunying Wu
- Hao Feng (ORCID: https://orcid.org/0000-0002-0794-8422)
- G. Xia
Institutions
- Hohai University (CN)
- Jinling Institute of Technology (CN)
Publication Details
- Journal
- International Journal of Quantum Chemistry
- Published
- 2025-03-06
- DOI
- https://doi.org/10.1002/qua.70023
- Citations
- 2
- Primary Topic
- Petroleum Processing and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 1.50
Funders
- Jinling Institute of Technology
- Fundamental Research Funds for the Central Universities