Prediction of Molecular Structure of Asphaltenes in Heavy Oils

Asphaltene is a crucial component of petroleum. The molecular structure is difficult to determine, posing challenges for its analysis and application. In this study, a program named Prediction of Molecular Structures of Asphaltenes (PMSA) was developed to predict asphaltene structures with its validity rigorously verified through molecular dynamics simulations. Using the modified Brown–Ladner method, key structural parameters (with corresponding probabilities) were first derived from basic experimental data, including molecular weight, elemental composition, and 1 H NMR spectra. Based on these parameters, 5000 candidate asphaltene structures were constructed by integrating Monte Carlo sampling with a pre-established library of aromatic building blocks. Nonlinear optimization with a least-squares objective function was then employed to screen out 4–6 dominant molecular structures and determine their respective molar fractions in the sample. To validate the predicted structures, asphaltene–toluene systems were established, and analyses of radial distribution functions (RDF) and dihedral angle distributions between aromatic planes were conducted. The results showed that PMSA-generated molecules can form stable π–π stacked aggregates, exhibiting an aggregation free energy of approximately 4–6 kcal/mol, which aligns well with the characteristic structural features of asphaltenes and provides robust theoretical support for the reliability and applicability of the PMSA program.