Coarse-Grained Molecular Simulation and Nonlinear Manifold Learning of Archipelago Asphaltene Aggregation and Folding.

Asphaltenes constitute the heaviest aromatic component of crude oil. The myriad of asphaltene molecules falls largely into two conceptual classes: continental-possessing a single polyaromatic core-and archipelago-possessing multiple polyaromatic cores linked by alkyl chains. In this work, we study the influence of molecular architecture upon aggregation behavior and molecular folding of prototypical archipelago asphaltenes using coarse-grained molecular dynamics simulation and nonlinear manifold learning. The mechanistic details of aggregation depend sensitively on the molecular structure. Molecules possessing three polyaromatic cores show a higher aggregation propensity than those with two, and linear archipelago architectures more readily form a fractal network than ring topologies, although the resulting aggregates are more susceptible to disruption by chemical dispersants. The Yen-Mullins hierarchy of self-assembled aggregates is attenuated at high asphaltene mass fractions because of the dominance of promiscuous parallel stacking interactions within a percolating network rather than the formation of rodlike nanoaggregates and nanoaggregate clusters. The resulting spanning porous network possesses a fractal dimension of 1.0 on short length scales and 2.0 on long length scales regardless of the archipelago architecture. The incompatibility of the observed assembly behavior with the Yen-Mullins hierarchy lends support that high-molecular weight archipelago architectures do not occur at significant levels in natural crude oils. Low-dimensional free energy surfaces discovered by nonlinear dimensionality reduction reveal a rich diversity of metastable configurations and folding behavior reminiscent of protein folding and inform how intramolecular structures can be modulated by controlling asphaltene mass fraction and dispersant concentration.