Asphaltenes constitute the heaviest fraction of the aromatic group in crude oil. Aggregation and precipitation of asphaltenes during petroleum processing costs the petroleum industry billions of dollars each year due to downtime and production inefficiencies. Asphaltene aggregation proceeds via a hierarchical self-assembly process that is well-described by the Yen-Mullins model. Nevertheless, the microscopic details of the emergent cluster morphologies and their relative stability under different processing conditions remain poorly understood. We perform coarse-grained molecular dynamics simulations of a prototypical asphaltene molecule to establish a phase diagram mapping the self-assembled morphologies as a function of temperature, pressure, and n-heptane:toluene solvent ratio informing how to control asphaltene aggregation by regulating external processing conditions. We then combine our simulations with graph matching and nonlinear manifold learning to determine low-dimensional free energy surfaces governing asphaltene self-assembly. In doing so, we introduce a variant of diffusion maps designed to handle data sets with large local density variations, and report the first application of many-body diffusion maps to molecular self-assembly to recover a pseudo-1D free energy landscape. Increasing pressure only weakly affects the landscape, serving only to destabilize the largest aggregates. Increasing temperature and toluene solvent fraction stabilizes small cluster sizes and loose bonding arrangements. Although the underlying molecular mechanisms differ, the strikingly similar effect of these variables on the free energy landscape suggests that toluene acts upon asphaltene self-assembly as an effective temperature.

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.

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