61st Annual Report on Research 2016

During the second project year, we focused on simulation studies of aggregation of heavy oil fractions using multiscale modeling tools developed during the first year, according to the proposed research program. Modeling was performed on three different scales: (i) atomistic molecular dynamics of the structure of individual asphaltene-resin aggregates (ii) mesoscale simulation studies of asphaltenes and resins in oil (iii) micron-scale modeling of asphaltene aggregation and precipitation using Brownian dynamics.

II. Atomistic modeling of asphaltene-resin primary aggregates

Using atomistic simulations with empirical forcefields we simulated solutions of asphaltenes and resins in hexane and toluene-hexane mixtures and observed aggregation of polyaromatic compounds into primary aggregates of 1-2 nm in diameter. We characterized the structure and dynamic properties of the aggregates, namely the distance between the polyaromatic asphaltene cores, the surface density of resins and diffusion coefficient of the aggregate as a whole. These characteristics were later used in the parameterization of mesoscale and macroscale models for dissipative and Brownian dynamics simulations.

Figure 1. Individual molecules representing componnts of oil in molecular dynamics simulations: asphaltene, resin and hexane

Figure 2. A priary asphaltene cluster held together by van der Waals interactions and hydrogen bonds between heterogroups (solvent not shown)

III. Mesoscale modeling of colloidal structure of asphaltenes

On the next stage, we explored asphaltene aggregation from uniform solution into colloidal structures using the DPD methodology developed during the first year. We composed models of characteristic asphaltenes of different molecular mass and geometry and model their aggregation. The results show that the behavior of polyaromatic systems cannot be described with a single characteristic asphaltene model. The presence of archipelago and big asphaltenes considerably increases the size of the aggregates and makes the shape much more complex; we could follow the birth of fractalic structures typical during the asphaltene precipitation process. At the same time, the toluene insoluble fractions only weakly influences by the presence of smaller asphaltenes. The presence of smaller polyaromatic compounds with higher hydrogen to carbon ratio indeed substantially increase the dispersity of the system hindering asphaltene aggregation.

Figure 3. Final configurations of (a) 5% S-asphaltene and 95% toluene;(b) 5% S-asphaltene, 47.5% toluene, 47.5% hexane; (c) 5% S-asphaltene and 95% hexane; (d) 5% S-asphaltene, 5% resin and 90% toluene; (e) 5% S-asphaltene, 5% resin, 45% toluene and 45% hexane; (f) 5% S-asphaltene, 5% resin and 90% hexane; (g) 5% S-asphaltene, 20% resin and 75% toluene; (h) 5% S-asphaltene, 20% resin, 37.5% toluene and 37.5% hexane; (i) 5% S-asphaltene, 20% resin and 75% hexane. Bead P (tan) represents the aromatic cores of S-asphaltene, F (pink) the aliphatic chains and Q (cyan) the hetero-group, resins and solvents are not shown.

IV. Large-scale simulations of aggregation of primary particles

To describe asphaltene precipitation into micro-size aggregates, we have developed a simulation scheme, where each primary clusters is modeled by one particle. The method is based on Brownian Dynamics (BD). The particles interact via soft potentials which is attractive at shorter distances due to van der Waals interactions and hydrogen bonding between the polyaromatic cores of the primary aggregates and repulsive at longer distances due to entropic repulsion between aliphatic sidechains. The particles can also reversibly associate which is modelled by Monte Carlo style random moves. We parameterized the potentials to experimental data and atomistic simulations of primary aggregates (section II) and studied the aggregation of asphaltenes from solution of the primary particles into micron scale aggregates. The hydrophilicity of the polyaromatic cores and the surface density of resin aliphatic tails determine the mechanisms of precipitation. The agglomerates of the primary clusters adapt a fractal structure, which evolves from diffusion fractals to bulk 3D objects. The evolution is prevented both by purely kinetic and thermodynamic factors. Therefore, the fractal structures may be entirely unstable or metastable. The metastable structures can exist infinitely long but their rapid precipitation may be triggered by change of environmental conditions, in particular by temperature.

Figure 4. (a) Clusters in the system with well depth -6.0 kT and 4.12 kT barrier and volume fraction 3%. (b) Radius of gyration vs cluster mass.

V. Impact on students involved in the project.

The project involved two Rutgers students pursuing Master degree in chemical engineering: Tianying Ma and Ravish Kumar, two undergraduate students (David Woo and Nish Basheri) and a postdoc (Santo Polouse). The PI teaches the mater students directly; they receive one-on-one instruction. Working on the project not only give them experience in modeling techniques. Two students have graduated during 2015-2016 academic year: Tianying Ma completed and defended a thesis in chemical engineering entitled “Modeling of Asphaltene Aggregation in Crude Oil by Dissipative Particle Dynamics” and graduated with MS degree in Chemical Engineering.

The students obtained valuable experience in presenting their work to others. Undergraduate student David Woo (who took 3 research credits) presented his work at the Rutgers School of Engineering undergraduate symposium and was awarded the best poster award by the faculty. Since than he has graduated and was hired by Collagen Matrix Inc as an research technician. Nish Basheri, an undergraduate student, who recently started working with the PI, received an Undergraduate Research Assistance fellowship from Aresti foundation; the topic of his project is “Nanostructure and dynamics of heavy fractions of crude oil” and his undergraduate research will be supported for 2016-2017 academic year.

(( word_count = 878 ))