Mesoscale computer modeling of asphaltene aggregation in liquid paraffin

Area of Science:

• Materials Science
• Computational Chemistry
• Nanotechnology

Background:

• Asphaltenes are emerging carbon nanofillers with potential in advanced applications like polymer nanocomposites and energy storage.
• Understanding asphaltene aggregation is crucial for optimizing their performance in various technological fields.

Purpose of the Study:

• To investigate the aggregation behavior and mobility of asphaltenes in liquid paraffin using advanced computational modeling.
• To explore how chemical modifications, specifically the presence or absence of aliphatic side groups, affect asphaltene self-assembly and diffusion.

Main Methods:

• Development and refinement of a coarse-grained Martini model against atomistic simulation data.
• Microsecond-timescale molecular dynamics simulations of thousands of asphaltene molecules in liquid paraffin.
• Analysis of asphaltene cluster formation, stack development, super-aggregate emergence, and diffusion coefficients.

Main Results:

• Native asphaltenes with aliphatic side groups form small, uniformly distributed clusters in paraffin.
• Modified asphaltenes (aliphatic periphery removed) form concentration-dependent stacks and disordered super-aggregates.
• Aliphatic side groups reduce asphaltene mobility by interacting with paraffin, while modified asphaltenes exhibit higher mobility.
• Diffusion coefficients show limited sensitivity to system size, especially at high asphaltene concentrations.

Conclusions:

• The study provides insights into asphaltene aggregation and mobility at microsecond timescales, crucial for designing materials.
• Chemical modification significantly alters asphaltene self-assembly and dynamics, offering pathways for tailored material properties.
• Computational modeling effectively captures complex asphaltene behavior, aiding in the development of new carbon-based nanomaterials.