Modeling the Multicomponent Compositional Effects of Asphaltenes on Interfacial Phenomena

Abstract

The polydisperse nature of asphaltenes is not usually considered in studies of asphaltenes adsorption effects at interfaces, e.g., water–oil interfaces. We recently proposed a methodology that takes into account the mixture nature of asphaltenes and showed that a binary mixture model for diffusion-limited adsorption at water–oil interfaces could describe qualitatively all of the features of asphaltenes’ interfacial dilatational rheology [LiuF. Liu, F. 10.1021/acs.langmuir.6b03958Langmuir20173319271042]. On the quantitative side, however, use of only two pseudocomponents did not adequately predict some other aspects of their behavior, such as dynamic interfacial tension over the full range of time scales. To address these limitations, a methodology for calculating interfacial rheological properties for an n-component mixture was first developed [LiuF. Liu, F. 10.1016/j.colsurfa.2017.05.080Colloids Surf. A2017532140143]. To capture, first, the interfacial tension behavior and then the rheological properties within the same methodological structure, we discuss here an approach using a multicomponent model that inversely solves the Ward–Tordai equations and extracts the properties of individual pseudocomponents (concentration and adsorption coefficient) from dynamic interfacial tension measurements. Using ternary mixture models proves sufficient to capture the data obtained for asphaltenes over large adsorption time scales (up to 24 h) and large frequency range. Quaternary mixture models do not significantly improve the predictions. Another feature revealed by this methodology is the aggregation behavior of the different pseudocomponents. For dilute solutions, the calculated sum of the pseudocomponents’ concentrations falls in the range of the actual asphaltenes concentration. As the actual asphaltenes concentration is increased, the calculated concentration of the most surface-active pseudocomponents levels offs, indicating that the most surface-active asphaltenes are also the most prone to aggregate due perhaps to π–π interactions. This result would be expected as asphaltenes adsorption at the water–oil interface appear to be driven by the interactions of the π electrons of their aromatic cores as previously demonstrated [RaneJ. P. Rane, J. P. 10.1021/acs.energyfuels.5b00179Energy Fuels20152935843590]. Finally, the result obtained by this model indicates that the presence of a very small fraction of extremely surface-active asphaltenes components could explain both the “everlasting” interfacial tension decay observed and the apparent irreversibility of adsorption during washout experiments.

Structure–Dynamic Function Relations of Asphaltenes

“…In addition, this treatment helps keep the number of adjustable parameters to a minimum. This assumption is also consistent with measurement of different surfactant species in asphaltenes. , When a third component of even higher interfacial activity and even lower concentration is present in asphaltenes, Figure shows that the predicted reduction of surface tension with time occurs for very long times …”

“…Recent research implemented a ternary mixture model for diffusion-limited adsorption at a water–oil interface (cf. Figures and ) . As observed from the figure above, the smallest fraction, i.e., pseudocomponent 1 (<0.5%), seems to be responsible for the long-term interfacial tension decay.…”

“…Experimental data for 0.005% asphaltenes in a toluene–water interface showing a long-term, continuous decrease of IFT . Numerical IFT curves generated using different numbers of components: 1 (yellow), 2 (green), 3 (orange), and 4 (black) …”

“…At short times, diffusion delivers surfactant to the interface. For a single surfactant, as time progresses, the surface becomes saturated with surfactant, and the IFT ceases to change . For a second component of higher interfacial activity but lower concentration, it will take longer to diffuse to the interface, but once it arrives, it can displace the first component.…”

“…Pseudocomponent 3 (blue) is the least interfacially active but highest concentration. The total fraction coverage of the model (gray) increases with time …”