“Our new technique allows us to model much larger and more complex polyelectrolyte systems, and to do so much more quickly,” says Nan Li, lead author of a paper on the work and a Ph.D. student in NC State’s Department of Materials Science and Engineering. “This is a big step forward for this field.”
Polyelectrolytes are chains of molecules that are positively or negatively charged when placed in water. Because they are sensitive to changes in their environment, polyelectrolytes hold promise for use in applications such as drug delivery mechanisms. The term polyelectrolyte system refers to any collection of molecules that interacts in some way and includes polyelectrolytes.
Researchers are interested in computation models that simulate the behavior of polyelectrolyte systems because these models can be used to determine which polyelectrolytes are most likely to have desirable characteristics for use in various applications. The models can also be used to help researchers understand the behavior of polyelectrolyte systems such as DNA, RNA or synthetic ionic polymers.
Polyelectrolyte systems are difficult to model, because the systems can be large and include a lot of ions that can interact with the polyelectrolytes, changing the actual charge, shape, properties and behaviors of the polyelectrolytes. The change in charge affects how the polyelectrolytes interact with each other. The more ions there are in the system, the more likely it is that the polyelectrolytes will be drawn to each other. This interaction of polyelectrolytes changes the behavior and characteristics of the overall system.
“The problem is that tracking all of the ion-polyelectrolyte interactions takes a lot of computing power,” Li says. “We’ve developed a more efficient technique to account for the effect of the ions, and that allows us to use less computing power and get quicker results. The computational cost of calculating the electrostatic interactions between the ions and polyelectrolytes is reduced to zero because the parameter is already accounted for within an existing model.”
“Previous modeling techniques took an explicit approach, accounting for each individual ion,” says William Fuss, an undergraduate at NC State and co-author of the paper. “Our technique takes an implicit approach, which is why we call it the ‘implicit solvent ionic strength method,’ or ISIS. We use a single parameter to control for the effect of the ions in a Dissipative Particle Dynamics model, which is already in widespread use. That means our method could be easily implemented by anyone using DPD software.”
Using the ISIS method, researchers can identify potential polyelectrolyte system candidates for an application and then control the behavior of the polyelectrolytes by tweaking the number of ions in the system. This is done by increasing the concentration of salts in the system, because all salts are ionic when in an aqueous solution.
A video using the ISIS model to illustrate the behavior of a polyelectrolyte system can be seen at www.youtube.com/watch?v=HdY7VqgWzzA. The video is of self-assembling polyelectrolyte diblock copolymers in an aqueous solution.
The paper, “An implicit solvent ionic strength (ISIS) method to model polyelectrolyte systems with dissipative particle dynamics,” is published online in the journal Macromolecular Theory and Simulations. Senior author of the paper is Dr. Yaroslava Yingling, an associate professor of materials science and engineering at NC State. The research was supported by the National Science Foundation under grants CMMI-1150682 and DMR-1121107.
Note to Editors: The study abstract follows.
“An implicit solvent ionic strength (ISIS) method to model polyelectrolyte systems with dissipative particle dynamics”
Authors: Nan K. Li, William H. Fuss, and Yaroslava G. Yingling, North Carolina State University
Published: Aug. 14 in Macromolecular Theory and Simulations
Abstract: Herein, a new coarse-grained methodology for modeling and simulations of polyelectrolyte systems using implicit solvent ionic strength (ISIS) with dissipative particle dynamics (DPD) is presented. This ISIS model is based on mean-field theory approximation and the soft repulsive potential is used to reproduce the effect of solvent ionic strength. The capability of the ISIS model is assessed via two test cases: dynamics of a single long polyelectrolyte chain and the self-assembly of polyelectrolyte diblock copolymers in aqueous solutions with variable ionic strength. The results are in good agreement with previous experimental observations and theoretical predictions, which indicates that our polyelectrolyte model can be used to effectively and efficiently capture salt-dependent conformational features of large-scale polyelectrolyte systems in aqueous solutions, especially at the salt-dominated regime.