4.8 Review

Molecular Dynamics Simulations of Ionic Liquids and Electrolytes Using Polarizable Force Fields


Volume 119, Issue 13, Pages 7940-7995


DOI: 10.1021/acs.chemrev.8b00763




  1. Austrian Science Fund [FWF P28556-N34]
  2. Army Research Laboratory [W911NF-12-2-0023]
  3. National Institutes of Health [GM131710, GM072558]
  4. Joint Center for Energy Storage Research, an Energy Innovations Hub - U.S. Department of Energy, Office of Science, Basic Energy Sciences through IAA [SN2020957]
  5. Austrian Science Fund (FWF) [P28556] Funding Source: Austrian Science Fund (FWF)

Ask authors/readers for more resources

Many applications in chemistry, biology, and energy storage/conversion research rely on molecular simulations to provide fundamental insight into structural and transport properties of materials with high ionic concentrations. Whether the system is comprised entirely of ions, like ionic liquids, or is a mixture of a polar solvent with a salt, e.g., liquid electrolytes for battery applications, the presence of ions in these materials results in strong local electric fields polarizing solvent molecules and large ions. To predict properties of such systems from molecular simulations often requires either explicit or mean-field inclusion of the influence of polarization on electrostatic interactions. In this manuscript, we review the pros and cons of different treatments of polarization ranging from the mean-field approaches to the most popular explicit polarization models in molecular dynamics simulations of ionic materials. For each method, we discuss their advantages and disadvantages and emphasize key assumptions as well as their adjustable parameters. Strategies for the development of polarizable models are presented with a specific focus on extracting atomic polarizabilities. Finally, we compare simulations using polarizable and nonpolarizable models for several classes of ionic systems, discussing the underlying physics that each approach includes or ignores, implications for implementation and computational efficiency, and the accuracy of properties predicted by these methods compared to experiments.


I am an author on this paper
Click your name to claim this paper and add it to your profile.


Primary Rating

Not enough ratings

Secondary Ratings

Scientific rigor
Rate this paper


No Data Available
No Data Available