Ionic Correlations in Random Ionomers

Boran Ma, Trung Dac Nguyen, Victor A. Pryamitsyn, Monica Olvera De La Cruz*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

35 Scopus citations

Abstract

Understanding the electrostatic interactions in ion-containing polymers is crucial to better design shape memory polymers and ion-conducting membranes for multiple energy storage and conversion applications. In molten polymers, the dielectric permittivity is low, generating strong ionic correlations that lead to clustering of the charges. Here, we investigate the influence of electrostatic interactions on the nanostructure of randomly charged polymers (ionomers) using coarse-grained molecular dynamics simulations. Densely packed branched structures rich in charged species are found as the strength of the electrostatic interactions increases. Polydispersity in charge fraction and composition combined with ion correlations leads to percolated nanostructures with long-range fluctuations. We identify the percolation point at which the ionic branched nanostructures percolate and offer a rigorous investigation of the statistics of the shape of the aggregates. The extra degree of freedom introduced by the charge polydispersity leads to bicontinuous structures with a broad range of compositions, similar to neutral A-B random copolymers, as well as to desirable percolated ionic structure in randomly charged-neutral diblock copolymers. These findings provide insight into the design of conducting and robust nanostructures in ion-containing polymers.

Original languageEnglish (US)
Pages (from-to)2311-2318
Number of pages8
JournalACS nano
Volume12
Issue number3
DOIs
StatePublished - Mar 27 2018

Keywords

  • electrostatic effects
  • ionic clusters
  • ionomers
  • molecular dynamics
  • morphology

ASJC Scopus subject areas

  • Materials Science(all)
  • Engineering(all)
  • Physics and Astronomy(all)

Fingerprint

Dive into the research topics of 'Ionic Correlations in Random Ionomers'. Together they form a unique fingerprint.

Cite this