Multiscale Simulations of Lamellar PS–PEO Block Copolymers Doped with LiPF6 Ions

Vaidyanathan Sethuraman, Santosh Mogurampelly, Venkat Ganesan

Research output: Contribution to journalArticlepeer-review

41 Scopus citations


We report the results of atomistic simulations of the structural equilibrium properties of PS–PEO block copolymer (BCP) melt in the ordered lamellar phase doped with LiPF6 salt. A hybrid simulation strategy, consisting of steps of coarse-graining and inverse coarse-graining, was employed to equilibrate the melt at an atomistic resolution in the ordered phase. We characterize the structural distributions between different atoms/ions and compare the features arising in BCPs against the corresponding behavior in PEO homopolymers for different salt concentrations. In addition, the local structural distributions are characterized in the lamellar phase as a function of distance from the interface. The cation–anion radial distribution functions (RDF) display stronger coordination in the block copolymer melts at high salt concentrations, whereas the trends are reversed for low salt concentrations. Radial distribution functions isolated in the PEO and PS domains demonstrate that the stronger coordination seen in BCPs arises from the influence of both the higher fraction of ions segregated in the PS phase and the influence of interactions in the PS domain. Such a behavior also manifests in the cation–anion clusters, which show a larger fraction of free ions in the BCP. While the average number of free anions (cations) decreases with increasing salt concentration, higher order aggregates of LiPF6 increase with increasing salt concentration. Further, the cation–anion RDFs display spatial heterogeneity, with a stronger cation–anion binding in the interfacial region compared to bulk of the PEO domain.
Original languageEnglish (US)
Pages (from-to)4542-4554
Number of pages13
Issue number11
StatePublished - Jun 2 2017
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): OSR-2016-CRG5-2993-1
Acknowledgements: V.G. acknowledges funding in part by grants from the Robert A. Welch Foundation (Grant F1599), the National Science Foundation (DMR-1306844), and the US Army Research Office under Grant W911NF-13-1-0396, to King Abdullah University of Science and Technology (OSR-2016-CRG5-2993-1). Acknowledgment is also made to the Donors of the American Chemical Society Petroleum Research Fund for partial support of this research (56715-ND9). The authors acknowledge the Texas Advanced Computing Center (TACC) for computing resources.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.


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