Correlations in Disordered Melts of Asymmetric Diblock Copolymers

Taher Ghasimakbari, David C. Morse

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Simulations of several different coarse-grained models are used to characterize how the structure factor S(q) in melts of compositionally asymmetric diblock copolymers varies with changes in the volume fraction f of the minority block, the parameter χeN (where χe is an effective interaction parameter and N is degree of polymerization), and the invariant degree of polymerization N. We focus here on systems with 0.25 ≤ f < 0.5. Results obtained with several different models are consistent in the expected sense, demonstrating the validity of the corresponding states principle when applied to asymmetric copolymers. Analysis is simplified by a demonstration that the effective χ parameter for these simple models is almost independent of composition. Results are compared to renormalized one-loop theory predictions, which become rapidly less accurate with increasing asymmetry. In the absence of an adequate predictive theory, a quantitative empirical relationship is developed to describe the dependence of peak intensity on χeN, f, and N over the range 0.25 < f < 0.5. The dependences of the peak intensity on χN in asymmetric and symmetric copolymers are qualitatively similar and exhibit a crossover from a weakly fluctuating regime in which the random-phase approximation (RPA) is nearly valid to a regime of strong composition fluctuations, with a crossover centered on the RPA spinodal value of χN. This crossover becomes noticeably sharper for more asymmetric systems, however, reflecting a more abrupt appearance of well-segregated disordered domains with increasing χ in asymmetric copolymer melts.

Original languageEnglish (US)
Pages (from-to)2335-2348
Number of pages14
JournalMacromolecules
Volume51
Issue number6
DOIs
StatePublished - Mar 27 2018

Bibliographical note

Funding Information:
This work was supported by NSF Grant DMR-1310436 using computational resources of the Minnesota Supercomputing Institute.

Publisher Copyright:
© 2018 American Chemical Society.

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