Disordered Micelle Regime in a Conformationally Asymmetric Diblock Copolymer Melt

Guo Kang Cheong, Kevin D. Dorfman

Research output: Contribution to journalArticlepeer-review

Abstract

We report results from Monte Carlo field-theoretic simulations (MC-FTS) of a compositionally asymmetric diblock copolymer melt (fA = 0.2) at an invariant degree of polymerization of N¯ = 104 for both a conformationally symmetric system, where the statistical segment lengths are equal, and a high statistical segment length ratio of ϵ = 3 that promotes the formation of Frank-Kasper phases. For this conformationally symmetric system, the disordered micelle regime emerges near the order-disorder transition predicted by self-consistent field theory (SCFT), consistent with theory and recent observations from molecular dynamics simulations of a related system. The disordered micelle regime is associated with a sharp increase in the number of micellar particles per unit volume, which need to fuse to reach the particle density required to form an ordered body-centered cubic (bcc) state past the order-disorder transition. The addition of conformational asymmetry for this system does not significantly impact the location of the order-disorder transition, but it increases the SCFT order-disorder transition to a higher segregation strength. As a result, the disordered micelle regime is suppressed, with the number density of particles increasing monotonically to the bcc number density. If this tentative conclusion about the role of conformational asymmetry obtained from observations for a single system proves to be valid in general, it suggests that thermal processing routes toward Laves phases in particle-forming diblock copolymer melts, which presumably require access to a disordered micelle regime, must operate at low invariant degrees of polymerization to realize a sufficiently wide disordered micelle regime.

Original languageEnglish (US)
Pages (from-to)9868-9878
Number of pages11
JournalMacromolecules
Volume54
Issue number21
DOIs
StatePublished - Nov 9 2021

Bibliographical note

Funding Information:
The authors thank Anshul Chawla, David C. Morse, and Timothy P. Lodge for useful discussions. This work was supported by NSF DMR-1719692. Computational resources were provided from Minnesota Supercomputing Institute (MSI) and UMN MRSEC through DMR-2011401.

Funding Information:
This work was supported by NSF DMR-1719692. Computational resources were provided from Minnesota Supercomputing Institute (MSI) and UMN MRSEC through DMR-2011401.

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