Campus Units

Mechanical Engineering, Electrical and Computer Engineering

Document Type

Article

Publication Version

Submitted Manuscript

Publication Date

2-15-2017

Journal or Book Title

Journal of Computational Physics

Volume

331

First Page

280

Last Page

296

DOI

10.1016/j.jcp.2016.11.020

Abstract

Self-consistent field theory (SCFT) has proven to be a powerful tool for modeling equilibrium microstructures of soft materials, particularly for multiblock polymers. A very successful approach to numerically solving the SCFT set of equations is based on using a spectral approach. While widely successful, this approach has limitations especially in the context of current technologically relevant applications. These limitations include non-trivial approaches for modeling complex geometries, difficulties in extending to non-periodic domains, as well as non-trivial extensions for spatial adaptivity. As a viable alternative to spectral schemes, we develop a finite element formulation of the SCFT paradigm for calculating equilibrium polymer morphologies. We discuss the formulation and address implementation challenges that ensure accuracy and efficiency. We explore higher order chain contour steppers that are efficiently implemented with Richardson Extrapolation. This approach is highly scalable and suitable for systems with arbitrary shapes. We show spatial and temporal convergence and illustrate scaling on up to 2048 cores. Finally, we illustrate confinement effects for selected complex geometries. This has implications for materials design for nanoscale applications where dimensions are such that equilibrium morphologies dramatically differ from the bulk phases.

Comments

This is a manuscript of an article is published as Ackerman, David M., Kris Delaney, Glenn H. Fredrickson, and Baskar Ganapathysubramanian. "A finite element approach to self-consistent field theory calculations of multiblock polymers." Journal of Computational Physics 331 (2017): 280-296. DOI:10.1016/j.jcp.2016.11.020. Posted with permission.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Copyright Owner

Elsevier Inc.

Language

en

File Format

application/pdf

Published Version

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