Research Data Leeds Repository

Citation

Merin, Joseph, Read, Daniel J. and Rucklidge, Alastair (2025) Dataset for 'A flexible implementation of strong segregation theory for two dimensional ABC star terpolymer morphologies'. University of Leeds. [Dataset] https://doi.org/10.5518/1879

Dataset description

The dataset contains the data for generating the figures in the paper. There are three main parameters: NChiAB, NChiBC and NchiAC, whose values are given in the paper and specified in the names of the directories. For these directories, the degree of polymerization parameter is N=1000. Each directory contains subdirectories for each of the ten morphologies considered in the paper. Each subdirectory has (up to) six files giving the free energy as a function of phi_A, phi_B and phi_C, one file for each of the six ways of distributing the three polymer types. There are two further directories containing data (with the same structure) for different degrees of polymerization N=300 and N=10000 and equal values of NChi. In addition, a sample python script is given, including appropriate input files for each morphology.

Keywords:	polymer phase separation, ABC terpolymers, Strong Segregation Theory
Subjects:	G000 - Mathematical sciences > G100 - Mathematics > G120 - Applied mathematics
Divisions:	Faculty of Engineering and Physical Sciences > School of Mathematics
License:	Creative Commons Attribution 4.0 International (CC BY 4.0)
Date deposited:	05 Jun 2026 13:11
URI:	https://archive.researchdata.leeds.ac.uk/id/eprint/1560
Additional details Additional details Creators or authors: Creators ORCID Other ID Email Primary affiliation Primary affiliation ID Primary affiliation ID type Secondary affiliation Secondary affiliation ID Secondary affiliation ID type Merin, Joseph https://orcid.org/0000-0002-0441-9365 University of Leeds https://ror.org/024mrxd33 ror Read, Daniel J. https://orcid.org/0000-0003-1194-9273 University of Leeds https://ror.org/024mrxd33 Rucklidge, Alastair https://orcid.org/0000-0003-2985-0976 University of Leeds https://ror.org/024mrxd33 Type of data: Dataset Research funders: EPSRC; Leverhulme Trust Grant numbers: EP/L015536/1, EP/P015611/1; RF-2018-449/9 Publication date: 2025 Resource language: English Metadata language: English Publisher: University of Leeds Contact email: A.M.Rucklidge@leeds.ac.uk Last Modified: 08 Jun 2026 08:40

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Documentation

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Data

SSP_data.zip [6MB] SSP_data.zip [6MB] SSP_data.zip [6MB] Security: Anyone File name: SSP_data.zip Content type: Data Mime-Type: application/zip License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 6MB

Program

SSP_code.zip [307kB] SSP_code.zip [307kB] SSP_code.zip [307kB] Security: Anyone File name: SSP_code.zip Content type: Program Mime-Type: application/zip License: MIT License File size: 307kB