Published March 30, 2024 | Version v1
Computational notebook Open

Data and Code for "Gradient elasticity in Swift-Hohenberg and phase-field crystal models"

  • 1. ROR icon TU Dresden

Description

Research data supporting the paper  ""Gradient elasticity in Swift-Hohenberg and phase-field crystal models"".

 

Python Notebooks

Notebooks (extensions .ipynb) work "as is" with the dataset from folder TRI1_100

 

Code (apfc-fft.zip)

The implementation of the APFC model is performed in python by exploiting the pseudo-spectral Fourier method. Library pyfftw is adopted. However, standard fft libraries can be used as well by changing the corresponding module/functions.

 

GitLab repository

https://gitlab.com/3ms-group/apfc-fft-ge

Notes

We gratefully acknowledge support from the German Research Foundation under Grant No. SA4032/2 -- Emmy Noether Programme -- (MS) and SA4032/3 -- FOR3013 -- (LMB), and from the Center for Information Services and High-Performance Computing [Zentrum für Informationsdienste und Hochleistungsrechnen (ZIH)] at TU Dresden for computing time.

Files

apfc_fft.zip

Files (906.4 MB)

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md5:6fcc03ccddf65f1253219673773a15dd
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md5:9c78368a1ab37ea26478634c88054876
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md5:ca990a17c01e89dfd6824c869d9fbf93
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md5:5811333584fc36d787c6512537b394d8
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md5:81d11d070c75ed487205000c5edf6ede
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