Check our paper: Marcin Abram, Keith Burghardt, Greg Ver Steeg, Aram Galstyan, and Remi Dingreville, Inferring topological transitions in pattern-forming processes with self-supervised learning, npj Computational Materials 8, 205 (2022), URL https://www.nature.com/articles/s41524-022-00889-2.

Samples illustrating data used in the study are located in the data_sample folder.

Code illustrating our framework is located in the code folder.

Workflow to identify transition regimes in pattern-forming processes via self-supervised learning.

Predicting the process parameters for spinodal deposition of a two-phase mixture.

Identifying microstructural topological transitions for the physical vapor deposition of thin films.

@article{Abram-npj-2022,
  doi = {10.1038/s41524-022-00889-2},
  url = {https://www.nature.com/articles/s41524-022-00889-2},
  year = {2022},
  month = sep,
  publisher = {Springer Science and Business Media {LLC}},
  volume = {8},
  number = {1},
  pages = {205},
  author = {Marcin Abram and Keith Burghardt and Greg Ver Steeg and Aram Galstyan and Remi Dingreville},
  title = {Inferring topological transitions in pattern-forming processes with self-supervised learning},
  journal = {npj Computational Materials}
}