MKS Tutorial at the CHiMaD Phase Field Meeting

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This is the repository for the Materials Knowledge System (MKS) tutorial scheduled for 08/03/2017 at the CHiMaD Phase Field Workshop. The tutorial will explore materials informatics using the PyMKS package. The primary focus will be on demonstrating how PyMKS is used to create process-structure-property relationships. In no particular order the tutorial will try to cover some of the following (time permitting),

  • Decomposing microstructure into a digital signal

  • Quantifying microstructure using 2 point statistics

  • Learning from a Cahn-Hilliard simulation

  • Using Dask to make PyMKS work in a threaded or multiprocessing environment

  • Using Scikit-Learn to cross-validate results

Some reading:

  • Materials Knowledge Systems in Python—a Data Science Framework for Accelerated Development of Hierarchical Materials, D. B. Brough, D. Wheeler and S. R. Kalidindi; Integrating Materials and Manufacturing Innovation, 2017, vol. 6, issue 1, pp 36-52, doi:10.1007/s40192-017-0089-0.

  • See the PyMKS theory documentation.

For more details, please see the relevant GitHub repository.

Cite this work

Researchers should cite this work as follows:

  • Daniel Wheeler (2017), "MKS Tutorial at the CHiMaD Phase Field Meeting,"

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Aleksandr Blekh

Georgia Institute of Technology