v0.6.0

Major Changes

• Created an example end-use tutorial on Path Planning in Functionally Graded Materials based on thermodynamic calculations and machine learning while leveraging nimplex to effortlessly create design spaces formed by alloy powders while relating them to underlying elemental space and describing all possible changes to every composition through simplex graphs which can then encode property-related problems such as avoiding high gradient magnitude changes (see example below).
  
  The thermodynamic calculations use pycalphad and modified strength surrogate model by Tandoc2023 (10.1038/s41524-023-00993-x) is used as an example for property modeling. You can quickly play with it by opening the Codespace below. Everything is pre-installed and you just need to follow a Jupyter notebook (Tutorial 02):

  

• Added a high entropy alloy thermodynamic database by @ShuangLin212 for users to play with when combined with pycalphad in the aforementioned tutorial.

• Added a (beta of) high-quality high-performance plotting script under utils/ternaryPlot.nim which generates neat highly-automated ternary plots with compositional, property, desirability, and feasibility overlays. Multiple axis and labeling options can be used. In the future, this will be turned into a binary nim and python libraries callable from tools like PyTorch. You can see example renders at the end of this release note.

• Improved the CLI interface experience by colorizing the terminal outputs and streamlining instructions.

Minor Changes

• Updated Action definitions.
• Proofread of documentation and tutorial by @amkrajewski, @amr8004, @rdamaral, and @bocklund.
• Minor updates in the first tutorial.

New Contributors

• @bocklund made their first contribution in #3
• @amr8004 made their first contribution in #4

Full Changelog: v0.5.1...v0.6.0