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feat: implement `get_density_from_cloud()` using MP/COD workflow · Issue #286 · diffpy/diffpy.utils · GitHub

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feat: implement get_density_from_cloud() using MP/COD workflow #286

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Description

Problem

We want to automatically compute sample mass density based on sample composition, if user specified packing fraction.
See #278 for more discussions.

Proposed solution

We could offer other approaches:

  1. given a composition, try and get density from COD or Materials Project. For different polymorphs the densities will be different for the same composition, so we would have to handle that ("material-density" not "sample-density").
  • Obtain material density from MP API, with the user's API key added to the global config.
  • Density = number of atoms/unit cell volume (from composition and cif files), then converted to mass density adjusted by the packing fraction.
  1. as a fallback, use a "best effort" atomic density (most tightly packed materials are around 5x10^22 cm^-3)? This would be "magic" which we don't normally like, but if we use this fallback we could give a warning.

Activity

  1. added this to the 3.7.0 release milestone on Dec 28, 2024
  2. changed the title [-]automatic density computation[/-] [+]material density estimation based on sample composition[/+] on Dec 28, 2024
  3. sbillinge commented on Dec 28, 2024

    Contributor

    I was thinking more about this and something like:

    if both density and packing fractions are set and raise errors (no change)
    if packing fraction is None:
        packing fraction = 1
        get_density_from_material_structure(composition)
      
    current workflow for the part when density is passed in.
    
  4. changed the title [-]material density estimation based on sample composition[/-] [+]materials project/COD workflow: implement `get_density_from_cloud()`[/+] on Dec 29, 2024
  5. changed the title [-]materials project/COD workflow: implement `get_density_from_cloud()`[/-] [+]feat: implement `get_density_from_cloud()` using MP/COD workflow[/+] on Dec 29, 2024
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