Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

More robust parsing of (electronic) piezoelectric tensor from OUTCAR #3919

Open
knoori opened this issue Jul 12, 2024 · 0 comments
Open

More robust parsing of (electronic) piezoelectric tensor from OUTCAR #3919

knoori opened this issue Jul 12, 2024 · 0 comments
Labels
enhancement A new feature or improvement to an existing one

Comments

@knoori
Copy link

knoori commented Jul 12, 2024

Feature Requested

Using VASP v6.3.2:

  1. Running a calculation with LEPSILON=.TRUE. and LRPA=.FALSE. produces the following OUTCAR line: PIEZOELECTRIC TENSOR (including local field effects) for field in x, y, z (C/m^2). This line does not match the search string in pymatgen > io > vasp > outputs.py line 2909, resulting in an improperly parsed piezo_tensor
  2. It would be useful to define a read_lcalceps() method, equivalent to read_lepsilon(), to extract the piezoelectric tensor from calculations using LCALCEPS=.TRUE. since it is sometimes beneficial to use the finite differences approach

Proposed Solution

  1. Modify the search string to look for the relevant elements of the output string, i.e. "PIEZOELECTRIC TENSOR" && "for field in x, y, z (C/m^2)" as opposed to the whole string. This would accommodate variations in the output related to VASP versions.
  2. Add a check for lcalceps and create a duel of the read_lepsilon()

Relevant Information

These changes would allow for

  1. greater compatibility with different VASP versions, which seem to use different output strings in the OUTCAR.
  2. ability to parse the piezolectric tensor from LCALCEPS calculations
@knoori knoori added the enhancement A new feature or improvement to an existing one label Jul 12, 2024
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
enhancement A new feature or improvement to an existing one
Projects
None yet
Development

No branches or pull requests

1 participant