BadELF: Spin Separated Charge

It is common for systems to have differing ELF topologies in the spin-up and spin-down electron systems. In these cases, it is useful to perform separate analyses on each spin system. Here we use the classic magnetic system of Fe as an example.

VASP

1. Create your Fe POSCAR file.

   Fe1
   1.0
   -1.4315177494749578    1.4315177494749580    1.4315177494749580
   1.4315177494749578   -1.4315177494749580    1.4315177494749580
   1.4315177494749582    1.4315177494749580   -1.4315177494749578
   Fe
   1
   direct
   0.0000000000000000    0.0000000000000000    0.0000000000000000 Fe
   

2. Create your INCAR file. Below is a minimal example that writes the required CHGCAR and ELFCAR files. In general, the grid density should be at least 10 pts/Å along each lattice vector for well converged Bader analysis.

   Global Parameters
   ISPIN = 2             # Spin-polarized
   LELF = True           # Write ELFCAR file
   EDIFF  = 1E-06        # SCF energy convergence, in eV
   ENCUT  = 520
   
   Grid Size             # Moderately grid density
   NGX    = 30
   NGY    = 30
   NGZ    = 30
   "Fine" Grid Size      # Must Match Standard Grid
   NGXF   = 30
   NGYF   = 30
   NGZF   = 30
   

3. Create your POTCAR. We cannot provide an example for this as the files are proprietary. You MUST use a POTCAR with extra valence electrons such as 'Fe_sv' to ensure the ELF contains some core electrons or you will overestimate the electron counts.

4. Run VASP. Depending on your system how you do this may vary. On our system we use the following command.

   mpirun -np 12 vasp_std
   

BaderKit

PythonCommand Line

1. If you would like to follow along, open your preferred IDE in an environment with BaderKit installed. Alternatively, the complete python script from this tutorial is available at the end of this page.

2. Import the Grid and Badelf class

   from baderkit import Grid
   from baderkit.elf_analysis import Badelf
   

3. Load the spin polarized grids

   polarized_charge = Grid.from_vasp("CHGCAR", total_only=False)
   polarized_elf = Grid.from_vasp("ELFCAR", total_only=False)
   

4. Split the polarized grids into their spin-up and spin-down components

   charge_up, charge_down = polarized_charge.split_to_spin()
   elf_up, elf_down = polarized_elf.split_to_spin()
   

5. Create the polarized BadELF objects.

   badelf_up = Badelf(
       charge_grid=charge_up,
       reference_grid=elf_up,
       )
   badelf_down = Badelf(
       charge_grid=charge_down,
       reference_grid=elf_down,
       )
   

6. Finally, print some useful information to the console.

   metal_bonds_up = badelf_up.nnas_per_reduced_formula
   metal_bonds_down = badelf_down.nnas_per_reduced_formula
   
   print(f"Spin-up metal bond population: {metal_bonds_up}")
   print(f"Spin-down metal bond population: {metal_bonds_down}")
   

   You should see logging information as BaderKit runs, then outputs similar to the following:

   Spin-up metal bond population: 0.9585707826
   Spin-down metal bond population: 1.317401248
   

1. If you are using an environment manager, load your baderkit environment. For conda:

   conda activate baderkit
   

2. Split the charge density and ELF into spin-up and spin-down systems

   baderkit split CHGCAR
   baderkit split ELFCAR
   

3. Run the Badelf analysis on each system separately. Make sure to change the name of the output .json file to avoid overwriting it.

   baderkit badelf CHGCAR_up ELFCAR_up
   mv badelf.json badelf_up.json
   baderkit badelf CHGCAR_down ELFCAR_down
   mv badelf.json badelf_down.json
   

And that's it! Try playing around with what else the Badelf class offers.

Download Resources

Tutorial Script: spin_badelf.py

VASP Inputs/Outputs: Fe.zip