In this tutorial, we will have brief look at how to calculate the optical properties of metals, looking at aluminium in particular, and how the results are different from a standard Optados optics calculation. It is highly recommended that you first go through the previous tutorial, where we go more into depth on it - this tutorial is mostly just highlighting how it is slightly different for metals.

We need 3 files

Al-optics.cell

%BLOCK LATTICE_CART
       4.050000000000000       0.000000000000000       0.000000000000000
       0.000000000000000       4.050000000000000       0.000000000000000
       0.000000000000000       0.000000000000000       4.050000000000000
%ENDBLOCK LATTICE_CART

%BLOCK POSITIONS_FRAC
  Al   0.0000000000000000   0.0000000000000000   0.0000000000000000
  Al   0.5000000000000000   0.5000000000000000   0.0000000000000000
  Al   0.5000000000000000   0.0000000000000000   0.5000000000000000
  Al   0.0000000000000000   0.5000000000000000   0.5000000000000000
%ENDBLOCK POSITIONS_FRAC

KPOINTS_MP_GRID 15 15 15
SPECTRAL_KPOINTS_MP_GRID 15 15 15

SYMMETRY_GENERATE

Al-optics.param

TASK                   : SPECTRAL
SPECTRAL_TASK          : optics
NEXTRA_BANDS           : 10

Al-optics.odi

TASK               : optics
JDOS_SPACING       : 0.01
JDOS_MAX_ENERGY    : 30
OPTICS_INTRABAND   : true
EFERMI             : optados
DOS_SPACING        : 0.1
ADAPTIVE_SMEARING  : 0.8  
BROADENING         : adaptive # Default
OPTICS_GEOM        : polycrystalline     # Default

 There is 1 key difference to before: it contains the line OPTICS_INTRABAND : true. This is to include the intraband contribution, which is necessary for metals.

We're starting with the high spacing so we get few results (measuring only at 3 energies) - this makes it easier to have a quick look at what's going on. We will use those results for the remainder of the tutorial.

 

Note

There are 2 ways to use the pseudopotentials:

- Using an external pseudopotential with extention .usp

- Using an internal pseudopotential created by the code during the execution according to type mentioned  in the param file which we will do it in this tutorial.


Execution

For serial calculation

/Al-optics$ castep.serial Al-optics
/Al-optics$ optados Al-optics 

For parallel calculation 

/Al-optics$ mpirun -np 4 castep.mpi Al-optics

/Al-optics$ optados.mpi Al-optics

 


Dielectric Dat File

The file Al_epsilon.dat contains the following data:

0.0000000000000000        2.1445746376579851        0.0000000000000000     
  15.000000000000000        1.1673581523361172        1.6007294583641971     
  30.000000000000000       0.66031465886470098       0.39432835642313052     


  0.0000000000000000       -32490.319172606654                            NaN
  15.000000000000000       0.37438389209757406        2.7452531094084771E-003
  30.000000000000000       0.84359371433743857        3.4316159432482577E-004


  0.0000000000000000       -32489.174597968995                            NaN
  15.000000000000000       0.54174204443369112        1.6034747114736059     
  30.000000000000000       0.50390837320213944       0.39467151801745531

You can see here that there are 3 columns like before (energy, real and imaginary dielectric), but there's 3 separate sets of them, separated by a double space. The 1st set corresponds to the interband contribution, the 2nd to the intraband, and the 3rd to the total. Though normally it'd be easiest to visualise this data by plotting the agr file on xmgrace, this would only give the interband term - if you're interested in other information you will have to use the .dat file.

You may choose to use/plot this data in your preferred method, but this tutorial will give you the necessary files to plot it using xmgrace. Firstly, we will create a new file called Al_epsilon_sep.dat file that turns separates the data into columns - we can do that with this Python script. The output file looks like

0.0000000000000000           2.1445746376579851           0.0000000000000000      -32490.3191726066543197           0.0000000000000000      -32489.1745979689949309           0.0000000000000000
15.0000000000000000           1.1673581523361172           1.6007294583641971           0.3743838920975741           0.0027452531094085           0.5417420444336911           1.6034747114736059
30.0000000000000000           0.6603146588647010           0.3943283564231305           0.8435937143374386           0.0003431615943248           0.5039083732021394           0.3946715180174553

It's exactly the same data except all the data is in separate columns now: 1 is still energy, 2 is interband real, 3 is interband imaginary, 4 is intraband real, 5 is intraband imaginary, 6 is total real and 7 is total imaginary dielectric.

Now let's make a graph of more useful data: rerun Optados with JDOS_SPACING : 0.01 set instead (to get more data for more meaningful graphs), and rerun the Python script. You could plot it with xmgrace (and using any accompanying batch files as you wish), but it is more convenient to plot it using plotly (and Bokeh to add a bit more functionality) - this is because the values vary greatly.

To replicate this, you may use this Python script to use plotly to get a basic output, and to get 1 with a bit of extra functionality (such as being able to manually select the range of values to look at) use this script. Make sure you have all the required libraries installed if doing this: pandas and plotly are required for the 1st, and Bokeh is also required for the 2nd. The 1st generates an output HTML file called interactive_graph.html and the 2nd generates interactive_graph_extra.html. The latter is embedded here for your convenience:

 

Plotting 

/Al-optics$ xmgrace Al-optics_epsilon.agr
/Al-optics$ xmgrace Al-optics_absorption.agr
/Al-optics$ xmgrace Al-optics_conductivity.agr
/Al-optics$ xmgrace Al-optics_loss_fn.agr
/Al-optics$ xmgrace Al-optics_reflection.agr
/Al-optics$ xmgrace Al-optics_refractive_index.agr
   

 We will get the following pictures






 

 Reference:   https://castep-docs.github.io/castep-docs/tutorials/Optics/Optics_aluminium/