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--- exercises:2016_uzh_cmest:band_structure_calculation [2016/11/05 22:37] – created tmueller
+++ exercises:2016_uzh_cmest:band_structure_calculation [2020/08/21 10:15] (current) – external edit 127.0.0.1
@@ Line 60: / Line 60: @@
           SPECIAL_POINT 0.0   0.0   0.0
           SPECIAL_POINT 1./2. 0.0   0.0
-          SPECIAL_POINT 1./3. 1./3. 0.0
+          NPOINTS 5
-          SPECIAL_POINT 0.0   0.0   0.0
-          NPOINTS 40
         &END
       &END BAND_STRUCTURE
@@ Line 93: / Line 91: @@
 &END FORCE_EVAL
 </code>
+<note important>At present (CP2K 4.1) it is not possible to get the projected density of states when doing a K-Point calculation. Plus there is currently an issue with the ''UNITS'' specification for the special point coordinates: even though the unit is set to Cartesian coordinates (in Bohr), the special points are multiplied by the reciprocal vectors and must therefore be given in terms of the b-vectors.</note>
+Some notes on the input file:
+  * By specifying the ''KPOINT'' section you are enabling the K-Point calculation.
+  * While you could specify the K-Points directly, we are using the Monkhorst-Pack scheme [(http://journals.aps.org/prb/abstract/10.1103/PhysRevB.13.5188)] to generate them. The numbers following the keyword ''MONKHORST-PACK'' specify the tiling of the brillouin zone.
+  * After the basic calculation, CP2K calculates the energies along certain lines, denoted as ''KPOINT_SET'' (when you check [[https://manual.cp2k.org/trunk/CP2K_INPUT/FORCE_EVAL/DFT/KPOINTS/BAND_STRUCTURE/KPOINT_SET.html|the documentation]] you will note that this section can be repeated).
+  * The keyword ''NPOINTS'' specifies how many points (in the addition to the starting point) should be sampled between two special points.
+  * The ''SPECIAL_POINT'' keyword is used to specify the start-, mid- and endpoints of the line. Those points usually denote special points in the reciprocal lattice/unit cell, like the $\Gamma$, $M$ or $K$ point. You can find the definition for these in the appendix section of [[http://www.sciencedirect.com/science/article/pii/S0927025610002697|this paper]]. This keyword can also be specified multiple times, making it possible to directly get the band structure for a complete //path//.
+Now, when you run this input file you will get in addition the the output file, a file named ''graphene.bs'' which will look similar to the following:
+<code>
+ SET:       1                 TOTAL POINTS:      6
+   POINT   1                     0.000000    0.000000    0.000000
+   POINT   2                     0.500000    0.000000    0.000000
+       Nr.    1    Spin 1        K-Point  0.00000000  0.00000000  0.00000000
+           -15.30752034     -3.31285773      0.93143545      1.03651421
+.71874068     12.74920179     12.83785311     15.50144316
+       Nr.    2    Spin 1        K-Point  0.02500000  0.00000000  0.00000000
+           -15.29453364     -3.29547462      0.87472486      1.00321991
+.31998068     12.81500348     12.93001933     15.45108207
+       Nr.    3    Spin 1        K-Point  0.05000000  0.00000000  0.00000000
+[...]
+</code>
+For each set there is a block named ''SET'' with the special points listed as ''POINT'', followed by sub-blocks for each K-Point containing the energies for each MO.
+Your tasks:
+  * Lookup the special points for the $\Gamma$, $M$, $K$ points in the mentioned paper (make sure you choose the right lattice). Calculate and plot the band structure for graphene from $\Gamma$ over $M$, $K$ back to $\Gamma$ (you are free to decide whether to use multiple K-Point sets are multiple special points in a single set). Mark the special points. Choose an appropriate number of interpolation points to get a smooth plot.
+  * Compare your plot with plots from literature. What is different?
+  * Why do you get 8 orbital energies? Try to change the input to get more unoccupied orbitals.
+To convert the band structure file to a file which can be loaded directly into MATLAB for example, you can use the script ''cp2k_bs2csv.py'' from below, which when passed a band structure file ''graphene.bs'' as an argument will write files ''graphene.bs-setN.csv'' for each set containing the K-Point coordinates and the energies in one line.
+<file python cp2k_bs2csv.py>
+#!/usr/bin/env python
+"""
+Convert the CP2K band structure output to CSV files
+"""
+import re
+import argparse
+SET_MATCH = re.compile(r'''
+[ ]*
+  SET: [ ]* (?P<setnr>\d+) [ ]*
+  TOTAL [ ] POINTS: [ ]* (?P<totalpoints>\d+) [ ]*
+  \n
+(?P<content>
+  [\s\S]*?(?=\n.*?[ ] SET|$)  # match everything until next 'SET' or EOL
+)
+''', re.VERBOSE)
+SPOINTS_MATCH = re.compile(r'''
+[ ]*
+  POINT [ ]+ (?P<pointnr>\d+) [ ]+ (?P<a>\S+) [ ]+ (?P<b>\S+) [ ]+ (?P<c>\S+)
+''', re.VERBOSE)
+POINTS_MATCH = re.compile(r'''
+[ ]*
+  Nr\. [ ]+ (?P<nr>\d+) [ ]+
+  Spin [ ]+ (?P<spin>\d+) [ ]+
+  K-Point [ ]+ (?P<a>\S+) [ ]+ (?P<b>\S+) [ ]+ (?P<c>\S+) [ ]*
+  \n
+[ ]* (?P<npoints>\d+) [ ]* \n
+(?P<values>
+  [\s\S]*?(?=\n.*?[ ] Nr|$)  # match everything until next 'Nr.' or EOL
+)
+''', re.VERBOSE)
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument('bsfilename', metavar='bandstructure-file', type=str,
+                        help="the band structure file generated by CP2K")
+    args = parser.parse_args()
+    with open(args.bsfilename, 'r') as fhandle:
+        for kpoint_set in SET_MATCH.finditer(fhandle.read()):
+            filename = "{}.set-{}.csv".format(args.bsfilename,
+                                              kpoint_set.group('setnr'))
+            set_content = kpoint_set.group('content')
+            with open(filename, 'w') as csvout:
+                print(("writing point set {}"
+                       " (total number of k-points: {totalpoints})"
+                       .format(filename, **kpoint_set.groupdict())))
+                print("  with the following special points:")
+                for point in SPOINTS_MATCH.finditer(set_content):
+                    print("  {pointnr}: {a}/{b}/{c}".format(
+                        **point.groupdict()))
+                for point in POINTS_MATCH.finditer(set_content):
+                    results = point.groupdict()
+                    results['values'] = " ".join(results['values'].split())
+                    csvout.write("{a} {b} {c} {values}\n".format(**results))
+</file>