Graphite interlayer distance

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Task

Determine the interlayer distance of graphite in the stacking direction using the method of Tchatchenko and Scheffler to account for van der Waals interactions.

Input

POSCAR

• Graphite:

graphite
1.0
1.22800000 -2.12695839  0.00000000
1.22800000  2.12695839  0.00000000
0.00000000  0.00000000  6.71
4
direct
   0.00000000  0.00000000  0.25000000
   0.00000000  0.00000000  0.75000000
   0.33333333  0.66666667  0.25000000
   0.66666667  0.33333333  0.75000000

• Graphene:

graphite
1.0
1.22800000 -2.12695839  0.00000000
1.22800000  2.12695839  0.00000000
0.00000000  0.00000000  20.
2
direct
   0.00000000  0.00000000  0.25000000
   0.33333333  0.66666667  0.25000000

INCAR

IVDW = 202           
LVDWEXPANSION =.TRUE. 
NSW = 1 
IBRION = 2
ISIF = 4
PREC = Accurate
EDIFFG = 1e-5
LWAVE = .FALSE.
LCHARG = .FALSE.
ISMEAR = -5
SIGMA = 0.01
EDIFF = 1e-6
ALGO = Fast
NPAR = 2

KPOINTS

• Graphite:

Monkhorst Pack
0
gamma
16 16 8
0 0 0

• Graphene:

Monkhorst Pack
0
gamma
16 16 1
0 0 0

Calcualtion

Semilocal DFT at the GGA level underestimates long-range dispersion interactions. This problem causes a bad overestimation of graphite lattice in the stacking direction (8.84 A (PBE) vs. 6.71 A (exp)).

In this example, dispersion correction method of Tchatchenko and Scheffler (PRL 102, 073005 (2009)) is used to cope with this problem.

Optimal length of the lattice vector c normal to the stacking direction is determined in a series of single point calculations with varied value of c (all other degrees of freedom are fixed at their experimental values).

The computed c vs. energy dependence is written in the file results.dat and can be visualized e.g. using xmgrace. The optimal value can be obtained using the attached utility (python with numpy or Numeric is needed):

./utilities/fit.py results.dat

200 iterations performed
Ch-square: 4.30305519481e-09
---------

       E0(eV):         -37.433456779
       d0(A):  6.65603352689

The computed value of 6.66 A agrees well with experiment (6.71 A).

Details of implementation of TS in VASP + a number of tests: Bucko et al., PRB 87, 064110 (2013).

Used INCAR Tags

ALGO, EDIFF, EDIFFG, IBRION, ISIF, ISMEAR, IVDW, LCHARG, LVDW_EWALD, LWAVE, NPAR, NSW, PREC, SIGMA

Download

graphiteDistance_ts.tgz

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