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libbeef Library
Johannes Voss has created a version of Quantum Espresso that includes the BEEF functional. Installation instructions can be found here:
https://github.com/vossjo/ase-espresso/wiki
libbeef Library
ported BEEF [1] (Bayesian Error Estimation Functional) to both Quantum Espresso and VASP. In both cases a small library called libbeef
must be built.
Version | Source Code | Precompiled Linux 64-bit binary |
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0.1.1 |
The latest development version can be obtained with this command:
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svngit coclone svnhttps://suncatls1.slac.stanford.edu/beef/trunk beefgithub.com/vossjo/libbeef |
Installation instructions for the different versions are contained in the README file in the above downloadable files.
Espresso with BEEF
Installation instructions (including an ASE python interface) can be found here:
https://github.com/vossjo/ase-espresso/wiki
VASP
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with BEEF
Newer versions of VASP (V. 5.4.x and up) only need changes to the makefile to enable the BEEF functionals: add -Dlibbeef to the CPP flags and -Lproperpath -lbeef to the library linker flags.
For older versions of VASP, a
To use BEEF with VASP, either build libbeef
from source or unpack a binary version, as described above.
A patch file must now be applied to the appropriate unmodified version of the VASP source code. These The patch files can be downloaded from here:
VASP Version | Patch File |
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5.0.3 |
Apply the patch within the VASP directory containing the fortran files by executing the a command like:
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patch -p1 < vasp.5.3.beef.diff
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Then edit your VASP Makefile to add the following after to your Makefile
line where the LIB
variable is defined:
Code Block |
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LIB+= -Lpathtobeeflibrary/lib -lbeef
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Then build VASP as usual. The following lines should be appended to your .INCAR
file to run a BEEF calculation (the last line is optional and triggers the calculation of ensemble energies for error estimation):
Code Block |
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GGA = BF
LUSE_VDW = .TRUE.
Zab_VDW = -1.8867
LBEEFENS = .TRUE.
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Instructions for doing the error estimations in VASP can be found in the libbeef
README
file.
[1] Jess Wellendorff, Keld T. Lundgaard, Andreas Møgelhøj, Vivien Petzold, David D. Landis, Jens K. Nørskov, Thomas Bligaard, and Karsten W. Jacobsen, "Density functionals for surface science: Exchange-correlation model development with Bayesian error estimation", Phys. Rev. B 85, 235149 (2012).