If you want to use these artifacts in your calculation to automatically retrieve the required pseudopotentials, follow these instructions. An example showing these pseudopotentials in action with a DFT calculation (using DFTK.jl) is given in the DFTK documentation. If you know how artifacts work in Julia skip to the next section.
Make sure you are using a local project environment (or you are within a package environment). If you don't know what either of this is, see the Pkg.jl documentation on working with environments.
Install the LazyArtifacts package into the local environment. Note down the location
of your Project.toml.
Download the Artifacts.toml
of this repository and put it in the same folder as your Project.toml.
Select the pseudopotential you want to use. E.g. the silicon pseudopotential of the
pd_nc_sr_pbe_stringent_0.4.1_upf pseudopotential collection (more on what this means below).
To use this file in a script / calculation employ the following code:
using LazyArtifacts
# ... other code and things
pseudofile = artifact"pd_nc_sr_pbe_stringent_0.4.1_upf/Si.upf"
# Use pseudofile as full path to the UPF file with the pseudo definition.This will now automatically download the pseudopotential file from this
repository and directly put the full path to the downloaded pseudopotential
file into the pseudofile variable, e.g. a string such as
/home/user/.julia/artifacts/56094b8162385233890d523c827ba06e07566079/Si.upf,
which luckily you don't usually have to know or remember. Note further
that this path may differ between computers, julia versions etc., so it
is highly recommended to use the artifact" ... " way of specifying the
file instead of the expanded path.
The currently available pseudopotential collections can be found in the pseudos subfolder.
Each collection name starts with a prefix for the pseudopotential family, including quantifiers
such as sr (scalar relativistic) or fr (full relativistic). Next comes the XC functional
for which the pseudo was constructed (e.g. pbe, lda, pbesol), potentially followed
by some details on the promised accuracy (strigent, standard, loose) or a version indication.
The name closes in the file format in which the pseudos are stored (e.g. upf, hgh, psp8),
which is also the extension used for all file names.
The list of available pseudo families with links to further resources and the appropriate references:
Kevin F. Garrity, Joseph W. Bennett, Karin M. Rabe, David Vanderbilt,
Pseudopotentials for high-throughput DFT calculations,
Computational Materials Science,
Volume 81,
2014,
https://doi.org/10.1016/j.commatsci.2013.08.053.C. Hartwigsen, S. Goedecker, J. Hutter,
Relativistic separable dual-space Gaussian pseudopotentials from H to Rn,
Physical Review B,
Volume 58,
1998,
https://doi.org/10.1103/PhysRevB.58.3641S. Goedecker, M. Teter, J. Hutter,
Separable dual-space Gaussian pseudopotentials,
Physical Review B,
Volume 54,
1996,
https://doi.org/10.1103/PhysRevB.54.1703M.J. van Setten, M. Giantomassi, E. Bousquet, M.J. Verstraete, D.R. Hamann, X. Gonze, G.-M. Rignanese,
The PseudoDojo: Training and grading a 85 element optimized norm-conserving pseudopotential table,
Computer Physics Communications,
Volume 226,
2018,
https://doi.org/10.1016/j.cpc.2018.01.012.M. Schlipf, F. Gygi,
Optimization algorithm for the generation of ONCV pseudopotentials,
Computer Physics Communications,
Volume 196,
2015,
https://doi.org/10.1016/j.cpc.2015.05.011.P. Scherpelz, M. Govoni, I. Hamada, G. Galli,
Implementation and Validation of Fully Relativistic GW Calculations: Spin–Orbit Coupling in Molecules, Nanocrystals, and Solids,
Journal of Chemical Theory and Computation,
Volume 12,
2016,
https://doi.org/10.1021/acs.jctc.6b00114G. Prandini, A. Marrazzo, I.E. Castelli, N. Mounet, N. Marzari,
Precision and efficiency in solid-state pseudopotential calculations,
npj Computational Materials,
Volume 4,
2018,
https://doi.org/10.1038/s41524-018-0127-2