Pseudopotentials

In this example, we'll look at how to use various pseudopotential (PSP) formats in DFTK and discuss briefly the utility and importance of pseudopotentials.

Currently, DFTK supports norm-conserving (NC) PSPs in separable (Kleinman-Bylander) form. Two file formats can currently be read and used: analytical Hartwigsen-Goedecker-Hutter (HGH) PSPs and numeric Unified Pseudopotential Format (UPF) PSPs.

In brief, the pseudopotential approach replaces the all-electron atomic potential with an effective atomic potential. In this pseudopotential, tightly-bound core electrons are completely eliminated ("frozen") and chemically-active valence electron wavefunctions are replaced with smooth pseudo-wavefunctions whose Fourier representations decay quickly. Both these transformations aim at reducing the number of Fourier modes required to accurately represent the wavefunction of the system, greatly increasing computational efficiency.

Different PSP generation codes produce various file formats which contain the same general quantities required for pesudopotential evaluation. HGH PSPs are constructed from a fixed functional form based on Gaussians, and the files simply tablulate various coefficients fitted for a given element. UPF PSPs take a more flexible approach where the functional form used to generate the PSP is arbitrary, and the resulting functions are tabulated on a radial grid in the file. The UPF file format is documented on the Quantum Espresso Website.

In this example, we will compare the convergence of an analytical HGH PSP with a modern numeric norm-conserving PSP in UPF format from PseudoDojo. Then, we will compare the bandstructure at the converged parameters calculated using the two PSPs.

using AtomsBuilder
using DFTK
using Unitful
using UnitfulAtomic
using PseudoPotentialData
using Plots

Here, we will use a Perdew-Wang LDA PSP from PseudoDojo, which is available via the JuliaMolSim PseudoPotentialData package. See the documentation of PseudoPotentialData for the list of available pseudopotential families.

pseudopotentials_upf = PseudoFamily("dojo.nc.sr.lda.v0_4_1.oncvpsp3.standard.upf");

Such a PseudoFamily object acts like a dictionary from an element symbol to a pseudopotential file. They can be directly employed to select the appropriate pseudopotential when constructing an ElementPsp or a model based on an AtomsBase-compatible system. For the latter see the run_bands function below for an example.

Note that an alternative to a PseudoFamily object is in all cases a plain Dict to map from atomic symbols to the employed pseudopotential file. This we employ in combination with the HGH-type pseudopotentials:

pseudopotentials_hgh = Dict(:Si => "hgh/lda/si-q4.hgh");

First, we'll take a look at the energy cutoff convergence of these two pseudopotentials. For both pseudos, a reference energy is calculated with a cutoff of 140 Hartree, and SCF calculations are run at increasing cutoffs until 1 meV / atom convergence is reached.

The converged cutoffs are 26 Ha and 18 Ha for the HGH and UPF pseudos respectively. We see that the HGH pseudopotential is much harder, i.e. it requires a higher energy cutoff, than the UPF PSP. In general, numeric pseudopotentials tend to be softer than analytical pseudos because of the flexibility of sampling arbitrary functions on a grid.

Next, to see that the different pseudopotentials give reasonably similar results, we'll look at the bandstructures calculated using the HGH and UPF PSPs. Even though the converged cutoffs are higher, we perform these calculations with a cutoff of 12 Ha for both PSPs.

function run_bands(pseudopotentials)
    system = bulk(:Si; a=10.26u"bohr")

    # These are (as you saw above) completely unconverged parameters
    model = model_DFT(system; functionals=LDA(), temperature=1e-2, pseudopotentials)
    basis = PlaneWaveBasis(model; Ecut=12, kgrid=(4, 4, 4))

    scfres   = self_consistent_field(basis; tol=1e-4)
    bandplot = plot_bandstructure(compute_bands(scfres))
    (; scfres, bandplot)
end;

The SCF and bandstructure calculations can then be performed using the two PSPs, where we notice in particular the difference in total energies.

result_hgh = run_bands(pseudopotentials_hgh)
result_hgh.scfres.energies

Energy breakdown (in Ha):
    Kinetic             3.1590032 
    AtomicLocal         -2.1424103
    AtomicNonlocal      1.6042722 
    Ewald               -8.4004648
    PspCorrection       -0.2948928
    Hartree             0.5515531 
    Xc                  -2.4000880
    Entropy             -0.0031625

    total               -7.926189843946

result_upf = run_bands(pseudopotentials_upf)
result_upf.scfres.energies

Energy breakdown (in Ha):
    Kinetic             3.0954112 
    AtomicLocal         -2.3650646
    AtomicNonlocal      1.3082428 
    Ewald               -8.4004648
    PspCorrection       0.3952219 
    Hartree             0.5521739 
    Xc                  -3.1011607
    Entropy             -0.0032196

    total               -8.518859913855

But while total energies are not physical and thus allowed to differ, the bands (as an example for a physical quantity) are very similar for both pseudos:

plot(result_hgh.bandplot, result_upf.bandplot, titles=["HGH" "UPF"], size=(800, 400))