{ "cells": [ { "cell_type": "markdown", "source": [ "# Pseudopotentials\n", "\n", "In this example, we'll look at how to use various pseudopotential (PSP)\n", "formats in DFTK and discuss briefly the utility and importance of\n", "pseudopotentials.\n", "\n", "Currently, DFTK supports norm-conserving (NC) PSPs in\n", "separable (Kleinman-Bylander) form. Two file formats can currently\n", "be read and used: analytical Goedecker-Teter-Hutter (GTH) PSPs\n", "and numeric Unified Pseudopotential Format (UPF) PSPs.\n", "\n", "In brief, the pseudopotential approach replaces the all-electron\n", "atomic potential with an effective atomic potential. In this pseudopotential,\n", "tightly-bound core electrons are completely eliminated (\"frozen\") and\n", "chemically-active valence electron wavefunctions are replaced with\n", "smooth pseudo-wavefunctions whose Fourier representations decay quickly.\n", "Both these transformations aim at reducing the number of Fourier modes required\n", "to accurately represent the wavefunction of the system, greatly increasing\n", "computational efficiency.\n", "\n", "Different PSP generation codes produce various file formats which contain the\n", "same general quantities required for pesudopotential evaluation. GTH PSPs\n", "are constructed from a fixed functional form based on Gaussians, and the files\n", "simply tablulate various coefficients fitted for a given element. UPF PSPs\n", "take a more flexible approach where the functional form used to generate the\n", "PSP is arbitrary, and the resulting functions are tabulated on a radial grid\n", "in the file. The UPF file format is documented\n", "[on the Quantum Espresso Website](http://pseudopotentials.quantum-espresso.org/home/unified-pseudopotential-format).\n", "\n", "In this example, we will compare the convergence of an analytical GTH PSP with\n", "a modern numeric norm-conserving PSP in UPF format from\n", "[PseudoDojo](http://www.pseudo-dojo.org/).\n", "Then, we will compare the bandstructure at the converged parameters calculated\n", "using the two PSPs." ], "metadata": {} }, { "outputs": [], "cell_type": "code", "source": [ "using AtomsBuilder\n", "using DFTK\n", "using Unitful\n", "using UnitfulAtomic\n", "using PseudoPotentialData\n", "using Plots" ], "metadata": {}, "execution_count": 1 }, { "cell_type": "markdown", "source": [ "Here, we will use a Perdew-Wang LDA PSP\n", "from [PseudoDojo](http://www.pseudo-dojo.org/),\n", "which is available via the\n", "[JuliaMolSim PseudoPotentialData](https://github.com/JuliaMolSim/PseudoPotentialData.jl)\n", "package. See [the documentation of PseudoPotentialData](https://juliamolsim.github.io/PseudoPotentialData.jl/stable/)\n", "for the list of available pseudopotential families." ], "metadata": {} }, { "outputs": [], "cell_type": "code", "source": [ "family_upf = PseudoFamily(\"dojo.nc.sr.lda.v0_4_1.standard.upf\");" ], "metadata": {}, "execution_count": 2 }, { "cell_type": "markdown", "source": [ "Such a `PseudoFamily` object acts like a dictionary from an element symbol\n", "to a pseudopotential file. They can be directly employed to select the\n", "appropriate pseudopotential when constructing an `ElementPsp`\n", "or a model based on an `AtomsBase`-compatible system. For the latter\n", "see the `run_bands` function below for an example.\n", "\n", "An alternative to a `PseudoFamily` object is in all cases a plain\n", "`Dict` to map from atomic symbols to the employed pseudopotential file.\n", "For demonstration purposes we employ this\n", "in combination with the GTH-type pseudopotentials:" ], "metadata": {} }, { "outputs": [ { "output_type": "execute_result", "data": { "text/plain": "Dict{Symbol, String} with 1 entry:\n :Si => \"/home/runner/.julia/artifacts/966fd9cdcd7dbaba6dc2bf43ee50dd81e63e883…" }, "metadata": {}, "execution_count": 3 } ], "cell_type": "code", "source": [ "family_gth = PseudoFamily(\"cp2k.nc.sr.lda.v0_1.semicore.gth\")\n", "pseudopotentials_gth = Dict(:Si => family_gth[:Si])" ], "metadata": {}, "execution_count": 3 }, { "cell_type": "markdown", "source": [ "First, we'll take a look at the energy cutoff convergence of these two pseudopotentials.\n", "For both pseudos, a reference energy is calculated with a cutoff of 140 Hartree, and\n", "SCF calculations are run at increasing cutoffs until 1 meV / atom convergence is reached." ], "metadata": {} }, { "cell_type": "markdown", "source": [ "" ], "metadata": {} }, { "cell_type": "markdown", "source": [ "The converged cutoffs are 26 Ha and 18 Ha for the GTH\n", "and UPF pseudos respectively. We see that the GTH pseudopotential\n", "is much *harder*, i.e. it requires a higher energy cutoff, than the UPF PSP. In general,\n", "numeric pseudopotentials tend to be softer than analytical pseudos because of the\n", "flexibility of sampling arbitrary functions on a grid." ], "metadata": {} }, { "cell_type": "markdown", "source": [ "For some pseudopotentials the `PseudoFamily` contains hints for the recommended\n", "cutoffs as metadata. For most PseudoDojo potentials this is indeed the case:" ], "metadata": {} }, { "outputs": [ { "output_type": "execute_result", "data": { "text/plain": "(Ecut = 16.0, supersampling = 2.0, Ecut_density = 64.0)" }, "metadata": {}, "execution_count": 4 } ], "cell_type": "code", "source": [ "recommended_cutoff(family_upf, :Si)" ], "metadata": {}, "execution_count": 4 }, { "cell_type": "markdown", "source": [ "We see the recommended value is very close to what we determined above.\n", "Sometimes more detailed information is also available by looking at the raw\n", "metadata associated to this combination of pseudopotential family and element:" ], "metadata": {} }, { "outputs": [ { "output_type": "execute_result", "data": { "text/plain": "Dict{String, Any} with 6 entries:\n \"rcut\" => 10.0\n \"Ecut\" => 16\n \"supersampling\" => 2.0\n \"cutoffs_normal\" => Dict{String, Any}(\"Ecut\"=>16, \"supersampling\"=>2.0)\n \"cutoffs_high\" => Dict{String, Any}(\"Ecut\"=>22, \"supersampling\"=>2.0)\n \"cutoffs_low\" => Dict{String, Any}(\"Ecut\"=>12, \"supersampling\"=>2.0)" }, "metadata": {}, "execution_count": 5 } ], "cell_type": "code", "source": [ "pseudometa(family_upf, :Si)" ], "metadata": {}, "execution_count": 5 }, { "cell_type": "markdown", "source": [ "Here, we see that multiple recommended cutoffs are made available in the metadata." ], "metadata": {} }, { "cell_type": "markdown", "source": [ "Next, to see that the different pseudopotentials give reasonably similar results,\n", "we'll look at the bandstructures calculated using the GTH and UPF PSPs. Even though\n", "the converged cutoffs are higher, we perform these calculations with a cutoff of\n", "12 Ha for both PSPs." ], "metadata": {} }, { "outputs": [], "cell_type": "code", "source": [ "function run_bands(pseudopotentials)\n", " system = bulk(:Si; a=10.26u\"bohr\")\n", "\n", " # These are (as you saw above) completely unconverged parameters\n", " model = model_DFT(system; functionals=LDA(), temperature=1e-2, pseudopotentials)\n", " basis = PlaneWaveBasis(model; Ecut=12, kgrid=(4, 4, 4))\n", "\n", " scfres = self_consistent_field(basis; tol=1e-4)\n", " bandplot = plot_bandstructure(compute_bands(scfres))\n", " (; scfres, bandplot)\n", "end;" ], "metadata": {}, "execution_count": 6 }, { "cell_type": "markdown", "source": [ "The SCF and bandstructure calculations can then be performed using the two PSPs,\n", "where we notice in particular the difference in total energies." ], "metadata": {} }, { "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "n Energy log10(ΔE) log10(Δρ) Diag Δtime\n", "--- --------------- --------- --------- ---- ------\n", " 1 -7.921042851715 -0.69 5.5 290ms\n", " 2 -7.925596217955 -2.34 -1.24 2.2 240ms\n", " 3 -7.926166944625 -3.24 -2.41 3.4 192ms\n", " 4 -7.926189248829 -4.65 -3.00 2.9 196ms\n", " 5 -7.926189837547 -6.23 -3.94 2.5 207ms\n", " 6 -7.926189862274 -7.61 -4.60 3.2 462ms\n" ] }, { "output_type": "execute_result", "data": { "text/plain": "Energy breakdown (in Ha):\n Kinetic 3.1589973 \n AtomicLocal -2.1424233\n AtomicNonlocal 1.6042935 \n Ewald -8.4004648\n PspCorrection -0.2948928\n Hartree 0.5515483 \n Xc -2.4000856\n Entropy -0.0031626\n\n total -7.926189862274" }, "metadata": {}, "execution_count": 7 } ], "cell_type": "code", "source": [ "result_gth = run_bands(pseudopotentials_gth)\n", "result_gth.scfres.energies" ], "metadata": {}, "execution_count": 7 }, { "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "n Energy log10(ΔE) log10(Δρ) Diag Δtime\n", "--- --------------- --------- --------- ---- ------\n", " 1 -8.515500761230 -0.93 5.6 201ms\n", " 2 -8.518481172899 -2.53 -1.46 3.0 185ms\n", " 3 -8.518838246047 -3.45 -2.79 3.0 199ms\n", " 4 -8.518855339592 -4.77 -3.15 4.5 558ms\n", " 5 -8.518855463360 -6.91 -3.41 2.1 171ms\n", " 6 -8.518855540041 -7.12 -4.64 1.5 156ms\n" ] }, { "output_type": "execute_result", "data": { "text/plain": "Energy breakdown (in Ha):\n Kinetic 3.0954230 \n AtomicLocal -2.3650786\n AtomicNonlocal 1.3082410 \n Ewald -8.4004648\n PspCorrection 0.3952264 \n Hartree 0.5521802 \n Xc -3.1011633\n Entropy -0.0032195\n\n total -8.518855540041" }, "metadata": {}, "execution_count": 8 } ], "cell_type": "code", "source": [ "result_upf = run_bands(family_upf)\n", "result_upf.scfres.energies" ], "metadata": {}, "execution_count": 8 }, { "cell_type": "markdown", "source": [ "But while total energies are not physical and thus allowed to differ,\n", "the bands (as an example for a physical quantity) are very similar for both pseudos:" ], "metadata": {} }, { "outputs": [ { "output_type": "execute_result", "data": { "text/plain": "Plot{Plots.GRBackend() n=116}", "image/png": 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