{
"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 Hartwigsen-Goedecker-Hutter (HGH) 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. HGH 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 here:\n",
"http://pseudopotentials.quantum-espresso.org/home/unified-pseudopotential-format.\n",
"\n",
"In this example, we will compare the convergence of an analytical HGH PSP with\n",
"a modern UPF PSP from [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 DFTK\n",
"using Downloads\n",
"using Unitful\n",
"using Plots"
],
"metadata": {},
"execution_count": 1
},
{
"cell_type": "markdown",
"source": [
"Here, we will use Perdew-Wang LDA PSP from [PseudoDojo](http://www.pseudo-dojo.org/),\n",
"which is available in the JuliaMolSim\n",
"[PseudoLibrary](https://github.com/JuliaMolSim/PseudoLibrary)."
],
"metadata": {}
},
{
"outputs": [],
"cell_type": "code",
"source": [
"PSEUDOLIB = \"https://raw.githubusercontent.com/JuliaMolSim/PseudoLibrary\"\n",
"COMMIT = \"56d1774708e1adfff35d30a403004cb98de4224b\"\n",
"URL_UPF = PSEUDOLIB * \"/$COMMIT/pseudos/pd_nc_sr_lda_standard_04_upf/Li.upf\";"
],
"metadata": {},
"execution_count": 2
},
{
"cell_type": "markdown",
"source": [
"We load the HGH and UPF PSPs using `load_psp`, which determines the\n",
"file format using the file extension."
],
"metadata": {}
},
{
"outputs": [],
"cell_type": "code",
"source": [
"psp_hgh = load_psp(\"hgh/lda/li-q3.hgh\");\n",
"path_upf = Downloads.download(URL_UPF, joinpath(tempdir(), \"Li.upf\"))\n",
"psp_upf = load_psp(path_upf);"
],
"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": [
"![](\"https://docs.dftk.org/stable/assets/li_pseudos_ecut_convergence.png\")
"
],
"metadata": {}
},
{
"cell_type": "markdown",
"source": [
"The converged cutoffs are 128 Ha and 36 Ha for the HGH\n",
"and UPF pseudos respectively. We see that the HGH 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": [
"Next, to see that the different pseudopotentials give reasonbly similar results,\n",
"we'll look at the bandstructures calculated using the HGH and UPF PSPs. Even though\n",
"the convered cutoffs are 128 and 36 Ha, we perform these calculations with a cutoff of\n",
"24 Ha for both PSPs."
],
"metadata": {}
},
{
"outputs": [],
"cell_type": "code",
"source": [
"function run_bands(psp)\n",
" a = -1.53877u\"Å\"\n",
" b = -2.66523u\"Å\"\n",
" c = -4.92295u\"Å\"\n",
" lattice = [ a a 0;\n",
" -b b 0;\n",
" 0 0 -c]\n",
" Li = ElementPsp(:Li; psp)\n",
" atoms = [Li, Li]\n",
" positions = [[1/3, 2/3, 1/4],\n",
" [2/3, 1/3, 3/4]]\n",
"\n",
" # These are (as you saw above) completely unconverged parameters\n",
" model = model_LDA(lattice, atoms, positions; temperature=1e-2)\n",
" basis = PlaneWaveBasis(model; Ecut=24, kgrid=(6, 6, 4))\n",
"\n",
" scfres = self_consistent_field(basis; tol=1e-4)\n",
" bandplot = plot_bandstructure(scfres)\n",
" (; scfres, bandplot)\n",
"end;"
],
"metadata": {},
"execution_count": 4
},
{
"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 -13.91967405931 -0.12 5.3 \n",
" 2 -13.98183883897 -1.21 -0.71 1.9 1.03s\n",
" 3 -13.98666559711 -2.32 -1.53 2.6 1.13s\n",
" 4 -13.98668186065 -4.79 -2.27 1.1 818ms\n",
" 5 -13.98668227674 -6.38 -2.98 2.2 948ms\n",
" 6 -13.98668235968 -7.08 -3.93 2.4 978ms\n",
" 7 -13.98668236476 -8.29 -4.38 3.3 1.20s\n",
"Computing bands along kpath:\n",
" Γ -> M -> K -> Γ -> A -> L -> H -> A and L -> M and H -> K\n",
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]
},
{
"output_type": "execute_result",
"data": {
"text/plain": "Energy breakdown (in Ha):\n Kinetic 11.3792090\n AtomicLocal -20.7901733\n AtomicNonlocal 0.0000000 \n Ewald -5.0511706\n PspCorrection -0.0009254\n Hartree 3.7115851 \n Xc -3.2266835\n Entropy -0.0085236\n\n total -13.986682364761"
},
"metadata": {},
"execution_count": 5
}
],
"cell_type": "code",
"source": [
"result_hgh = run_bands(psp_hgh)\n",
"result_hgh.scfres.energies"
],
"metadata": {},
"execution_count": 5
},
{
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"n Energy log10(ΔE) log10(Δρ) Diag Δtime\n",
"--- --------------- --------- --------- ---- ------\n",
" 1 -14.14867070483 -0.15 5.2 \n",
" 2 -14.21787398009 -1.16 -0.76 2.0 1.17s\n",
" 3 -14.22231399034 -2.35 -1.54 2.4 1.15s\n",
" 4 -14.22233968310 -4.59 -2.63 1.1 883ms\n",
" 5 -14.22234159368 -5.72 -2.95 3.2 1.24s\n",
" 6 -14.22234164490 -7.29 -4.08 1.1 798ms\n",
"Computing bands along kpath:\n",
" Γ -> M -> K -> Γ -> A -> L -> H -> A and L -> M and H -> K\n",
"\rDiagonalising Hamiltonian kblocks: 1%|▏ | ETA: 0:01:10\u001b[K\rDiagonalising Hamiltonian kblocks: 2%|▎ | ETA: 0:00:55\u001b[K\rDiagonalising Hamiltonian kblocks: 2%|▍ | ETA: 0:00:47\u001b[K\rDiagonalising Hamiltonian kblocks: 3%|▌ | ETA: 0:00:42\u001b[K\rDiagonalising Hamiltonian kblocks: 3%|▌ | ETA: 0:00:39\u001b[K\rDiagonalising Hamiltonian kblocks: 4%|▋ | ETA: 0:00:36\u001b[K\rDiagonalising Hamiltonian kblocks: 5%|▊ | ETA: 0:00:35\u001b[K\rDiagonalising Hamiltonian kblocks: 5%|▉ | ETA: 0:00:33\u001b[K\rDiagonalising Hamiltonian kblocks: 6%|▉ | ETA: 0:00:32\u001b[K\rDiagonalising Hamiltonian kblocks: 6%|█ | ETA: 0:00:32\u001b[K\rDiagonalising Hamiltonian kblocks: 7%|█▏ | ETA: 0:00:31\u001b[K\rDiagonalising Hamiltonian kblocks: 7%|█▎ | ETA: 0:00:30\u001b[K\rDiagonalising Hamiltonian kblocks: 8%|█▎ | ETA: 0:00:30\u001b[K\rDiagonalising Hamiltonian kblocks: 9%|█▍ | ETA: 0:00:29\u001b[K\rDiagonalising Hamiltonian kblocks: 9%|█▌ | ETA: 0:00:29\u001b[K\rDiagonalising Hamiltonian 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| ETA: 0:00:14\u001b[K\rDiagonalising Hamiltonian kblocks: 51%|████████▏ | ETA: 0:00:13\u001b[K\rDiagonalising Hamiltonian kblocks: 52%|████████▎ | ETA: 0:00:13\u001b[K\rDiagonalising Hamiltonian kblocks: 52%|████████▍ | ETA: 0:00:13\u001b[K\rDiagonalising Hamiltonian kblocks: 53%|████████▌ | ETA: 0:00:13\u001b[K\rDiagonalising Hamiltonian kblocks: 53%|████████▌ | ETA: 0:00:13\u001b[K\rDiagonalising Hamiltonian kblocks: 54%|████████▋ | ETA: 0:00:13\u001b[K\rDiagonalising Hamiltonian kblocks: 55%|████████▊ | ETA: 0:00:12\u001b[K\rDiagonalising Hamiltonian kblocks: 55%|████████▉ | ETA: 0:00:12\u001b[K\rDiagonalising Hamiltonian kblocks: 56%|████████▉ | ETA: 0:00:12\u001b[K\rDiagonalising Hamiltonian kblocks: 56%|█████████ | ETA: 0:00:12\u001b[K\rDiagonalising Hamiltonian kblocks: 57%|█████████▏ | ETA: 0:00:12\u001b[K\rDiagonalising Hamiltonian kblocks: 57%|█████████▎ | ETA: 0:00:12\u001b[K\rDiagonalising Hamiltonian kblocks: 58%|█████████▎ | ETA: 0:00:11\u001b[K\rDiagonalising 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ETA: 0:00:07\u001b[K\rDiagonalising Hamiltonian kblocks: 74%|███████████▉ | ETA: 0:00:07\u001b[K\rDiagonalising Hamiltonian kblocks: 75%|████████████ | ETA: 0:00:07\u001b[K\rDiagonalising Hamiltonian kblocks: 75%|████████████ | ETA: 0:00:07\u001b[K\rDiagonalising Hamiltonian kblocks: 76%|████████████▏ | ETA: 0:00:07\u001b[K\rDiagonalising Hamiltonian kblocks: 76%|████████████▎ | ETA: 0:00:07\u001b[K\rDiagonalising Hamiltonian kblocks: 77%|████████████▍ | ETA: 0:00:06\u001b[K\rDiagonalising Hamiltonian kblocks: 78%|████████████▍ | ETA: 0:00:06\u001b[K\rDiagonalising Hamiltonian kblocks: 78%|████████████▌ | ETA: 0:00:06\u001b[K\rDiagonalising Hamiltonian kblocks: 79%|████████████▋ | ETA: 0:00:06\u001b[K\rDiagonalising Hamiltonian kblocks: 79%|████████████▊ | ETA: 0:00:06\u001b[K\rDiagonalising Hamiltonian kblocks: 80%|████████████▊ | ETA: 0:00:06\u001b[K\rDiagonalising Hamiltonian kblocks: 80%|████████████▉ | ETA: 0:00:05\u001b[K\rDiagonalising Hamiltonian kblocks: 81%|█████████████ | 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0:00:01\u001b[K\rDiagonalising Hamiltonian kblocks: 96%|███████████████▍| ETA: 0:00:01\u001b[K\rDiagonalising Hamiltonian kblocks: 97%|███████████████▌| ETA: 0:00:01\u001b[K\rDiagonalising Hamiltonian kblocks: 97%|███████████████▌| ETA: 0:00:01\u001b[K\rDiagonalising Hamiltonian kblocks: 98%|███████████████▋| ETA: 0:00:01\u001b[K\rDiagonalising Hamiltonian kblocks: 98%|███████████████▊| ETA: 0:00:00\u001b[K\rDiagonalising Hamiltonian kblocks: 99%|███████████████▉| ETA: 0:00:00\u001b[K\rDiagonalising Hamiltonian kblocks: 99%|███████████████▉| ETA: 0:00:00\u001b[K\rDiagonalising Hamiltonian kblocks: 100%|████████████████| Time: 0:00:27\u001b[K\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": "Energy breakdown (in Ha):\n Kinetic 10.2239402\n AtomicLocal -10.9142053\n AtomicNonlocal -8.9743168\n Ewald -5.0511706\n PspCorrection 0.1151544 \n Hartree 3.5205945 \n Xc -3.1341549\n Entropy -0.0081831\n\n total -14.222341644904"
},
"metadata": {},
"execution_count": 6
}
],
"cell_type": "code",
"source": [
"result_upf = run_bands(psp_upf)\n",
"result_upf.scfres.energies"
],
"metadata": {},
"execution_count": 6
},
{
"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=150}",
"image/png": 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",
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},
"metadata": {},
"execution_count": 7
}
],
"cell_type": "code",
"source": [
"plot(result_hgh.bandplot, result_upf.bandplot, titles=[\"HGH\" \"UPF\"], size=(800, 400))"
],
"metadata": {},
"execution_count": 7
}
],
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"metadata": {
"language_info": {
"file_extension": ".jl",
"mimetype": "application/julia",
"name": "julia",
"version": "1.8.5"
},
"kernelspec": {
"name": "julia-1.8",
"display_name": "Julia 1.8.5",
"language": "julia"
}
},
"nbformat": 4
}