{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "66146e02-48f2-4b2d-b2e3-50bda5cf345f", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/bauer/opt/anaconda3/lib/python3.9/site-packages/scipy/__init__.py:146: UserWarning: A NumPy version >=1.16.5 and <1.23.0 is required for this version of SciPy (detected version 1.26.0\n", " warnings.warn(f\"A NumPy version >={np_minversion} and <{np_maxversion}\"\n" ] } ], "source": [ "from feos import *\n", "from feos.si import *\n", "from feos.dft import *\n", "from feos.saftvrqmie import *\n", "\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import pandas as pd\n", "import seaborn as sns\n", "\n", "sns.set_palette(\"Paired\")\n", "colors = sns.color_palette(\"Dark2\", 3)\n", "sns.set_context(\"talk\")\n", "sns.set_style(\"ticks\")" ] }, { "cell_type": "markdown", "id": "88ead60a-eb91-4d29-8f0a-00aaef3a2e71", "metadata": {}, "source": [ "# Radial distribution function: comparison between Molecular Dynamics and DFT\n", "\n", "In this notebook, we compare the radial distribution function (rdf) as obtained from Molecular Dynamics (MD) simulations using LAMMPS and classical DFT.\n", "The steps needed are:\n", "\n", "1. Read parameters of the SAFT-VRQ Mie equation of state from files, including binary parameters $k_{ij}$ and $l_ {ij}$.\n", "2. Once the parameters are defined, we can initialize the functional.\n", "3. We calculate the phase diagram of the mixture. We then select thermodynamic conditions for the simulation in the stable liquid phase.\n", "4. Generate the LAMMPS tables for energies and forces for all interaction pairs. Run the simulation (not done here; we provide the simulation output).\n", "5. Read in LAMMPS simulation results. Calculate the rdf using 1D DFT in spherical coordinates.\n", "6. Plot the results." ] }, { "cell_type": "markdown", "id": "31f54a8d-9128-42bf-8ffe-ecfbaec5d370", "metadata": { "tags": [] }, "source": [ "## Example system: Deuterium-Neon\n", "\n", "In this example, we will take a look at the binary system consisting of deuterium and neon.\n", "When you run this example, make sure to adjust the relative path to the parameter files.\n", "Parameters are published in the [FeO$_\\mathrm{s}$ github repository](https://github.com/feos-org/feos) in the `parameters` directory.\n", "\n", "As part of the SI you will find LAMMPS input files for all binary systems that we presented in the main article.\n", "The procedure to calculate the rdf's is the same as presented in this document." ] }, { "cell_type": "markdown", "id": "acefbecf-e020-44cf-bcc9-401773638ef2", "metadata": {}, "source": [ "### Read in parameters\n", "\n", "We can read parameter from a *json* file using the `SaftVRQMieParameters.from_json` method.\n", "By default, a list of *names* to define a mixture of substances has to be provided.\n", "We also have to provide a file with the SAFT-VRQ Mie parameters and optionally another file with binary interaction parameters.\n", "If we wanted to use other identifiers instead of the name (CAS, SMILES, ...), we could change the `IdentifierOption` to the appropriate data type." ] }, { "cell_type": "code", "execution_count": 2, "id": "0f0a312b-5b2b-40ad-a2b4-f5edd9d30b70", "metadata": {}, "outputs": [ { "data": { "text/markdown": [ "|component|molarweight|$\\sigma$|$\\varepsilon$|$\\lambda_r$|$\\lambda_a$|fh|\n", "|-|-|-|-|-|-|-|\n", "|deuterium|4.028209954364|3.0087|39.2388|11|7|1|\n", "|neon|20.17969806457545|2.7778|37.501|13|6|1|" ], "text/plain": [ "SaftVRQMieParameters(\n", "\tmolarweight=[4.028209954364, 20.17969806457545]\n", "\tm=[1, 1]\n", "\tsigma=[3.0087, 2.7778]\n", "\tepsilon_k=[39.2388, 37.501]\n", "\tk_ij=\n", "[[0, 0.13],\n", " [0.13, 0]]\n", ")" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "parameters = SaftVRQMieParameters.from_json(\n", " [\"deuterium\", \"neon\"], \n", " \"../../parameters/saftvrqmie/hammer2023.json\",\n", " \"../../parameters/saftvrqmie/aasen2020_binary.json\",\n", " identifier_option=IdentifierOption.Name\n", ")\n", "parameters" ] }, { "cell_type": "code", "execution_count": 5, "id": "7a677dd4-9271-4b12-bbb8-fe3f3825f2c3", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(array([[0. , 0.13],\n", " [0.13, 0. ]]),\n", " array([[0., 0.],\n", " [0., 0.]]))" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "parameters.k_ij, parameters.l_ij" ] }, { "cell_type": "markdown", "id": "81301dbd-b4e7-4db1-80b9-14ee24af7573", "metadata": {}, "source": [ "### Define the functional\n", "\n", "Once the parameters are set, we can define the functional.\n", "This is done by the `HelmholtzEnergyFunctional.saftvrqmie` method.\n", "We will use most of the default options in this example; note however that we can include or ignore the non-additive correction to the hard-sphere reference.\n", "To calculate the phase diagram, we will **include the correction term**. \n", "Later we will use both cases and compare the effect on the rdf." ] }, { "cell_type": "code", "execution_count": 6, "id": "1ad06f2f-3190-4d10-897b-8f1b359602b6", "metadata": {}, "outputs": [], "source": [ "functional = HelmholtzEnergyFunctional.saftvrqmie(parameters, inc_nonadd_term=True)" ] }, { "cell_type": "markdown", "id": "5f1c838c-1dfd-4d1c-a986-7ff6e81ae82c", "metadata": {}, "source": [ "### Phase diagram\n", "\n", "First, we generate the phase diagram ($p-x,y$ diagram) from which we then select appropriate thermodynamic conditions for our simulation in the stable liquid phase.\n", "The phase diagram is constructed using the `PhaseDiagram.binary_vle` method.\n", "We can either provide a temperature or a pressure as input (FeO$_\\mathrm{s}$ checks the actual unit to decide which diagram to compute), in conjunction with the numper of VLE's to be included.\n", "Here, we use a constant temperature of $T = 32$K.\n", "We can access all thermodynamic states of the VLE using the `liquid` and `vapor` fields.\n", "With that, we can generate a nice plot." ] }, { "cell_type": "code", "execution_count": 7, "id": "9e2b7efd-fb69-4275-b168-df0c4dfbddfd", "metadata": {}, "outputs": [], "source": [ "temperature = 32 * KELVIN\n", "dia = PhaseDiagram.binary_vle(functional, temperature, npoints=50)" ] }, { "cell_type": "code", "execution_count": 8, "id": "1c41dbca-fdd1-478b-bb2a-944ef77b801c", "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(12, 7))\n", "plt.title(r\"{} (0), {} (1) at T = {}\".format(\n", " parameters.pure_records[0].identifier.name,\n", " parameters.pure_records[1].identifier.name,\n", " temperature))\n", "\n", "plt.plot(dia.liquid.molefracs[:, 0], dia.liquid.pressure / BAR, label=\"liquid\")\n", "plt.plot(dia.vapor.molefracs[:, 0], dia.vapor.pressure / BAR, label=\"vapor\")\n", "plt.xlim(0, 1.0)\n", "plt.ylim(3, 9)\n", "plt.xlabel(r\"$x_0$\")\n", "plt.ylabel(r\"$p$ / bar\")\n", "plt.legend(frameon=False);" ] }, { "cell_type": "markdown", "id": "565cc63a-2c10-495b-996a-ac012b6b2ae9", "metadata": {}, "source": [ "We can now specify the thermodynamic condition for our simulation.\n", "Here, we use a pressure of $p = 8$ bar with a molefraction for deuterium of $x_0 = 0.2$.\n", "Note that the order of the indices is the order in which we defined our substances when we read our parameters from files.\n", "\n", "In LAMMPS, we conduct a NVT simulation, i.e. at constant temperature ($T = 32$ K), volume and number of molecules.\n", "Thus, given temperature, pressure and the composition, we can calculate the mass density.\n", "We will use the density and composition to later calculate the appropriate volume of our simulation box for a specific number of molecules, here $N=4000$.\n", "\n", "The density for given $T, p, \\mathbf{x}$ can be calculated using the `State` constructor.\n", "The mass density and the temperature will be inputs for our LAMMPS input file." ] }, { "cell_type": "code", "execution_count": 9, "id": "739c6bf6-bbaf-44fb-a75e-a828a35fc5ba", "metadata": {}, "outputs": [], "source": [ "pressure = 8 * BAR\n", "x0 = 0.2\n", "molefracs = np.array([x0, 1-x0])" ] }, { "cell_type": "code", "execution_count": 10, "id": "97413ca2-802d-48ec-857f-5c6805c74394", "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$812.99\\,\\mathrm{\\frac{kg}{m^{3}}}$" ], "text/plain": [ "812.9908034253755 kg/m³" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "state = State(functional, temperature, pressure=pressure, molefracs=molefracs)\n", "state.mass_density()" ] }, { "cell_type": "markdown", "id": "8405fa0c-7a8f-4a3a-a2d7-4e34bfbdc6b6", "metadata": {}, "source": [ "### Generate LAMMPS energy and force tables\n", "\n", "In FeO$_\\mathrm{s}$ we provide an utility function to directly export LAMMPS `table` files from the parameters via the `lammps_tables` method of the `SaftVRQMieParameters` object.\n", "This method will create files for all interaction pairs. Here, three files will be generated, one for deuterium-deuterium interactions, one for neon-neon and one for deuterium-neon.\n", "\n", "We have to provide the temperature (32 K), the number of points to store in the table (5000), and the minimum and maximum distance (0.1 and 12 Angstrom, respectively)." ] }, { "cell_type": "code", "execution_count": 11, "id": "3b074123-73bc-4fce-94d1-60ae739afaf6", "metadata": {}, "outputs": [], "source": [ "parameters.lammps_tables(temperature, 5000, 0.1 * ANGSTROM, 12.0 * ANGSTROM)" ] }, { "cell_type": "markdown", "id": "5956e018-19a4-407b-8ef1-6a05af60f3b2", "metadata": {}, "source": [ "We provide an input file for the LAMMPS simulation that you can use or adjust for your system.\n", "There are several adjustments necessary, depending on the system of interest.\n", "\n", "This is how the LAMMPS input file starts (here it is named `in.binary_deuterium_neon`)\n", "\n", "```\n", "units real\n", "atom_style atomic\n", "\n", "# substance\n", "variable substance1 string deuterium\n", "variable substance2 string neon\n", "variable molarweight1 equal 4.028209954364\n", "variable molarweight2 equal 20.17969806457545\n", "\n", "# thermodynamic state\n", "variable x1 equal 0.2\n", "variable initial_density equal 812.99 # kg / m3 @ p = 8 bar\n", "variable t equal 32\n", "variable natoms equal 4000\n", "variable n1 equal v_x1*v_natoms\n", "variable n2 equal v_natoms-v_n1\n", "\n", "variable molarweight_mix equal v_x1*v_molarweight1+(1-v_x1)*v_molarweight2\n", "variable avogadro equal 6.022*10^23\n", "variable initial_density_mol equal v_initial_density/v_molarweight_mix*v_avogadro*10^(-27) # N / V\n", "variable unit_cell_volume equal 1/v_initial_density_mol\n", "variable box_length equal v_unit_cell_volume^(1/3)*v_natoms^(1/3)\n", "\n", "variable rc equal 12.0\n", "\n", "```\n", "\n", "When changing to other substances, the following changes have to be done\n", "\n", "- Adjust the name of the `substance1` and `substance2` variables. The order has to match the order of the parameters for the functional (this will be the filename we generate with `lammps_table`)\n", "- Adjust the molar weights accordingly. Those will be used to calculate the number density from which the volume of the simulation box is calculated.\n", "- Adjust the mole fraction `x1`. Note that in this input we start indexing at `1`.\n", "- Adjust the density (`initial_density`) and temperature variables.\n", "- Adjust the cut-off radius `rc` above which the potential energies and forces are set to zero. That value should match the upper bound that we used to generate our LAMMPS tables.\n", "\n", "The substance names are used for the filenames that are generated during the simulation.\n", "\n", "You should always **check** the simulation log or output. **A simple consistency check is the density** reported by LAMMPS which has to match the density we computed from the `State` object above.\n", "\n", "*Example log output after equilibration:* \n", "```\n", "Step Temp PotEng KinEng Volume Density \n", " 0 31.487142 -1205.8191 375.3349 138480.42 0.81297093 \n", " 1000 31.608622 -1204.7169 376.78297 138480.42 0.81297093 \n", " 2000 31.951485 -1198.6872 380.86999 138480.42 0.81297093 \n", " 3000 32.182406 -1201.8826 383.62263 138480.42 0.81297093 \n", " 4000 31.835575 -1200.741 379.48831 138480.42 0.81297093 \n", " 5000 31.941999 -1206.9745 380.75691 138480.42 0.81297093 \n", " 6000 31.438711 -1208.0502 374.75759 138480.42 0.81297093 \n", " 7000 31.62501 -1207.2402 376.97832 138480.42 0.81297093\n", "```" ] }, { "cell_type": "markdown", "id": "e0fa60a1-aebd-4d8f-936d-a1ef8a718252", "metadata": {}, "source": [ "### Read simulation results and compute rdf via DFT\n", "\n", "Simulation results can be read using `pandas.read_csv`.\n", "To make parsing easier, we can add a `#` in the fourth line and define it as comment when reading the lammps results." ] }, { "cell_type": "code", "execution_count": 12, "id": "61208cab-04c8-408c-a1d1-c97db8701577", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " i r g11 c11 g12 c12 g21 c21 g22 c22\n", "0 1 0.012 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", "1 2 0.036 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", "2 3 0.060 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", "3 4 0.084 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", "4 5 0.108 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "simulation = pd.read_csv(\n", " 'deuterium_neon_32K.rdf', \n", " delim_whitespace=True, \n", " comment=\"#\",\n", ")\n", "simulation.head()" ] }, { "cell_type": "markdown", "id": "e91537d2-3c3f-4129-9621-b0952a0600f5", "metadata": {}, "source": [ "For DFT, we construct a second functional without the non-additive correction term (called `functional_additive`).\n", "FeO$_\\mathrm{s}$ provides an object to calculate the rdf, the `PairCorrelation`.\n", "\n", "`PairCorrelation` takes a `State` as input, which we generate for given $T, p, \\mathbf{x}$ for both functionals.\n", "We can then define the index of the substance that acts as fixed particle, the number of grid points and the maximum radial distance.\n", "Once defined, we call the `solve` method to run the DFT calculation.\n", "\n", "After solving the equilibrium density profile, we can access the rdf for each substance given a fixed particle $i$ where $i$ is the index we used to initialize the `PairCorrelation` object.\n", "To get all rdf for a binary system, two DFT calculations have to be conducted: one for substance 0 and one for substance 1 acting as fixed particle." ] }, { "cell_type": "code", "execution_count": 13, "id": "1d0d0f49-be2b-4784-a630-9c2343768a63", "metadata": {}, "outputs": [], "source": [ "functional_additive = HelmholtzEnergyFunctional.saftvrqmie(parameters, inc_nonadd_term=False)\n", "state_additive = State(functional_additive, temperature, pressure=pressure, molefracs=molefracs)\n", "\n", "state = State(functional, temperature, pressure=pressure, molefracs=molefracs)\n", "\n", "rdf0_additive = PairCorrelation(state_additive, 0, 1024, 12 * ANGSTROM).solve()\n", "rdf1_additive = PairCorrelation(state_additive, 1, 1024, 12 * ANGSTROM).solve()\n", "\n", "rdf0 = PairCorrelation(state, 0, 1024, 12 * ANGSTROM).solve()\n", "rdf1 = PairCorrelation(state, 1, 1024, 12 * ANGSTROM).solve()" ] }, { "cell_type": "markdown", "id": "67956e16-8add-4042-8d0b-a66cb0e73ee5", "metadata": {}, "source": [ "### Plot the results" ] }, { "cell_type": "code", "execution_count": 14, "id": "d3b96038-d595-4d36-9823-f15458766bfc", "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(13, 7))\n", "plt.plot(rdf0_additive.r / ANGSTROM, rdf0_additive.pair_correlation_function[0], color=colors[0], linestyle='dashed', label=r\"$g_{00}$ (DFT)\")\n", "plt.plot(rdf0.r / ANGSTROM, rdf0.pair_correlation_function[0], color=colors[0], linestyle='dotted', label=r\"$g_{00}$ (DFT, nonadditive)\")\n", "plt.plot(simulation.r, simulation.g11, color=colors[0], label=r\"$g_{00}$ (MD)\")\n", "\n", "plt.plot(rdf1_additive.r / ANGSTROM, rdf1_additive.pair_correlation_function[1], color=colors[1], linestyle='dashed', label=r\"$g_{11}$ (DFT)\")\n", "plt.plot(rdf1.r / ANGSTROM, rdf1.pair_correlation_function[1], color=colors[1], linestyle='dotted', label=r\"$g_{11}$ (DFT, nonadditive)\")\n", "plt.plot(simulation.r, simulation.g22, color=colors[1], label=r\"$g_{11}$ (MD)\")\n", "\n", "plt.plot(rdf0_additive.r / ANGSTROM, rdf0_additive.pair_correlation_function[1], color=colors[2], linestyle='dashed', label=r\"$g_{01}$ (DFT)\")\n", "plt.plot(rdf0.r / ANGSTROM, rdf0.pair_correlation_function[1], color=colors[2], linestyle='dotted', label=r\"$g_{01}$ (DFT, nonadditive)\")\n", "plt.plot(simulation.r, simulation.g12, color=colors[2], label=r\"$g_{01}$ (MD)\")\n", "\n", "plt.hlines(1.0, 0, 15, color=\"black\", linestyle=\"dashed\", alpha=0.5)\n", "plt.xlim(2, 12)\n", "plt.ylim(0, 4.0)\n", "\n", "plt.xlabel(r\"r / $\\mathrm{\\AA}$\")\n", "plt.ylabel(\"$g(r)$\")\n", "\n", "plt.legend(frameon=False, loc=\"best\", ncol=3);\n", "plt.tight_layout()" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.12" } }, "nbformat": 4, "nbformat_minor": 5 }