{ "cells": [ { "cell_type": "markdown", "id": "87161496-0816-4bf9-a536-54ee33d91697", "metadata": {}, "source": [ "The goal of this second part of the tutorial is to demonstrate how to resume\n", "the calculation from the first part and visualize the results. In addition,\n", "we will compare these results to an analytical model to assess their quality.\n", "Before we begin, make sure we have the working directory generated by\n", "``CoverageAndReactionRate.ipynb`` or ``CoverageAndReactionRate.py``. We'll\n", "assume it's called ``plams_workdir``, which is the default value. However,\n", "keep in mind that each time you run any of the above scripts, PLAMS will\n", "create a new working directory by appending a sequential number to its name,\n", "for example, ``plams_workdir.001``. If this is the case, simply replace\n", "``plams_workdir`` with the appropriate value.\n", "\n", "So, let's get started!\n", "\n", "First, we load the required packages and retrieve the ``ZacrosParametersScanJob``\n", "(``job``) and corresponding results object (``results``) from the working\n", "directory, as shown below: " ] }, { "cell_type": "code", "execution_count": 1, "id": "d0e2630b-24e0-4634-bc18-f96aa8674287", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "PLAMS working folder: /home/aguirre/Develop/pyzacros/examples/ZiffGulariBarshad/plams_workdir.002\n", "[27.01|09:45:00] PLAMS run finished. Goodbye\n" ] } ], "source": [ "import scm.pyzacros as pz\n", "import scm.pyzacros.models\n", "\n", "scm.pyzacros.init()\n", "\n", "job = scm.pyzacros.load(\"plams_workdir/plamsjob/plamsjob.dill\")\n", "results = job.results\n", "\n", "scm.pyzacros.finish()" ] }, { "cell_type": "markdown", "id": "dcbc8ac1-155e-4221-8902-b3159d803f6a", "metadata": {}, "source": [ "To be certain, we generate and print the same summary table from the end of\n", "the first part of the tutorial. They must be exactly the same: " ] }, { "cell_type": "code", "execution_count": 2, "id": "0a18a701-c66f-4a99-b95b-401910c0535e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "------------------------------------------------\n", "cond x_CO ac_O ac_CO TOF_CO2\n", "------------------------------------------------\n", " 0 0.05 0.665594 0.028219 54.733748\n", " 1 0.14 0.615375 0.082844 135.299544\n", " 2 0.23 0.582250 0.126594 198.215992\n", " 3 0.32 0.532375 0.178719 257.936395\n", " 4 0.41 0.497031 0.221625 300.382949\n", " 5 0.50 0.442750 0.272969 329.214754\n", " 6 0.59 0.402031 0.318562 352.259276\n", " 7 0.68 0.351687 0.372437 351.805662\n", " 8 0.77 0.297906 0.422687 332.247334\n", " 9 0.86 0.232156 0.488156 310.444388\n", " 10 0.95 0.144281 0.554344 220.656898\n" ] } ], "source": [ "x_CO = []\n", "ac_O = []\n", "ac_CO = []\n", "TOF_CO2 = []\n", "\n", "results_dict = results.turnover_frequency()\n", "results_dict = results.average_coverage(last=10, update=results_dict)\n", "\n", "for i in range(len(results_dict)):\n", " x_CO.append(results_dict[i][\"x_CO\"])\n", " ac_O.append(results_dict[i][\"average_coverage\"][\"O*\"])\n", " ac_CO.append(results_dict[i][\"average_coverage\"][\"CO*\"])\n", " TOF_CO2.append(results_dict[i][\"turnover_frequency\"][\"CO2\"])\n", "\n", "print(\"------------------------------------------------\")\n", "print(\"%4s\" % \"cond\", \"%8s\" % \"x_CO\", \"%10s\" % \"ac_O\", \"%10s\" % \"ac_CO\", \"%12s\" % \"TOF_CO2\")\n", "print(\"------------------------------------------------\")\n", "for i in range(len(x_CO)):\n", " print(\"%4d\" % i, \"%8.2f\" % x_CO[i], \"%10.6f\" % ac_O[i], \"%10.6f\" % ac_CO[i], \"%12.6f\" % TOF_CO2[i])" ] }, { "cell_type": "markdown", "id": "bb2f92f9-c6a1-4f81-827d-039b12a77182", "metadata": {}, "source": [ "Additionally, you can see the aforementioned results visually if you have\n", "installed the package [matplotlib](https://matplotlib.org/). Please review\n", "the code below." ] }, { "cell_type": "code", "execution_count": 3, "id": "5256b826-334e-4400-9e15-5fe472aa80d7", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "\n", "fig = plt.figure()\n", "\n", "ax = plt.axes()\n", "ax.set_xlim([0.0, 1.0])\n", "ax.set_xlabel(\"Molar Fraction CO\", fontsize=14)\n", "ax.set_ylabel(\"Coverage Fraction (%)\", color=\"blue\", fontsize=14)\n", "ax.plot(x_CO, ac_O, marker=\"$\\u25CF$\", color=\"blue\", linestyle=\"-.\", markersize=4, zorder=2)\n", "ax.plot(x_CO, ac_CO, marker=\"$\\u25EF$\", color=\"blue\", markersize=4, zorder=4)\n", "plt.text(0.3, 0.60, \"O*\", fontsize=18, color=\"blue\")\n", "plt.text(0.7, 0.45, \"CO*\", fontsize=18, color=\"blue\")\n", "\n", "ax2 = ax.twinx()\n", "ax2.set_ylabel(\"TOF (mol/s/site)\", color=\"red\", fontsize=14)\n", "ax2.plot(x_CO, TOF_CO2, marker=\"$\\u25EF$\", color=\"red\", markersize=4, zorder=6)\n", "plt.text(0.3, 200.0, \"CO$_2$\", fontsize=18, color=\"red\")\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "881b9b8f-42b4-4777-b3eb-5938c2322882", "metadata": {}, "source": [ "Starting from the left side of the figure, it shows that by increasing\n", "the ``x_CO``; the net $CO$ oxidation reaction tends to progress more quickly\n", "(like a first-order reaction). Then the reaction rate peaks at around\n", "``x_CO=0.7``, becoming almost independent of ``x_CO`` (like a zero-order\n", "reaction). And finally, it then begins to decline (like a negative-order\n", "reaction). Furthermore, we can see that as we increase the coverage of $CO*$,\n", "we decrease the coverage of $O*$. As a result, when we mostly cover the\n", "surface with one of the reactants (either $CO*$ or $O*$), the rate of $CO_2$\n", "production becomes slow because there isn't enough of the complementary\n", "reactant on the surface. So, it is not a surprise, that the maximum $CO_2$\n", "generation coincides with the point at which $CO*$ coverage equals $O*$\n", "coverage." ] }, { "cell_type": "markdown", "id": "267730e7-d08f-4399-96be-b9cf2db856dc", "metadata": {}, "source": [ "In the Zacros tutorial [What's KMC All About and Why Bother?](https://zacros.org/tutorials/12-about-kinetic-monte-carlo?showall=1),\n", "there is a thorough discussion of Langmuir-Hinshelwood-type models, their\n", "approximations with respect to a real system, and how to obtain analytical\n", "expressions for reactant coverages and the net reaction rates concerning\n", "gas phase composition. In particular, these expressions are reached by\n", "making the fundamental assumption that both diffusion and\n", "adsorption/desorption events are quasi-equilibrated (being the later one\n", "the rate-limiting factor), occurring on a much faster timescale than the\n", "oxidation event. We use the same argument to speed up our calculations.\n", "Thus, we can use the analytical expressions we obtained to assess the\n", "overall quality of our results. Our results should be indistinguishable\n", "from the Langmuir-Hinshelwood deterministic equations, which are shown\n", "below:\n", "\n", "$$\n", "\\begin{gather}\n", "\\theta_\\text{O} = \\frac{ \\sqrt{B_{\\text{O}_2}x_{\\text{O}_2}} }{ 1 + B_\\text{CO}x_\\text{CO} + \\sqrt{B_{\\text{O}_2}x_{\\text{O}_2}} } \\\\\n", "\\theta_\\text{CO} = \\frac{ B_\\text{CO}x_\\text{CO} }{ 1 + B_\\text{CO}x_\\text{CO} + \\sqrt{B_{\\text{O}_2}x_{\\text{O}_2}} } \\\\[7mm]\n", "\\text{TOF}_{\\text{CO}_2} = 6 \\, A_\\text{oxi}\\theta_\\text{CO}\\theta_\\text{O}\n", "\\end{gather}\n", "$$\n", "\n", "Here $B_\\text{CO}$/$B_{\\text{O}_2}$ represent the ratio of the adsorption-desorption\n", "pre-exponential terms of $CO$/$O_2$ (``pe_ratio`` in Zacros), $x_\\text{CO}$/$x_{\\text{O}_2}$\n", "the molar fractions of $CO$/$O_2$; $\\theta_\\text{CO}$/$\\theta_\\text{O}$\n", "the coverage of $CO*$/$O*$, $A_\\text{oxi}$ the pre-exponential factor of the\n", "CO oxidation step (``pre_expon`` in Zacros), and TOF$_{\\text{CO}_2}$ the turnover\n", "frequency or production rate of $CO_2$. The number 6 is because, in our lattice,\n", "each site has 6 neighbors, so the oxidation event is \"replicated\" across\n", "each neighboring site.\n", "\n", "Notice that to get the above expressions based on the ones shown in the Zacros\n", "tutorial, you need the following equalities:\n", "\n", "$$\n", "\\begin{gather}\n", "K_s P_s = \\left( \\frac{A^\\text{ads}_s P^{-1}}{A^\\text{des}_s} \\right) x_s P = B_s x_s \\qquad \\therefore\\qquad s=\\text{CO},\\text{O}_2\n", "\\\\\n", "k_\\text{oxi} = A_\\text{oxi}\n", "\\end{gather}\n", "$$\n", "\n", "The final equality follows from the fact that in pyZacros, the activation energy\n", "for all elementary reactions is equal to zero.\n", "\n", "The code below simply computes the coverages and TOF of $CO_2$ using the analytical\n", "expression described above: " ] }, { "cell_type": "code", "execution_count": 4, "id": "819145e0-d7aa-421a-b120-055bfcfc8386", "metadata": {}, "outputs": [], "source": [ "import numpy\n", "\n", "lh = pz.models.LangmuirHinshelwood()\n", "\n", "B_CO = lh.mechanism.find_one(\"CO_adsorption\").pe_ratio\n", "B_O2 = lh.mechanism.find_one(\"O2_adsorption\").pe_ratio\n", "A_oxi = lh.mechanism.find_one(\"CO_oxidation\").pre_expon\n", "\n", "x_CO_model = numpy.linspace(0.0, 1.0, 201)\n", "\n", "ac_O_model = []\n", "ac_CO_model = []\n", "TOF_CO2_model = []\n", "\n", "for i in range(len(x_CO_model)):\n", " x_O2 = 1 - x_CO_model[i]\n", " ac_O_model.append(numpy.sqrt(B_O2 * x_O2) / (1 + B_CO * x_CO_model[i] + numpy.sqrt(B_O2 * x_O2)))\n", " ac_CO_model.append(B_CO * x_CO_model[i] / (1 + B_CO * x_CO_model[i] + numpy.sqrt(B_O2 * x_O2)))\n", " TOF_CO2_model.append(6 * A_oxi * ac_CO_model[i] * ac_O_model[i])" ] }, { "cell_type": "markdown", "id": "385f7a09-e47f-4be0-b134-5a107a60c6ae", "metadata": {}, "source": [ "Additionally, if you have installed the package [matplotlib](https://matplotlib.org/),\n", "you can see the aforementioned results visually. Please look over the code below, and\n", "notice we plot the analytical and simulation results together. The points in the\n", "figure represent simulation results, while the lines represent analytical model results.\n", "They are nearly identical. " ] }, { "cell_type": "code", "execution_count": 5, "id": "7edf60f6-f241-4597-9e6d-645ca484a31e", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "\n", "x_CO_max = (B_O2 / B_CO**2 / 2.0) * (numpy.sqrt(1.0 + 4.0 * B_CO**2 / B_O2) - 1.0)\n", "\n", "fig = plt.figure()\n", "\n", "ax = plt.axes()\n", "ax.set_xlim([0.0, 1.0])\n", "ax.set_xlabel(\"Molar Fraction CO\", fontsize=14)\n", "ax.set_ylabel(\"Coverage Fraction (%)\", color=\"blue\", fontsize=14)\n", "ax.vlines(\n", " x_CO_max,\n", " 0,\n", " max(ac_O_model),\n", " colors=\"0.8\",\n", " linestyles=\"--\",\n", ")\n", "ax.plot(x_CO_model, ac_O_model, color=\"blue\", linestyle=\"-.\", lw=2, zorder=1)\n", "ax.plot(x_CO, ac_O, marker=\"$\\u25CF$\", color=\"blue\", lw=0, markersize=4, zorder=2)\n", "ax.plot(x_CO_model, ac_CO_model, color=\"blue\", linestyle=\"-\", lw=2, zorder=3)\n", "ax.plot(x_CO, ac_CO, marker=\"$\\u25EF$\", color=\"blue\", markersize=4, lw=0, zorder=4)\n", "plt.text(0.3, 0.60, \"O*\", fontsize=18, color=\"blue\")\n", "plt.text(0.7, 0.45, \"CO*\", fontsize=18, color=\"blue\")\n", "\n", "ax2 = ax.twinx()\n", "ax2.set_ylabel(\"TOF (mol/s/site)\", color=\"red\", fontsize=14)\n", "ax2.plot(x_CO_model, TOF_CO2_model, color=\"red\", linestyle=\"-\", lw=2, zorder=5)\n", "ax2.plot(x_CO, TOF_CO2, marker=\"$\\u25EF$\", color=\"red\", markersize=4, lw=0, zorder=6)\n", "plt.text(0.3, 200.0, \"CO$_2$\", fontsize=18, color=\"red\")\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "eb5d6a8d-f9de-4658-a583-a67942d6b37e", "metadata": {}, "source": [ "As a final note, we included in the code above the value of the $CO$ molar fraction\n", "($x_\\text{CO}^*$) on which we get the maximum $CO_2$ production rate. The figure shows\n", "this value as a vertical gray dashed line. It is simple to deduce it from the\n", "preceding analytical expressions: \n", "\n", "$$\n", "x_{CO}^* = \\frac{B_{\\text{O}_2}}{2 B_\\text{CO}^2}\\left( \\sqrt{1+\\frac{4 B_\\text{CO}^2}{B_{\\text{O}_2}}} - 1 \\right)\\approx 0.656\n", "$$\n", "\n", "Notice that the position of this maximum $x_\\text{CO}*$ depends exclusively on the ratio\n", "of the ``pe_ratio`` parameters for $CO$ and $O_2$ in the Langmuir-Hinshelwood model." ] } ], "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": "3.8.12" } }, "nbformat": 4, "nbformat_minor": 5 }