{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "87ed6cf5-01f3-4983-8480-3d2a676fd7fb",
   "metadata": {},
   "source": [
    "This example is inspired in the seminal paper: Kinetic Phase Transitions in\n",
    "an Irreversible Surface-Reaction Model by Robert M. Ziff, Erdagon Gulari,\n",
    "and Yoav Barshad in 1986\n",
    "[Phys. Rev. Lett. 56, (1986) 2553](https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.56.2553>).\n",
    "The authors proposed a simple model for catalytic reactions of carbon monoxide\n",
    "oxidation to carbon dioxide on a surface. This model is now known as the\n",
    "Ziff-Gulari-Barshad (ZGB) model after their names.  While the model leaves\n",
    "out many important steps of the real system, it exhibits interesting\n",
    "steady-state off-equilibrium behavior and two types of phase transitions,\n",
    "which actually occur in real systems. Please refer to the original paper\n",
    "for more details. In this example, we will analyze the effect of changing\n",
    "the composition of the gas phase, namely partial pressures for $O_2$ and $CO$,\n",
    "in the $CO_2$ Turnover frequency (TOF) in the ZGB model."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db348e0d-a14a-4800-b535-25f3b4092e8d",
   "metadata": {},
   "source": [
    "The first step is to import all packages we need:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "55aad7db-eccd-4f5b-a506-1e48121c2eed",
   "metadata": {},
   "outputs": [],
   "source": [
    "import multiprocessing\n",
    "import numpy\n",
    "import scm.plams\n",
    "import scm.pyzacros as pz"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94c93e75-a3b3-438b-9819-41dba9db5f6d",
   "metadata": {},
   "source": [
    "First must define the system. So, we have to specify species, lattice, cluster\n",
    "expansion, and mechanisms. As we said above, we will use the ZGB model, which\n",
    "consists on:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fad722b7-ec7a-464d-bbb5-ab421f279ed1",
   "metadata": {},
   "source": [
    "**1. Three gas species:** $CO$, $O_2$, and $CO_2$. Notice that the ``gas_energy``\n",
    "by default is zero unless otherwise stated. That's the case for $CO$ and $O2$,\n",
    "which are used as energy references."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5626ecb8-b05f-47c9-9ea7-518b47bf2475",
   "metadata": {},
   "outputs": [],
   "source": [
    "CO_gas = pz.Species(\"CO\")\n",
    "O2_gas = pz.Species(\"O2\")\n",
    "CO2_gas = pz.Species(\"CO2\", gas_energy=-2.337)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de861c15-eac1-490d-bf1e-db348cd84307",
   "metadata": {},
   "source": [
    "**2. Three surface species:** $*$, $CO^*$, $O^*$. The species $*$ represents the\n",
    "empty adsorption site. All of them have denticity equal to 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1ab7b234-7b4c-4830-8b84-453dc8c24f44",
   "metadata": {},
   "outputs": [],
   "source": [
    "s0 = pz.Species(\"*\", 1)\n",
    "CO_ads = pz.Species(\"CO*\", 1)\n",
    "O_ads = pz.Species(\"O*\", 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5007b98d-f6e5-4011-97f3-08984baac9c5",
   "metadata": {},
   "source": [
    "**3. A rectangular lattice with a single site type**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "2cd44048-68f1-436b-9b9e-3da59f6dda81",
   "metadata": {},
   "outputs": [],
   "source": [
    "lattice = pz.Lattice(lattice_type=pz.Lattice.RECTANGULAR, lattice_constant=1.0, repeat_cell=[50, 50])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "91ccd9fc-21ed-4832-bf09-b7b1a521c115",
   "metadata": {},
   "source": [
    "**4. Two clusters in the cluster-expansion Hamiltonian:** $CO^*$-bs and $O^*$-bs.\n",
    "They are attached to a single binding site. No lateral interactions are considered."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "76bf61a4-a0ea-4a8a-ba78-3bfb91ec6c2c",
   "metadata": {},
   "outputs": [],
   "source": [
    "CO_point = pz.Cluster(species=[CO_ads], energy=-1.3)\n",
    "O_point = pz.Cluster(species=[O_ads], energy=-2.3)\n",
    "\n",
    "cluster_expansion = [CO_point, O_point]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "781a718d-fc91-4735-942d-79f70e346d51",
   "metadata": {},
   "source": [
    "**5. Three irreversible events**: adsorption of $CO$, dissociative adsorption\n",
    "of $O_2$, and $CO$ oxidation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c50f1199-2162-47c9-bbe4-2a50f5361871",
   "metadata": {},
   "outputs": [],
   "source": [
    "# CO_adsorption:\n",
    "CO_adsorption = pz.ElementaryReaction(\n",
    "    initial=[s0, CO_gas], final=[CO_ads], reversible=False, pre_expon=10.0, activation_energy=0.0\n",
    ")\n",
    "\n",
    "# O2_adsorption:\n",
    "O2_adsorption = pz.ElementaryReaction(\n",
    "    initial=[s0, s0, O2_gas],\n",
    "    final=[O_ads, O_ads],\n",
    "    neighboring=[(0, 1)],\n",
    "    reversible=False,\n",
    "    pre_expon=2.5,\n",
    "    activation_energy=0.0,\n",
    ")\n",
    "\n",
    "# CO_oxidation:\n",
    "CO_oxidation = pz.ElementaryReaction(\n",
    "    initial=[CO_ads, O_ads],\n",
    "    final=[s0, s0, CO2_gas],\n",
    "    neighboring=[(0, 1)],\n",
    "    reversible=False,\n",
    "    pre_expon=1.0e20,\n",
    "    activation_energy=0.0,\n",
    ")\n",
    "\n",
    "mechanism = [CO_adsorption, O2_adsorption, CO_oxidation]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a7666b1-3500-4b82-a40b-d8b7b38d6f79",
   "metadata": {},
   "source": [
    "Now, we initialize the **pyZacros** environment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "513cd76f-ae22-445e-841d-7861a431de3a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PLAMS working folder: /home/aguirre/Develop/pyzacros/examples/ZiffGulariBarshad/plams_workdir\n"
     ]
    }
   ],
   "source": [
    "scm.pyzacros.init()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9766a041-d1ad-4cd9-99c2-35fe48009d08",
   "metadata": {},
   "source": [
    "This calculation is relatively fast. On a typical laptop, it should take\n",
    "around 1 min to complete. However, to illustrate how to run several in\n",
    "parallel Zacros calculations, we'll use the ``plams.JobRunner`` class,\n",
    "which easily allows us to run as many parallel instances as we request.\n",
    "In this case, we choose to use the maximum number of simultaneous processes\n",
    "(``maxjobs``) equal to the number of processors in the machine. Additionally,\n",
    "by setting ``nproc =  1`` we establish that only one processor will be used\n",
    "for each zacros instance. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "adaa16bb-5c20-4e4c-8194-8ad3da304521",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running up to 8 jobs in parallel simultaneously\n"
     ]
    }
   ],
   "source": [
    "maxjobs = multiprocessing.cpu_count()\n",
    "scm.plams.config.default_jobrunner = scm.plams.JobRunner(parallel=True, maxjobs=maxjobs)\n",
    "scm.plams.config.job.runscript.nproc = 1\n",
    "print(\"Running up to {} jobs in parallel simultaneously\".format(maxjobs))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1db5742a-41bf-4748-99d2-c51e8c7a74ce",
   "metadata": {},
   "source": [
    "Now we have to set up the calculation using a ``Settings`` object. Firstly,\n",
    "we set a reactants gas phase composition of 45% $CO$ and 55% $O_2$. Notice\n",
    "that we assumed that the gas phase is composed only of $CO$ and $O_2$; thus,\n",
    "$x_\\text{CO} +x_{\\text{O}_2} =1$. Keep in mind that these values are actually\n",
    "not affecting the calculation because, later on, these are the ones we will\n",
    "modify systematically. Then, we set the physical parameters as temperature\n",
    "(500 K) and pressure (1 bar). Finally, we set the maximum time for the\n",
    "simulation to 10 s (``max_time``), and we save snapshots of the lattice state\n",
    "every 0.5 s (``snapshots``) and the number of species every 0.1 s\n",
    "(``species_numbers``). The last line sets the random seed to make the\n",
    "calculations reproducible."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "09008bb3-59d2-4cd2-8b73-ea2134ba8240",
   "metadata": {},
   "outputs": [],
   "source": [
    "sett = pz.Settings()\n",
    "sett.molar_fraction.CO = 0.45\n",
    "sett.molar_fraction.O2 = 0.55\n",
    "sett.temperature = 500.0\n",
    "sett.pressure = 1.0\n",
    "sett.max_time = 10.0\n",
    "sett.snapshots = (\"time\", 0.5)\n",
    "sett.species_numbers = (\"time\", 0.1)\n",
    "sett.random_seed = 953129"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e8ab1ca-9645-4261-b1fc-a7939844a3a6",
   "metadata": {},
   "source": [
    "The calculation parameters setup is ready. Therefore, we can proceed to run\n",
    "the calculations. In this instance, we are interested in exploring the\n",
    "production of $CO_2$ by ranging the $CO$ molar fraction ``x_CO`` from 0.02\n",
    "to 0.8 in steps of 0.01. Remember that $O_2$ molar fraction is set to satisfy\n",
    "$x_\\text{CO}+x_{\\text{O}_2}=1$. The loop creates one ``ZacrosJob`` for each\n",
    "value of ``x_CO`` (condition) using the settings and system's properties\n",
    "defined above and executing it by invoking the function ``run()``. Notice\n",
    "that results are stored in the vector ``results`` for further analysis once\n",
    "they are finished. In the output, observe that **pyZacros** creates a new\n",
    "folder for each condition, following the sequence ``plamsjob.002``,\n",
    "``plamsjob.003``, ``plamsjob.004``, and so on for ``x_CO=0.20, 0.21, 0.22, ...``\n",
    "respectively. The second loop calls the method ``job.ok()`` of every job to\n",
    "ensure that every calculation was completed successfully and wait for all\n",
    "parallel processes to complete before proceeding to access the results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b6c6bbad-1a26-4093-a5b4-56c41b8229c8",
   "metadata": {
    "scrolled": true,
    "tags": [
     "cut_output=10_10"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[02.02|22:23:20] JOB plamsjob STARTED\n",
      "[02.02|22:23:20] JOB plamsjob STARTED\n",
      "[02.02|22:23:20] Renaming job plamsjob to plamsjob.002\n",
      "[02.02|22:23:20] JOB plamsjob STARTED\n",
      "[02.02|22:23:20] Renaming job plamsjob to plamsjob.003\n",
      "[02.02|22:23:20] JOB plamsjob STARTED\n",
      "[02.02|22:23:20] Renaming job plamsjob to plamsjob.004\n",
      "[02.02|22:23:20] JOB plamsjob STARTED\n",
      "[02.02|22:23:20] Renaming job plamsjob to plamsjob.005\n",
      "[02.02|22:23:20] JOB plamsjob STARTED\n",
      "[02.02|22:23:20] JOB plamsjob RUNNING\n",
      "[02.02|22:23:20] Renaming job plamsjob to plamsjob.006\n",
      "[02.02|22:23:20] JOB plamsjob STARTED\n",
      "[02.02|22:23:20] JOB plamsjob.002 RUNNING\n",
      "[02.02|22:23:20] Renaming job plamsjob to plamsjob.007\n",
      "[02.02|22:23:20] JOB plamsjob STARTED\n",
      "[02.02|22:23:20] JOB plamsjob.003 RUNNING\n",
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      "[02.02|22:23:20] Renaming job plamsjob to plamsjob.008\n",
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      "[02.02|22:23:20] Renaming job plamsjob to plamsjob.047\n",
      "[02.02|22:23:20] Renaming job plamsjob to plamsjob.048\n",
      "[02.02|22:23:20] JOB plamsjob STARTED\n",
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      "[02.02|22:23:20] Renaming job plamsjob to plamsjob.049\n",
      "[02.02|22:23:20] JOB plamsjob STARTED\n",
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      "[02.02|22:23:21] Renaming job plamsjob to plamsjob.050\n",
      "[02.02|22:23:21] JOB plamsjob STARTED\n",
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      "[02.02|22:23:21] Renaming job plamsjob to plamsjob.051\n",
      "[02.02|22:23:21] JOB plamsjob STARTED\n",
      "[02.02|22:23:21] Renaming job plamsjob to plamsjob.052\n",
      "[02.02|22:23:21] JOB plamsjob STARTED\n",
      "[02.02|22:23:21] JOB plamsjob.011 FINISHED\n",
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      "[02.02|22:23:21] Renaming job plamsjob to plamsjob.053\n",
      "[02.02|22:23:21] JOB plamsjob STARTED\n",
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      "[02.02|22:23:21] JOB plamsjob.010 FINISHED\n",
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      "[02.02|22:23:21] Renaming job plamsjob to plamsjob.054\n",
      "[02.02|22:23:21] JOB plamsjob STARTED\n",
      "[02.02|22:23:21] JOB plamsjob.014 FINISHED\n",
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      "[02.02|22:23:21] JOB plamsjob.011 SUCCESSFUL\n",
      "[02.02|22:23:21] Renaming job plamsjob to plamsjob.055\n",
      "[02.02|22:23:21] JOB plamsjob STARTED\n",
      "[02.02|22:23:22] JOB plamsjob.006 SUCCESSFUL\n",
      "[02.02|22:23:22] JOB plamsjob SUCCESSFUL\n",
      "[02.02|22:23:22] JOB plamsjob.004 SUCCESSFUL\n",
      "[02.02|22:23:22] JOB plamsjob STARTED\n",
      "[02.02|22:23:22] JOB plamsjob.003 SUCCESSFUL\n",
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      "[02.02|22:23:23] Renaming job plamsjob to plamsjob.057\n",
      "[02.02|22:23:23] JOB plamsjob STARTED\n",
      "[02.02|22:23:23] JOB plamsjob STARTED\n",
      "[02.02|22:23:23] Renaming job plamsjob to plamsjob.058\n",
      "[02.02|22:23:23] JOB plamsjob.016 SUCCESSFUL\n",
      "[02.02|22:23:23] JOB plamsjob.018 SUCCESSFUL\n",
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      "[02.02|22:23:23] Renaming job plamsjob to plamsjob.059\n",
      "[02.02|22:23:23] JOB plamsjob.020 SUCCESSFUL\n",
      "[02.02|22:23:23] JOB plamsjob STARTED\n",
      "[02.02|22:23:23] JOB plamsjob.055 RUNNING\n",
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      "[02.02|22:23:23] JOB plamsjob.023 SUCCESSFUL\n",
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      "[02.02|22:23:24] Renaming job plamsjob to plamsjob.060\n",
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      "[02.02|22:23:24] Renaming job plamsjob to plamsjob.061\n",
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      "[02.02|22:23:28] Waiting for job plamsjob.051 to finish\n",
      "[02.02|22:23:28] JOB plamsjob.052 SUCCESSFUL\n",
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      "[02.02|22:23:28] Waiting for job plamsjob.054 to finish\n",
      "[02.02|22:23:28] JOB plamsjob.054 SUCCESSFUL\n",
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      "[02.02|22:23:28] JOB plamsjob.055 SUCCESSFUL\n",
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      "[02.02|22:23:28] JOB plamsjob.058 SUCCESSFUL\n",
      "[02.02|22:23:28] Waiting for job plamsjob.058 to finish\n",
      "[02.02|22:23:28] JOB plamsjob.059 SUCCESSFUL\n",
      "[02.02|22:23:28] Waiting for job plamsjob.061 to finish\n",
      "[02.02|22:23:28] JOB plamsjob.061 SUCCESSFUL\n"
     ]
    }
   ],
   "source": [
    "x_CO = numpy.arange(0.2, 0.8, 0.01)\n",
    "\n",
    "results = []\n",
    "for x in x_CO:\n",
    "    sett.molar_fraction.CO = x\n",
    "    sett.molar_fraction.O2 = 1.0 - x\n",
    "\n",
    "    job = pz.ZacrosJob(settings=sett, lattice=lattice, mechanism=mechanism, cluster_expansion=cluster_expansion)\n",
    "\n",
    "    results.append(job.run())\n",
    "\n",
    "for i, x in enumerate(x_CO):\n",
    "    if not results[i].job.ok():\n",
    "        print(\"Something went wrong with condition xCO={}!\".format(x))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8122809b-ba6f-40e3-82ab-9c348ff93f6c",
   "metadata": {},
   "source": [
    "If the script worked successfully, you should have seen several\n",
    "``SUCCESSFUL`` messages at the output's end."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a44a784-ac4f-44d3-9941-0cbe0480eb23",
   "metadata": {
    "tags": []
   },
   "source": [
    "Now we need to extract the results we want, in this case, the\n",
    "average coverage and the turnover frequency of $CO_2$, and store\n",
    "them conveniently, as in arrays. We use the ``turnover frequency``\n",
    "method for the latter, and average coverage for the former, specifying\n",
    "that we want to use the last five lattice states (``last=5``):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "6fd42e72-7809-4223-9c3b-ed1e33063b20",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "ac_O = []\n",
    "ac_CO = []\n",
    "TOF_CO2 = []\n",
    "\n",
    "for i, x in enumerate(x_CO):\n",
    "    ac = results[i].average_coverage(last=5)\n",
    "    TOFs, _, _, _ = results[i].turnover_frequency()\n",
    "\n",
    "    ac_O.append(ac[\"O*\"])\n",
    "    ac_CO.append(ac[\"CO*\"])\n",
    "    TOF_CO2.append(TOFs[\"CO2\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "072ef844-684b-40f1-ab91-c883d378243b",
   "metadata": {},
   "source": [
    "Finally, we just nicely print the results in a table."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "3dd5915c-8c11-4424-a8ca-527d8a0bea7a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "----------------------------------------------\n",
      "cond     x_CO       ac_O      ac_CO    TOF_CO2\n",
      "----------------------------------------------\n",
      "   0     0.20   0.998000   0.000000   0.049895\n",
      "   1     0.21   1.000000   0.000000   0.046695\n",
      "   2     0.22   1.000000   0.000000   0.051747\n",
      "   3     0.23   0.998880   0.000000   0.053747\n",
      "   4     0.24   0.997600   0.000000   0.061937\n",
      "   5     0.25   0.996560   0.000000   0.087368\n",
      "   6     0.26   0.998960   0.000000   0.073600\n",
      "   7     0.27   0.998160   0.000000   0.085537\n",
      "   8     0.28   0.997680   0.000000   0.098905\n",
      "   9     0.29   0.994560   0.000000   0.111011\n",
      "  10     0.30   0.995840   0.000000   0.123811\n",
      "  11     0.31   0.996320   0.000000   0.134463\n",
      "  12     0.32   0.991760   0.000000   0.163811\n",
      "  13     0.33   0.991680   0.000000   0.165958\n",
      "  14     0.34   0.989360   0.000000   0.224589\n",
      "  15     0.35   0.981680   0.000000   0.273811\n",
      "  16     0.36   0.962960   0.000240   0.319789\n",
      "  17     0.37   0.963440   0.000160   0.352800\n",
      "  18     0.38   0.938000   0.000320   0.404000\n",
      "  19     0.39   0.936640   0.000400   0.508589\n",
      "  20     0.40   0.898320   0.000480   0.577095\n",
      "  21     0.41   0.872800   0.000880   0.640084\n",
      "  22     0.42   0.868560   0.001280   0.756400\n",
      "  23     0.43   0.827680   0.001680   0.895537\n",
      "  24     0.44   0.808400   0.002160   1.002884\n",
      "  25     0.45   0.759280   0.002960   1.266484\n",
      "  26     0.46   0.732080   0.006480   1.337684\n",
      "  27     0.47   0.657520   0.009200   1.523621\n",
      "  28     0.48   0.641520   0.010880   1.729979\n",
      "  29     0.49   0.592960   0.020000   1.872905\n",
      "  30     0.50   0.567280   0.022480   2.108442\n",
      "  31     0.51   0.567920   0.024880   2.259958\n",
      "  32     0.52   0.432000   0.066880   2.537432\n",
      "  33     0.53   0.402960   0.078960   2.770863\n",
      "  34     0.54   0.062480   0.757680   2.093579\n",
      "  35     0.55   0.019520   0.913760   1.770484\n",
      "  36     0.56   0.000000   1.000000   0.940568\n",
      "  37     0.57   0.000000   1.000000   0.489347\n",
      "  38     0.58   0.000000   1.000000   0.356063\n",
      "  39     0.59   0.000000   1.000000   0.253705\n",
      "  40     0.60   0.000000   1.000000   0.221453\n",
      "  41     0.61   0.000000   1.000000   0.154316\n",
      "  42     0.62   0.000000   1.000000   0.107621\n",
      "  43     0.63   0.000000   1.000000   0.066926\n",
      "  44     0.64   0.000000   1.000000   0.059116\n",
      "  45     0.65   0.000000   1.000000   0.042695\n",
      "  46     0.66   0.000000   1.000000   0.040632\n",
      "  47     0.67   0.000000   1.000000   0.029074\n",
      "  48     0.68   0.000000   1.000000   0.012905\n",
      "  49     0.69   0.000000   1.000000   0.009411\n",
      "  50     0.70   0.000000   1.000000   0.008863\n",
      "  51     0.71   0.000000   1.000000   0.007221\n",
      "  52     0.72   0.000000   1.000000   0.003768\n",
      "  53     0.73   0.000000   1.000000   0.002063\n",
      "  54     0.74   0.000000   1.000000   0.002105\n",
      "  55     0.75   0.000000   1.000000   0.000611\n",
      "  56     0.76   0.000000   1.000000   0.000758\n",
      "  57     0.77   0.000000   1.000000   0.000400\n",
      "  58     0.78   0.000000   1.000000   0.000000\n",
      "  59     0.79   0.000000   1.000000   0.000758\n",
      "  60     0.80   0.000000   1.000000   0.000589\n"
     ]
    }
   ],
   "source": [
    "print(\"----------------------------------------------\")\n",
    "print(\"%4s\" % \"cond\", \"%8s\" % \"x_CO\", \"%10s\" % \"ac_O\", \"%10s\" % \"ac_CO\", \"%10s\" % \"TOF_CO2\")\n",
    "print(\"----------------------------------------------\")\n",
    "\n",
    "for i, x in enumerate(x_CO):\n",
    "    print(\"%4d\" % i, \"%8.2f\" % x_CO[i], \"%10.6f\" % ac_O[i], \"%10.6f\" % ac_CO[i], \"%10.6f\" % TOF_CO2[i])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d05115c2-32ea-44f6-b7a4-0a7885205c7c",
   "metadata": {},
   "source": [
    "The above results are the final aim of the calculation. However, we\n",
    "can take advantage of python libraries to visualize them. Here, we\n",
    "use matplotlib. Please check the matplotlib documentation for more\n",
    "details at [matplotlib](https://matplotlib.org/). The following lines\n",
    "of code allow visualizing the effect of changing the $CO$ molar\n",
    "fraction on the average coverage of $O*$ and $CO*$ and the production\n",
    "rate of $CO_2$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "bd26fdc6-031b-4213-ba61-d5c32c475fc5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fig = plt.figure()\n",
    "\n",
    "ax = plt.axes()\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, color=\"blue\", linestyle=\"-.\", lw=2, zorder=1)\n",
    "ax.plot(x_CO, ac_CO, color=\"blue\", linestyle=\"-\", lw=2, zorder=2)\n",
    "plt.text(0.3, 0.9, \"O\", fontsize=18, color=\"blue\")\n",
    "plt.text(0.7, 0.9, \"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, color=\"red\", lw=2, zorder=5)\n",
    "plt.text(0.37, 1.5, \"CO$_2$\", fontsize=18, color=\"red\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b936999c-77eb-4969-b88c-f84b1ddf8e77",
   "metadata": {},
   "source": [
    "This model assumes that gas-phase molecules of $CO$ and $O_2$ are\n",
    "adsorbed immediately on empty sites, and when the $0*$ and $CO*$ occupy\n",
    "adjacent sites, they react immediately. This model is intrinsically\n",
    "irreversible because the molecules are sticky to their original sites\n",
    "and remain stationary until they are removed by a reaction. This leads\n",
    "to the figure above having three regions:\n",
    "\n",
    "1. Oxygen poisoned state, $x_\\text{CO}<0.32$.\n",
    "2. Reactive state $0.32<x_\\text{CO}<0.55$.\n",
    "3. CO poisoned state $x_\\text{CO}>0.55$.\n",
    "\n",
    "The first transition at $x_\\text{CO}=0.32$ is continuous, and therefore\n",
    "it is of the second order. The second transition at $x_\\text{CO}=0.55$\n",
    "occurs abruptly, implying that this is of a first-order transition.\n",
    "As you increase the simulation time, the transition becomes more abrupt.\n",
    "We will discuss this effect in the next tutorial\n",
    "**Ziff-Gulari-Barshad model: Steady State Conditions**."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87277127-9129-4853-ba7b-bda8a0bf52cb",
   "metadata": {},
   "source": [
    "**pyZacros** also offers some predefined plot functions that use matplotlib\n",
    "as well. For example, it is possible to see a typical reactive state\n",
    "configuration $x_\\text{CO}=0.54$ and one in the process of being poisoned\n",
    "by $CO$ ($x_\\text{CO}=0.55$). Just get the last lattice state with the\n",
    "``last_lattice_state()`` function and visualize it with ``plot()``. See\n",
    "the code and figures below."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e28d394-22eb-4006-87af-2f800c4c72e6",
   "metadata": {},
   "source": [
    "The state at $x_\\text{CO}=0.54$ is a prototypical steady-state,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "b2679be9-7a1f-4386-a57d-b220f87c8f9f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results[33].last_lattice_state().plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f188f2e-7798-4a6c-b314-dff2bc5e03d4",
   "metadata": {},
   "source": [
    "contrary to the one at $x_\\text{CO}=0.55$, is a good example\n",
    "where we can see the two phases coexisting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "248b86e4-6254-41c6-b823-30b4e3841bd2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results[34].last_lattice_state().plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "576b729b-4929-4deb-b3ae-50931b6e8203",
   "metadata": {},
   "source": [
    "In the previous paragraph, we introduced the concept of steady-state.\n",
    "However, let's define it slightly more formally. For our study system,\n",
    "the steady-state for a given composition is characterized when the\n",
    "derivative of the $CO_2$ production (TOF) with respect to time is zero\n",
    "and remains so:\n",
    "\n",
    "$$\n",
    "\\frac{d}{dt}TOF_{\\text{CO}_2} = 0, \\,\\,\\text{for all present and future}\\,\\, t\n",
    "$$\n",
    "\n",
    "**pyZacros** also offers the function ``plot_molecule_numbers()`` to\n",
    "visualize the molecule numbers and its first derivative as a function\n",
    "of time. See code and figures below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "97c8c748-abaf-4968-9184-f4b3d86a97d2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results[33].plot_molecule_numbers([\"CO2\"], normalize_per_site=True)\n",
    "results[34].plot_molecule_numbers([\"CO2\"], normalize_per_site=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "57761799-3a5b-41af-938c-9e73d52a980e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results[33].plot_molecule_numbers([\"CO2\"], normalize_per_site=True, derivative=True)\n",
    "results[34].plot_molecule_numbers([\"CO2\"], normalize_per_site=True, derivative=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d33aa4ee-66d6-4cac-9e0e-f57bf77bc118",
   "metadata": {},
   "source": [
    "From the figures above, it is clear that we have reached a steady-state for\n",
    "$x_\\text{CO}=0.54$. Notice that the first derivative is approximately constant\n",
    "at 2.7 mol/s/site within a tolerance of 5 mol/s/site. Contrary, this is not\n",
    "the case of $x_\\text{CO}=0.55$, where the first derivative continuously decreases."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a30d22a-d760-4a9e-ace5-1c2bffe7b9e5",
   "metadata": {},
   "source": [
    "Now, we can close the pyZacros environment:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "553680f4-3131-4f5b-abfd-2e23547c2ba4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[02.02|22:24:09] PLAMS run finished. Goodbye\n"
     ]
    }
   ],
   "source": [
    "scm.pyzacros.finish()"
   ]
  }
 ],
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