{ "cells": [ { "cell_type": "markdown", "id": "dbdeb9b0-adaf-4663-8558-0cbc72ae1a0b", "metadata": {}, "source": [ "## Initial imports" ] }, { "cell_type": "code", "execution_count": 1, "id": "0aa88d32-1696-4a3a-9394-1533e5a955dc", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "PLAMS working folder: /path/plams/examples/AMSTSWorkflow/plams_workdir\n" ] } ], "source": [ "from scm.plams import *\n", "import numpy as np\n", "import os\n", "import matplotlib.pyplot as plt\n", "from typing import List\n", "\n", "# this line is not required in AMS2025+\n", "init()" ] }, { "cell_type": "markdown", "id": "6757c176-5f21-40a3-8544-5b9d90fd7128", "metadata": {}, "source": [ "## Function definitions\n", "\n", "The ``addition()`` function \n", "\n", "* performs a preliminary MD simulation with UFF to arrange the two reactant molecules at an approximate transition state,\n", "\n", "* then does a transition state search with DFTB, specifying the known reaction coordinate (bond formation),\n", "\n", "* then uses the PESExploration LandscapeRefinement tool to get the two corresponding minima and energy landscape. Alternatively, one could also do an IRC (intrinsic reaction coordinate) calculation." ] }, { "cell_type": "code", "execution_count": 2, "id": "38725c5d-09d3-472e-b6de-5aa5b4a97ef0", "metadata": {}, "outputs": [], "source": [ "def addition(\n", " mol1: Molecule,\n", " mol2: Molecule,\n", " covalent_radius_multiplier: float = 1.2,\n", "):\n", " mol1_ind = get_active_i(mol1)\n", " mol2_ind = get_active_i(mol2)\n", " if len(mol1_ind) != 2:\n", " raise ValueError(f\"Set at.properties.active_bond for two atoms in mol1. Current mol1_ind: {mol1_ind}\")\n", " if len(mol2_ind) != 2:\n", " raise ValueError(f\"Set at.properties.active_bond for two atoms in mol2. Current mol2_ind: {mol2_ind}\")\n", "\n", " target_distances = []\n", "\n", " for i1, i2 in zip(mol1_ind, mol2_ind):\n", " r = get_atom_radius(mol1[i1]) + get_atom_radius(mol2[i2])\n", " target_distances.append(r * covalent_radius_multiplier)\n", "\n", " combined = mol1.copy()\n", " combined.add_molecule(mol2, margin=2)\n", " combined.properties.charge = mol1.properties.get(\"charge\", 0) + mol2.properties.get(\"charge\", 0)\n", "\n", " mol2_ind = [x + len(mol1) for x in mol2_ind]\n", "\n", " preliminary_md_results = preliminary_md(\n", " combined,\n", " mol1_ind,\n", " mol2_ind,\n", " target_distances=target_distances,\n", " temperature=600,\n", " nsteps=20000,\n", " )\n", " mol = preliminary_md_results.get_main_molecule()\n", "\n", " ts_search_results = ts_search(mol, mol1_ind, mol2_ind)\n", " mol = ts_search_results.get_main_molecule()\n", "\n", " relax_from_saddle_results = relax_from_saddle(mol)\n", "\n", " return preliminary_md_results, ts_search_results, relax_from_saddle_results\n", "\n", "\n", "def ts_search(molecule, atom_indices_1: List[int], atom_indices_2: List[int], settings: Settings = None) -> AMSResults:\n", " if settings is None:\n", " settings = Settings()\n", " settings.input.DFTB\n", " # settings.runscript.nproc = 1\n", " settings.input.ams.GeometryOptimization.InitialHessian.Type = \"Calculate\"\n", " settings.input.ams.Properties.NormalModes = \"Yes\"\n", " settings.input.ams.GeometryOptimization.Convergence.Quality = \"Good\"\n", "\n", " s = settings.copy()\n", " s.input.ams.task = \"TransitionStateSearch\"\n", " s.input.ams.TransitionStateSearch.ReactionCoordinate.Distance = [\n", " f\"{a1} {a2} 1.0\" for a1, a2 in zip(atom_indices_1, atom_indices_2)\n", " ]\n", "\n", " job = AMSJob(settings=s, name=\"ts_search\", molecule=molecule)\n", " job.run()\n", "\n", " return job.results\n", "\n", "\n", "def relax_from_saddle(molecule: Molecule, settings: Settings = None) -> AMSResults:\n", " if settings is None:\n", " settings = Settings()\n", " settings.input.DFTB\n", " settings.input.ams.GeometryOptimization.InitialHessian.Type = \"Calculate\"\n", " # settings.runscript.nproc = 1\n", "\n", " s = settings.copy()\n", " s.input.ams.task = \"PESExploration\"\n", " s.input.ams.PESExploration.Job = \"LandscapeRefinement\"\n", " s.input.ams.PESExploration.LandscapeRefinement.RelaxFromSaddlePoint = \"T\"\n", "\n", " m = {\"state1 ts=Yes\": molecule}\n", "\n", " job = AMSJob(settings=s, name=\"refinement\", molecule=m)\n", " job.run()\n", "\n", " return job.results\n", "\n", "\n", "def irc(molecule: Molecule, settings: Settings = None):\n", " if settings is None:\n", " settings = Settings()\n", " settings.input.DFTB\n", " # settings.runscript.nproc = 1\n", "\n", " s = settings.copy()\n", " s.input.ams.task = \"IRC\"\n", " s.input.ams.IRC.MinEnergyProfile = \"Yes\"\n", "\n", " job = AMSJob(settings=s, name=\"irc\", molecule=molecule)\n", " job.run()\n", "\n", " converged = job.results.get_history_property(\"Converged\")\n", " direction = job.results.get_history_property(\"IRCDirection\")\n", " energies = job.results.get_history_property(\"Energy\")\n", " ind = dict()\n", " energy = dict()\n", " for i, (c, d, e) in enumerate(zip(converged, direction, energies)):\n", " if c:\n", " ind[d] = i + 1\n", " energy[d] = e\n", "\n", " min1 = job.results.get_history_molecule(ind[1])\n", " min2 = job.results.get_history_molecule(ind[2])\n", " ts = job.results.get_input_molecule()\n", "\n", " return min1, energy[1], min2, energy[2], ts, energies[0]\n", "\n", "\n", "def preliminary_md(\n", " molecule: Molecule,\n", " atom_indices_1: List[int],\n", " atom_indices_2: List[int],\n", " target_distances: List[float],\n", " nsteps: int = 10000,\n", " kappa: float = 100000,\n", " settings: Settings = None,\n", " temperature: float = 300,\n", ") -> Molecule:\n", " if settings is None:\n", " settings = Settings()\n", " settings.input.ForceField.Type = \"UFF\"\n", " settings.runscript.nproc = 1\n", "\n", " plumed_input = \"\\n\"\n", " for a1, a2, d in zip(atom_indices_1, atom_indices_2, target_distances):\n", " # current_d = molecule[a1].distance_to(molecule[a2])\n", " plumed_input += f\"DISTANCE ATOMS={a1},{a2} LABEL=d_{a1}_{a2}\\n\"\n", " plumed_input += f\"MOVINGRESTRAINT ARG=d_{a1}_{a2}\"\n", " plumed_input += f\" STEP0=1 AT0={d*0.1} KAPPA0=0\"\n", " plumed_input += f\" STEP1={1*nsteps//4} KAPPA1={kappa/1000}\"\n", " plumed_input += f\" STEP2={2*nsteps//4} KAPPA2={kappa/100}\"\n", " plumed_input += f\" STEP3={3*nsteps//4} KAPPA3={kappa/10}\"\n", " plumed_input += f\" STEP4={4*nsteps//4} KAPPA4={kappa}\"\n", " plumed_input += f\"\\n\"\n", "\n", " plumed_input += \" End\"\n", " settings.input.ams.MolecularDynamics.Plumed.Input = plumed_input\n", "\n", " job = AMSNVTJob(\n", " name=\"preliminary_md\",\n", " settings=settings,\n", " molecule=molecule,\n", " nsteps=nsteps,\n", " temperature=3 * [temperature] + [1],\n", " )\n", " job.run()\n", "\n", " return job.results\n", "\n", "\n", "def set_active(mol: Molecule, indices: List[int]):\n", " for at in mol:\n", " if \"active_bond\" in at.properties:\n", " del at.properties[\"active_bond\"]\n", " for i, ind in enumerate(indices, 1):\n", " mol[ind].properties.active_bond = i\n", "\n", "\n", "def get_active_i(mol: Molecule) -> List[int]:\n", " d = {}\n", " for i, at in enumerate(mol, 1):\n", " if \"active_bond\" in at.properties and at.properties.active_bond:\n", " d[i] = at.properties.active_bond\n", "\n", " return sorted(d, key=lambda x: d[x])\n", "\n", "\n", "def get_atom_radius(at: Atom) -> float:\n", " return PeriodicTable.get_radius(at.symbol)" ] }, { "cell_type": "markdown", "id": "39594112-2dc1-4649-a478-07205f37cc51", "metadata": {}, "source": [ "## Run the calculations" ] }, { "cell_type": "code", "execution_count": 3, "id": "6c98359e-a2d9-484b-b8ed-6f4c2296cea2", "metadata": {}, "outputs": [], "source": [ "diene_smiles = \"C1C=CC=C1\"\n", "diene = from_smiles(\n", " diene_smiles\n", ") # carbon 2, 4 will form bonds. Do diene.write('diene.xyz') and open diene.xyz in the AMS GUI to find out which atom indices are correct.\n", "set_active(diene, [2, 4])" ] }, { "cell_type": "code", "execution_count": 4, "id": "f3ed28c8-59e0-4aa2-9182-bd4ca7808e5e", "metadata": {}, "outputs": [ { "data": { "image/png": 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/jkWLFiEnJwchISEwNDSkWhJNB4FBCB2rgYaGCuiWj4aGImjz0dBQBG0+GhqKoM1HQ0MRtPloaCiCHudTYMrKylBaWgoejwdtbW1069YN6urqVMuikRF0y6dg8Pl8REZGwsXFBfr6+ujbty8GDBiAnj17okuXLli+fDlSUlKolkkjA2jzKQiEEPj7+6NHjx6YNWsW6urqEBwcjGvXriEpKQkXL17E1q1bcenSJQwePBgODg5ITEykWjZNW5D1RFMa6REKhcTb25sAIIsXLyZpaWnNphUIBOT06dPE3t6esFgsEhkZ2Y5KaWQJbT4F4KuvviIMBoMEBga2OA+PxyMeHh5ERUWFXLx4UY7qaOQFPb2MYsLDwzF37lzs27cPPj4+UuUVCARwd3dHfHw8njx5Qs8r7WDQ5qMYBwcHaGtr4+LFi63KX1ZWBjabja1bt2Lr1q0yVkcjT+gOFwq5c+cObt++LXWL9y56enqYP38+AgMDIRAIZKiORt7Q5qOQgIAAmJmZwc3NrU3leHl5IS8vD2fPnpWRMpr2gDYfhVy+fBkeHh7N7iPZUgYNGoQ+ffrg8uXLMlJG0x7Q5qMQLpcrs04SQ0PDNm38S9P+0OajEIFAILM4cyoqKuDz+TIpi6Z9oM1HITo6OjJrrbhcbpPBXmgUF9p8FGJnZ4fz58+3uZyCggKkp6ejtrYWjx8/ljo8MQ010OajkLVr1yIpKanNE6XF2+SHhITA0tIS/fv3R1BQ0Ed3eqahFnqQnUIEAgF69eqFsWPH4s8//2xVGXw+H6ampjA3N8fkyZPx7NkzJCUl4eHDh9DQ0MCSJUvw1VdfSQKl0CgOdMtHISoqKvDw8EBoaCgSEhJaVcbOnTtRXFyM4cOHQ11dHba2tli+fDm2bduGoUOHIiQkBDY2NvDz85NJSC4a2UG3fBQhEokQEBCAr7/+GiKRCOrq6rh69Wqz8eCawt/fH97e3nBzc8PYsWObTFNXV4czZ84gLi4Ozs7OCA4ORq9evWR0FjRtgW75KKCiogLjxo2Dj48PBg0ahG+++QadO3fG8OHDcfTo0Y8OGZSWluKrr76Ct7c3nJ2dPxhDrlOnTpg1axa8vLzw8OFD9OvXDxEREbI+JZpWQLd87UxJSQnGjRuH7OxseHp6SkI+19XVISwsDOnp6TAwMMDq1auxfPlymJqagsFgQCgU4s6dO/Dz80N4eDhEIhHc3NwwatSoFgcEraurQ0REBFJTU3HgwIEG4dBo2h/afO1IWVkZRowYgYKCAqxevRrGxsaN0hQWFiI+Ph4pKSmora2FsrIy1NTUJD2XXbp0wbBhw+Dg4NAoNHFLEIlEiIqKws2bNxEYGEgbkEJo87UTNTU1GDNmDDIyMuDt7f3RaWW1tbXIzMxEdXU1+Hw+1NTUoKenBwsLCygpte1tgRCCkydPIi4uDseOHYOHh0ebyqNpHbT52gkfHx8cPHgQ69atg6mpKdVyIBKJEBYWhoyMDDx48KBBHHea9oHucGkHYmNj4efnBzc3N4UwHvA29PHs2bOhpqaGZcuW0cMQFECbT85UV1dj6dKlsLCwwIgRI6iW0wAWiwUPDw9cu3YNgYGBVMv57KDNJ2e+++47FBUVYc6cOW1+V5MHffv2haOjIzZt2oTc3Fyq5XxWKN7d8AlRUlKCwMBAjB07Fl27dqVaTrNMmTIFSkpK8PX1pVrKZwVtPjkSHBwMQggcHR2plvJBWCwWhgwZguDgYLx584ZqOZ8NtPnkhFAohL+/PwYMGAANDQ2q5XwUR0dHVFZW4tixY1RL+WygzScnYmJikJeXp3CdLM3RpUsXWFlZYd++ffR6wHaCNp+ciIiIAJvNhpmZGdVSWszQoUORlpaGnJwcqqV8FtDmkxO3b99G9+7dqZYhFeKB9jt37lCs5OMIBAKUlpaCy+V22DFKOj6fHKiursaTJ08wcOBAqqVIRefOnaGnp4eUlJRmp5yJRCJkZWUhJSUFWVlZePPmDerq6sBkMsFiscBms8HhcNCvXz906tRJpvqqqqoQFhaGgIAApKenS44zGAyMGDECXl5emD59OlRVVWVar7ygzScH0tLSQAgBm82mWorUmJiYNGr5nj59iuDgYMTFxSE1NVUyyVtHRwedOnWCsrIyRCIR+Hy+pCViMpmwtraGg4MDFi5ciOHDh7d49cX7VFVVYevWrTh8+DBqamrg7u6OdevWQV9fH0KhECUlJYiIiMDcuXNhYGAAb29vbNmyRWY7w8kLxVbXQUlNTQWTyYSRkRHVUqSGzWbj1q1bEAqFiImJgZ+fHy5cuAB1dXX07t0bo0aNgqmpKdhsdpO9uPX19SgsLER+fj7y8vIQFRWFoKAgWFtbw8fHBwsXLkTnzp1brKeoqAhubm7Izs7G+vXrsWrVqian6InXK/r7++PHH39EUlISwsPDFbqnmZ5YLQe2bduGwMBAbNu2jWopUpOUlIR//vkHpqamyMvLQ/fu3eHo6IiBAwe26nFO/JgaHx+PBw8eQE1NDVu2bMHmzZvBZDI/mLe8vBxOTk6oqKhATEwM+vXr16I6L1y4gFmzZsHJyQlnzpz5aD1UQbd8coDH4yn8I09ziG9UdXV1fPXVV23urVVSUkLfvn3Rt29fcLlcXL9+HT/88AMiIyMREhLyQUMtXLgQL1++REJCgmTRcUsYP348Tp06hQkTJmDLli347bff2nQO8oLu7ZQDQqFQIedxtgSxbk9PT5kPk+jq6mLatGnYsGEDXr58CQ6Hg507dzYZXen+/fs4e/Ys9u/fL5XxxLi4uOC7775DQEAAKioqZCFf5nTMO0TBYbFYHTZcl1i3PHsMzczMsHHjRjg7O+OHH37ArFmzUFtb2yBNQEAADA0NMWvWrFbXs3r1atTX1+PIkSNtlSwXaPPJAU1NTfB4PKpltIra2looKSnJ/bFZRUUFkydPxvLlyxETE4PJkydLrlllZSVCQ0OxatWqNr2vGRsbY/r06fD391fIWTu0+eSAtbU1qqqqFPZx50MUFBTAwMCg1cMC0mJjY4NVq1YhLi4Os2bNAp/Px82bN1FdXY1Fixa1uXxPT09kZmbi2bNnMlArW2jzyQEOhwMAyM/Pp1iJ9OTn57f7ansLCwssXboUFy9ehLe3N16/fg0AMhknFZdRVlbW5rJkDW0+OWBmZgZdXV3k5eVRLUUqBAIBCgsLKdnqwtLSEtOnT8fBgweRmpoKQDbvneJZNnV1dW0uS9bQ5pMDDAYDgwcP7nDmKyoqglAopGxmjqOjIywtLREaGgoAMnlsF4dgU8TwabT55MTo0aMlcx87Cvfu3QOLxYKJiQkl9TMYDMyZM0dyza5fv97mMq9fvw4Wi6UwG1e9Cz3D5QPw+Xw8fPgQKSkpkr/S0lLU1tZCJBKBxWJBU1MTdnZ24HA44HA4GDhwILS0tPDy5UuYmZlJdpVWdAQCAXbs2IFBgwZhxowZlGq5desWwsPDMWTIECQlJbW6HKFQiF69esHFxQXBwcEyVCgbOuY0DDlCCMH169fh5+eHM2fOoK6uDgwGA4aGhjAxMUGPHj3AZDLBYDDA5/PB4/Fw69YtnDhxAvX19ZJHTm9vb0ydOhU3b97EyJEjFX7Q/d69e6iuroaTkxPVUuDg4IDLly/j9u3bePLkCfr06dOqcs6dO4cXL17A29tbxgplA93y/R+VlZU4cuQI9u/fj8ePH8PQ0BD29vbo2bMnTExMPro8RigUori4GHl5eUhLS0NGRgY0NTVRXV2NtWvXtmqWRnuyd+9eKCsrK8yNevXqVZw5cwYTJkzAf//7X6l/vGpqajB8+HAwmUzcvn1bTirbBm0+AGfOnMHKlSvx6tUr2NnZwcnJCRYWFm0a63r16hXi4+Nx8+ZNGBkZ4csvv4SysrIMVcuOhw8f4uDBg1i2bBns7OyolgPg7ZrIHTt2QCAQwMfHB76+vi02YG1tLWbOnIkbN27g5s2bUoVda08U+1lIznC5XCxatAhTpkyBvr4+vv/+eyxZsgS9e/du8yBz165dMW3aNKxZswYFBQWIjY2VkWrZ8ubNG4SHh8Pa2rrFqwbaA01NTQwcOBD6+vrYv38/5s+fj5KSko/me/bsGVxdXREbG4sTJ04orPGAz9h8V69ehZWVFU6ePIl58+Zh5cqVcumOFq+Bi4mJwcuXL2VefluJiopCfX09PDw82m1WS0uxs7PD69evceDAAURHR8PU1BQLFy5EQkJCg+liQqEQZ8+ehZubGywsLJCVlYXY2FiMHz+eQvUf57M038mTJzFx4kRoa2tj8+bNcHBwkOuNN3HiROjr6+Pvv/9WqAnXDx48QHJyMqZPnw4dHR2q5TRCPDxgYGCAvLw8/PLLL0hMTISTkxP09fVhYWGBnj17QkdHB5MnT8bLly9x6NAh5OTkwMHBgWL1H+eze+c7fvw45s6diwEDBmD+/Pnttu7u+fPn2LdvH+zs7LBo0SLKez9zc3Ph7++P3r17Y/ny5QrX6gFve563b9+OL774Aj///DOAt4tzL126hLt374LL5UJZWRm6urpwdnaGvb29Qp5Hc3Q481VWViIyMhJ5eXmoqqqChoYGDAwMMGPGDBgYGHww7/nz5zFlyhTY2dlhwYIF7W6Ae/fu4fDhw3BwcICHhwdlBszPz4e/vz8MDAywZs0amW90JEuCgoJgZmaGmJgYqqXInA5jvvv378Pf3x+hoaHg8Xjo1q0bOnfujJqaGpSUlIDBYGDmzJnw8vJqcrOevLw82NjYwMzMDMuWLaOs5/H27dv4559/MGDAACxYsKDdV7w/e/YMQUFB6Nq1K9auXQt1dfV2rV9azpw5gydPnuDFixdUS5E5Cv/Ox+fzsXLlStjZ2eH06dPYtGkTXrx4gaKiIjx58gQFBQUoKSnBrl27kJKSgpEjR2LixImorKyUlEEIwYoVK6CsrIwFCxZQ2uU/ZMgQLFmyBOnp6fD19UVRUVG71CsUCnHp0iX4+fmBzWbD29tb4Y0HvF2Y3JGm6EmDQrd89fX1mDZtGi5fvoy9e/di+fLlH1xcKRKJ8N///heenp7o3r07rl69Cn19ffz5559YsWIFVq1aBWtr63Y8g+bJzc3F33//jdLSUkyYMAFjxoyR249CUVERwsLCUFBQgDFjxmDChAkKu6nQ+1y7dg2XL19GVVUV1VJkjsKajxCCxYsXIzw8HGfPnoWrq2uL8z58+BCjRo2CpaUlgoODweFwYGVlhfnz58tRsfTw+XycP38eV69ehZGRESZPngxLS0uZvQtWVFQgLi4OV69eBZPJxNq1azvcLtpXrlzBjRs3UF5eTrUUmaOwcztjYmIQGhqKsLAwqYwHvF0dfebMGYwcORJLly4Fg8HAtGnT5CO0DTCZTLi7u8POzg6BgYGSd7Fhw4bBwcGhVXtOEkLw9OlTxMfHIz09HaqqqrCyssKbN286nPGAtz9QLBaLahlyQWFbvsmTJ6OoqAh37txpdffx/PnzceLECYwaNQpubm4yVihbcnJy4OvrizFjxiAuLg6EEFhYWIDNZksCrujo6DS6FuJNavPy8pCXl4fc3FwUFxejT58+8PHxgaenJ3bu3Im//vqrQ+4jeuzYMdTU1DTYHv5TQSFbvpycHJw7dw4HDx5s07iNl5cX/vnnn48OQSgCPXr0gKmpKdTU1JCfn4+QkBBcu3YNd+7cwaVLlwC83UuTxWJBRUUFIpEIAoEAlZWVku3ZbWxsMHXqVMyZMwejR4+WXLtBgwZh9+7dqK6uhqamJpWnKTUFBQUYO3Ys1TLkgkKa79ChQ9DS0sK8efPaVI6TkxOsra1x//59DB48WEbq5AODwYCjoyMiIiJQU1ODTZs2YdOmTQDedpikpKTg0aNHqKmpQW1tLVRUVMBisWBgYAAOhwNbW9tmx+vEe8rk5eXBysqq3c6prfD5fBQWFkr0f2oopPkeP34MBweHNneFMxgMuLi44OTJkzJSJl8GDRqE6OhohIWFYevWrZLj4s6YyZMnt6pcc3NzaGlpIT8/v0OZT7ythaL/cLYWhRznKy8vl9lcQ11d3Q4zTtSpUyeYmZm1afV2UygpKYHD4Sjk9nkf4tmzZ1BRUVGYZU6yRiHNp6qqivr6epmUJY4d11Fgs9lyCU45d+5cPH78WCG30GsKQgiSkpIwderUT7a3UyHNp6+vL7Odv/Lz86GmpiaTstoDU1NTFBUVyXz50fz586GhoYFbt27JtFx5kZ2djaKiIoVZWS8PFNJ8bm5ukg6GtlBRUYGoqKgO9Z4jXkaTkpIi03I1NTWxZMkSJCUlKdSypuZISEhAnz59OsTmU61FIc03Y8YMdOvWDQEBAW0qJzQ0FLW1tRg2bJiMlMkfPT09KCkpyWXPz7Vr16KyslKyKa2iUlZWhvT0dPj4+HSoJULSopDmU1VVxcqVKxESEtLqjVOFQiH2798POzs7aGtry1ih/GAwGFBVVW0UtUcWWFlZYebMmThz5owktLOiQQhBREQEDAwMsHjxYqrlyBWFNB8ArFmzRrKJKp/PlyovIQTr1q1DVlYWnJ2d5aRQfigrK8usw+l9/Pz8wGQyceLECbmU31YSExORmZmJ4OBgaGlpUS1Hriis+dhsNk6ePIkrV6402MX4Y4hEImzcuBEBAQEYOXIkevbsKWelsofP58ttgauBgQH8/f2RlpaGtLQ0udTRWrhcLqKjo7Fs2TKF339FFiis+YC30UWjoqJw4cIFODg4ICQkpNm4dwKBAKdPn8bo0aPh6+sL4O3mRR0NkUgEPp8v1x5aDw8PTJ8+HSdOnMCrV6/kVo801NfX4+jRo9DV1cWePXuoltMuKLT5gLcTrG/evAkTExMsWbIEbDYbGzduxNGjRxEdHY2///4bO3bsQK9evTBt2jTU1dUhOjoa6urqKC4uplq+1JSUlEgmVcsLBoOBoKAgGBsb48CBA5Qv1xEKhThy5AgKCgoQERHRod7R24LCrmpoiuzsbBw4cACHDx+WxHAD3k44njdvHtauXSuZB+jo6Ija2toO99KenJyMsLAwcLlcue8olp+fL7lOa9asgb6+vlzrawo+n48jR44gMzMT0dHRmDBhQrtroIoOZb534fF4qKyshKamJtTV1Rt1SW/YsAHHjh3Dli1bKFLYOk6ePIn8/Hw8ffq0Xep7/vw5XFxcUFZWhiVLlqBHjx7tUi/wdhz26NGjyMvLk2zn+Dmh8I+dzaGmpgYDAwNoaGg0ORbE4XBQXFzc4WKjFxQUwN7evt3q69GjB+Lj49G7d2/s3bsX0dHRUvcuSwshBHfu3MGuXbtQXl6OixcvfnbGAzqw+T6Go6MjACAjI4NiJS2nuroaubm5Eu3thaGhIRISErBz507ExcXh999/x/Pnz+VSV0VFBYKDg3H06FG4u7sjIyMDI0aMkEtdik6HfexsCaNGjUJBQQF8fHyoltIiLl++jIsXL6KwsJCS9y/g7f43np6eSE1NhZmZGUxMTKCnpweBQABlZWWoqKhAS0sLbDYb3bp1a/F+MwUFBYiLi0Nqaiq0tLRw4MAByuMAUo1CrueTFd7e3vDw8EBRURGMjIyolvNBRCIREhMTMW/ePEqMV15ejqNHj+L69esoLS0FALx48QIFBQVgMplgMpkghEAgEEhm36iqqkq2uRg0aBC6d+8ueQUghKC8vBzZ2dlITEzE06dPYWhoiC1btsDb2xtdunRp93NUND7plo/P54PNZqNPnz6YNWsW1XI+iDhMV1JSEoYMGdJu9aampsLf3x9hYWHg8/no2bMn2Gw2TE1NwWaz0bVr10at25s3b5Cfn4/8/Hzk5eXh2bNnqKiogK6uLgwNDSESiVBUVCTZO3X06NHw9vbGlClTOtTyLnnzSZsPALZv345///vf2Lx5M2WPch9DJBJh37590NbWRmpqartMJr579y68vLyQmJgIPT09DB06FEOHDm3VlC6RSITMzEzcvHkTGRkZYDKZcHJywrp16zB06FAYGxvL4Qw6Pp+8+SorK2FtbQ1NTU3JfFFF49q1azh9+jSuX78u986H+vp67Ny5E7/88gsMDQ0xbtw42NjYyGzD3tevX0uCUtrZ2SEkJOSTXYneVj558wHAhQsXMGHCBMyePVshYo4Db1fY5+fnIzMzE1euXMHAgQMxatQosFgsaGpqwtbWFhwOR6bvqnfv3oWnpycyMjLg6uqKsWPHyi1WxIsXL3Ds2DG8evUK33//Pb799lv6kfM9PgvzAcCKFSsQFhaGr7/+mpLHT6FQiIcPHyI9PR15eXmSaWTKyspQV1eXTBQQCAR48+aNZCK5gYEBBg8eDFdXVyxevLjVATyjo6Mxe/ZsdOvWDXPnzgWbzZbl6TWJQCDAhQsXcOXKFYwbNw6RkZEdIj5Ee/HZmK+yshI2NjYA3u7n2V43QWVlJRITE5GQkIDy8nKYmJg06NQwNDRs9MhHCAGXy5VshJufn4/s7GyoqKhg3rx58Pb2lmo7vX/++QeLFi2Cra0tFi1a1O6RkR4/fozg4GDY29sjJiamw+0dKi8+G/MBbyOxjhw5Ejo6Oli9erVcN+bh8XiIjo5GUlISVFRUwOFw4OTk1OoWp6qqComJibh16xbKysowbNgwBAYGfjSO+unTpzFz5kxwOBzMmTOHsghNOTk5CAoKwrBhw3D27NlPdlMkafiszAe8jY/n6uoKPT09rFq1qlXxED5GRkYGwsPDwePxMGHCBJnsQSpGKBTi0aNHiImJwatXr7B9+3Zs3ry5yfep5ORkDB8+HNbW1vD09KQ8Gu7Tp08RGBiIGTNm4J9//qFUiyLw2ZkPeDu2NX78eCgpKWHevHkyW3DL4/Fw6tQpJCUloW/fvpg7d26r39E+xrvvU/3790dISEiDVrC2thYDBgwAj8fDF1980e6Pms2RmpqKI0eOIDw8HB4eHlTLoZTP0nwAkJWVhYULFyI5ORnOzs6YNGkSVFVVW11eZWUlAgICUFZWhmnTpmHo0KHtMqwh7lUsLy/H6dOnJRGdtmzZgt9++w0bN25UuNk9hw8fRl5eHh49eoRu3bpRLYcyPlvzAW8f4fbs2YNt27ZBV1cX06dPR9++faU2DZfLhZ+fH/h8PtauXQtDQ0M5KW6a+vp6HD58GNnZ2Th+/DgMDQ0xbNgwTJw4USGDjFRVVWHXrl0YN26cwu4l0x581uYTk5mZiaVLlyIxMVFy49rb27foPa26uhp79+4Fn8+Hj48PZbNoBAIBQkNDkZGRATabDYFAgPXr11MaAvtD3L17FyEhIYiJifmsFtC+C22+/4MQghs3bsDPzw9RUVFQVlZGv3790KNHD5iZmcHIyKhRp4ZQKISvry+4XC6++OILdO3alSL1bxEIBDh06BAeP36MOXPmYOjQoZTq+Rh79uyBjY0Nzp07R7UUSqDN1wRFRUU4dOgQjh8/joyMDMlyGmNjY2hqaoLJZILBYKCoqAivXr3Chg0bFCbqa11dHXbt2oXOnTvjiy++oLyH80MkJiYiPDwc2dnZ6NWrF9Vy2h3F/Z+hECMjI3z//fdIT09HVVUVkpKSsG/fPowfPx59+/aFkZER1NTUUFpaChcXF4UxHvA20tGCBQuQm5uLa9euUS3ngwwaNAjq6uoIDAykWgol0C1fK+Dz+XBwcMDLly+xceNGhenGf5eoqCjEx8fj66+/VujIvFFRUbh//z6Kiora1NvcEaFbvlYQFBSEe/fuYd68eQppPOBtsBldXV2FDww6cOBAlJWV4f79+1RLaXdo80kJIQS+vr7o378/zMzMqJbTLKqqqhg/fjweP36s0PuXGhsbQ0lJSS4xCRUd2nxSEhsbi6ysLIVZmvQh+vfvDw0NDSQkJFAtpVlUVVVhZGQk85BoHQHafFLi5+cHIyMjmJubUy3lozCZTAwdOhRJSUmoq6ujWk6zmJiYIDk5mWoZ7Q5tPil4+fIlTp8+DUdHR4VcEd8Ujo6OqKurw927d6mW0izGxsZtDoTaEaHNJwXx8fEQCoUdalsEfX19sNnsdtsBuzWoqamhvr6+Q0TMlSW0+aQgJSUFurq6HS6Qh6mpqVwi3coK8cwheQQEVWRo80lBcnIyTExMqJYhNaampiguLlbY9z6RSAQACjsPVV7Q5mshhBCkpKS0y94nssbU1BSEEBQWFlItpUnEsSHkFRBUUaHN10JKSkrA5XI75B6UhoaGYDAYePnyJdVSmkS84a4iz0OVB5/X2bYB8W5iHXHvERUVFTCZTLnFeW8r+fn5Um0I9alAm6+FiDsDFHU62cdQUVGRe+iv1lJQUIDBgwdTLaPdoc3XQsSdAeLOgY6GSCRSyA6NyspKcLlcuuWjaR41NTUAUNjW42Pw+XyFbLVzcnIAgDYfTfPo6+tDSUkJ5eXlVEuRmqqqKgiFQnTu3JlqKY1ISkrCwIED2zUctaJAm6+FqKuro2/fvgo9WN0cYs2KNkxSWlqKjIwM+Pj4dJjperKENp8U2Nvbo6CggGoZUpOXlwd1dXWFC5GWkJAALS0tzJ07l2oplECbTwo4HA4KCgo63BzEvLw8sNlshWpd6urqcPv2bSxbtuyzDZ5Cm08KBg8eDIFA0KEePYVCIXJzc2Fqakq1lAacOXMGQqEQX3zxBdVSKIM2nxQ4ODiAzWbj1q1bVEtpMQ8fPkRVVRUGDBhAtRQJT548QVxcHHbt2vVZdrSIoc0nBcrKyvDy8kJaWhpqamqoltMi4uLi0L17d4Vp+erq6hAREQFnZ2d4eXlRLYdSaPNJyfLly0EIwe3bt6mW8lFKSkrw5MkT2NraUi0FwNvJ6SdOnEBNTQ2Cg4M/yzV870KbT0q6deuGWbNmISEhQeFvnBs3boDJZCIuLg6lpaWUaiGE4NSpU0hOToaBgQGsra2hpqYGJpMJbW1tzJkzB9evX8fntJMlvW9nK0hPTweHw8GYMWMwadIkyfHy8nLk5+dLJmGrq6vD1NSUksW3z58/x969e/Hdd9/h77//RkVFBVavXk1JVCBCCKKjoxEbGwsAcHd3h6urK3R0dMDn81FYWIiwsDA8fvwY1tbW2LRpE5YsWaJQvbPygDZfK9mxYwd+/vlnbNiwAbW1tYiPj8f9+/cbzf0Ux3xwcnKChYVFu9xQ9fX12LNnj6RzqLi4GC4uLigqKsLSpUtlFo+wpVqOHz+O5ORkjB07FkFBQU12shBCEBsbi/379yMqKgre3t7w9fVVyPmosoI2Xyupr6+Hra0t8vLyUFtbC0tLS/j4+GDatGno0qULgLczOE6ePIn9+/fjyZMnMDExweLFi+Xe+kRHRyMuLg53796FtbW1RIu7uztu376NUaNGYeLEiU1Gs5Ulz549Q1hYGLhcLn799Vds3ry5RfmCgoLg5eWFlStXwt/f/5NtAWnztZJbt25h4sSJMDQ0RGBgIEaOHNnsTUIIwbVr17B27VoUFBRg5cqVcovvkJGRgYMHD2Lnzp349ttvG3wnEAjw+++/44cffoCenh7mzp0rl67++vp6nD17FtevX4eqqirOnTsHFxcXqcr4888/sWLFCvj5+X2yvaK0+VpBZmYmHB0dYWtri+joaOjo6LQoH5fLxaRJk/DgwQOsX79e5iHFnj17hgMHDsDV1RWnT59udhXDo0ePsHjxYqSmpsLW1hZOTk7o3bt3m1eSV1RUIDExEYmJiaipqZGY8N33Ymnw9PTEtWvXkJOT80k+ftLmkxJCCDgcDurq6hAfH99i44kpKyvD0KFDwefzsWHDBpnpys7Oxp9//gl7e3ucP39esgSqOQQCAYKDg7F37148fPgQBgYGGDp0KOzs7KCnp9fiR726ujo8f/4ciYmJSE9Ph6qqKhYuXIj8/Hw8e/YMGRkZrX5sTElJweDBg3H69GlMmTKlVWUoMrT5pCQhIQFOTk44f/48xo8f36oyzpw5gylTpuCrr76SSbyH1NRUHDt2DCNGjMCpU6egqanZ4ryEEMTHx8PPzw+RkZHg8/nQ1NQEm82GiYkJjI2NwWKxoKKiApFIBD6fDy6Xi7y8PBQWFuLly5cQiUTo3bs3fHx84OnpCR6PBzMzM/z+++9tnj7m4OAAXV1dnD9/vk3lKCK0+aRk0aJFuHXrFp48edLqxzShUIgePXrA2NgY8+fPb7WWqqoqREZGIi0tDXPnzsXhw4fbtAPY69evkZiYiDt37kj+mtp0SVVVFf369YO9vT04HA4GDx6M/v37S1q44OBgLF++HFwuV+ong/cJCAiAl5cXampqPrkJ2Iq3tFmBKS0tRUREBH755Zc2vR+Jp6nt2LEDU6dOhYaGhtRlpKWlITIyEqqqqggPD4eHh0er9YjR19eHm5sb3NzcJMcqKirA4/HA4/HAZDLBYrGgra39wZ7S0tJS6OjotNl4ACQdU1wulzbf58yDBw9QX1+PyZMnt7ksd3d3fPfddyguLm5xSOT6+nqkpaUhISEBz58/x4wZMxAQECDXoQttbW2pJwnU1tbKbJc3cTmf4m7WtPmkgMvlAgD09PTaXJa4DB6P98F0AoEAhYWFuHv3LpKTk1FdXY1x48bBz8+v1b2I8kZHR0dm222Iy5FFK6po0OaTAvGjpixek8UzYe7du4eamhqoqqqCwWCAz+eDx+OhsLAQ+fn5KCoqgkAggI6ODlavXo01a9bAwsKizfXLEwsLC9TW1iIlJaXNGyPFx8dDT0+PNt/njri1KikpafOj3qtXrwC8nSf6/goJZWVlWFlZwdXVFRwOBxwOBwMGDOgwG/aOGzcOpqamCAgIwKFDh1pdzps3b/DXX39hxYoVn+Q4H20+KRgwYAA0NTVx/PjxNi/TiYiIgLa2NvLz88FkMlFbWwuhUAgWiwUWi9Wht05XUVHB6tWrsXPnTuzevRu6urqtKic8PBzl5eVYvXq1jBUqCIRGKtauXUsMDQ1JfX19q8uora0lXbp0IevXr5edMAWjqKiIMJlM8uWXX7YqP5fLJX369CETJ06UsTLFgTaflKSnpxMAJDw8vNVlHD16lAAgmZmZMlSmeOzZs4cAIL6+vlLlq66uJqNHjya6urokIyNDTuqohzZfKxgzZgwxNjYmL168kDpvTk4OMTAwIBMmTJCDMsVCJBKRTZs2EQDk22+/JW/evPlonpycHGJvb080NDTIjRs32kElddDmawVFRUWke/fuxNLSkuTm5rY437Nnz0jv3r1Jr169SHFxsRwVKg4ikYj89ttvhMFgEF1dXbJx40aSlZXVII1QKCQxMTHE3d2dKCkpESMjI5KamkqR4vaDNl8refz4MenRowcxMjIiwcHBH/xVr6mpIYcOHSIGBgbE3NycZGdnt6NSxSArK4ts2rSJ6OnpEQCkZ8+eZNCgQcTW1pZ07dqVACD9+/cnQUFBpKqqimq57QI9t7MNFBcXY8WKFTh79ix0dHSwdOlSTJ8+HV26dAEhRLKY9vDhw6ioqIC7uzsOHTok86VEHQkej4cTJ07g4cOHKC8vB5PJhJ6eHiZMmIChQ4d+sgtnm4I2nwx4+vQpAgMD8eeff6KsrKzBd/r6+lixYgVWr17drts30Cg+tPlkCI/Hw9OnT8HlcsFgMKCrqwtzc/MOMzhO077Q5qOhoYiOO42ChqaDQ5uPhoYiaPPR0FAEbT4aGoqgzUdDQxG0+WhoKII2Hw0NRdDmo6GhCNp8NDQUQZuPhoYiaPPR0FDE/wKL8A+ukAcTuAAAAABJRU5ErkJggg==\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_molecule(diene)\n", "plt.title(\"Diene (cyclopentadiene)\");" ] }, { "cell_type": "code", "execution_count": 5, "id": "1e191434-aa36-4789-8259-0954078d60fb", "metadata": {}, "outputs": [], "source": [ "dienophile = from_smiles(\"N#CC=C\") # carbon 1, 2 will form bonds\n", "set_active(dienophile, [1, 2])" ] }, { "cell_type": "code", "execution_count": 6, "id": "64c3cdb4-3c66-440a-882b-5d998afac2b2", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_molecule(dienophile)\n", "plt.title(\"Dienophile (acrylonitrile)\");" ] }, { "cell_type": "code", "execution_count": 7, "id": "cf21dd46-46ef-42ae-b67a-8489e684950c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[10.02|14:35:03] JOB preliminary_md STARTED\n", "[10.02|14:35:03] JOB preliminary_md RUNNING\n", "[10.02|14:35:08] JOB preliminary_md FINISHED\n", "[10.02|14:35:08] JOB preliminary_md SUCCESSFUL\n", "[10.02|14:35:08] JOB ts_search STARTED\n", "[10.02|14:35:08] JOB ts_search RUNNING\n", "[10.02|14:35:14] JOB ts_search FINISHED\n", "[10.02|14:35:14] JOB ts_search SUCCESSFUL\n", "[10.02|14:35:14] JOB refinement STARTED\n", "[10.02|14:35:14] JOB refinement RUNNING\n", "[10.02|14:35:23] JOB refinement FINISHED\n", "[10.02|14:35:23] JOB refinement SUCCESSFUL\n" ] } ], "source": [ "preliminary_md_results, ts_search_results, relax_from_saddle_results = addition(diene, dienophile)" ] }, { "cell_type": "markdown", "id": "757adcce-c9c3-440c-be89-f24863ca0e31", "metadata": {}, "source": [ "## Preliminary biased MD results (UFF)" ] }, { "cell_type": "code", "execution_count": 8, "id": "dd2cb7b9-510d-48f0-af47-f736b089f2fb", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "final_md_system = preliminary_md_results.get_main_molecule()\n", "plot_molecule(final_md_system)\n", "plt.title(\"Final system from preliminary biased MD\");" ] }, { "cell_type": "markdown", "id": "d0bc51bd-1ac6-4dac-a769-7d309636c8ac", "metadata": {}, "source": [ "## TS search results (DFTB)" ] }, { "cell_type": "code", "execution_count": 9, "id": "0d1af8ff-303b-4d0f-a658-55cc4bc62ad0", "metadata": {}, "outputs": [ { "data": { "image/png": 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JySEuLo6goCCOHTuGnZ0d+/btK/fBT7dv31aM5UlLSyMsLAx/f39q167N0KFDiz1+wYIFdO3alRYtWjB69GhF17ehoWGhIzAfPHiAj48PXbp04ezZs4pu4bzEBuDm5sbx48f5+eefsbS0xMHBQdG4W94mTZrE8+fPmTZtGtu2bcv3mqurK66urgwdOpQ//viD8ePHc/LkSVq1akVubi6RkZH88ccfHDlyBHd3dxo3bsygQYNYsWIFSUlJtGzZkhMnTnD37l2lYnFycsLIyIhVq1ZhYGCAnp4ezZo1y1cz/KeWLVtibGzM8OHDmTRpEjKZjM2bNyt161iUTp06YW5uTqtWrahVqxYREREsW7YMb29vDAwMijzOzc2NlStX8uOPP1K7dm1q1qxZoOYCr9sq5s2bx8iRI/Hy8mLQoEGKrm97e3umTJlS6tjf5O/vz4oVK+jduzdOTk6kpKSwZs0aqlevrvjHqKOjg7OzM9u3b6du3brUqFGDBg0a0KBBA9q0acP8+fPJzs7GysqKo0ePFlpjdHNzA+Cbb75h4MCBVKtWjR49euDk5MSPP/7IjBkziIqKolevXhgYGPDgwQP+/PNPxo0bx9SpU5W7GKX7raT/dRXm/Whqakrm5uZSx44dpSVLlkjJyckFjsnrpn3+/LlS5yhp17e6urpkbW0tjRs3ToqLi1P6Wo4fPy61atVK0tHRkapXry716NFDunnzZqGx37x5U+rbt69kYGAgGRsbSxMnTszX3SlJkhQZGSm1adNG0tHRkQBFN3hRXd/e3t6FXtuECRPybXvw4IEESAsWLCgQV5687uDCft7sDs3KypLmzZsnubi4SFpaWpKxsbHk5uYmzZkzR0pKSlLsl56eLk2aNEkyMTGR9PT0pB49ekjR0dFKdX1LkiTt3btXcnZ2ljQ0NPJ1g3t5eRXZHR0SEiI1b95c0tHRkSwtLaVp06YphgO82e1fVBnDhw/PN5zit99+k9q0aSOZmJhIWlpakpOTk/TVV1/lu87CPpunT59K3t7ekoGBgQQousH/2fWdZ/v27VKTJk0kLS0tqUaNGtLgwYOlmJiYArHp6ekViLm4IQySJEmXL1+WBg0aJNna2kpaWlpSzZo1pe7du0sXL17Mt19oaKjk5uYmaWpq5vucYmJipN69e0tGRkaSoaGh1K9fP+nx48eFfpY//PCDZGVlJampqRV4X3bt2iV5enpKenp6kp6envTBBx9IEyZMkG7duvXW+N9Uomej3jd5z3U9f/5cZT1pgvC+qlpPlAmC8K8lko0gCBVCJBtBECqEaLMRBKFCiJqNIAgVQiQbQRAqhEg2giBUCJFsBEGoECLZCIJQIf4ds2YL5SYzM5OdO3dy8OBBXrx4gaamJvb29owaNarANBaC8DaiZiMUKisri2+//RZra2uGDBnC/fv30dPTQ5Ikdu/eTZMmTWjRogXHjh2r7FCFd4RINkIBqampdOvWjfnz5zN48GAiIyMJCwtj165d7N+/n6ioKP788080NDTo0qUL69atq+yQhXeAGNQn5COXy+nVqxdBQUEcPHgQLy+vIvfNzc1l4sSJ/Pbbb+zevZtevXpVXKDCO0ckGyGfQ4cO4e3tzd69e/Hx8Sl2f7lcTs+ePQkPD+f+/fsqX5BP+PcQyUYgNjaWnTt38uzZM3bs2IGenh6XL19WeorMvCV39+3bR48ePco5WuFdJZLNe+zs2bMsWrSIPXv2oKGhgZmZGTExMaxdu5bRo0eXqKwPP/yQR48esWLFCnr16lXoCgrC+000EL+n1q5dS+vWrbl58yZLlizh0aNHipUrO3bsWOLyunbtSlpaGgMGDMDW1padO3eqOmThHSeSzXsoICCAsWPHMm7cOP7++288PDzw8vJSJIh/ri6hDD09PTQ0NJg+fTq1atWiX79+9OvXj+fPn6s6fOEdJZLNeyYpKYmxY8cyZMgQli9fzvLly2nRogVpaWn069cPKLguuzJevHiBjo4OFhYWjBw5kmHDhnH48GGcnZ05f/68qi9DeAeJZPOe2bRpE5mZmcyfP5+5c+fy+eef4+Xlxeeff46rqyuampolvgXKzc1l586dilU+ZTIZH374IdOnT6d69eq0b9+e4ODg8rgc4R0iGojfI5Ik4ezsjKurKy1atGDKlCl069aNTp06KfbZunUrjx8/JioqSulu7Lzu8smTJ+dbuA9eP+6wbt06Hj9+zKlTpxRLhgjvH1GzeY8kJiYSGRmJi4sLX3zxBe3bt8+XaAA8PT2JiYlh0aJFSpWZkpLC119/ja2tbaGrQGppaTF69GhMTEzo3bs3KSkpKrkW4d0jks17JDk5GYDVq1djb29P9+7dC+xja2tLhw4dmD59umLlz6K8ePGCbt26cffuXQYOHFjkuBwtLS2GDh2qWEhPeD+JZPMeyetliouLY+DAgaipFf7xd+vWjXbt2jFp0iSaNWvGli1byMjIULweFRXFjBkzqFu3LlevXmXcuHFYWlq+9dympqZ4e3uzatUqTpw4obqLEt4Zos3mPfLw4UNFjaZDhw7F7n/jxg3++usvbt26hZaWFiYmJmRlZZGQkICOjg7u7u54eXlhYmKi1PnlcjnLly/H0NCQS5culfVyhHeMmM/mPbJ+/Xq0tLTw9PRUan8XFxdcXFyIi4sjIiKCtLQ0NDQ0MDY2xtXVFS0trRKdX01NjXbt2rF27VouXLiAh4dHaS5DeEeJms17Ijs7G2tra+rUqaMYT1MZ5HI5c+fOpUePHmzYsKHS4hAqnmizKYOoqChmzpxJt27daNOmDd7e3syZM4fHjx9XdmgFHDlyhGfPntGqVatKjUNNTY3mzZsTEBBAenp6pcYiVCyRbEohMjKSHj164OjoyIoVK9DU1MTOzg41NTUWLFiAra0t/fr14+HDh5UdqkJYWBiGhoZYWFhUdijUq1ePzMxMrl27VtmhCBVItNmUUFhYGN26dcPExITVq1czaNCgfM8SJSUlsXnzZubPn0/z5s05evQoDRs2rMSIX7t48SJWVlZKTxtRniwtLdHQ0ODSpUs0b968ssMRKoio2ZTA3bt38fb2xtnZmQsXLjBmzJgCDy0aGhoyceJELly4QK1atejatWul31ZJksTFixextrau1DjyaGhoYGFhIXqk3jMi2ZTA7Nmz0dfXZ//+/RgZGb1131q1ahEYGEhmZibz5s2rmACLkJ6eTkJCAmZmZpUax5tMTU2Jioqq7DCECiSSjZLyZrGbNGkSxsbGSh1jYWHB2LFj2bhxI6mpqeUcYdHyBuRVpQmtqlWrRlpaWmWHIVQgkWyU5O/vj5qaGiNGjCjRcZ988gkpKSls27atfAJTQl47TVUa5SBJUpEjmIV/J/FpKykiIoJGjRopPVo2j52dHU5OTkRGRpZTZMXT0dEBXq8FVVVkZWWhq6tb2WEIFUgkGyWlpaWV+o9DT0+vUm+jtLW1sbS05OnTp5UWwz89f/6cunXrVnYYQgUSXd9KMjQ0JCIiosTHSZJEQkIChoaGim3p6elcv36dhIQEMjMzqVatGtWrV6dhw4b59lMlDw+PSq1dvSkzM5OnT5+KuW3eMyLZKKlNmzasXr2ayMhIPvjgA6WPCwsLIyYmBh0dHUaNGsWFCxeIiIggNze30P0dHR3x8PCgS5cuDBgwQHELVFbu7u4cP34cSZIqfaxNbGwscrlcJJv3jHg2SkmZmZlYW1szePBgfvnlF6WPGzJkCDt37iQzMxNLS0vs7OywtrbGxsaG6tWro6GhQW5uLmlpacTExBAdHU10dDQPHjzAyMiI0aNH4+fnh6OjY5niP3XqFO3ateOzzz7DycmpTGWV1f79+zl//jyBgYFcu3aN+/fvk56ejkwmQ1tbGycnJ9zc3HB1dUVbW7tSYxVURySbEpg5cyZLliwhODiYDz/8sNj9T58+zUcffYSFhQV9+/bFzs5O6VrF8+fPCQ0N5fz582RnZzN79my++uorNDRKVxmVy+XUrVsXQ0NDhg0bVqoyVCE7O5tZs2aRnp6OJEmoq6tjamqq6JbPysoiPj6e3NxcNDQ0aNKkCWPHjsXX17dUqz4IVYdINiWQmppKu3btiIqK4sCBAzRt2rTIfU+ePImPjw+1atXi008/LXWSyMrK4vDhw5w6dYomTZqwadMmnJ2dS1XW4sWLmTZtGrNmzcLAwKBUZZTVxYsX2bJlC126dMHZ2RkLCwuqVauWb5/s7GweP35MdHQ0kZGR3LhxA319fUaOHMk333xDzZo1KyV2oWxEsimh+Ph4fHx8OH/+PL1798bPz4+2bdsik8mQy+UcOXKEZcuWERgYSL169RgxYoRKbgWioqLYtm0bycnJ7Nu3j48++qjEZbx8+RJLS0uaNWtG7969yxxTSeXk5LBgwQIMDQ3x8/NT+riEhATOnj1LWFgYmpqarFixgv79+1d625NQMiLZlEJ6ejrr1q1jxYoVREREoKOjg76+PklJSWRlZWFpaUnr1q1p2rSp0isUKCMzM5ONGzdy79499u/fX2CycmUsXLiQadOm8dlnn5W5HaikDh48SFBQEF9++WWx04gWJiUlhV27dnH16lX69OnDunXrin1sRKg6RLIpA0mS+OuvvwgODmbhwoXI5XIGDhyIs7Nzuf3XzcnJYf369Tx48IC//voLd3f3Eh2fm5uLp6cnDx484Msvv6ywRxgePXrEL7/8QufOnencuXOZyrp69So7duzAycmJo0ePUqtWLRVFKZQnkWzKSJIk+vTpQ1BQEFOmTFH6uamyyMrKYvny5WhqanLt2rUSd4/funWLRo0a4ezszNChQ8v9sYGkpCR+/fVXdHR0mDJlikpqe0+ePGHVqlVYWVkRHBxMjRo1VBCpUJ7ECOIy2r59O3v27KFPnz4Vkmjg9QOVgwYNIioqilmzZpX4+Hr16hEQEEB4eDjbtm0rcsyPKiQlJbFixQpyc3MZPXq0ym4rLSws+PTTT3n06BE+Pj7leg2CaoiaTRnEx8dTr1497OzsGD58eIWf//jx4xw6dIiwsLBSTR4eEBDA0KFDcXFxYeDAgSp/Vik2Npb169eTm5uLn59fufQi3bt3j2XLlvGf//wHDw8Prly5Qnx8vGJktoGBAa6urri5uVG7dm3x8GclEsmmDP773/8ye/Zsvv3220rpSs7NzWXBggW0atWqxOtz59m/fz9DhgxBTU2Nfv364eLiopK4jh07pmhPGTt2bLnc5sTFxRESEsL58+cV02jo6+tjZGSEuro6crmctLQ0EhISADAwMKBTp05MmDBB0YMoVByRbEopNzcXe3t7LC0t8fX1rbQ4goOD2bNnD48ePSpVDw9ATEwMY8eO5fDhw3z44Ye0a9cOGxubEpeTm5vLjRs3OHLkCE+ePKFDhw506tSp1GOMinLr1i2OHz/OnTt30NfXx93dHQcHB2xtbTEyMiqQRFJTU4mJieHhw4dcuXKFJ0+eUK9ePaZMmcKYMWNU2mMoFE0km1Lav38/Pj4+fPHFF9ja2lZaHOnp6cyZM4evv/66VO03eSRJwt/fn//85z/ExsZib29PixYtqFu3bqF/wHlyc3OJi4vj77//JiQkhOTkZBwcHOjTp0+pEtbbpKens2fPHs6dO4ednR1t2rShUaNGJUpmkiRx9+5dQkJCuHr1Kq1atWLDhg3UqVNHpbEKBYlkU0rDhw8nKCiIqVOnVnYobN26lVevXnHjxo0yl5WTk8PBgwdZvnw5x44dA6B69epYWVlhYmJCtWrVkMvlZGVlERcXR0xMDFlZWaipqdG0aVM8PT3LZa7jO3fu8Pvvv5Oenk6vXr1o3rx5mW+D7t27x/bt20lOTmbhwoVMmDBBRdEKhRHJppTq169PjRo16N+/f2WHwtmzZ9mxYwcpKSkqbeR98uQJFy5c4NKlS1y8eJHo6GjS09NRV1dHR0cHZ2dnnJ2d+f7772nbti3dunVT2bnfdO3aNTZt2oSjoyO+vr4q7fXLzMzkwIEDBAcHM23aNH766SfRllNOxBQTpZCamsrt27crdWXJN1lbWyOXy7l27RotWrRQWbkWFhb4+Pjg4+NT5D4HDhwgKyvrrc+JlUV4eDj+/v40btyYwYMHq7x9RUtLi48//hhTU1Pmz5+PTCbjp59+Uuk5hNdEsimF8PBw5HK5ytskSsvCwgINDQ0uX76s0mSjjEuXLqGvr1/i6VKVER0djb+/P66urooes/Li5eUFwLx586hVqxZDhgyhWrVq6OnpFXhQVCgdkWxKIT4+HnjdllEVaGhooK+vr+jirUh561Gp+tYjJyeHrVu3YmFhUa6JJjs7m+vXrxMVFcWjRzGoqWnwxRdf8MUXXwCgrq5OvQ9caNbUDXd3d/r06YO5uXm5xPJvJ5JNCUiSRFhYGCdPngRQeZduWVSrVk0x1qQihYeHU7t2bZWXe+TIEeLi4pg6dWq5vM8JCQmEhIRwNuw86Wmv0Na3R9vQjVr1R6GpY4tMTQukHHKy4nmaeIWde6/g77+ZSZM+5+OPP2bCBD9at24t2ndKoOr8tVRhiYmJ+Pv7s2LFCm7fvq3YXpWGyOfk5FTKulApKSkqm7o0T1xcHCdOnKBTp06lHjtUlJycHI4ePcqxY8dRr6aPsc0o7BzGoq1ffNd3TtZLXjzawoEjq/njDy+6dvNm7ZrVKo/x30qM3S5GREQEjRs3ZurUqTRp0oSTJ0+yd+9egCqzyJpcLic9Pb1SRjHn5OSovNE2JCQEXV1dOnTooNJyY2JiWLhwMceOBVGr3kycO0Vh1XC+UokGQEPTmJq1P6NO23Dsm24j6NQlPqjvgr+/f5Vak6uqEjWbt7h//z5eXl7UqlWLO3fuYG9vD/yvzSY2NrZKTG8QHx9PRkYGrq6uFX5uLS0tcnJyVFZeZmYm58+fp3Xr1iq9fbp58ybr129EU68udbx2o2vUqNRlyWQyjCx7oW/ahsd/f8mIESO4efOm6DYvhkg2RZAkiUGDBmFoaMjJkycxNTVVvHb9+nXU1dWJjo5Wai5iVZHL5cTHxxMdHc3jx49JT08nNzeXly9fAvD48WMePnyIra3tW7/0eQP3Tp8+TVJSErq6unzwwQcMHjy4xJNRmZmZkZiYWIaryu/y5ctkZmaqtFft5s2brF27DoNaXbFz34KaumomUdfQrIGt2wZ0jNyYP38q2dnZLFq0SCScIohkU4QLFy5w/vx5Dh48mC/RPHz4EB8fH3R0dHj06FG5xyFJEvfu3ePMmTNERkYqGoGNjY3R09NDXV2drKws9PT0FEsD16hRg48//hg/Pz8aN26sKCszM5NFixaxatUqoqOjcXJywsTEhPT0dFatWsW0adMYMmQIM2fOxM7OTqn43N3dCQ4OVtn13rp1CwcHB5U9uBkTE8P69RsxqNUVe48AZGqq78Y2c5qITFaNxYs/x8bGhilTpqj8HP8GItkUYcWKFdjb2+ebVU6SJEaPHo2GhgZt27Zlz549vHjxolyeaJbL5Zw/f55Tp07x9OlTatasSfv27bG1tcXGxqbQlQaSkpKIjo4mKiqKnTt3smbNGpo3b87XX39N27Zt6dmzJ2fPnmXo0KF8+umn+dZtevLkCWvXrmXFihXs3buXQ4cOKVVrc3d3V8yJo4q2m+joaBo2bFjmcuB1DW7L7wFo6tXFzn1LuSSaPKaOn5CZep+vv55Bly5dqF+/frmd610lkk0RAgMDCzwRvHr1ak6cOMEnn3yCo6MjgYGBnD17Fm9vb5WeOz4+nm3btnH37l1cXV3p06cPderUKbZ6bmhoiKGhIQ0aNKBr167cuHGD4OBgevXqhbm5ORkZGQQFBdGqVasCx1pYWPDtt98yfvx4vL296dKlC6GhocV2a7u7u5Odnc2jR49wcHAo03WnpqaSkJCgssGSR48eJe5pHHW8dqvs1ultLJxnkxofyNBhIwg7G1KlhkZUBaI3qggvX77EwsJC8XtSUhJTp06lefPm1K9fHy0tLTw8PDh79qxKG0jPnj3L/PnzSUhIwM/Pj1GjRlG3bt0StwOoq6vj6uqKn58fzZo1Iy4ujr179xaaaN5kZmZGYGAg+vr6Sj1k2qxZM6ytrTl37lyJ4itM3lrkquhKTkhI4Nix49SsO71MjcEloaaug1Wj1Vy6dIH169dXyDnfJSLZFEFLS4usrCzF75s2bSItLY2uXbsqtrVu3Zq0tDTF09FlIUkSgYGBbN++HTc3N6ZPn07dunXLXC687jXr3r07bdq0UWp/ExMTpk2bxv79+4ttl1JXV+fTTz/l8uXLZR4KkJmZCaCSh0lDQkJQ19CnVp0vy1xWSejVaI6RRQ+WLFkmusP/QSSbIjg6OhIWFga8TgTLli3D1dUVQ0NDxT41a9akY8eOHDt2jJiYmDKd78iRIxw5coTu3bszYMAAlS07GxUVRUxMTImnTxg8eDB6enqsXr262H1Hjx6NJEmcPXu2tGECr9upgDI/mpCdnc3ZsPMY2w5HTUO1U50qw8R+HDdvvp7fR/gfkWyKMHr0aP7880+ePHlCcHAwt2/fLvQWpGPHjpibm/P777+TnZ1dqnOdP3+ew4cP4+3trfKBbNHR0WhqatKxY8cSHWdgYED79u25dOlSsfvWqlWLMWPGcOzYsTI9n5XXPlbW29Lr16+TnvYKE4dxZSqntPTN2qNbvTbr1q2rlPNXVSLZFGHYsGFoamqyePFiTp06hb6+fqGNpRoaGgwePJj4+Hj8/f1L/AhDYmIiu3fvxt3dXeWJBl7fmujr65eqtmBoaEhKSopS+86bNw8zMzO2b9+uqKGUVN4I6LKO24mKinr9rJOSI4NVTSZTQ9ekI8HBZavp/duIZFMEIyMjZsyYwYIFC/jzzz/f+mSzlZUVI0eO5ObNm/j7+yv9n1mSJLZt24aWlhZ9+vQpl8FgWlpavHr1qlQJICkpSelHIAwMDNiwYQO3b9/m9OnTJT4XgLm5Oerq6mW+JX30KAZtQ7fidyxHOkZNuHfvFsnJyZUaR1Uiks1bfPPNN3zyySeEh4djZWX11n2dnZ0ZPXo0ERERLFu2jOfPnxdb/rVr14iMjKR///4qX0Ylj42NDVlZWZw4caJEx7169YqTJ0+WaIT0Rx99xLRp09i7dy/nz58vaahoaGhgaWlJdHR0iY/NI5fLiYmJQceo4kZ2F0bX+HWyu3LlSqXGUZWIZPMWMpmM+fPnI5fLleqOdXFxwc/Pj5SUFObPn8+pU6feWqM4ffo0derUUcnyKUWxt7fHysqK5cuXl+i4rVu3kpKSwrhxJWv3+Omnnxg1ahQBAQGlaiC1sbHh/v37pe7JycrKIjs7E02dypuEHlCcP687XxDJplh53bnK9g45ODgwbdo0mjdvzp49e1iwYAGhoaGKbt08sbGxPHjwAE9PT5XH/CaZTEbLli3Zv3+/0n/8L168YP78+XTv3l3pxxbePN+aNWvw8/Njx44dbN68mdTUVKWPb9KkCfHx8dy7d69E582TdwsrU9Mq1fGqIlN/ff7KmGOoqhLJphh5Db4laU/Jm9d20qRJmJiYsGPHDmbNmsX27ds5d+4cjx8/5syZM4rRvuWtWbNmODk50b17d0V3flHi4+Px9vYmMTGRRYsWlep8ampqLF26FH9/f+7evcv8+fMJDw9XqrZSu3ZtatasyZkzZ0p9bgAk1Q20LBX56/NXxhxDVZUYT12MvBpNabpjHR0dcXR05MWLF5w9e5arV68qxqKoq6vTqlWrClkgTUNDg5EjR7J27Vq8vLwYMWIEfn5+NGr0v5G1cXFxrFu3juXLl5Odnc3hw4fLtJaSTCZj2LBhdOjQgbFjx7J+/XosLCxo2bIl7u7uRU64JZPJ8PT0LPVzZ1paWshkauRkxZc6dlXIyXrdZvfmuKz3nVjKpRi5ubno6+vTuXNn2rVrV+byMjIyuHfvHmvWrGHw4MGlWqO7tLKzszlx4gRhYWEkJiZSu3ZtTE1NefXqFZGRkVSrVg1fX1+++eabMj/n9CZJkjh58iQrVqxgz549VKtWTdGWZGNjQ61atRSTimdnZxMdHc3u3buxs7Nj/PjxJe6l+2neQrI0O2LbZKXKrqGkEh/vJer8AGJjY8VMfv+fqNkUQ11dnUaNGpW5OzaPtra24g+roldnqFatGl26dKFjx45cv36de/fuKebEycnJ4fLlyyp74vpNMpmM9u3b0759e2JjY9m8eTOhoaFcvHixyF4yNTU1bt26xblz52jevHmJzmdrY8n128UPRixP6YmXMTUzF4nmDSLZKMHDw4OdO3eqrLwnT56goaFBzZo1VVZmSeQl0LzbqJcvXzJnzhyVTu9QFCsrK77++mvF70+fPuXBgwekp6cjk8nQ1tbGyMiIQ4cOMW/ePHbv3o2Dg0OJZkS0tbXlwoU95GS9RENTdQvalUTayxBaN3WvlHNXVaKBWAkeHh48ffpUZTPSZWZmoq2tXa7rIJVEXvvJq1evKvzc5ubmtGjRgvbt29OuXTtatGhB/fr1+fLLL7l9+zaOjo789ttvvHjxQukyXV1dkckkXjzaUo6RFy0j5RYpz8/gO2hgpZy/qqoa3/YqrmfPnujq6pb5QcM8crm8yiQa+F8PTmmf7SovRkZGHD9+nOrVq7Ns2TLi4uKUOq569eq4NnLlRdRKJKl0j06URfyDNdQwMaNv374Vfu6qrOp846swQ0NDhg4dyrlz51SyfIuGhoZK58Apq7xYVPWkuSpZWVkREhJCzZo1Wbx4MSEhIUp1obf29CTj1X2SnuyrgCj/JzvjKUmxm/hk3Bi0tCp3rE9VI5KNkj799FMSExOVegq6OPr6+qSnpxcY6FdZ8m4PK6sNqTiWlpacO3eOoUOHsmPHDlauXKlY4aIojo6OODu78Dh8EjlZyt+ClYUkScSGT6K6gbZiRU3hf0SyUVKjRo34+OOP2b9/v9JPQhfF2tr69RczNlZF0ZVNdHQ0Mpks3+ToVU316tVZvXo1R48eJTU1lblz57J27Vpu3rxZ6CMhMpmMAQP6o8YrYsMrZgKtxJjtJD7ex+rfVuabJF94TYyzKYFnz57h7OyMjY2NYiWDknj+/DnR0dGkp6eza9cu2rdvT/fu3VUfaAnt2rWLuLg4bt26VdmhKCU1NZWAgACWLl1KeHg4NWrUwNbWFmtra2xsbKhevToaGhrk5uZy+fJljh49ilXDhZg5TSy3mNISL/MgtDO9e3Vj+/Zt5Xaed5lINiX0xx9/MGDAAAYMGKDU2kZyuZzr168TGhpKZGRkgdfr1q1Ly5YtcXV1rbRG459++omUlBS6deuGm5ubYoL1qi5v7fWdO3dy8eJFLl++XGiPmpqaGnK5HCvXXzBzHK/yONISLxMV1oNGrnUIOnEMfX19lZ/j30AkmxKSJAk/Pz9Wr17N0KFDadKkSZH7Zmdn8/vvv3P16lWaNm3KxIkT8fHxwcDAgFevXnHo0CGWLl1KaGgoDRo0YOjQoRXeqPjo0SN+/vlnGjRoQEZGBjExMWRkZNCpUycmTJiAt7d3hTxSoQpyuZy7d++SkJBARkYGmpqaGBgYULduXWbOnMnixYsxc5qEhfMc1NTLvj65JEkkxmzn8d+f0aiRM0ePBGJsXDnjet4FItmUQm5uLsOHDycgIIB+/foVWsORy+WKyaS2bt1Knz59iizv4MGD9O/fHzs7uwLLx5S3rVu3cufOHb799lvU1NTIysri6tWrhIaGEhUVhYuLC5s2barQlT/LgyRJ/PLLL3z99Qw0dOywarQGvRrNSl1edsZTYsMnkfh4H/37D2DdurWiRlMM0UBcCurq6vj7+zN27Fi2b9/Oxo0bC1Tfz5w5w40bN9i1a9dbEw2At7c3+/bt486dO5w8ebI8Q88nOTmZK1eu0KpVK8UtnKamJk2bNmXy5MlMnjyZ5ORkmjZtyrfffptvtYl3jUwmY8qUKVy5cpn6dYy4G9yWqPP9SXl2vERjcTJSbhETPpXbJ11RyzzLzp072b59m0g0ShA1mzKQJInt27czYcIEsrOz6dmzJ02aNEFNTY158+bRunVr/vjjD6XLGzlyJPv37+ebb74p9/YbSZLYsGED9+/fZ8aMGYWusAmva3HHjh3j2LFjeHh4cOjQoXf+ViEnJ4f169ezZMkybt78G93qtdE16YiOURN0jT5EU9cWmbo2kjybnMznpCddJT3xMmkvQ0l5fgbjGqZ8Mm4MX3zxBWZmZpV9Oe8MkWxUIC4uDj8/P3bv3o2xsTF16tTh/PnznD59Wum1muD1+uJNmzZl7Nix5Tp7H8ClS5fYvHkzI0eOzDfVRFGioqJYu3YtDg4OnDp1qlyWHK5okiQREhLCunXrCA4+y/37t4scMGhqZk7Tpu74DhpI3759xYC9UhDJRoWuXLnCypUr2bBhAyYmJjx58qTE0yPUrl0bS0tLPv7443KK8vVqkYsWLaJu3bol6sJ/8uQJy5cvx8XFhaCgoHKbN7my5N1WPn36VNHAbGhoSOPGjcXT2yogkk05GDFiBOHh4Vy+fLnEx3p6epKZmcmQIUPKIbLXKyb8+uuvyGQyJk+eXOK2hkePHrFs2TImTJjAzz//XC4xCv9OooG4HBgaGpa6MbUk8/WWVHx8PL/++iu5ubn4+fmVqlHT1taWrl278ssvv5R66k7h/SSSTTmoXbs2t2/f5tmzZyU6LjExkYiICK5fv87NmzdVFk/e4LeFCxeipqbG559/XqY2Fy8vLxwcHBg+fDjp6ekqi1P4dxPJphwMHjwYdXV11q9fX6Lj8ha4s7a2ZvXq1fz+++9lnmMmISGB3377jW3btuHq6sqUKVPK3JukpqbGgAEDePDgAVu3bi1TWcL7Q7TZlJORI0dy/Phx/v77b4yMjIrd/9WrV7i6umJkZMSwYcM4d+4ce/bsIScnhyZNmtCqVSvs7OyUanCWy+Xcvn1bMdanevXqDBgwAGdnZxVc2f+sWbMGDQ0Nrly5Ui6reQr/LiLZlJPbt2/TrFkzGjduzL59+966jG1aWhp9+vTh9OnTfP7551hYWACvE1BYWBihoaG8ePECMzMzbG1tsbGxwdraGj09PdTV1cnJySElJYXo6Giio6N5+PAhiYmJWFhY4Onpibu7e7l01d68eZPVq1cTFhZGs2alH40rvB9EsilHwcHBeHt7Y29vz3fffUfPnj0Vk53D68FlBw4c4Pvvv+fmzZuMGjWKevXqFShHLpcTERFBREQE0dHRPHr0qNDxIFpaWlhbW2NtbU2jRo1wcHAo1xqHXC5n7ty5DBo0iKVLl5bbeYR/B5Fsyll4eDgTJkzgzJkzWFhY0K1bNwwNDUlOTiYwMJDY2FgcHBzo3bs3trbFLxmblZXF9OnT6dSpE/Xr1yc3Nxd1dXX09PQwMTGp8CfHN2/ejLq6OufOnavQ8wrvHrG6QjlzdXUlODiY8PBwVq5cydGjR4mOjsbCwgIbGxsGDhxYoiVdHj9+jCRJNGjQoMKXgimMjY0Nhw8fJicnBw0N8XUSiiZ6oyqIq6srK1euZNq0aeTm5vLFF1+UONHA61n11NXVFe06lc3GxoaMjAwiIiIqOxShihPJpoKpqakhSZJSk3YXJjk5WTETXVWQ143+5MmTSo5EqOpEsqlgOjo6SJJU6hHGVe12Ja/BOyMjo5IjEao6kWwqWF5v09OnT0t1fF7NqKrIm2y8KiVAoWoSyaaCNWzYEA0NDaKjo0t1fLVq1arUIwJ5NZqi5sMRhDwi2VQwbW1tnJ2dS51sLCwsSE1NJSkpScWRlc7jx48BVD46Wfj3EcmmErRt25bIyMhSrYppbW0NQExMjKrDKpXo6GisrKzEjHVCsUSyqQRjx44lKSmJ8PDwEh9bo0YNdHV1efToUTlEVnIxMTG4u7tXdhjCO0Akm0rQoEEDWrduTWhoaImPlclk1KlTh2vXrlV6Q3FycjL37t2jffv2lRqH8G4QyaaSTJw4kbt375ZqFcpWrVrx9OlT7t+/Xw6RKS8sLIxq1aoxbNiwSo1DeDeIZFNJ+vbtS9u2bfnjjz9KPEalTp061KxZs1JnysvNzSUsLIzBgwcrNYWGIIhkU0nU1NRYv3496enp7Nu3r0THymQyWrduzdWrVyut7ebMmTO8ePGCiRPLb/1s4d9FJJtK5ODgwMKFCwkNDS1x+03Lli2xsrJi69atperVKovnz59z8OBBJk6cSOPGjSv03MK7SySbSjZ+/Hj8/PzYsWNHiaZpUFdXx9fXl+fPn3P48OFyjDC/vAXedHV10dXVZf78+Zw6darSG6uFqk+MMa9kMpmMpUuXkp2dzZo1a0hMTKRDhw5KrfdtaWlJly5dOHjwIObm5uXaBZ2ZmUlISAgnTpwgNTUVQ0NDAgICSEpKIjk5mfr16+Pn58fYsWPFAm5CoUTNpgpQU1Pjt99+47vvvuPIkSP8+uuvSj871aFDB5o2bcrWrVu5dOlSucSXkpLC8uXLCQwMpFevXoSGhvLy5UsePXpEYmIiQUFBuLi4MHnyZLp06UJiYmK5xCG828RMfVVMWFgYw4YN48GDB7Ru3RpPT09MTEzeekxubi7bt2/nwoULdO3alY8++kipmpEyMjIyWLp0KVlZWRw9evStbTRnzpzBx8eHhg0bcvToUVHDEfIRyaYKSk9P58cff2TZsmWkpKTg7OyMh4cH9vb2GBoaFjqvsFwuZ8+ePQQHB2NpacmQIUNUMsHWunXruHv3LufOnaNhw4bF7h8SEkK7du344YcfmD59epnPL/x7iGRThaWmphIQEMDSpUsVjzbo6+tjY2ODvr4+Ghoa5OTkkJqayuPHjxW3L9ra2mRnZ9OiRQs8PT0xNzcv0XklSeLOnTucPn2ayMhIJk+ezMKFC5U+fvjw4QQHB3Pnzh2V1bCEd59INu8ASZKIjY1l/PjxnDx5krZt25KYmEhmZiZaWloYGRnRpEkT3NzccHNzw8zMjAULFrB06VLi4+NxdHTEw8MDW1tbzM3NC00AmZmZxMbGEhUVxfnz53n69CkWFhY8efKEO3fuULt2baXjPXfuHM2bN+fAgQN4e3ur8q0Q3mEi2bxDIiIicHZ2ZvHixUyePLnY/bOysujRowdBQUHk5uYiSRKamppYWFigo6ODmpoaubm5pKSk8PTpU+RyOZqamvTs2ZMJEyawZcsWLl68yJUrV0oUpyRJ2NraMnToUP7v//6vlFcr/NuIru93SP369Zk0aRJffvkltWrVYtCgQUXuK0kSCxcu5OjRoyxdupThw4dz7do1Ll26RHh4OMnJyWRlZaGtrY2pqSkffvghbm5uuLi4KKb6XLlyZanWBJfJZJiYmFSZOXeEqkEkm3fMzz//TGJiIr6+vgQGBjJx4kQ8PDwUjcZyuZwTJ06wZMkSDh48yOzZsxWPFHh6euLp6an0uXR1dUlLSytVnK9evRKz9wn5iGTzjlFXV2fjxo24ubmxePFiNm/eTIMGDXB0dEQul3Pz5k3u379Pw4YN2bZtGwMGDCj1uVxcXNi6dSvx8fGYmpoqfdy9e/e4f/8+Li4upT638O8j2mzeYbm5uRw+fJgdO3bw/PlzxXpSQ4cOpVWrVmVeejc+Ph5ra2t++OEHvvrqK6WPmzZtGmvXriUmJgZdXd0yxSD8e4hkI7zVsGHDOHnyJFeuXFGqdhMdHU2jRo0YMWIEP//8cwVEKLwrRLIR3ur+/fs0b94cBwcHDh069NbRzLGxsXTq1InU1FTCwsJKPL5H+HcTz0YJb+Xo6EhgYCD379/H3d2dZcuWkZycnG+fhIQEFi5ciIeHBykpKRw+fFgkGqEAUbMRlHL37l1mzJjBn3/+iba2Np6enhgYGJCYmEhwcDCSJNGvXz/mz5+PpaVlZYcrVEEi2QglEhsby9q1a7l27RqvXr3CwMAADw8PRo8eLZZzEd5KJBtBECqEaLMRBKFCiGQjCEKFEMlGEIQKIZKNIAgVQiQbQRAqhEg2giBUCJFsBEGoECLZCIJQIUSyEQShQohkIwhChRDJRhCECvH/AKEPxTHth1TEAAAAAElFTkSuQmCC\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "final_ts_system = ts_search_results.get_main_molecule()\n", "plot_molecule(final_ts_system)\n", "plt.title(\"DFTB-optimized transition state\");" ] }, { "cell_type": "markdown", "id": "744d0264-086e-4d57-b8f0-81357d59250e", "metadata": {}, "source": [ "## Energy landscape refinement results (DFTB)" ] }, { "cell_type": "code", "execution_count": 10, "id": "37602521-c365-40ae-a2dd-dfcadad61747", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "All stationary points:\n", "======================\n", "State 1: C8H9N local minimum @ -24.90404981 Hartree (found 1 times, results on Refined1_MIN)\n", "State 2: C8H9N local minimum @ -24.83552141 Hartree (found 1 times, results on Refined2_MIN)\n", "State 3: C8H9N transition state @ -24.82079293 Hartree (found 1 times, results on Refined3_TS_1-2)\n", " +- Reactants: State 1: C8H9N local minimum @ -24.90404981 Hartree (found 1 times, results on Refined1_MIN)\n", " Products: State 2: C8H9N local minimum @ -24.83552141 Hartree (found 1 times, results on Refined2_MIN)\n", " Prefactors: 0.000E+00:0.000E+00 s^-1\n", " Barriers: 2.266:0.401 eV\n" ] } ], "source": [ "landscape = relax_from_saddle_results.get_energy_landscape()\n", "print(landscape)" ] }, { "cell_type": "markdown", "id": "a00e9def-80eb-4e18-912a-a26fbb95634d", "metadata": {}, "source": [ "Above we see that the forward and backward barriers are 2.27 and 0.39 eV, respectively." ] }, { "cell_type": "code", "execution_count": 11, "id": "6a1f9ecd-ebe4-43f0-b776-e09d48c41110", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Ha2eV = Units.convert(1.0, \"hartree\", \"eV\")\n", "energies = landscape[1].energy, landscape[3].energy, landscape[2].energy\n", "energies = (np.array(energies) - landscape[1].energy) * Ha2eV\n", "plt.plot(energies)\n", "plt.ylabel(\"Relative energy (eV)\")\n", "plt.xticks([0, 1, 2], [\"State 1 (min)\", \"State 3 (TS)\", \"State 2 (min)\"]);" ] }, { "cell_type": "code", "execution_count": 12, "id": "62c6c64d-b847-4697-957b-140f5f6a64fa", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_molecule(landscape[1].molecule)\n", "plt.title(\"State 1 (minimum)\");" ] }, { "cell_type": "code", "execution_count": 13, "id": "9fc165bb-7ac1-4f6c-b2f3-2db1abedee94", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_molecule(landscape[2].molecule)\n", "plt.title(\"State 2 (minimum)\");" ] }, { "cell_type": "code", "execution_count": 14, "id": "0d4f3bd2-de8a-458e-bd40-309e8e336b3f", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_molecule(landscape[3].molecule)\n", "plt.title(\"State 3 (Transition state)\");" ] } ], "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": "3.8.16" } }, "nbformat": 4, "nbformat_minor": 5 }