diff --git a/CO2_SGD.ipynb b/CO2_SGD.ipynb
index dc3a2592c740bcf1f558d902fbe47f7ebe2fce69..6b6e598793c27cc4cde37c71e3a7b643bb8e5b8b 100644
--- a/CO2_SGD.ipynb
+++ b/CO2_SGD.ipynb
@@ -2,11 +2,11 @@
  "cells": [
   {
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-   "execution_count": 70,
+   "execution_count": 43,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:36:03.094663Z",
-     "start_time": "2020-09-23T07:36:03.087177Z"
+     "end_time": "2020-09-28T14:12:28.012331Z",
+     "start_time": "2020-09-28T14:12:28.005590Z"
     },
     "init_cell": true,
     "scrolled": false
@@ -195,11 +195,11 @@
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   {
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+   "execution_count": 44,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:36:03.115573Z",
-     "start_time": "2020-09-23T07:36:03.108326Z"
+     "end_time": "2020-09-28T14:12:28.030086Z",
+     "start_time": "2020-09-28T14:12:28.016401Z"
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     "init_cell": true,
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@@ -248,11 +248,11 @@
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   {
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-   "execution_count": 5,
+   "execution_count": 45,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:36:03.763324Z",
-     "start_time": "2020-09-23T07:36:03.117731Z"
+     "end_time": "2020-09-28T14:12:28.595497Z",
+     "start_time": "2020-09-28T14:12:28.032964Z"
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@@ -261,7 +261,7 @@
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@@ -276,7 +276,7 @@
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@@ -290,7 +290,7 @@
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@@ -304,7 +304,7 @@
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@@ -589,11 +589,11 @@
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+   "execution_count": 46,
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-     "start_time": "2020-09-23T07:36:03.764778Z"
+     "end_time": "2020-09-28T14:12:28.598765Z",
+     "start_time": "2020-09-28T14:12:28.596921Z"
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     "init_cell": true
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@@ -605,11 +605,11 @@
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+   "execution_count": 47,
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-     "end_time": "2020-09-23T07:36:04.096381Z",
-     "start_time": "2020-09-23T07:36:03.767898Z"
+     "end_time": "2020-09-28T14:12:28.900939Z",
+     "start_time": "2020-09-28T14:12:28.599926Z"
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     "init_cell": true,
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@@ -618,7 +618,7 @@
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        "version_major": 2,
        "version_minor": 0
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@@ -750,11 +750,11 @@
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-   "execution_count": 9,
+   "execution_count": 48,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:36:04.415693Z",
-     "start_time": "2020-09-23T07:36:04.098412Z"
+     "end_time": "2020-09-28T14:12:29.240892Z",
+     "start_time": "2020-09-28T14:12:28.902210Z"
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     "init_cell": true,
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@@ -763,7 +763,7 @@
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        "version_major": 2,
        "version_minor": 0
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@@ -881,11 +881,11 @@
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    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 49,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:36:04.420323Z",
-     "start_time": "2020-09-23T07:36:04.417135Z"
+     "end_time": "2020-09-28T14:12:29.247982Z",
+     "start_time": "2020-09-28T14:12:29.243540Z"
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     "init_cell": true
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@@ -905,11 +905,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 50,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:36:04.455929Z",
-     "start_time": "2020-09-23T07:36:04.421700Z"
+     "end_time": "2020-09-28T14:12:29.292045Z",
+     "start_time": "2020-09-28T14:12:29.249833Z"
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@@ -918,7 +918,7 @@
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        "version_minor": 0
       },
@@ -928,18 +928,6 @@
      },
      "metadata": {},
      "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<script type='text/javascript'>Jupyter.notebook.execute_cell_range(Jupyter.notebook.get_selected_index()+1,Jupyter.notebook.get_selected_index()+14)</script>"
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@@ -960,11 +948,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:34:46.205293Z",
-     "start_time": "2020-09-23T07:34:46.179965Z"
+     "end_time": "2020-09-28T14:11:35.155349Z",
+     "start_time": "2020-09-28T14:11:35.124188Z"
     },
     "scrolled": true
    },
@@ -1057,25 +1045,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:34:46.222876Z",
-     "start_time": "2020-09-23T07:34:46.206849Z"
+     "end_time": "2020-09-28T14:11:35.169839Z",
+     "start_time": "2020-09-28T14:11:35.156839Z"
     }
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The best subgroup found by SGD of sites characterized by small OCO angles is defined as:\n",
-      "['near_cat1>=1.7925', 'near_cat2>2.143', 'pband_max>-6.048']\n",
-      "\n",
-      "quality function (size*shift*narowness) is 0.18623*0.22797*0.3418 = 0.01451106878958\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "print(\"The best subgroup found by SGD of sites characterized by small OCO angles is defined as:\")\n",
     "print(OCO_subgroup[:-1])\n",
@@ -1084,25 +1061,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:34:46.238695Z",
-     "start_time": "2020-09-23T07:34:46.224645Z"
+     "end_time": "2020-09-28T14:11:35.186374Z",
+     "start_time": "2020-09-28T14:11:35.171260Z"
     }
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The best subgroup found by SGD of sites characterized by large C-O bond distances is defined as:\n",
-      "['VBM_surf<=-5.182', 'VBM_surf>-5.5255', 'qH_catMIN<0.4803', 'qH_catMIN>=0.41769999999999996']\n",
-      "\n",
-      "quality function (size*shift*narowness) is 0.02024*0.45283*0.7825 = 0.007171830974000001\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "print('The best subgroup found by SGD of sites characterized by large C-O bond distances is defined as:')\n",
     "print(lCO_subgroup[:-1])\n",
@@ -1111,11 +1077,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:34:46.389297Z",
-     "start_time": "2020-09-23T07:34:46.240140Z"
+     "end_time": "2020-09-28T14:11:35.353742Z",
+     "start_time": "2020-09-28T14:11:35.188635Z"
     }
    },
    "outputs": [],
@@ -1239,102 +1205,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:34:46.394242Z",
-     "start_time": "2020-09-23T07:34:46.390697Z"
+     "end_time": "2020-09-28T14:11:35.358277Z",
+     "start_time": "2020-09-28T14:11:35.354996Z"
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "text/markdown": [
-       "The plot below shows the distribution of OCO-angles in the identified subgroups of small OCO-angles and long C-O bonds. In the small OCO-angles subgroup the sites providing smaller values are dominating as expected, whereas the sites delivering longer C-O bond exhibit average OCO-values for our data set."
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "display(Markdown('The plot below shows the distribution of OCO-angles in the identified subgroups of small OCO-angles and long C-O bonds. In the small OCO-angles subgroup the sites providing smaller values are dominating as expected, whereas the sites delivering longer C-O bond exhibit average OCO-values for our data set.'))\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:34:46.684146Z",
-     "start_time": "2020-09-23T07:34:46.395492Z"
+     "end_time": "2020-09-28T14:11:35.673139Z",
+     "start_time": "2020-09-28T14:11:35.360091Z"
     },
     "scrolled": false
    },
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "22b11ad2023345a098b9c94425f78a08",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "FigureWidget({\n",
-       "    'data': [{'mode': 'lines',\n",
-       "              'name': 'all sites',\n",
-       "              'type': 'scatte…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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-       "model_id": "f68a05bf4af64353ae79c4940f707280",
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-      "text/plain": [
-       "VBox(children=(Label(value=\"Click 'Print' to export the plot in the desired format. The resolution of the imag…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
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-      },
-      "text/plain": [
-       "Button(description='For a high-quality print of the plot, click to access the plot-appearance utils', layout=L…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
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-      "text/plain": [
-       "HBox(children=(VBox(children=(BoundedIntText(value=12, description='Font size'), BoundedIntText(value=7, descr…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "x12, y12, legen12 = [], [], []\n",
     "x22, y22, legen22 = [], [], []\n",
@@ -1595,102 +1488,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:34:46.688428Z",
-     "start_time": "2020-09-23T07:34:46.685393Z"
+     "end_time": "2020-09-28T14:11:35.677629Z",
+     "start_time": "2020-09-28T14:11:35.674529Z"
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "text/markdown": [
-       "The distribution of C-O bond lengths in identified subgroups shows that the sites in small OCO subgroup have average or smaller values of C-O bond lenghts (blue line in the plot below)."
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "display(Markdown('The distribution of C-O bond lengths in identified subgroups shows that the sites in small OCO subgroup have average or smaller values of C-O bond lenghts (blue line in the plot below).'))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:34:47.004429Z",
-     "start_time": "2020-09-23T07:34:46.690355Z"
+     "end_time": "2020-09-28T14:11:35.954181Z",
+     "start_time": "2020-09-28T14:11:35.679652Z"
     },
     "scrolled": false
    },
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "1922c6a12fb544d3932fb649c121ef64",
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-       "version_minor": 0
-      },
-      "text/plain": [
-       "FigureWidget({\n",
-       "    'data': [{'mode': 'lines',\n",
-       "              'name': 'all sites',\n",
-       "              'type': 'scatte…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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-      },
-      "text/plain": [
-       "VBox(children=(Label(value=\"Click 'Print' to export the plot in the desired format. The resolution of the imag…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Button(description='For a high-quality print of the plot, click to access the plot-appearance utils', layout=L…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "HBox(children=(VBox(children=(BoundedIntText(value=12, description='Font size'), BoundedIntText(value=7, descr…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "x13, y13, legen13 = [], [], []\n",
     "x23, y23, legen23 = [], [], []\n",
@@ -1943,102 +1763,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:34:47.010168Z",
-     "start_time": "2020-09-23T07:34:47.006582Z"
+     "end_time": "2020-09-28T14:11:35.958412Z",
+     "start_time": "2020-09-28T14:11:35.955556Z"
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "text/markdown": [
-       "In the figure below the distributions of adsorption energies for adsorption sites in the subgroups of smaller OCO-angles and larger $l$(C-O) are shown. For the majority of the sites in the small OCO subgroup the adsorption energies are high (strong adsorption). The sites in the larger C-O bond subgroup, in contrast, have average and lower values of adsorption energies. Elongation of C-O bonds occurs not only due to the charge transfer as in the case of sites from smaller OCO subgroup, but also due to additional covalent interaction between O-atoms of adsorbed CO$_2$ and neighboring surface cations."
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "display(Markdown('In the figure below the distributions of adsorption energies for adsorption sites in the subgroups of smaller OCO-angles and larger $l$(C-O) are shown. For the majority of the sites in the small OCO subgroup the adsorption energies are high (strong adsorption). The sites in the larger C-O bond subgroup, in contrast, have average and lower values of adsorption energies. Elongation of C-O bonds occurs not only due to the charge transfer as in the case of sites from smaller OCO subgroup, but also due to additional covalent interaction between O-atoms of adsorbed CO$_2$ and neighboring surface cations.'))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:34:47.295137Z",
-     "start_time": "2020-09-23T07:34:47.012002Z"
+     "end_time": "2020-09-28T14:11:36.256145Z",
+     "start_time": "2020-09-28T14:11:35.960208Z"
     },
     "scrolled": false
    },
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "36d7badb062e44b98114afb1c3b659a5",
-       "version_major": 2,
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-      },
-      "text/plain": [
-       "FigureWidget({\n",
-       "    'data': [{'mode': 'lines',\n",
-       "              'name': 'all sites',\n",
-       "              'type': 'scatte…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
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-       "VBox(children=(Label(value=\"Click 'Print' to export the plot in the desired format. The resolution of the imag…"
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-      "text/plain": [
-       "Button(description='For a high-quality print of the plot, click to access the plot-appearance utils', layout=L…"
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-     },
-     "metadata": {},
-     "output_type": "display_data"
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-       "HBox(children=(VBox(children=(BoundedIntText(value=12, description='Font size'), BoundedIntText(value=7, descr…"
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-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "x14, y14, legen14 = [], [], []\n",
     "x24, y24, legen24 = [], [], []\n",
@@ -2291,27 +2038,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:34:47.299318Z",
-     "start_time": "2020-09-23T07:34:47.296382Z"
+     "end_time": "2020-09-28T14:11:36.261952Z",
+     "start_time": "2020-09-28T14:11:36.258014Z"
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "text/markdown": [
-       "Indeed, materials with sites from small OCO subgroup are known to be prone to formation of strongly bonded carbonates. Very high adsorption energies indicate, in accordance to Sabatier principle, that these materials are not good catalysts in CO$_2$ conversion. So, OCO-angle is not a good indicator of enhanced catalytic activity of semiconducting oxides. <br/><br/> In contrast, several materials with adsorption sites from long C-O bond subgroup have been experimentally shown to be active in different reactions of CO$_2$ conversion. This means that C-O bond length is a good indicator of catalytic activity for semiconductor oxide catalysts."
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "display(Markdown('Indeed, materials with sites from small OCO subgroup are known to be prone to formation of strongly bonded carbonates. Very high adsorption energies indicate, in accordance to Sabatier principle, that these materials are not good catalysts in CO$_2$ conversion. So, OCO-angle is not a good indicator of enhanced catalytic activity of semiconducting oxides. <br/><br/> In contrast, several materials with adsorption sites from long C-O bond subgroup have been experimentally shown to be active in different reactions of CO$_2$ conversion. This means that C-O bond length is a good indicator of catalytic activity for semiconductor oxide catalysts.'))"
    ]
@@ -2339,11 +2073,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": 51,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:36:04.483717Z",
-     "start_time": "2020-09-23T07:36:04.457921Z"
+     "end_time": "2020-09-28T14:12:29.325080Z",
+     "start_time": "2020-09-28T14:12:29.293678Z"
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     "init_cell": true
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@@ -2351,7 +2085,7 @@
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        "version_major": 2,
        "version_minor": 0
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@@ -2382,75 +2116,15 @@
   },
   {
    "cell_type": "code",
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+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:34:53.381148Z",
-     "start_time": "2020-09-23T07:34:53.103422Z"
+     "end_time": "2020-09-28T14:11:41.695877Z",
+     "start_time": "2020-09-28T14:11:41.401690Z"
     },
     "scrolled": false
    },
-   "outputs": [
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-      "text/plain": [
-       "FigureWidget({\n",
-       "    'data': [{'mode': 'lines',\n",
-       "              'name': 'larger l(C-O), MSE',\n",
-       "              'type'…"
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+   "outputs": [],
    "source": [
     "dCO_mse_CV_minLeaf = [0.03255627329984329, 0.034132247895190954, 0.031672092812331014, 0.03059461226995024, 0.030839488861288206, 0.030377333724731434, 0.029382804378371364, 0.028910821550302973, 0.028364501740508002, 0.02780484946404478, 0.02705321359075288, 0.028075143704071444, 0.02989078608329612, 0.029233949367941697, 0.02846342790168268, 0.02870721288864, 0.02879431163747176, 0.02858119669679526, 0.028673638285909592, 0.028226012372936125, 0.027789710645324477, 0.027609437112001405, 0.02777988051498181, 0.027837583150554263, 0.027803473449669068, 0.02749314486784524, 0.027295443275648642, 0.02726767633959103, 0.027267676339591047, 0.027534507530945742, 0.0280959414929495, 0.027480781967643038, 0.02731191115591742, 0.02696332989063625, 0.027187774260358847, 0.026901245336512208, 0.027017396161290685, 0.026870887344675756, 0.025736113939583312, 0.02527495831980791, 0.02527495831980791, 0.02527495831980794, 0.025274958319807937, 0.02527495831980792, 0.0250764071134889, 0.02507207982446077, 0.025376084945028035, 0.02548596237954964, 0.025391326447260297, 0.025175095250391456, 0.025175095250391466, 0.025175095250391487, 0.025175095250391497, 0.025175095250391438, 0.02517509525039145, 0.026128007765774234, 0.026128007765774237, 0.02612800776577423, 0.02600847388530928, 0.026008473885309243, 0.025970336693884984, 0.025968909548618392, 0.02600386972794675, 0.026072093212203405, 0.026126753848822536, 0.026492885309641293, 0.02644625768410604, 0.02664999545584807, 0.026649995455848098, 0.02664999545584813, 0.026649995455848112, 0.026649995455848115, 0.02664999545584812, 0.026649995455848133, 0.026649995455848112, 0.0266499954558481, 0.026649995455848098, 0.026649995455848074, 0.026649995455848133, 0.0266499954558481, 0.02664999545584811, 0.026649995455848095, 0.02664999545584813, 0.026649995455848112, 0.026649995455848112, 0.02664999545584807, 0.02664999545584812, 0.026649995455848112, 0.026649995455848095, 0.026649995455848122, 0.026649995455848105, 0.026649995455848133, 0.026649995455848133, 0.02664999545584811, 0.026649995455848112, 0.0266499954558481, 0.026649995455848095, 0.026649995455848122, 0.0266499954558481, 0.02664999545584809, 0.02664999545584809, 0.026649995455848112, 0.026649995455848098, 0.026649995455848074, 0.026649995455848095, 0.026649995455848112, 0.026649995455848084, 0.02664999545584805, 0.026649995455848115, 0.026649995455848112, 0.026649995455848122, 0.026667332293300965, 0.026945483544038307, 0.026945483544038352, 0.026945483544038338, 0.02694548354403829, 0.02694548354403835, 0.026945483544038328, 0.02694548354403835, 0.026945483544038317]\n",
     "dCO_mae_CV_minLeaf = [0.03214951155332549, 0.032439042803013005, 0.03230212261610794, 0.03228395961747872, 0.030708848900760144, 0.03040094754010197, 0.03065095054367432, 0.030210077547485743, 0.02893116219146731, 0.028616549103466213, 0.029383717157774592, 0.02846681070546699, 0.029698041757168545, 0.029862149549362685, 0.03014940865266288, 0.029193425165171934, 0.028488935276671554, 0.02948129510611096, 0.030938786369608794, 0.030571662012697693, 0.030959683853222696, 0.031057149880574276, 0.03040382726813531, 0.02979914204128638, 0.02960172538466276, 0.029214878218328088, 0.02994054499867722, 0.029364955427983386, 0.029749698055828343, 0.029334263035812783, 0.029148093180041638, 0.029815203441789638, 0.030375617485934724, 0.030189784313954256, 0.030136984823485802, 0.030647681223421642, 0.030158068726490794, 0.03061944818718082, 0.03052910604307758, 0.03010975200814355, 0.030246457282426555, 0.029897226118064148, 0.028169060179867634, 0.028351752368207837, 0.02981219895408143, 0.02904265326209066, 0.027607995526731925, 0.027785543673769737, 0.027461622098104637, 0.028621588777172267, 0.02754921984684937, 0.027523692407173405, 0.027146047497505797, 0.027177777299613137, 0.027194437839247777, 0.0279788634797669, 0.027836803908169182, 0.02792097726906992, 0.027914505828108994, 0.02864553720249341, 0.0286413498822406, 0.028390442167703787, 0.028072293168259273, 0.028096583710378948, 0.027709671793999524, 0.027670359329526252, 0.027586063341627023, 0.02835653570887858, 0.028372914323461337, 0.02836857972809836, 0.02833446850151168, 0.028357606495503906, 0.02858392005708733, 0.028604397187522373, 0.02861640762613472, 0.028598275053443135, 0.02860361872296201, 0.028596877041352234, 0.028615346523852572, 0.028613135767712322, 0.028594930328396148, 0.028599956116724064, 0.028597337154142376, 0.028617946154559436, 0.02858469905811349, 0.028599460655711156, 0.028620439456022856, 0.028599903032026086, 0.028610889464527597, 0.028599956116724046, 0.02861600087491042, 0.02860473333612409, 0.02859050548781154, 0.028621288189943892, 0.02860627249242605, 0.02861025268508569, 0.028614002404473902, 0.028596293041380418, 0.028605617918832277, 0.02862834231676134, 0.028615877079911964, 0.02765905420205519, 0.027650270331277264, 0.02767056051164016, 0.027696610383233674, 0.02767880771928468, 0.027708521175786118, 0.027673029445733858, 0.027656712109293758, 0.027651240354049374, 0.02770874034484382, 0.027952859391807094, 0.027544277935055102, 0.02754427793505511, 0.02754427793505511, 0.027544277935055105, 0.0275442779350551, 0.0275442779350551, 0.02754427793505512, 0.027544277935055105]\n",
@@ -2687,74 +2361,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:34:53.648575Z",
-     "start_time": "2020-09-23T07:34:53.382702Z"
+     "end_time": "2020-09-28T14:11:41.987399Z",
+     "start_time": "2020-09-28T14:11:41.697264Z"
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "f59ee1c5b8f74b4ba2d4d24557941651",
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-      "text/plain": [
-       "FigureWidget({\n",
-       "    'data': [{'mode': 'lines+markers',\n",
-       "              'name': 'larger l(C-O), MSE',\n",
-       "            …"
-      ]
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-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "dCO_mse_CV_maxDep = [0.026649995455848098, 0.025072079824460806, 0.025072079824460785, 0.025072079824460768, 0.025072079824460813, 0.02507207982446082]\n",
     "dCO_mae_CV_maxDep = [0.028616142354252888, 0.02726003139654996, 0.027227245077200268, 0.02721512365332162, 0.027130084739560027, 0.027100278618762835, 0.02734672041413569]\n",
@@ -2990,166 +2604,43 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:34:53.652986Z",
-     "start_time": "2020-09-23T07:34:53.650278Z"
+     "end_time": "2020-09-28T14:11:41.994618Z",
+     "start_time": "2020-09-28T14:11:41.991653Z"
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "text/markdown": [
-       "### 5.2 Discussion of the TR results"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "display(Markdown('### 5.2 Discussion of the TR results'))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:34:53.672052Z",
-     "start_time": "2020-09-23T07:34:53.654344Z"
+     "end_time": "2020-09-28T14:11:42.013444Z",
+     "start_time": "2020-09-28T14:11:41.996077Z"
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "text/markdown": [
-       "For the four considered cases (OCO and l(C-O) as target properties, each choice tested via MSE- and MAE-base cost functions), we found the following pairs of hyperparameters {min. size, max. depth}:<br><br>l(C-O), MSE : {46, 2}<br><br>l(C-O), MAE: {53, 5}<br><br>zz<br><br>OCO, MSE {32, 5}<br><br>OCO, MAE {30, 4}<br><br>For these sets of hyperparameters the next tree models are identified."
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "display(Markdown('For the four considered cases (OCO and l(C-O) as target properties, each choice tested via MSE- and MAE-base cost functions), we found the following pairs of hyperparameters {min. size, max. depth}:<br><br>l(C-O), MSE : {46, 2}<br><br>l(C-O), MAE: {53, 5}<br><br>zz<br><br>OCO, MSE {32, 5}<br><br>OCO, MAE {30, 4}<br><br>For these sets of hyperparameters the next tree models are identified.'))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:34:54.941519Z",
-     "start_time": "2020-09-23T07:34:53.673719Z"
+     "end_time": "2020-09-28T14:11:43.330613Z",
+     "start_time": "2020-09-28T14:11:42.014705Z"
     },
     "scrolled": false
    },
-   "outputs": [
-    {
-     "data": {
-      "text/markdown": [
-       "Decision tree for OCO, with MSE cost function, fitting accuracy (RMSE) = 3.24 degree (stand. dev. = 3.64):"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
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\n",
-      "text/plain": [
-       "<Figure size 648x648 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "Decision tree for OCO, with MAE cost function, fitting accuracy (RMSE) = 3.15 degree (stand. dev. = 3.64):"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 648x648 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "Decision tree for l(C-O), with MSE cost function, fitting accuracy (RMSE) = 0.025 Å (stand. dev. = 0.028):"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 720x720 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "Decision tree for l(C-O), with MAE cost function, fitting accuracy (RMSE) = 0.020 Å (stand. dev. = 0.028):"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 720x720 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "df = pd.read_csv(\"./data/co2/train.csv\")\n",
     "Y_dCO = df['dCO']\n",
@@ -3181,101 +2672,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:34:54.946186Z",
-     "start_time": "2020-09-23T07:34:54.943075Z"
+     "end_time": "2020-09-28T14:11:43.335373Z",
+     "start_time": "2020-09-28T14:11:43.332108Z"
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "text/markdown": [
-       "Next, we analyze the leaves with extreme values of the target property, obtained for each TR model. For OCO-angle these leaves are those which have lowest mean values - white boxes in two upper trees; for C-O bond these are patterns with largest mean values, marked with the darkest color.<br><br>For OCO-angle, both MSE and MAE cost functions deliver the same leaf with smallest angle values, defined with condition (M  > -5.463 eV). This leaf overlaps with the small OCO-angle subgroup for 85% of samples and contains the sites with high values of adsorption energies (prone to carbonation). The distribution of adsorption energies for the sites in this leaf is shown below in comparison to SGD subgroups."
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "display(Markdown('Next, we analyze the leaves with extreme values of the target property, obtained for each TR model. For OCO-angle these leaves are those which have lowest mean values - white boxes in two upper trees; for C-O bond these are patterns with largest mean values, marked with the darkest color.<br><br>For OCO-angle, both MSE and MAE cost functions deliver the same leaf with smallest angle values, defined with condition (M  > -5.463 eV). This leaf overlaps with the small OCO-angle subgroup for 85% of samples and contains the sites with high values of adsorption energies (prone to carbonation). The distribution of adsorption energies for the sites in this leaf is shown below in comparison to SGD subgroups.'))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:34:55.282382Z",
-     "start_time": "2020-09-23T07:34:54.947394Z"
+     "end_time": "2020-09-28T14:11:43.637644Z",
+     "start_time": "2020-09-28T14:11:43.337381Z"
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "cddb2a81f39140bcaa693a46e7f3655f",
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-       "version_minor": 0
-      },
-      "text/plain": [
-       "FigureWidget({\n",
-       "    'data': [{'mode': 'lines',\n",
-       "              'name': 'all sites',\n",
-       "              'type': 'scatte…"
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-     },
-     "metadata": {},
-     "output_type": "display_data"
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-      "text/plain": [
-       "VBox(children=(Label(value=\"Click 'Print' to export the plot in the desired format. The resolution of the imag…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
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-       "Button(description='For a high-quality print of the plot, click to access the plot-appearance utils', layout=L…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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-       "HBox(children=(VBox(children=(BoundedIntText(value=12, description='Font size'), BoundedIntText(value=7, descr…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "large_lco_mae, large_lco_mse, small_oco = [], [], []\n",
     "large_lco_mae_E, large_lco_mse_E, small_oco_E = [], [], []\n",
@@ -3545,102 +2963,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:34:55.287911Z",
-     "start_time": "2020-09-23T07:34:55.284585Z"
+     "end_time": "2020-09-28T14:11:43.641917Z",
+     "start_time": "2020-09-28T14:11:43.639230Z"
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "text/markdown": [
-       "For C-O bond length, the MAE and MSE cost functions deliver different leaves with largest values - (EA_B ≤ -0.24 eV) AND (qH_catMIN ≤ 0.47 e) and (EA_B ≤ -0.24 eV) AND (α_catMIN > 94.80), respectively. Both of them have significant overlap with the large $l$(C-O) subgroup. However, they also contain sites on materials prone to formation of carbonates. This is clearly seen in the plots of adsorption energy distribution as shoulders with high values that are missing in the large $l$(C-O) subgroup:"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "display(Markdown('For C-O bond length, the MAE and MSE cost functions deliver different leaves with largest values - (EA_B ≤ -0.24 eV) AND (qH_catMIN ≤ 0.47 e) and (EA_B ≤ -0.24 eV) AND (α_catMIN > 94.80), respectively. Both of them have significant overlap with the large $l$(C-O) subgroup. However, they also contain sites on materials prone to formation of carbonates. This is clearly seen in the plots of adsorption energy distribution as shoulders with high values that are missing in the large $l$(C-O) subgroup:'))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:34:55.531069Z",
-     "start_time": "2020-09-23T07:34:55.289278Z"
+     "end_time": "2020-09-28T14:11:43.907176Z",
+     "start_time": "2020-09-28T14:11:43.643159Z"
     },
     "scrolled": false
    },
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "3ca7521dc41e45d783f0655bfcb291a3",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "FigureWidget({\n",
-       "    'data': [{'mode': 'lines',\n",
-       "              'name': 'larger l(C-O) leaf, MAE',\n",
-       "              '…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
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-      "text/plain": [
-       "VBox(children=(Label(value=\"Click 'Print' to export the plot in the desired format. The resolution of the imag…"
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-     "metadata": {},
-     "output_type": "display_data"
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-      "text/plain": [
-       "Button(description='For a high-quality print of the plot, click to access the plot-appearance utils', layout=L…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "8a8f0bbc3adb4ab5a3865eeaaf9df886",
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-      "text/plain": [
-       "HBox(children=(VBox(children=(BoundedIntText(value=12, description='Font size'), BoundedIntText(value=7, descr…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "data_tuples18 = list(zip(gauss_large_lco_mae[0], gauss_large_lco_mae[1]))\n",
     "data_tuples28 = list(zip(gauss_lCO_ener[0], gauss_lCO_ener[1]))\n",
@@ -3864,39 +3209,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:34:55.544925Z",
-     "start_time": "2020-09-23T07:34:55.533057Z"
+     "end_time": "2020-09-28T14:11:43.915521Z",
+     "start_time": "2020-09-28T14:11:43.909566Z"
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "text/markdown": [
-       "This analysis clearly demonstrates the tendency of TR to overemphasize the importance of data points based solely on the value of target property. TR minimizes the overall cost function, so that the local regularities are not explicitly considered and are finally sacrificed, whereas the SGD is exactly focused on revealing such local subsets. As a result, materials with sites where C-O bond is elongated due to a large charge transfer (the same as in small OCO subgroup or equivalent TR pattern), are selected by TR together with materials providing moderate charge transfer. At the same time, additional bonding of O atom in adsorbed CO$_2$ with a surface cation, which also leads to C-O bond elongation."
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "Thus, in this case, TR fails to distinguish these two very different activation mechanisms."
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "display(Markdown('This analysis clearly demonstrates the tendency of TR to overemphasize the importance of data points based solely on the value of target property. TR minimizes the overall cost function, so that the local regularities are not explicitly considered and are finally sacrificed, whereas the SGD is exactly focused on revealing such local subsets. As a result, materials with sites where C-O bond is elongated due to a large charge transfer (the same as in small OCO subgroup or equivalent TR pattern), are selected by TR together with materials providing moderate charge transfer. At the same time, additional bonding of O atom in adsorbed CO$_2$ with a surface cation, which also leads to C-O bond elongation.')) \n",
     "display(Markdown('Thus, in this case, TR fails to distinguish these two very different activation mechanisms.')) "
@@ -3904,75 +3224,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 69,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:34:55.818478Z",
-     "start_time": "2020-09-23T07:34:55.552030Z"
+     "end_time": "2020-09-28T14:11:44.201815Z",
+     "start_time": "2020-09-28T14:11:43.917336Z"
     },
     "scrolled": false
    },
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "2aa1fd0ef3f34ac797ae5fc8e2cf9504",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "FigureWidget({\n",
-       "    'data': [{'mode': 'lines',\n",
-       "              'name': 'larger l(C-O) leaf, MSE',\n",
-       "              '…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
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-      "text/plain": [
-       "VBox(children=(Label(value=\"Click 'Print' to export the plot in the desired format. The resolution of the imag…"
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-     "metadata": {},
-     "output_type": "display_data"
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-    {
-     "data": {
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-      },
-      "text/plain": [
-       "Button(description='For a high-quality print of the plot, click to access the plot-appearance utils', layout=L…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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-       "model_id": "578f89a6d9e44b1a9f771660f7592b7a",
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-      },
-      "text/plain": [
-       "HBox(children=(VBox(children=(BoundedIntText(value=12, description='Font size'), BoundedIntText(value=7, descr…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "data_tuples19 = list(zip(gauss_large_lco_mse[0], gauss_large_lco_mse[1]))\n",
     "data_tuples29 = list(zip(gauss_lCO_ener[0], gauss_lCO_ener[1]))\n",
@@ -4223,11 +3483,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 82,
+   "execution_count": 52,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2020-09-23T07:36:04.522493Z",
-     "start_time": "2020-09-23T07:36:04.485451Z"
+     "end_time": "2020-09-28T14:12:29.350223Z",
+     "start_time": "2020-09-28T14:12:29.326604Z"
     },
     "init_cell": true
    },
@@ -4235,7 +3495,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "786c0c0e84d7405283e22939a9707b9d",
+       "model_id": "415e2ad840b94d678595a601664432d2",
        "version_major": 2,
        "version_minor": 0
       },
@@ -4457,7 +3717,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.9"
+   "version": "3.7.9"
   }
  },
  "nbformat": 4,