diff --git a/assets/cmlkit/fhi.png b/assets/cmlkit/fhi.png
new file mode 100644
index 0000000000000000000000000000000000000000..4a2d4e45a9e35d7f224a7c373a54ac1a3aa74d37
Binary files /dev/null and b/assets/cmlkit/fhi.png differ
diff --git a/assets/cmlkit/nomad.png b/assets/cmlkit/nomad.png
new file mode 100644
index 0000000000000000000000000000000000000000..2187e3b9351e11aa693758559114c1f2a6670731
Binary files /dev/null and b/assets/cmlkit/nomad.png differ
diff --git a/cmlkit.ipynb b/cmlkit.ipynb
index 9bedea0872f746c46503fbce688fcd762e4bfad4..be39ba5b6c58cdf2cb027a8d180a171485a915e5 100644
--- a/cmlkit.ipynb
+++ b/cmlkit.ipynb
@@ -4,13 +4,40 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# `cmlkit`: <br />Toolkit for Machine Learning in Computational Condensed Matter Physics and Quantum Chemistry\n",
-    "# *A Tutorial Introduction*\n",
-    "\n",
-    "by Marcel F. Langer<sup>‡</sup>, langer@fhi-berlin.mpg.de\n",
-    "\n",
-    "<sup>‡</sup><i>Fritz Haber Institute of the Max Planck Society, Faradayweg 4-6, D-14195 Berlin, Germany</i>\n",
+    "<div id=\"teaser\" style=' background-position:  right center; background-size: 00px; background-repeat: no-repeat; \n",
+    "    padding-top: 20px;\n",
+    "    padding-right: 10px;\n",
+    "    padding-bottom: 170px;\n",
+    "    padding-left: 10px;\n",
+    "    border-bottom: 14px double #333;\n",
+    "    border-top: 14px double #333;' > \n",
+    "\n",
+    "   \n",
+    "   <div style=\"text-align:center\">\n",
+    "       <b><font size=\"6.4\"><span style=\"font-family: monospace;\">cmlkit:</span><br>\n",
+    "       Toolkit for Machine Learning in Computational Condensed Matter Physics and Quantum Chemistry</font></b>    \n",
+    "  </div>\n",
+    "    \n",
+    "<p style=\"text-align:center;\">\n",
+    " created by:\n",
+    " Marcel F. Langer<sup>1</sup> <br><br>\n",
+    "<sup>1</sup> Fritz Haber Institute of the Max Planck Society, Faradayweg 4-6, D-14195 Berlin, Germany <br>\n",
+    "<span class=\"nomad--last-updated\" data-version=\"v1.0.0\">[ Last updated: November 24, 2020 ]</span>\n",
+    "</p>\n",
+    "    \n",
+    "<div> \n",
+    "<img  style=\"float: left; margin: 0; height: 8em; width: auto;\" src=\"assets/cmlkit/fhi.png\"> \n",
+    "<img  style=\"float: right; margin: 0; height: 8em; width: auto;\" src=\"assets/cmlkit/nomad.png\">\n",
+    "</div>\n",
+    "</div>\n",
     "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
     "**Related publication: [Langer, Goeßmann, Rupp (2020)](http://marcel.science/repbench/)**\n",
     "\n",
     "***\n",
@@ -21,7 +48,7 @@
     "\n",
     "You will get the most out of this tutorial if you:\n",
     "\n",
-    "- Have some familiarity with Python 3,\n",
+    "- Are familiar with Python 3,\n",
     "- Know a little bit about chemistry and/or physics,\n",
     "- Know roughly how kernel ridge regression works, and know a bit about machine learning in general.\n",
     "\n",
@@ -35,7 +62,7 @@
     "- \"ML\": Machine learning, here, we can basically substitute it with \"fitting\" or \"interpolation\".\n",
     "- \"KRR\": Kernel ridge regression, a regression (i.e. \"fitting\") method.\n",
     "- \"HP\": Hyper-parameters. These are the \"free\" parameters of a ML model, which aren't directly determined by training.\n",
-    "- \"SOAP\": Smooth Overlap of Atomic Positions representaton ([Bartók, Kondor, Csányi (2013)](https://doi.org/10.1103/PhysRevB.87.184115)).\n",
+    "- \"SOAP\": Smooth Overlap of Atomic Positions representation ([Bartók, Kondor, Csányi (2013)](https://doi.org/10.1103/PhysRevB.87.184115)).\n",
     "- \"MBTR\": Many-Body Tensor Representation [(Huo, Rupp (2017))](https://arxiv.org/abs/1704.06439).\n",
     "- \"System\" or \"structure\": Either a molecule, other finite system, or a periodic system.\n",
     "\n",
@@ -1016,7 +1043,7 @@
    "source": [
     "<br /><br /><br />\n",
     "\n",
-    "Thanks to Luca Ghiringelli, Xiaojuan Hu, Daniel Speckhard and Thomas Purcell for feedback on this tutorial.\n",
+    "Thanks to Luca Ghiringelli, Xiaojuan Hu, Daniel Speckhard, Nikita Rybin, and Thomas Purcell for feedback on this tutorial.\n",
     "\n",
     "The technical requirements for running this tutorial are:\n",
     "\n",