diff --git a/assets/soap_atomic_charges/Logo_NOMAD.png b/assets/soap_atomic_charges/Logo_NOMAD.png
new file mode 100644
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diff --git a/soap_atomic_charges.ipynb b/soap_atomic_charges.ipynb
index 1493b163d41d615e0f2ed31468c2ab25b22c8c70..25e4c81d6093f969508ca9deab090dda11a37355 100644
--- a/soap_atomic_charges.ipynb
+++ b/soap_atomic_charges.ipynb
@@ -4,10 +4,37 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Learning atomic charges\n",
-    "\n",
-    "_Gábor Csányi (gc121@cam.ac.uk), James R. Kermode (j.r.kermode@warwick.ac.uk)_\n",
-    "\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\">Learning atomic charges</font></b>    \n",
+    "  </div>\n",
+    "    \n",
+    "<p>\n",
+    " created by:\n",
+    "    Gábor Csányi,\n",
+    "    James R. Kermode\n",
+    "<br><p>  \n",
+    "gc121@cam.ac.uk, j.r.kermode@warwick.ac.uk\n",
+    "<br><br>  \n",
+    "\n",
+    "<div> \n",
+    "<img  style=\"float: right;\" src=\"assets/soap_atomic_charges/Logo_NOMAD.png\" width=\"250\">\n",
+    "</div>\n",
+    "</div>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
     "In this tutorial, we will use Gaussian process regression, GPR (or equivalently, Kernel Ridge Regression, KRR) to train and predict charges of atoms in small organic molecules. "
    ]
   },
@@ -450,13 +477,6 @@
     "\n",
     "4. For the low-quality fit above, you see that there are two groups of H atoms that are clearly separated. Try to identify what characterises those groups? Inspect the molecules and H atoms in each group. "
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
@@ -476,7 +496,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.3"
+   "version": "3.7.7"
   }
  },
  "nbformat": 4,