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diff --git a/session-decarb/1a_4_5x_D.png b/session-decarb/1a_4_5x_D.png
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diff --git a/session-decarb/Readme.md b/session-decarb/Readme.md
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+++ b/session-decarb/Readme.md
@@ -0,0 +1,10 @@
+# General procedure
+
+- `Set Scale` 100um -> 171 px
+- `Set Measurements...` bounding rectangle, display label, Decimals 4, Redirect none
+- `Measure` and `Clear Measurements` to produce a new and clear measuremens table
+- Use the `Straight` tool to draw a line thta fits into the decarburated area
+- Press `^+m` to add the measurement into the table
+- Repeat the process at least 50 times
+
+![Example of measurements.](measurements-example.jpg)
diff --git a/session-decarb/analysis.ipynb b/session-decarb/analysis.ipynb
new file mode 100644
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+++ b/session-decarb/analysis.ipynb
@@ -0,0 +1,97 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "c9e8a83f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0     57.313\n",
+       "1     52.632\n",
+       "2     43.922\n",
+       "3     44.448\n",
+       "4     60.245\n",
+       "5     60.305\n",
+       "6     67.839\n",
+       "7     60.819\n",
+       "8     71.989\n",
+       "9     71.939\n",
+       "10    74.911\n",
+       "11    76.080\n",
+       "12    61.988\n",
+       "13    67.846\n",
+       "14    72.517\n",
+       "Name: Length, dtype: float64"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# importing data\n",
+    "import pandas as pd\n",
+    "data = pd.read_csv('results-1.csv')\n",
+    "x = data['Length']\n",
+    "x"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "bbb4b0d9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x115566cf0>]"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "plt.plot(x, '.k')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv (3.14.2)",
+   "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": "3.14.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/session-decarb/example.csv b/session-decarb/example.csv
new file mode 100644
index 0000000..c14f646
--- /dev/null
+++ b/session-decarb/example.csv
@@ -0,0 +1,14 @@
+ ,Label,Angle,Length
+1,1a_1_5x_D.png,-92.7792,60.1290
+2,1a_1_5x_D.png,-91.2730,52.4911
+3,1a_1_5x_D.png,-90.6228,53.6475
+4,1a_1_5x_D.png,-91.9092,52.5073
+5,1a_1_5x_D.png,-88.5498,46.0789
+6,1a_1_5x_D.png,-92.3137,57.7730
+7,1a_1_5x_D.png,-90.9793,68.2315
+8,1a_1_5x_D.png,-90.9793,68.2315
+9,1a_1_5x_D.png,-92.2680,58.9383
+10,1a_1_5x_D.png,-91.1691,57.1548
+11,1a_1_5x_D.png,-93.0394,65.9820
+12,1a_1_5x_D.png,-91.1812,56.5718
+13,1a_1_5x_D.png,-90.4276,78.1363
diff --git a/session-decarb/measurements-example.jpg b/session-decarb/measurements-example.jpg
new file mode 100644
index 0000000..abc8165
Binary files /dev/null and b/session-decarb/measurements-example.jpg differ