diff --git a/degradation_model/run_current_profile.ipynb b/degradation_model/run_current_profile.ipynb
index 95c686d727..41d323d71e 100644
--- a/degradation_model/run_current_profile.ipynb
+++ b/degradation_model/run_current_profile.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 65,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -20,7 +20,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 66,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -30,7 +30,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 67,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -40,7 +40,7 @@
     "\n",
     "\n",
     "# hppc_data_raw = pd.read_csv('./data/hppc/' + 'GMJuly2022_CELL017_RPT_1_P25C_25P0PSI_20221121_R0_CH040_20221121171209_37_1_8_2818580181_HPPC' + '.csv')\n",
-    "file_path='Z:\\\\voltaiq_data\\\\Processed\\\\GMJuly2022\\\\GMJuly2022_CELL081\\\\RPT.pkl.gz'\n",
+    "file_path='V:\\\\voltaiq_data\\\\Processed\\\\GMJuly2022\\\\GMJuly2022_CELL081\\\\RPT.pkl.gz'\n",
     "\n",
     "with gzip.open(file_path, \"rb\") as f:\n",
     "    hppc_data_raw = pickle.load(f)\n",
@@ -50,13 +50,149 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 82,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "GMJuly2022_CELL081_RPT_3_P25C_5P0PSI_20230519_R0_CH018_20230519144723_36_3_2_2818579508\n",
+      "C/20 charge\n",
+      "3134.4598148214536\n",
+      "nan\n",
+      "GMJuly2022_CELL081_RPT_3_P25C_5P0PSI_20230519_R0_CH018_20230519144723_36_3_2_2818579508\n",
+      "HPPC\n",
+      "3136.2400448214535\n",
+      "3.0366000000003623\n",
+      "GMJuly2022_CELL081_RPT_3_P25C_5P0PSI_20230519_R0_CH018_20230519144723_36_3_2_2818579508\n",
+      "C/20 charge\n",
+      "3139.276644821454\n",
+      "nan\n",
+      "GMJuly2022_CELL081_RPT_3_P25C_5P0PSI_20230519_R0_CH018_20230519144723_36_3_2_2818579508\n",
+      "C/20 discharge\n",
+      "3142.236364821446\n",
+      "2.964099999992868\n",
+      "GMJuly2022_CELL081_RPT_3_P25C_5P0PSI_20230213_R0_CH018_20230213133903_36_3_2_2818579480\n",
+      "C/20 charge\n",
+      "1707.7409248628264\n",
+      "nan\n",
+      "GMJuly2022_CELL081_RPT_3_P25C_5P0PSI_20230213_R0_CH018_20230213133903_36_3_2_2818579480\n",
+      "HPPC\n",
+      "1709.5018448628264\n",
+      "3.302999999999656\n",
+      "GMJuly2022_CELL081_RPT_3_P25C_5P0PSI_20230213_R0_CH018_20230213133903_36_3_2_2818579480\n",
+      "C/20 charge\n",
+      "1712.804844862826\n",
+      "nan\n",
+      "GMJuly2022_CELL081_RPT_3_P25C_5P0PSI_20230213_R0_CH018_20230213133903_36_3_2_2818579480\n",
+      "C/20 discharge\n",
+      "1715.979284862817\n",
+      "3.1781999999925574\n",
+      "GMJuly2022_CELL081_EIS_3d_P25C_5P0PSI_20230328_R0_CH018_20230328112636_36_3_2_2818579489\n",
+      "C/20 charge\n",
+      "2426.891514842398\n",
+      "nan\n",
+      "GMJuly2022_CELL081_EIS_3d_P25C_5P0PSI_20230328_R0_CH018_20230328112636_36_3_2_2818579489\n",
+      "C/20 discharge\n",
+      "2429.9744048423886\n",
+      "3.0766999999927975\n",
+      "GMJuly2022_CELL081_RPT_1_P25C_5P0PSI_20221007_R0_CH018_20221007163459_36_3_2_2818579454\n",
+      "C/20 charge\n",
+      "210.04711487362005\n",
+      "nan\n",
+      "GMJuly2022_CELL081_RPT_1_P25C_5P0PSI_20221007_R0_CH018_20221007163459_36_3_2_2818579454\n",
+      "HPPC\n",
+      "212.55095487362004\n",
+      "3.6880999999967514\n",
+      "GMJuly2022_CELL081_RPT_1_P25C_5P0PSI_20221007_R0_CH018_20221007163459_36_3_2_2818579454\n",
+      "C/20 charge\n",
+      "216.2390548736168\n",
+      "nan\n",
+      "GMJuly2022_CELL081_RPT_1_P25C_5P0PSI_20221007_R0_CH018_20221007163459_36_3_2_2818579454\n",
+      "C/20 discharge\n",
+      "219.73416487360768\n",
+      "3.4957999999918457\n",
+      "GMJuly2022_CELL081_RPT_3_P25C_5P0PSI_20230704_R0_CH018_20230704095411_36_3_2_2818579516\n",
+      "C/20 charge\n",
+      "3846.463704798771\n",
+      "nan\n",
+      "GMJuly2022_CELL081_RPT_3_P25C_5P0PSI_20230704_R0_CH018_20230704095411_36_3_2_2818579516\n",
+      "HPPC\n",
+      "3848.2791247987707\n",
+      "2.9218000000005304\n",
+      "GMJuly2022_CELL081_RPT_3_P25C_5P0PSI_20230704_R0_CH018_20230704095411_36_3_2_2818579516\n",
+      "C/20 charge\n",
+      "3851.200924798771\n",
+      "nan\n",
+      "GMJuly2022_CELL081_RPT_3_P25C_5P0PSI_20230704_R0_CH018_20230704095411_36_3_2_2818579516\n",
+      "C/20 discharge\n",
+      "3854.0660147987633\n",
+      "2.871399999993173\n",
+      "GMJuly2022_CELL081_F_1_P25C_5P0PSI_20220706_R0\n",
+      "C/20 charge\n",
+      "8.329444444444444e-05\n",
+      "nan\n",
+      "GMJuly2022_CELL081_F_1_P25C_5P0PSI_20220706_R0\n",
+      "C/20 discharge\n",
+      "3.872462601249918\n",
+      "3.402625480555244\n",
+      "GMJuly2022_CELL081_F_1_P25C_5P0PSI_20220706_R1_20220707101250_35_3_6_2818580187\n",
+      "C/20 charge\n",
+      "7.275088081805162\n",
+      "nan\n",
+      "GMJuly2022_CELL081_F_1_P25C_5P0PSI_20220706_R1_20220707101250_35_3_6_2818580187\n",
+      "C/20 discharge\n",
+      "10.726250637360646\n",
+      "3.464288263891472\n",
+      "GMJuly2022_CELL081_F_1_P25C_5P0PSI_20220706_R1_20220707101250_35_3_6_2818580187\n",
+      "C/20 charge\n",
+      "14.190538901252118\n",
+      "nan\n",
+      "GMJuly2022_CELL081_F_1_P25C_5P0PSI_20220706_R1_20220707101250_35_3_6_2818580187\n",
+      "C/20 discharge\n",
+      "17.680595708203505\n",
+      "3.4773827916720847\n",
+      "GMJuly2022_CELL081_F_1_P25C_5P0PSI_20220706_R1_20220707101250_35_3_6_2818580187\n",
+      "C/20 charge\n",
+      "21.15797849987559\n",
+      "nan\n",
+      "GMJuly2022_CELL081_F_1_P25C_5P0PSI_20220706_R1_20220707101250_35_3_6_2818580187\n",
+      "C/20 discharge\n",
+      "24.648415941547885\n",
+      "3.478798930561652\n",
+      "GMJuly2022_CELL081_RPT_3_P25C_5P0PSI_20221214_R0_CH018_20221214161546_36_3_2_2818579474\n",
+      "C/20 charge\n",
+      "1330.5757648663077\n",
+      "nan\n",
+      "GMJuly2022_CELL081_RPT_3_P25C_5P0PSI_20221214_R0_CH018_20221214161546_36_3_2_2818579474\n",
+      "HPPC\n",
+      "1332.3311148663076\n",
+      "3.3777999999995245\n",
+      "GMJuly2022_CELL081_RPT_3_P25C_5P0PSI_20221214_R0_CH018_20221214161546_36_3_2_2818579474\n",
+      "C/20 charge\n",
+      "1335.7089148663072\n",
+      "nan\n",
+      "GMJuly2022_CELL081_RPT_3_P25C_5P0PSI_20221214_R0_CH018_20221214161546_36_3_2_2818579474\n",
+      "C/20 discharge\n",
+      "1338.946254866298\n",
+      "3.24269999999251\n",
+      "GMJuly2022_CELL081_RPT_1_P25C_5P0PSI_20221114_R0_CH018_20221115071355_36_3_2_2818579467\n",
+      "C/20 charge\n",
+      "953.1299448696577\n",
+      "nan\n",
+      "GMJuly2022_CELL081_RPT_1_P25C_5P0PSI_20221114_R0_CH018_20221115071355_36_3_2_2818579467\n",
+      "HPPC\n",
+      "954.8810648696577\n",
+      "3.4634999999992715\n",
+      "GMJuly2022_CELL081_RPT_1_P25C_5P0PSI_20221114_R0_CH018_20221115071355_36_3_2_2818579467\n",
+      "C/20 charge\n",
+      "958.344564869657\n",
+      "nan\n",
+      "GMJuly2022_CELL081_RPT_1_P25C_5P0PSI_20221114_R0_CH018_20221115071355_36_3_2_2818579467\n",
+      "C/20 discharge\n",
+      "961.639234869648\n",
+      "3.3135999999922205\n",
       "<class 'pandas.core.frame.DataFrame'>\n",
       "Index: 69975 entries, 4133198 to 4203172\n",
       "Data columns (total 6 columns):\n",
@@ -72,31 +208,21 @@
       "memory usage: 3.7 MB\n"
      ]
     },
-    {
-     "data": {
-      "text/plain": [
-       "<Axes: xlabel='Time [s]'>"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "760fb01c940c48cdb94369b2f5afd181",
+       "model_id": "7a4e60f1b5cc486098ed5b3f8fbc511a",
        "version_major": 2,
        "version_minor": 0
       },
-      "image/png": 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",
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",
       "text/html": [
        "\n",
        "            <div style=\"display: inline-block;\">\n",
        "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
        "                    Figure\n",
        "                </div>\n",
-       "                <img 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' 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+       "                <img 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' width=640.0/>\n",
        "            </div>\n",
        "        "
       ],
@@ -111,7 +237,21 @@
    "source": [
     "#display(hppc_data_raw[\"Data\"])\n",
     "#hppc_data_raw.Discharge\n",
+    "for i in range(len(hppc_data_raw)):\n",
+    "    data_slice=hppc_data_raw.iloc[i]\n",
+    "    print(data_slice[\"Test name\"])\n",
+    "    print(data_slice[\"Protocol\"])\n",
+    "    print(data_slice[\"Ah throughput [A.h]\"])\n",
+    "    print(data_slice[\"Discharge capacity [A.h]\"])\n",
+    "\n",
+    "\n",
     "a=hppc_data_raw.iloc[33]\n",
+    "ldc_expan=a['Data vdf']['Expansion [-]']\n",
+    "ldc_time=a['Data vdf']['Time [s]']\n",
+    "X2=1.6473\n",
+    "X1=\t-27.134\t\n",
+    "C=138.74\n",
+    "ldc_expan_mm=1000*(30.6-(X2*(ldc_expan/10**6)**2+X1*(ldc_expan/10**6)+C))\n",
     "hppc_data_pulse = hppc_data_raw.iloc[31].Data #HPPC\n",
     "hppc_data_charge = hppc_data_raw.iloc[32].Data #C/20 Discharge\n",
     "hppc_data_discharge = hppc_data_raw.iloc[33].Data #C/20 Discharge\n",
@@ -122,19 +262,20 @@
     "#hppc_data[\"Time [s]\"]\n",
     "hppc_data.info(show_counts=True, memory_usage=True, verbose=True)\n",
     "hppc_data.plot(x=\"Time [s]\",y=\"Voltage [V]\")\n",
-    "\n",
+    "plt.plot(ldc_time,ldc_expan_um)\n",
+    "plt.show()\n",
     "#hppc_data.plot(x=\"Time [s]\",y=\"Ah throughput [A.h]\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 69,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "f64af23e38274b1ca34658a7bc57eb20",
+       "model_id": "2513c1ea64bf4b5b9a084114dc4cd0ec",
        "version_major": 2,
        "version_minor": 0
       },
@@ -192,7 +333,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 70,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -207,7 +348,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 71,
    "metadata": {},
    "outputs": [
     {
@@ -312,22 +453,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 72,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "CasADi - 2023-10-03 21:49:00 WARNING(\"The options 't0', 'tf', 'grid' and 'output_t0' have been deprecated.\n",
-      "The same functionality is provided by providing additional input arguments to the 'integrator' function, in particular:\n",
-      " * Call integrator(..., t0, tf, options) for a single output time, or\n",
-      " * Call integrator(..., t0, grid, options) for multiple grid points.\n",
-      "The legacy 'output_t0' option can be emulated by including or excluding 't0' in 'grid'.\n",
-      "Backwards compatibility is provided in this release only.\") [.../casadi/core/integrator.cpp:515]\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "sim_0 = pybamm.Simulation(spme, parameter_values=parameter_values, \n",
     "                            solver=pybamm.CasadiSolver(\"safe\"))\n",
@@ -337,13 +465,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 73,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "e6f104b1fc2d4dcebe41893688cd2842",
+       "model_id": "06a864eba69a449ab99d44515bb311a5",
        "version_major": 2,
        "version_minor": 0
       },