msc_thesis/electrochemical_OCP_EIS_LPR/TAFEL.ipynb

{
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  {
   "cell_type": "markdown",
   "id": "a39d7464-a111-4ac6-80b0-bcaa20aa81fa",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "0dbb86a3-8915-43d6-b821-379ab76b2849",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy.optimize\n",
    "from scipy.signal import medfilt\n",
    "from scipy.optimize import curve_fit\n",
    "\n",
    "import warnings"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79273c57-b22e-4b9b-ad97-8b788969a4a6",
   "metadata": {},
   "source": [
    "## Data Loading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "9a43783f-d1bb-4c79-ae93-843086a00a26",
   "metadata": {},
   "outputs": [],
   "source": [
    "# --- Data Loading ---\n",
    "\n",
    "def lpr_cor_import(filename):\n",
    "    \"\"\" Import cor file as pandas dataframe.\"\"\"\n",
    "\n",
    "    try: \n",
    "        df = pd.read_csv(\n",
    "            filename,\n",
    "            skiprows=26,\n",
    "            sep='\\s+',\n",
    "            header=None,\n",
    "            names=[\"E\", \"i\", \"T\"],\n",
    "        ) \n",
    "        df.drop(columns=[\"T\"], inplace=True)\n",
    "        df[\"E\"] = df[\"E\"]*1e3 # Convert it to mV\n",
    "        \n",
    "    except FileNotFoundError as e:\n",
    "        print(f\"Error: File was not found.\")\n",
    "        print(e.message)\n",
    "        print(e.args)\n",
    "        return None\n",
    "    except Exception as e:\n",
    "        print(f\"Error reading the CSV file: {e}\")\n",
    "        return None   \n",
    "    else:\n",
    "        return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "6a2888b4-e151-4fae-97d5-7de521fb7b48",
   "metadata": {},
   "outputs": [],
   "source": [
    "HS1_1 = lpr_cor_import(\"HIPed_Stellite1_LPR/LPR_1.cor\")\n",
    "HS1_2 = lpr_cor_import(\"HIPed_Stellite1_LPR/LPR_2.cor\")\n",
    "HS1_3 = lpr_cor_import(\"HIPed_Stellite1_LPR/LPR_3.cor\")\n",
    "HS1_4 = lpr_cor_import(\"HIPed_Stellite1_LPR/LPR_4.cor\")\n",
    "HS1_5 = lpr_cor_import(\"HIPed_Stellite1_LPR/LPR_5.cor\")\n",
    "HS1_6 = lpr_cor_import(\"HIPed_Stellite1_LPR/LPR_6.cor\")\n",
    "\n",
    "# Keep it in the same cell to keep df reproducible, even if Vi clicks it multiple times\n",
    "area = 2 #cm^2\n",
    "\n",
    "for df in [HS1_1, HS1_2, HS1_3, HS1_4, HS1_5, HS1_6]:\n",
    "    df[\"i\"] = np.abs(df[\"i\"]/area) # Current density\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "0ad5c189-9bd6-4291-bdee-8b75fdd5a3cd",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>E</th>\n",
       "      <th>i</th>\n",
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       "            E             i\n",
       "0    -206.795  7.859750e-11\n",
       "1    -206.805  5.445100e-11\n",
       "2    -206.809  6.106750e-11\n",
       "3    -206.795  5.972600e-11\n",
       "4    -206.780  5.621750e-11\n",
       "...       ...           ...\n",
       "3999 -166.870  7.752900e-11\n",
       "4000 -166.854  7.931000e-11\n",
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       "4002 -166.850  7.296700e-11\n",
       "4003 -166.846  6.987300e-11\n",
       "\n",
       "[4004 rows x 2 columns]"
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     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "HS1_1 "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e293bb10-9bb3-43ab-858b-7a9c42f1f5f6",
   "metadata": {},
   "source": [
    "# Coding part!\n",
    "\n",
    "Separate code into analyze and plotting, with all answers in a dict.\n",
    "Can't believe it took me this long to really do it this way :|"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bec9f9bc-b531-470e-9c27-a89b512e97ba",
   "metadata": {},
   "source": [
    "## Analyze Tafel Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 305,
   "id": "d87b07b6-f893-4d5f-b06a-09643d170939",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "def analyze_tafel_data(\n",
    "    data: pd.DataFrame\n",
    ") -> dict | None:\n",
    "\n",
    "    INITIAL_KERNEL = 29\n",
    "    FIT_KERNEL = 99\n",
    "    \n",
    "    # 1. Estimate Corrosion Potential (Ecorr) using a median filter\n",
    "    ecorr_guess = data['E'].iloc[np.argmin(medfilt(data['i'], kernel_size=INITIAL_KERNEL))]\n",
    "\n",
    "    # 2. Split data into anodic and cathodic regions based on Ecorr\n",
    "    anodic_data = data[data['E'] > ecorr_guess]\n",
    "    cathodic_data = data[data['E'] < ecorr_guess]\n",
    "    if anodic_data.empty or cathodic_data.empty:\n",
    "        warnings.warn(\"No data in anodic or cathodic regions?. Ecorr guess may be incorrect.\")    \n",
    "    \n",
    "    # 3. Perform linear fit on E vs. i for each branch\n",
    "    medfilt_anodic_i = medfilt(anodic_data['i'].iloc[30:-90], kernel_size=FIT_KERNEL)\n",
    "    p_anodic = np.poly1d(np.polyfit(medfilt_anodic_i, anodic_data['E'].iloc[30:-90], 1))\n",
    "    medfilt_cathodic_i = medfilt(cathodic_data['i'].iloc[30:-90], kernel_size=FIT_KERNEL)\n",
    "    p_cathodic = np.poly1d(np.polyfit(medfilt_cathodic_i, cathodic_data['E'].iloc[30:-90], 1))\n",
    "    \n",
    "    # 4. Calculate the tangent at the extreme ends of the filtered data\n",
    "    i_extreme_anodic = medfilt_anodic_i.max()\n",
    "    e_extreme_anodic = p_anodic(i_extreme_anodic)\n",
    "    tangent_slope_anodic = p_anodic.coeffs[0] * (i_extreme_anodic * np.log(10))\n",
    "\n",
    "    i_extreme_cathodic = medfilt_cathodic_i.max()\n",
    "    e_extreme_cathodic = p_cathodic(i_extreme_cathodic)\n",
    "    tangent_slope_cathodic = p_cathodic.coeffs[0] * (i_extreme_cathodic * np.log(10))\n",
    "\n",
    "    print(f\"tangent_slope_anodic   {tangent_slope_anodic}\")\n",
    "    print(f\"tangent_slope_cathodic {tangent_slope_cathodic}\")\n",
    "    print(f\"p_anodic   {p_anodic}\")\n",
    "    print(f\"p_cathodic {p_cathodic}\")\n",
    "\n",
    "          \n",
    "    # 5. Calculate tangent lines    \n",
    "    log_i_extreme_anodic = np.log10(i_extreme_anodic)\n",
    "    log_i_tangent_anodic = np.linspace(log_i_extreme_anodic - 0.5, log_i_extreme_anodic, 100)\n",
    "    e_tangent_anodic = (\n",
    "        tangent_slope_anodic * (log_i_tangent_anodic - log_i_extreme_anodic)\n",
    "        + e_extreme_anodic\n",
    "    )\n",
    "\n",
    "    log_i_extreme_cathodic = np.log10(i_extreme_cathodic)\n",
    "    log_i_tangent_cathodic = np.linspace(log_i_extreme_cathodic - 0.5, log_i_extreme_cathodic, 100)\n",
    "    e_tangent_cathodic = (\n",
    "        tangent_slope_cathodic * (log_i_tangent_cathodic - log_i_extreme_cathodic)\n",
    "        + e_extreme_cathodic\n",
    "    )\n",
    "\n",
    "\n",
    "    # --- 3. Calculations ---\n",
    "    temp_kelvin = 25.0 + 273.15\n",
    "    R = 8.314  # Ideal Gas Constant (J/(mol·K))\n",
    "    F = 96485  # Faraday Constant (C/mol)\n",
    "    n = 2 # Number of electrons transferred in your electrochemical reaction.    \n",
    "    \n",
    "    # Calculate the anodic charge transfer coefficient (alpha_a)\n",
    "    # This value represents the fraction of the potential that assists the oxidation reaction.\n",
    "    try:\n",
    "        alpha_a = (2.303 * R * temp_kelvin) / (1e-3 * tangent_slope_anodic * n * F)\n",
    "        alpha_c = -(2.303 * R * temp_kelvin) / (1e-3 * tangent_slope_cathodic * n * F)    \n",
    "    except ZeroDivisionError as e:\n",
    "        print(\"Slope is zero, what happened?\")\n",
    "        print(e)\n",
    "  \n",
    "    \n",
    "    # 6. Package results into a dictionary\n",
    "    results = {\n",
    "        \"ecorr_guess\": ecorr_guess,\n",
    "        \"beta_a\": tangent_slope_anodic,        \n",
    "        \"beta_c\": tangent_slope_cathodic,\n",
    "        \"alpha_a\": alpha_a,        \n",
    "        \"alpha_c\": alpha_c,        \n",
    "        \"anodic_tangent_i\": 10**log_i_tangent_anodic,\n",
    "        \"anodic_tangent_E\": e_tangent_anodic,\n",
    "        \"cathodic_tangent_i\": 10**log_i_tangent_cathodic,\n",
    "        \"cathodic_tangent_E\": e_tangent_cathodic,   \n",
    "    }\n",
    "    return results"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "967c80c8-6271-405d-98e6-f2699a657fc5",
   "metadata": {},
   "source": [
    "## Plotting code\n",
    "\n",
    "Plot the additional stuff only if you have results.\n",
    "Use the same function for everything\n",
    "Again, why didn't I do this earlier :|\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 306,
   "id": "a49005dc-a2b9-4cf1-9ad8-e4f549bda1fd",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_tafel(data: pd.DataFrame, results: dict):\n",
    "    \"\"\"\n",
    "    Generates and displays a Tafel plot from the data and analysis results.\n",
    "\n",
    "    Args:\n",
    "        data (pd.DataFrame): The original experimental data.\n",
    "        results (dict): The dictionary returned by analyze_tafel_data.\n",
    "    \"\"\"\n",
    "    fig, ax = plt.subplots(figsize=(8, 4), dpi=150)\n",
    "\n",
    "    # Plot the raw experimental data\n",
    "    ax.semilogx(\n",
    "        np.abs(data[\"i\"].to_numpy()), data[\"E\"].to_numpy(),\n",
    "        marker='o', linestyle='', markersize=3, alpha=0.6, label=\"Experimental Data\"\n",
    "    )\n",
    "\n",
    "    # Plot the analysis results if available\n",
    "    if results:\n",
    "        \n",
    "        ax.axhline(  # Ecorr line\n",
    "            y=results[\"ecorr_guess\"],\n",
    "            color='green', linestyle='--', linewidth=2,\n",
    "            label=f'$E_{{corr}}$ = {results[\"ecorr_guess\"]:.2f} mV'\n",
    "        )\n",
    "        \n",
    "        ax.plot(     # Anodic tangent line\n",
    "            results[\"anodic_tangent_i\"], results[\"anodic_tangent_E\"],\n",
    "            color='red', linestyle='-.', linewidth=2,\n",
    "            label=f'Anodic Tangent {results[\"beta_a\"]:.2f}'\n",
    "        )\n",
    "        \n",
    "        ax.plot(     # Cathodic tangent line\n",
    "            results[\"cathodic_tangent_i\"], results[\"cathodic_tangent_E\"],\n",
    "            color='blue', linestyle='-.', linewidth=2,\n",
    "            label=f'Cathodic Tangent {results[\"beta_c\"]:.2f}'\n",
    "        )\n",
    "\n",
    "        bx = ax.twinx()  \n",
    "        ymin, ymax = ax.get_ylim()\n",
    "        bx.set_ylim(ymin-results[\"ecorr_guess\"], ymax-results[\"ecorr_guess\"])\n",
    "        bx.set_ylabel(\"Overpotential (mV)\")\n",
    "    \n",
    "    # Configure plot aesthetics\n",
    "    ax.set_xlabel(\"Current (A)\")\n",
    "    ax.set_ylabel(\"Potential (mV)\")\n",
    "    ax.legend()\n",
    "    ax.grid(True, which=\"both\", ls=\"--\", linewidth=0.5)\n",
    "    plt.tight_layout()\n",
    "    plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d83b0f6a-2961-4381-941f-2eda09ab713c",
   "metadata": {},
   "source": [
    "# Funspace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 307,
   "id": "2f0f4d93-90bd-4ea0-b481-5d2d0c0d35c5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tangent_slope_anodic   36.935982391954994\n",
      "tangent_slope_cathodic -54.436282369617466\n",
      "p_anodic    \n",
      "2.397e+11 x - 184\n",
      "p_cathodic  \n",
      "-5.085e+11 x - 181.9\n",
      "alpha_a 0.8009387773094865\n",
      "alpha_c 0.5434511558829113\n",
      "1.3443899331923976\n",
      "\n",
      "tangent_slope_anodic   32.33609922748971\n",
      "tangent_slope_cathodic -48.11484786212909\n",
      "p_anodic    \n",
      "2.421e+11 x - 182.5\n",
      "p_cathodic  \n",
      "-4.494e+11 x - 183.5\n",
      "alpha_a 0.9148741277546404\n",
      "alpha_c 0.614850963688116\n",
      "1.5297250914427565\n",
      "\n",
      "tangent_slope_anodic   33.64593158958795\n",
      "tangent_slope_cathodic -59.21671579699353\n",
      "p_anodic    \n",
      "2.375e+11 x - 182.9\n",
      "p_cathodic  \n",
      "-5.41e+11 x - 181.2\n",
      "alpha_a 0.8792581800556247\n",
      "alpha_c 0.4995795558327658\n",
      "1.3788377358883905\n",
      "\n",
      "tangent_slope_anodic   36.99409502392016\n",
      "tangent_slope_cathodic -52.39962161372843\n",
      "p_anodic    \n",
      "2.566e+11 x - 184.8\n",
      "p_cathodic  \n",
      "-5.576e+11 x - 182.8\n",
      "alpha_a 0.7996806127196425\n",
      "alpha_c 0.5645739351672425\n",
      "1.364254547886885\n",
      "\n",
      "tangent_slope_anodic   39.037818290543065\n",
      "tangent_slope_cathodic -51.88236612198446\n",
      "p_anodic    \n",
      "2.673e+11 x - 185.4\n",
      "p_cathodic  \n",
      "-5.525e+11 x - 183.2\n",
      "alpha_a 0.7578154177459187\n",
      "alpha_c 0.5702026100001164\n",
      "1.328018027746035\n",
      "\n",
      "tangent_slope_anodic   41.082268537703634\n",
      "tangent_slope_cathodic -50.05787314753787\n",
      "p_anodic    \n",
      "2.856e+11 x - 185.9\n",
      "p_cathodic  \n",
      "-5.686e+11 x - 183.9\n",
      "alpha_a 0.7201028966690741\n",
      "alpha_c 0.5909851680782454\n",
      "1.3110880647473195\n",
      "\n",
      "tangent_slope_anodic   36.935982391954994\n",
      "tangent_slope_cathodic -54.436282369617466\n",
      "p_anodic    \n",
      "2.397e+11 x - 184\n",
      "p_cathodic  \n",
      "-5.085e+11 x - 181.9\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# =============================================================================\n",
    "# --- Main Execution Block ---\n",
    "# =============================================================================\n",
    "\n",
    "# 1. Analyze the dataset\n",
    "for HS1_df in [HS1_1, HS1_2, HS1_3, HS1_4, HS1_5, HS1_6]:\n",
    "    analysis_results = analyze_tafel_data(HS1_df)\n",
    "    print(f\"alpha_a {analysis_results['alpha_a']}\")\n",
    "    print(f\"alpha_c {analysis_results['alpha_c']}\")\n",
    "    print(analysis_results['alpha_a'] + analysis_results['alpha_c'])\n",
    "    print()\n",
    "\n",
    "analysis_results = analyze_tafel_data(HS1_1)\n",
    "\n",
    "# 2. Plot the results\n",
    "if analysis_results:\n",
    "    plot_tafel(HS1_1, analysis_results)\n",
    "else:\n",
    "    print(\"Analysis could not be completed.\")\n",
    "\n",
    "#print(analysis_results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7a6fb1f0-efb2-4c23-83d7-1079955624a7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cf05eadf-1b38-403c-854f-59cd2a3a8fde",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2b5b05ad-31cd-4142-818f-003967634f80",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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