{ "cells": [ { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "\n", "## Chapter 4 [Spectroscopy](CH4_00-Spectroscopy.ipynb)\n", "\n", "\n", "
\n", "\n", "# Generation of Characteristic X-Rays \n", "[Download](https://raw.githubusercontent.com/gduscher/MSE672-Introduction-to-TEM/main/Spectroscopy/CH4_14-Characteristic_X_Rays.ipynb)\n", " \n", "\n", "[![OpenInColab](https://colab.research.google.com/assets/colab-badge.svg)](\n", " https://colab.research.google.com/github/gduscher/MSE672-Introduction-to-TEM/blob/main//Spectroscopy/CH4_14-Characteristic_X_Rays.ipynb)\n", "\n", "part of \n", "\n", " **[MSE672: Introduction to Transmission Electron Microscopy](../_MSE672_Intro_TEM.ipynb)**\n", "\n", "\n", "**Spring 2024**\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Gerd Duscher Khalid Hattar
Microscopy Facilities Tennessee Ion Beam Materials Laboratory
Materials Science & Engineering Nuclear Engineering
Institute of Advanced Materials & Manufacturing
The University of Tennessee, Knoxville
\n", "\n", "Background and methods to analysis and quantification of data acquired with transmission electron microscopes.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Load relevant python packages\n", "### Check Installed Packages" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "done\n" ] } ], "source": [ "import sys\n", "import importlib.metadata\n", "def test_package(package_name):\n", " \"\"\"Test if package exists and returns version or -1\"\"\"\n", " try:\n", " version = importlib.metadata.version(package_name)\n", " except importlib.metadata.PackageNotFoundError:\n", " version = '-1'\n", " return version\n", "\n", "if test_package('pyTEMlib') < '0.2024.2.3':\n", " print('installing pyTEMlib')\n", " !{sys.executable} -m pip install --upgrade pyTEMlib -q\n", "\n", "print('done')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## First we import the essential libraries\n", "All we need here should come with the annaconda or any other package" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%matplotlib widget\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import sys\n", "import os\n", "if 'google.colab' in sys.modules:\n", " from google.colab import output\n", " from google.colab import drive\n", " output.enable_custom_widget_manager()\n", " \n", "from pyTEMlib.xrpa_x_sections import x_sections\n", "\n", "__notebook__ = 'CH4_14-Characteristic-X_Rays'\n", "__notebook_version__ = '2019_08_21'\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## X-Ray Families\n", "The case is not always as simple as in the case of the carbon atom in the [Introduction](CH4_12-Introduction_X_Rays.ipynb#X-Rays)\n", "\n", "As the atomic number $Z$ increases the number of electrons in the respective energy states increases. With increasing complexity of the shell structure more options for relaxtions are available with different probabilities.\n", "\n", "For example a Na atom which has an M-shell The 1s state can be filled by an L- or an M-shell, producing two different characteristic X-rays:\n", "\n", "- K-L$_{2,3} ($K\\alpha$): $E_X = $E_K- E_L$ = 104 eV\n", "- K-M$_{2,3} ($K\\beta$): $E_X = $E_K- E_M$ = 1071 eV\n", "\n", "For heavier atoms than sodium more options exist:\n", "\n", "![Nomenclature](./images/Nomenclature.jpg)\n", "\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## X-ray Nomenclature \n", "\n", "Two systems are in use for naming characteristic X-ray lines.\n", "\n", "The oldest one is the Siegbahn system in wich first the shell where the ionization occured is listed and then a greek letter that suggests the order of their families by their **relative intensity** ($\\alpha>\\beta>\\gamma>\\eta>\\zeta$).\n", "\n", "For closely related memebers of a family additionally numebrs are attched such as $L \\beta_1$.\n", "\n", "While most commercial software still uses the Siegbahn system the [International Union of Pure and Applied Chemistry (IUPAC)](https://old.iupac.org/publications/pac/1991/pdf/6305x0735.pdf) has officially changed the system to a protocol that first dentoes the subshell were the ionization occured and followed with the term that indicates from which subshell the relaxation originates.\n", "\n", "So $K\\alpha_1$ is replaced by $K-L_3$.\n", "\n", "![eds-lines](./images/eds-lines.jpg)\n", "\n", "|Siegbahn| -----IUPAC----- |Siegbahn| -----IUPAC----- |Siegbahn| -----IUPAC----- |\n", "|--------| -------------- |--------| ------------ |--------| ------------- | \n", "| $K\\alpha_1$| $K-L_3$ |$L\\alpha_1$| $L_3-M_5$ |$M\\alpha_1$| $M_5-N_7$|\n", "| $K\\alpha_2$| $K-L_2$ |$L\\alpha_2$| $L_3-M_4$ |$M\\alpha_2$| $M_5-N_6$|\n", "| $K\\beta_1$| $K-M_3$ |$L\\beta_1$ | $L_2-M_4$ |$M\\beta$ | $M_4-N_6$|\n", "| $K\\beta_2$| $K-N_{2,3}$ |$L\\beta_2$ | $L_3-N_5$ |$M\\gamma$ | $M_3-N_5$|\n", "| | |$L\\beta_3$ | $L_1-M_3$ |$M\\zeta$ | $M_{4,5}-N_{2,3}$|\n", "| | |$L\\beta_4$ | $L_1-M_2$ | | $M_3-N_1$|\n", "| | |$L\\gamma_1$| $L_2-N_4$ | | $M_2-N_1$|\n", "| | |$L\\gamma_2$| $L_1-N_2$ | | $M_3-N_{4,5}$|\n", "| | |$L\\gamma_3$| $L_1-N_3$ | | $M_3-O_1$|\n", "| | |$L\\gamma_4$| $L_1-O_4$ | | $M_3-O_{4,5}$|\n", "| | |$L\\zeta$ | $L_2-M_1$ | | $M_2-N_4$|\n", "| | |$L\\iota$ | $L_3-M_1$ | ||" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## X-ray Weight of Lines\n", "\n", "Within the excitation probaility of the characteristic X-ray lines are not equal. \n", "\n", "For sodium (see above for energies), \n", "the ratio of $K-L_{2,3}$ to $K-M$ is approximatively 150: 1. \n", "\n", "This ratios between the lines are a strong function of the atomic number $Z$.\n", "\n", "We load the data of the X-Ray lines from data from [NIST](https://www.nist.gov/), the line weights are taken from the Program [DTSA-II](https://www.cstl.nist.gov/div837/837.02/epq/dtsa2/index.html), which is the quasi-standard in EDS analysis.\n" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "fd9da53d78bb4482bc7af885816fbea3", "version_major": 2, "version_minor": 0 }, "image/png": "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", "text/html": [ "\n", "
\n", "
\n", " Figure\n", "
\n", " \n", "
\n", " " ], "text/plain": [ "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "K_M5 = []\n", "ele_K_M5 = []\n", "L3_M1 = []\n", "ele_M3_M1 = []\n", "L1_N3 = []\n", "ele_L1_N3 = []\n", "L3_N5 =[]\n", "ele_L3_N5 = []\n", "L2_M4 = []\n", "ele_L2_M4 = []\n", "for element in range(5,82):\n", " if 'K-M5' in x_sections[str(element)]['lines']:\n", " K_M5.append(x_sections[str(element)]['lines']['K-M5']['weight']/x_sections[str(element)]['lines']['K-L3']['weight'])\n", " ele_K_M5.append(element)\n", " if 'L3-M5' in x_sections[str(element)]['lines']:\n", " \n", " if 'L3-M1' in x_sections[str(element)]['lines']:\n", " L3_M1.append(x_sections[str(element)]['lines']['L3-M1']['weight']/x_sections[str(element)]['lines']['L3-M5']['weight'])\n", " ele_M3_M1.append(element)\n", " \n", " if 'L1-N3' in x_sections[str(element)]['lines']:\n", " L1_N3.append(x_sections[str(element)]['lines']['L1-N3']['weight']/x_sections[str(element)]['lines']['L3-M5']['weight'])\n", " ele_L1_N3.append(element)\n", " \n", " if 'L3-N5' in x_sections[str(element)]['lines']:\n", " L3_N5.append(x_sections[str(element)]['lines']['L3-N5']['weight']/x_sections[str(element)]['lines']['L3-M5']['weight'])\n", " ele_L3_N5.append(element)\n", " \n", " if 'L2-M4' in x_sections[str(element)]['lines']:\n", " L2_M4.append(x_sections[str(element)]['lines']['L2-M4']['weight']/x_sections[str(element)]['lines']['L3-M5']['weight'])\n", " ele_L2_M4.append(element)\n", " \n", "ele = np.linspace(1,94,94)\n", "\n", "plt.figure()\n", "plt.plot(ele_K_M5 ,K_M5, label = 'K-M$_3$ / K-L$_3$')\n", "plt.plot(ele_M3_M1,L3_M1, label = 'L$_3$-M$_1$ / L$_3$-M$_5$')\n", "plt.plot(ele_L1_N3,L1_N3, label = 'L$_1$-N$_3$ / L$_3$-M$_5$')\n", "plt.plot(ele_L3_N5,L3_N5, label = 'L$_3$-N$_5$ / L$_3$-M$_5$')\n", "plt.plot(ele_L2_M4,L2_M4, label = 'L$_2$-M$_4$ / L$_3$-M$_5$')\n", "plt.ylabel('')\n", "plt.gca().set_yscale('log')\n", "plt.xlabel('atomic number')\n", "plt.ylabel('relative weights of lines')\n", "\n", "plt.legend();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Characteristic X-ray Intensity\n", "\n", "The cross section $Q_I$ (probability of excitation expressed as area) of an isolated atom ejecting an electron bound with energy $E_c$ (keV) by an electron with energy $E$ (keV) is:\n", "\n", "$$Q_I \\left(\\frac{ionizations}{e^- (atoms/cm^2)} \\right) = 6.51 \\times 10^{-20} \\left[ \\frac{n_s b_s}{E E_c}\\right]\\log_e (c_s E / E_c) $$\n", "\n", "where:\n", "- $n_s$: number of electrons in shell or subshell $s$\n", "- $b_s$, $c_s$: constants for a given shell $s$\n", "- $E$: energy of the exciting electron\n", "- $E_𝑐$: Critical ionization energy\n", "\n", "For example for a K shell (Powell 1979): $n_K = 2$, $b_K = 0.35$, and $c_k = 1$\n", "\n", "For silion the characteristic energy or binding energy for the K shell: $E_c = 1.838$ keV\n", "\n", "The relationship between energy of the exciting electron and critical energy is important and is expressed as **overvoltage** $U$:\n", "$$U =\\frac{E}{E_c}$$\n", "\n", "\n", "\n", "The overvoltage of the primary electron with energy $E_0$ is expressed as:\n", "$$ U_0 =\\frac{E_0}{E_c}$$\n", "\n", "We can express the cross section with the overvoltage:\n", "\n", "$$Q_I = 6.51 \\times 10^{-20} \\left[ \\frac{n_s b_s}{U E_c^2}\\right]\\log_e (c_s U) $$\n", "\n" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "c7ad8bfef695499faeec4cf78df8f6f6", "version_major": 2, "version_minor": 0 }, "image/png": "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", "text/html": [ "\n", "
\n", "
\n", " Figure\n", "
\n", " \n", "
\n", " " ], "text/plain": [ "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "n_K = 2.0\n", "b_K = 0.35\n", "c_K = 1.0\n", "\n", "# Silicon\n", "E_c_Si = 1.838 \n", "# Iron\n", "E_c_Fe = 6.401\n", "\n", "E = np.linspace(0,30,2048)+0.05\n", "U = E/E_c_Si\n", "\n", "Q_Si = 6.51*1e-20*n_K*b_K/(U * E_c_Si**2)* np.log(c_K * U)\n", "U = E/E_c_Fe\n", "Q_Fe = 6.51*1e-20*n_K*b_K/(U * E_c_Fe**2)* np.log(c_K * U)\n", "plt.figure()\n", "plt.plot(E,Q_Si, label ='Si')\n", "plt.plot(E,Q_Fe, label ='Fe')\n", "\n", "plt.ylim(0.,Q_Si.max()*1.1)\n", "plt.xlabel('excitation energy (keV)')\n", "plt.ylabel('Q (inizations/[e$^-$ (atoms /cm$^2$)])')\n", "plt.legend();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "[C.J. Powell,\"Cross sections for inelastic electron scattering in solids\", Ultramicroscopy **28** pp 24-31 (1989)](https://doi.org/10.1016/0304-3991(89)90264-7)\n", "\n", "[E. Casnati, A. Tartari, and C. Baraldi; J. Phys. B: At. Mol. Phys..li (1982) 155-167: *An empirical approach to K-shell ionisation cross section by electrons*](https://doi.org/10.1088/0022-3700/15/1/022)\n", "\n", "\n", "[D. Bote and F. Salvat \"Calculations of inner-shell ionization by electron impact with the distorted-wave and plane-wave Born approximations\",Phys. Rev. A 77, 042701](https://doi.org/10.1103/PhysRevA.77.042701)\n", " \n", " " ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'filename': 'None',\n", " 'excl before': 5,\n", " 'excl after': 50,\n", " 'onset': 7.26159,\n", " 'factor': 0.6666666666666666}" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "x_sections['25']['M4']" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "40d869d9cba246c6999c7600457bffd9", "version_major": 2, "version_minor": 0 }, "image/png": "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", "text/html": [ "\n", "
\n", "
\n", " Figure\n", "
\n", " \n", "
\n", " " ], "text/plain": [ "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ " \"\"\" \n", " (Casnati's equation) was found to fit cross-section data to\n", " typically better than +-10% over the range 1<=Uk<=20 and 6<=Z<=79.\"\n", " \n", " Note: This result is for K shell. L & M are much less well characterized.\n", " C. Powell indicated in conversation that he believed that Casnati's\n", " expression was the best available for L & M also.\n", "\"\"\"\n", "shell_occupancy={'K':2,'L1':2,'L2':2,'L3':4,'M1':2,'M1':2,'M2':2,'M3':4,'M4':4,'M5':6}\n", "import scipy.constants as const\n", "res = 0.0;\n", "beamE = 30\n", "rel = []\n", "Z= []\n", "shell = 'M4'\n", "for element in range(25,56):\n", " ee = x_sections[str(element)][shell]['onset']#getEdgeEnergy();\n", " u = ee/beamE;\n", " #print(u)\n", " if(u > 1.0):\n", " u2 = u * u;\n", " phi = 10.57 * np.exp((-1.736 / u) + (0.317 / u2));\n", " #psi = Math.pow(ee / PhysicalConstants.RydbergEnergy, -0.0318 + (0.3160 / u) + (-0.1135 / u2));\n", " psi = np.power(ee / const.Rydberg, -0.0318 + (0.3160 / u) + (-0.1135 / u2));\n", "\n", " i = ee / const.electron_mass# PhysicalConstants.ElectronRestMass;\n", " t = beamE / const.electron_mass#PhysicalConstants.ElectronRestMass;\n", " f = ((2.0 + i) / (2.0 + t)) * np.sqrt((1.0 + t) / (1.0 + i)) * np.power(((i + t) * (2.0 + t) * np.sqrt(1.0 + i))/ ((t * (2.0 + t) * np.sqrt(1.0 + i)) + (i * (2.0 + i))), 1.5);\n", " getGroundStateOccupancy = shell_occupancy[shell]\n", " res = ((getGroundStateOccupancy * np.sqrt((const.value('Bohr radius') * const.Rydberg) / ee) * f * psi * phi * np.log(u)) / u);\n", " \n", " rel.append(res)\n", " Z.append(element)\n", " #print(res)\n", " \n", "plt.figure()\n", "plt.title(f\"Casnati's cross section for beam energy {beamE:.0f} keV\")\n", "plt.plot(Z,rel)\n", "\n", "plt.xlabel('atomic number Z')\n", "plt.ylabel('Q [barns]');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Even though the cross section raises fast with overvoltage $U$, \n", "too low overvoltage leads to a small cross section, which results in poor excitation of the X-ray line.\n", "\n", "We can also see that the intial overvoltage $U_0$ varies with atomic number $Z$, which will affect the relative generation of X-rays from different elements.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## X-ray Production in a Thick Solid Sample\n", "\n", "If the sample is sufficient thick so that all electrons interact ( several micrometers) the X-ray intensity is found to follow an expression fo the form:\n", "\n", "$$I \\approx i_p \\left[ (E_0-E_c)/E_0\\right]^n \\approx i_p [U_0-1]^n$$\n", "\n", "where:\n", "- $i_p$: beam current \n", "- $n$: exponent $n$ depends on particular element and shell (Lifshin et al. 1980) \n", "\n", "The exponent $n$ is ususally between 1.5 and 2. See what changes in the plot below if you change this exponent." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "9f9ef7ead3644e04bce1a92de5e66763", "version_major": 2, "version_minor": 0 }, "image/png": "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", "text/html": [ "\n", "
\n", "
\n", " Figure\n", "
\n", " \n", "
\n", " " ], "text/plain": [ "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "n = 1.5\n", "\n", "U_0 = np.linspace(1,10, 2048)\n", "i_p = 1.0 # in nA\n", "I = i_p * (U_0-1.0)**n\n", "\n", "plt.figure()\n", "plt.plot(U_0,I)\n", "plt.axhline(y=0., color='gray', linewidth=0.5)\n", "plt.xlabel('overvoltage $U_0$ [kV]')\n", "plt.ylabel('$I$ [nA]');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## X-ray Production in a Thin Foil\n", "\n", "Now we have all the ingeedients to look at the total generation of X-rays.\n", "\n", "The number of photons $n_X$ produced in a thin foil of thickness $t$ is :\n", "$$ n_x = Q_I(E) \\ \\omega N_A \\frac{1}{A} \\rho \\ t $$\n", "\n", "- $n_X$ [photons/e$^-$]\n", "- $Q_I(E)$ [ ionizations/e$^-$ (atoms / cm$^2$)): ionization cross section\n", "- $\\omega$ [X-rays/ ionization]: fluorescent yield = number of X-rays generated per ionization\n", "- $ N_A$ [atoms per mol]: Avogadro’s number \n", "- $A$ [g/moles]: atomic weight\n", "- $\\rho$ [g/cm$^3$]: density of sample\n", "- $t$ [cm]: thickness of sample\n", "\n", "The number of X-rays increase linearly with the number of atoms per unit area ($N_A \\frac{1}{A} \\rho \\ t $).\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In the graph above, we can see the importance of the overvoltage $U$ by how the intensity increase with increasing $U_0$" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Quiz\n", "Why is the overvoltage increasing so much while the cross section remains rather constant above the threshold? " ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "\n", "## Navigation\n", "- **Back: [Bremsstrahlung](CH4_13-Bremsstrahlung.ipynb)** \n", "- **Next: [Detector Response](CH4_15-Detector.ipynb)** \n", "- **Chapter 4: [Spectroscopy](CH4_00-Spectroscopy.ipynb)** \n", "- **List of Content: [Front](../_MSE672_Intro_TEM.ipynb)** " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.11.7" }, "vscode": { "interpreter": { "hash": "838e0debddb5b6f29d3d8c39ba50ae8c51920a564d3bac000e89375a158a81de" } } }, "nbformat": 4, "nbformat_minor": 4 }