diff --git a/Activity02/Activity02.ipynb b/Activity02/Activity02.ipynb new file mode 100644 index 0000000..348a9d0 --- /dev/null +++ b/Activity02/Activity02.ipynb @@ -0,0 +1,200 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "88b65284-bdd1-4140-af28-526e77b9b4b6", + "metadata": {}, + "source": [ + "# Activity 2: Setting up the \"experiment\"\n", + "\n", + "To model a spectroscopy experiment, some parameters need to be correctly defined. For example the source direction with respect to the sample surface is important even if the light is not polarized. You can access those parameters in the \"source_parameters\" attribute of your calculator object.\n", + "\n", + "Other parameters are material specific. For example the inner potential. It is usually between 10 and 20 eV for most materials. This potential will add to the photoelectron kinetic energy inside the material. When the photoelectron escapes the sample, this internal potential is missing and this will create an energy step that will act as a refraction for the photoelectron intensity. The effect will be significant for large polar angles and for small kinetic energy of the photoelectron.\n", + "\n", + "## Sb-induced smooth growth of Ag on Ag(111) example\n", + "Let's look at the effect of those parameters on the following example. This example is based on ().\n", + "The idea is to use low energy photoelectron diffraction to see the substitution of Ag by Sb atoms on the surface plane.\n", + "\n", + "Let's start by building the cluster" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "0b0a420f-7074-443b-8cb4-1f609f5b123e", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "6fc0bcb7f39e4206b1c24637f021003f", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(NGLWidget(), VBox(children=(Dropdown(description='Show', options=('All', 'Sb', 'Ag'), value='Al…" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from ase.build import bulk\n", + "from ase.visualize import view\n", + "\n", + "from msspec.calculator import MSSPEC\n", + "from msspec.utils import hemispherical_cluster, get_atom_index, cut_plane\n", + "import numpy as np\n", + "from matplotlib import pyplot as plt\n", + "\n", + "# Only for jupyter\n", + "import nglview\n", + "from functools import partial\n", + "view = partial(view, viewer='ngl')\n", + "\n", + "# Create the silver cell\n", + "Ag = bulk('Ag', cubic=True)\n", + "# Orientate the cell in the [111] direction\n", + "Ag.rotate((1,1,1), (0,0,1), rotate_cell=True)\n", + "# Align the azimuth to match experimental reference\n", + "Ag.rotate(15, 'z', rotate_cell=True)\n", + "\n", + "# Create a cluster\n", + "cluster = hemispherical_cluster(Ag, diameter=20, emitter_plane=0)\n", + "cluster = cut_plane(cluster, z=-4.8)\n", + "cluster.emitter = get_atom_index(cluster, 0,0,0)\n", + "cluster[cluster.emitter].symbol = 'Sb'\n", + "\n", + "view(cluster)" + ] + }, + { + "cell_type": "markdown", + "id": "ae74eedc-5ea4-4782-a49a-dcc2feac6c7c", + "metadata": {}, + "source": [ + "Now create a calculator and configure experimental parameters" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "242638d5-aea4-46cb-8d26-061c695cbb3f", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "'NoneType' object has no attribute 'upper'\n", + "'integrals' is ignored since the 'spinpol' global parameter is set to False. Enable spin polarization in the constructor of your Calculator if you want to use this option.\n", + "The sample temperature was set, but will be ignored since 'use_debye_model' parameter is False.\n", + "The sample Debye temperature was set, but will be ignored since 'use_debye_model' parameter is False.\n" + ] + } + ], + "source": [ + "calc = MSSPEC(spectroscopy='PED', algorithm='inversion', txt='msspec.log')\n", + "calc.set_atoms(cluster)\n", + "\n", + "calc.source_parameters.theta = 0\n", + "calc.source_parameters.phi = 0\n", + "\n", + "calc.detector_parameters.angular_acceptance = 1\n", + "calc.detector_parameters.average_sampling = 'low'\n", + "\n", + "calc.muffintin_parameters.interstitial_potential = 0\n", + "data = calc.get_phi_scan(level='4d', theta=40, phi=np.linspace(0,240,121), kinetic_energy=45)\n", + "\n", + "# normalize data between [0,1]\n", + "dset = data[0]\n", + "dset.cross_section -= dset.cross_section.min()\n", + "dset.cross_section /= dset.cross_section.max()\n", + "\n", + "# Add experimental data points in the dataset\n", + "x, y = np.loadtxt('data.txt').T\n", + "dset.add_columns(experiment=y)\n", + "\n", + "# Add points to view\n", + "view = dset.views[0]\n", + "view.select('phi', 'experiment', legend='Exp. data')" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "bfedff51-12cc-43c0-b6ab-8e17038d271e", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "data[0].views[0].plot();" + ] + }, + { + "cell_type": "markdown", + "id": "0332a072-90b0-4d3e-8ee9-06cd16bb2608", + "metadata": {}, + "source": [ + "Try to change the source direction and the inner potential of Ag to better match the experiment...\n", + "\n", + "> **Note**:\n", + "> The cluster is smaller than it should for size convergence, but the calculation would take too much memory for this example" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9dc38bd9-8788-40fc-b0d3-448b341a0d51", + "metadata": { + "jupyter": { + "source_hidden": true + } + }, + "outputs": [], + "source": [ + "# Unfold to see the soluce\n", + "\n", + "# value hidden in refernce [] of the paper...\n", + "# The former SA73 Beamline in LURE\n", + "calc.source_parameters.theta = 22.5\n", + "\n", + "# Inner potentials are usually between 10 and 20 V. For Ag\n", + "calc.muffintin_parameters.interstitial_potential = 10.2" + ] + } + ], + "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": "3.11.13" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/Activity02/PhysRevB.55.R16061.pdf b/Activity02/PhysRevB.55.R16061.pdf new file mode 100644 index 0000000..9625e08 Binary files /dev/null and b/Activity02/PhysRevB.55.R16061.pdf differ diff --git a/Activity02/SbAg.py b/Activity02/SbAg.py new file mode 100644 index 0000000..ed144fc --- /dev/null +++ b/Activity02/SbAg.py @@ -0,0 +1,47 @@ +from ase.build import bulk +from msspec.calculator import MSSPEC +from msspec.utils import hemispherical_cluster, get_atom_index, cut_plane +import numpy as np +from matplotlib import pyplot as plt + + +Ag = bulk('Ag', cubic=True) +Ag.rotate((1,1,1), (0,0,1), rotate_cell=True) +Ag.rotate(15, 'z', rotate_cell=True) + +cluster = hemispherical_cluster(Ag, diameter=20, emitter_plane=0) + +cluster = cut_plane(cluster, z=-4.8) +cluster.emitter = get_atom_index(cluster, 0,0,0) +cluster[cluster.emitter].symbol = 'Sb' + +cluster.edit() + +calc = MSSPEC(spectroscopy='PED', algorithm='inversion') +calc.set_atoms(cluster) + +calc.source_parameters.theta = 0 +calc.source_parameters.phi = 0 + +calc.detector_parameters.angular_acceptance = 1 +calc.detector_parameters.average_sampling = 'low' + +calc.muffintin_parameters.interstitial_potential = 0 +data = calc.get_phi_scan(level='4d', theta=40, phi=np.linspace(0,240,121), kinetic_energy=45) + +# normalize data between [0,1] +dset = data[0] +dset.cross_section -= dset.cross_section.min() +dset.cross_section /= dset.cross_section.max() + +# Add experimental data points in the dataset +x, y = np.loadtxt('data.txt').T +dset.add_columns(experiment=y) + +# Add points to view +view = dset.views[0] +view.select('phi', 'experiment', legend='Exp. data') + +data.view() + +calc.shutdown() diff --git a/Activity02/data.txt b/Activity02/data.txt new file mode 100644 index 0000000..19f61b8 --- /dev/null +++ b/Activity02/data.txt @@ -0,0 +1,121 @@ +0.000000000000000000e+00 2.273853352828327234e-01 +2.000000000000000000e+00 2.135876322898652424e-01 +4.000000000000000000e+00 1.925265592281927285e-01 +6.000000000000000000e+00 1.852631891594877511e-01 +8.000000000000000000e+00 1.852631891594877511e-01 +1.000000000000000000e+01 1.831705825411805155e-01 +1.200000000000000000e+01 1.636929472985219347e-01 +1.400000000000000000e+01 1.279608696063064543e-01 +1.600000000000000000e+01 1.040430509934481690e-01 +1.800000000000000000e+01 3.015378633541379930e-02 +2.000000000000000000e+01 4.106459224097607462e-03 +2.200000000000000000e+01 1.971550450495464929e-02 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