182 lines
8.3 KiB
Python
182 lines
8.3 KiB
Python
# coding: utf-8
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from msspec.utils import *
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from ase.build import bulk
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from ase.visualize import view
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import numpy as np
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from msspec.calculator import MSSPEC, XRaySource
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from msspec.iodata import Data
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from itertools import product
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DATA = None
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def AlN_cluster(emitter_tag, emitter_plane, diameter=0, planes=0, term_anion=True, tetra_down=True):
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"""
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This function is a kind of overload of the hemispherical_cluster function with specific attributes
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to the AlN structure
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:param emitter_tag: An integer that allows to identify the kind of atom to use as the emitter
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:param emitter_plane: The plane where the emitter is. 0 means the surface.
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:param diameter: The diameter of the cluster (in Angstroms).
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:param planes: The total number of planes.
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:param term_anion: True if the surface plane is anion terminated, False otherwise
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:param tetra_down: The orientation of the tetrahedral
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:return:
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"""
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# create the initial cluster of AlN
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cluster = bulk('AlN', crystalstructure='wurtzite', a=3.11, c=4.975)
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# tag each atom in the unit cell because they are all in a different chemical/geometrical environment
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# (0 and 2 for Aluminum's atoms and 1 and 3 for Nitride's atoms)
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[atom.set('tag', i) for i, atom in enumerate(cluster)]
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# change the orientation of the tetrahedron
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if not tetra_down:
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cluster.rotate(180, 'y')
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# From this base pattern, creat an hemispherically shaped cluster
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cluster = hemispherical_cluster(cluster, emitter_tag=emitter_tag, emitter_plane=emitter_plane, diameter=diameter,
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planes=planes)
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# Depending on the number of planes above the emitter, the termination may not be the one you wish,
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# we test this and raise an exception in such a case
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# Get the termination by finding the kind of one atom located at the topmost z coordinate
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termination = cluster[np.argsort(cluster.get_positions()[:, 2])[-1]].symbol
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# test if the combination of parameters is possible
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assert (termination == 'N' and term_anion) or (termination == 'Al' and not term_anion), (
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"This termination isn't compatible with your others parameters, you must change the tag of "
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"your emitter, the plane of your emitter or your termination")
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return cluster
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def create_clusters(side='Al', emitter='Al', diameter=15, planes=6):
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clusters = []
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if side == 'Al':
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term_anion = tetra_down = False
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elif side == 'N':
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term_anion = tetra_down = True
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if emitter == 'Al':
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tags = (0, 2)
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level = '2p'
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ke = 1407.
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elif emitter == 'N':
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tags = (1, 3)
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level = '1s'
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ke = 1083.
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for emitter_tag, emitter_plane in product(tags, range(0, planes)):
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nplanes = emitter_plane + 2
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try:
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cluster = AlN_cluster(emitter_tag, emitter_plane, diameter=diameter, planes=nplanes, term_anion=term_anion,
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tetra_down=tetra_down)
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except AssertionError:
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continue
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cluster.absorber = get_atom_index(cluster, 0, 0, 0)
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cluster.info.update({'emitter_plane': emitter_plane,
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'emitter_tag': emitter_tag,
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'emitter': emitter,
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'side': side,
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'level': level,
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'ke': ke})
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clusters.append(cluster)
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return clusters
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def compute_polar_scans(clusters, theta=np.arange(-20., 80., 1.), phi=0., data=DATA):
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for ic, cluster in enumerate(clusters):
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# select the spectroscopy of the calculation and create a new folder for each calculation
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side, emitter, tag, plane, level, ke = [cluster.info[k] for k in ('side', 'emitter', 'emitter_tag',
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'emitter_plane', 'level', 'ke')]
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calc = MSSPEC(spectroscopy='PED', folder='calc{:0>3d}_S{}_E{}_T{:d}_P{:d}'.format(ic, side, emitter, tag,
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plane))
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calc.calculation_parameters.scattering_order = max(1, min(4, plane))
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calc.source_parameters.energy = XRaySource.AL_KALPHA
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calc.source_parameters.theta = -35
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calc.detector_parameters.angular_acceptance = 4.
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calc.detector_parameters.average_sampling = 'medium'
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calc.calculation_parameters.path_filtering = 'forward_scattering'
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calc.calculation_parameters.off_cone_events = 1
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[a.set('forward_angle', 30.) for a in cluster]
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calc.calculation_parameters.vibrational_damping = 'averaged_tl'
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[a.set('mean_square_vibration', 0.006) for a in cluster]
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calc.set_atoms(cluster)
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data = calc.get_theta_scan(level=level, theta=theta, phi=phi, kinetic_energy=ke, data=data)
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dset = data[-1]
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dset.title = 'Polar scan {emitter:s}({level:s} tag {tag:d}) in plane #{plane:d}'.format(emitter=emitter,
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level=level, tag=tag,
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plane=plane)
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for name, value in cluster.info.items():
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dset.add_parameter(group='AlnTuto', name=name, value=str(value), unit="")
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#data.save('all_polar_scans.hdf5', append=True)
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data.save('all_polar_scans.hdf5')
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def analysis(filename='all_polar_scans.hdf5'):
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data=Data.load(filename)
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# create datasets to store the sum of all emitter
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tmp_data = {}
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for dset in data:
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# retrieve some info
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side = dset.get_parameter(group='AlnTuto', name='side')['value']
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emitter = dset.get_parameter(group='AlnTuto', name='emitter')['value']
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try:
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key = '{}_{}'.format(side, emitter)
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tmp_data[key] += dset.cross_section
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except KeyError:
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tmp_data[key] = dset.cross_section.copy()
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# get the index of theta = 0;
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it0 = np.where(dset.theta == 0)[0][0]
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for key, cs in tmp_data.items():
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tmp_data[key + '_norm'] = cs / cs[it0]
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tmp_data['Al_side'] = tmp_data['Al_Al_norm'] / tmp_data['Al_N_norm']
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tmp_data['N_side'] = tmp_data['N_Al_norm'] / tmp_data['N_N_norm']
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# now add all columns
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substrate_dset = data.add_dset('Total substrate signal')
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substrate_dset.add_columns(theta=dset.theta.copy())
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substrate_dset.add_columns(**tmp_data)
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view = substrate_dset.add_view('Al side',
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title=r'AlN Polar scan in the (10$\bar{1}$0) azimuthal plane - Al side polarity',
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xlabel=r'$\Theta (\degree$)',
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ylabel='Signal (a.u.)')
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view.select('theta', 'Al_Al_norm', legend='Al 2p')
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view.select('theta', 'Al_N_norm', legend='N 1s')
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view.set_plot_options(autoscale=True)
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view = substrate_dset.add_view('N side',
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title=r'AlN Polar scan in the (10$\bar{1}$0) azimuthal plane - N side polarity',
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xlabel=r'$\Theta (\degree$)',
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ylabel='Signal (a.u.)')
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view.select('theta', 'N_Al_norm', legend='Al 2p')
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view.select('theta', 'N_N_norm', legend='N 1s')
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view.set_plot_options(autoscale=True)
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view = substrate_dset.add_view('Ratios',
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title=r'Al(2p)/N(1s) ratios on both polar sides of AlN in the (10$\bar{1}$0) '
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r'azimuthal plane',
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xlabel=r'$\Theta (\degree$)',
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ylabel='Intenisty ratio')
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view.select('theta', 'Al_side', legend='Al side', where="theta >= 0 and theta <=70")
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view.select('theta', 'N_side', legend='N side', where="theta >= 0 and theta <=70")
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view.set_plot_options(autoscale=True)
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data.save('analysis.hdf5')
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data.view()
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DIAMETER = 10
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PLANES = 4
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clusters = create_clusters(side='Al', emitter='Al', diameter=DIAMETER, planes=PLANES) + \
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create_clusters(side='Al', emitter='N', diameter=DIAMETER, planes=PLANES) + \
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create_clusters(side='N', emitter='Al', diameter=DIAMETER, planes=PLANES) + \
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create_clusters(side='N', emitter='N', diameter=DIAMETER, planes=PLANES)
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compute_polar_scans(clusters, phi=0.)
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analysis()
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