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pymatgen.electronic_structure.boltztrap2 module

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BoltzTraP2 is a python software interpolating band structures and -computing materials properties from dft band structure using Boltzmann -semi-classical transport theory. -This module provides a pymatgen interface to BoltzTraP2. -Some of the code is written following the examples provided in BoltzTraP2

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BoltzTraP2 has been developed by Georg Madsen, Jesús Carrete, Matthieu J. Verstraete.

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https://gitlab.com/sousaw/BoltzTraP2 -https://www.sciencedirect.com/science/article/pii/S0010465518301632

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References are:

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Georg K.H.Madsen, Jesús Carrete, Matthieu J.Verstraete -BoltzTraP2, a program for interpolating band structures and -calculating semi-classical transport coefficients -Computer Physics Communications 231, 140-145, 2018

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Madsen, G. K. H., and Singh, D. J. (2006). -BoltzTraP. A code for calculating band-structure dependent quantities. -Computer Physics Communications, 175, 67-71

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Todo: -- DONE: spin polarized bands -- read first derivative of the eigenvalues from vasprun.xml (mommat) -- handle magnetic moments (magmom)

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-class BandstructureLoader(bs_obj, structure=None, nelect=None, mommat=None, magmom=None)[source]
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Bases: object

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Loader for Bandstructure object

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Parameters:
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  • bs_obj – BandStructure object.

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  • structure – Structure object. It is needed if it is not contained in the BandStructure obj.

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  • nelect – Number of electrons in the calculation.

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  • mommat – Matrix of derivatives of energy eigenvalues. TODO Not implemented yet.

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  • magmom – Matrix of magnetic moments in non collinear calculations. Not implemented yet.

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Example

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vrun = Vasprun(‘vasprun.xml’) -bs = vrun.get_band_structure() -st = vrun.final_structure -ne = vrun.parameters[‘NELECT’] -data = BandstructureLoader(bs,st,ne)

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-bandana(emin=-inf, emax=inf)[source]
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Cut out bands outside the range (emin,emax)

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-get_lattvec()[source]
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Returns:
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The lattice vectors.

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-get_volume()[source]
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Returns:
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Volume

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-set_upper_lower_bands(e_lower, e_upper)[source]
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Set fake upper/lower bands, useful to set the same energy -range in the spin up/down bands when calculating the DOS

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-class BztInterpolator(data, lpfac=10, energy_range=1.5, curvature=True, save_bztInterp=False, load_bztInterp=False, save_bands=False, fname='bztInterp.json.gz')[source]
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Bases: object

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Interpolate the dft band structures

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Parameters:
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  • data – A loader

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  • lpfac – the number of interpolation points in the real space. By -default 10 gives 10 time more points in the real space than -the number of kpoints given in reciprocal space.

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  • energy_range – usually the interpolation is not needed on the entire energy -range but on a specific range around the fermi level. -This energy in eV fix the range around the fermi level -(E_fermi-energy_range,E_fermi+energy_range) of -bands that will be interpolated -and taken into account to calculate the transport properties.

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  • curvature – boolean value to enable/disable the calculation of second -derivative related transport properties (Hall coefficient).

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  • save_bztInterp – Default False. If True coefficients and equivalences are -saved in fname file.

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  • load_bztInterp – Default False. If True the coefficients and equivalences -are loaded from fname file, not calculated. It can be faster than -re-calculate them in some cases.

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  • save_bands – Default False. If True interpolated bands are also stored. -It can be slower than interpolate them. Not recommended.

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  • fname – File path where to store/load from the coefficients and equivalences.

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Example

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data = VasprunLoader().from_file(‘vasprun.xml’) -bztInterp = BztInterpolator(data)

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-get_band_structure(kpaths=None, kpoints_lbls_dict=None, density=20)[source]
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Return a BandStructureSymmLine object interpolating bands along a -High symmetry path calculated from the structure using HighSymmKpath -function. If kpaths and kpoints_lbls_dict are provided, a custom -path is interpolated. -kpaths: List of lists of following kpoints labels defining

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the segments of the path. E.g. [[‘L’,’M’],[‘L’,’X’]]

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kpoints_lbls_dict: Dict where keys are the kpoint labels used in kpaths

and values are their fractional coordinates. -E.g. {‘L’:np.array(0.5,0.5,0.5)},

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‘M’:np.array(0.5,0.,0.5), -‘X’:np.array(0.5,0.5,0.)}

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density: Number of points in each segment.

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-get_dos(partial_dos=False, npts_mu=10000, T=None, progress=False)[source]
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Return a Dos object interpolating bands

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Parameters:
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  • partial_dos – if True, projections will be interpolated as well -and partial doses will be return. Projections must be available -in the loader.

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  • npts_mu – number of energy points of the Dos

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  • T – parameter used to smooth the Dos

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  • progress – Default False, If True a progress bar is shown when -partial dos are computed.

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-get_partial_doses(tdos, eband_ud, spins, enr, npts_mu, T, progress)[source]
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Return a CompleteDos object interpolating the projections

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tdos: total dos previously calculated -npts_mu: number of energy points of the Dos -T: parameter used to smooth the Dos -progress: Default False, If True a progress bar is shown.

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-load(fname='bztInterp.json.gz')[source]
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Load the coefficient, equivalences, bands from fname

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-save(fname='bztInterp.json.gz', bands=False)[source]
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Save the coefficient, equivalences to fname. -If bands is True, also interpolated bands are stored.

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-class BztPlotter(bzt_transP=None, bzt_interp=None)[source]
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Bases: object

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Plotter to plot transport properties, interpolated bands along some high -symmetry k-path, and DOS.

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Example

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bztPlotter = BztPlotter(bztTransp,bztInterp) -fig = self.bztPlotter.plot_props(‘S’, ‘mu’, ‘temp’, temps=[300, 500]) -fig.show()

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Parameters:
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  • bzt_transP –

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  • bzt_interp –

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-plot_bands()[source]
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Plot a band structure on symmetry line using BSPlotter()

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-plot_dos(T=None, npoints=10000)[source]
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Plot the total Dos using DosPlotter()

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-plot_props(prop_y, prop_x, prop_z='temp', output='avg_eigs', dop_type='n', doping=None, temps=None, xlim=(-2, 2), ax=None)[source]
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Function to plot the transport properties.

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Parameters:
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  • prop_y – property to plot among (“Conductivity”,”Seebeck”,”Kappa”,”Carrier_conc”, -“Hall_carrier_conc_trace”). Abbreviations are possible, like “S” for “Seebeck”

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  • prop_x – independent variable in the x-axis among (‘mu’,’doping’,’temp’)

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  • prop_z – third variable to plot multiple curves (‘doping’,’temp’)

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  • output – ‘avg_eigs’ to plot the average of the eigenvalues of the properties -tensors; ‘eigs’ to plot the three eigenvalues of the properties -tensors.

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  • dop_type – ‘n’ or ‘p’ to specify the doping type in plots that use doping -levels as prop_x or prop_z

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  • doping – list of doping level to plot, useful to reduce the number of curves -when prop_z=’doping’

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  • temps – list of temperatures to plot, useful to reduce the number of curves -when prop_z=’temp’

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  • xlim – chemical potential range in eV, useful when prop_x=’mu’

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  • ax – figure.axes where to plot. If None, a new figure is produced.

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Example: -bztPlotter.plot_props(‘S’,’mu’,’temp’,temps=[600,900,1200]).show() -more example are provided in the notebook -“How to use Boltztra2 interface.ipynb”.

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-class BztTransportProperties(BztInterpolator, temp_r=None, doping=None, npts_mu=4000, CRTA=1e-14, margin=None, save_bztTranspProps=False, load_bztTranspProps=False, fname='bztTranspProps.json.gz')[source]
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Bases: object

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Compute Seebeck, Conductivity, Electrical part of thermal conductivity -and Hall coefficient, conductivity effective mass, Power Factor tensors -w.r.t. the chemical potential and temperatures, from dft band structure via -interpolation.

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Parameters:
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  • BztInterpolator – a BztInterpolator previously generated

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  • temp_r – numpy array of temperatures at which to calculate transport properties

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  • doping – doping levels at which to calculate transport properties. If provided, -transport properties w.r.t. these doping levels are also computed. See -compute_properties_doping() method for details.

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  • npts_mu – number of energy points at which to calculate transport properties

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  • CRTA – constant value of the relaxation time

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  • margin – The energy range of the interpolation is extended by this value on both sides. -Defaults to 9 * units.BOLTZMANN * temp_r.max().

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  • save_bztTranspProps – Default False. If True all computed transport properties -will be stored in fname file.

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  • load_bztTranspProps – Default False. If True all computed transport properties -will be loaded from fname file.

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  • fname – File path where to save/load transport properties.

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Upon creation, it contains properties tensors w.r.t. the chemical potential -of size (len(temp_r),npts_mu,3,3):

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Conductivity_mu (S/m), Seebeck_mu (microV/K), Kappa_mu (W/(m*K)), -Power_Factor_mu (milliW/K m); -cond_Effective_mass_mu (m_e) calculated as Ref.

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Also:

Carrier_conc_mu: carrier concentration of size (len(temp_r),npts_mu) -Hall_carrier_conc_trace_mu: trace of Hall carrier concentration of size

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(len(temp_r),npts_mu)

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mu_r_eV: array of energies in eV and with E_fermi at 0.0

where all the properties are calculated.

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Example

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bztTransp = BztTransportProperties(bztInterp,temp_r = np.arange(100,1400,100))

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-compute_properties_doping(doping, temp_r=None)[source]
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Calculate all the properties w.r.t. the doping levels in input.

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Parameters:
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  • doping – numpy array specifying the doping levels

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  • temp_r – numpy array specifying the temperatures

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When executed, it add the following variable at the BztTransportProperties -object:

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Conductivity_doping, Seebeck_doping, Kappa_doping, Power_Factor_doping, -cond_Effective_mass_doping are dictionaries with ‘n’ and ‘p’ keys and -arrays of dim (len(temp_r),len(doping),3,3) as values. -Carriers_conc_doping: carriers concentration for each doping level and T. -mu_doping_eV: the chemical potential corrispondent to each doping level.

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-load(fname='bztTranspProps.json.gz')[source]
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Load the transport properties from fname file.

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-save(fname='bztTranspProps.json.gz')[source]
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Save the transport properties to fname file.

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-class VasprunBSLoader(obj, structure=None, nelect=None)[source]
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Bases: object

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Loader for Bandstructure and Vasprun pmg objects

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Parameters:
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  • obj – Either a pmg Vasprun or a BandStructure object.

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  • structure – Structure object in case is not included in the BandStructure object.

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  • nelect – number of electrons in case a BandStructure obj is provided.

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Example

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vrun = Vasprun(‘vasprun.xml’) -data = VasprunBSLoader(vrun)

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-bandana(emin=-inf, emax=inf)[source]
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Cut out bands outside the range (emin,emax)

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-classmethod from_file(vasprun_file)[source]
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Get a vasprun.xml file and return a VasprunBSLoader

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-get_lattvec()[source]
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Returns:
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The lattice vectors.

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-get_volume()[source]
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Returns:
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Volume

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-class VasprunLoader(vrun_obj=None)[source]
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Bases: object

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Loader for Vasprun object

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vrun_obj: Vasprun object.

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-bandana(emin=-inf, emax=inf)[source]
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Cut out bands outside the range (emin,emax)

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-classmethod from_file(vasprun_file)[source]
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Get a vasprun.xml file and return a VasprunLoader

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-get_lattvec()[source]
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Returns:
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Lattice vectors

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-get_volume()[source]
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Returns:
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Volume of cell

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-merge_up_down_doses(dos_up, dos_dn)[source]
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Merge the up and down DOSs.

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Args: -dos_up: Up DOS. -dos_dn: Down DOS -Return: -CompleteDos object

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pymatgen.electronic_structure.boltztrap2 module

diff --git a/docs/pymatgen.electronic_structure.cohp.html b/docs/pymatgen.electronic_structure.cohp.html index 8beb3ed1f6f..ed76278855b 100644 --- a/docs/pymatgen.electronic_structure.cohp.html +++ b/docs/pymatgen.electronic_structure.cohp.html @@ -36,14 +36,18 @@