def test_element_dictionary(self):
newlist = ['O', 'Rb', 'W']
dictionary = smact.element_dictionary(newlist)
self.assertEqual(dictionary['O'].crustal_abundance, 461000.0)
self.assertEqual(dictionary['Rb'].oxidation_states, [-1, 1])
self.assertEqual(dictionary['W'].name, 'Tungsten')
self.assertTrue('Rn' in smact.element_dictionary())
def test_element_dictionary(self):
newlist = ['O', 'Rb', 'W']
dictionary = smact.element_dictionary(newlist)
self.assertEqual(dictionary['O'].crustal_abundance, 461000.0)
self.assertEqual(dictionary['Rb'].oxidation_states, [-1, 1])
self.assertEqual(dictionary['W'].name, 'Tungsten')
self.assertTrue('Rn' in smact.element_dictionary())
def band_gap_Harrison(anion,
cation,
verbose=False,
distance=None,
elements_dict=None):
"""
Estimates the band gap from elemental data.
The band gap is estimated using the principles outlined in
Harrison's 1980 work "Electronic Structure and the Properties of
Solids: The Physics of the Chemical Bond".
Args:
Anion (str): Element symbol of the dominant anion in the system.
Cation (str): Element symbol of the the dominant cation in the system.
Distance (float or str): Nuclear separation between anion and cation
i.e. sum of ionic radii.
verbose: An optional True/False flag. If True, additional information
is printed to the standard output. [Defult: False]
elements_dict (dict): Element symbol keys with smact.Element
objects values. This may be provided to prevent
excessive reading of data files.
Returns (float): Band gap in eV.
"""
# Set constants
hbarsq_over_m = 7.62
# Get anion and cation
An = anion
Cat = cation
d = float(distance)
# Get elemental data:
elements_dict = smact.element_dictionary((An, Cat))
An, Cat = elements_dict[An], elements_dict[Cat]
# Calculate values of equation components
V1_Cat = old_div((Cat.eig - Cat.eig_s), 4)
V1_An = old_div((An.eig - An.eig_s), 4)
V1_bar = old_div((V1_An + V1_Cat), 2)
V2 = 2.16 * hbarsq_over_m / (d**2)
V3 = old_div((Cat.eig - An.eig), 2)
alpha_m = old_div((1.11 * V1_bar), sqrt(V2**2 + V3**2))
# Calculate Band gap [(3-43) Harrison 1980 ]
Band_gap = (old_div(3.60, 3)) * (sqrt(V2**2 + V3**2)) * (1 - alpha_m)
if verbose:
print("V1_bar = ", V1_bar)
print("V2 = ", V2)
print("alpha_m = ", alpha_m)
print("V3 = ", V3)
return Band_gap
def band_gap_Harrison(anion, cation, verbose=False,
distance=None):
"""
Estimates the band gap from elemental data.
The band gap is estimated using the principles outlined in
Harrison's 1980 work "Electronic Structure and the Properties of
Solids: The Physics of the Chemical Bond".
Args:
Anion (str): Element symbol of the dominant anion in the system
Cation (str): Element symbol of the the dominant cation in the system
Distance (float or str): Nuclear separation between anion and cation
i.e. sum of ionic radii
verbose (bool) : An optional True/False flag. If True, additional
information is printed to the standard output. [Defult: False]
Returns :
Band_gap (float): Band gap in eV
"""
# Set constants
hbarsq_over_m = 7.62
# Get anion and cation
An = anion
Cat = cation
d = float(distance)
# Get elemental data:
elements_dict = smact.element_dictionary((An, Cat))
An, Cat = elements_dict[An], elements_dict[Cat]
# Calculate values of equation components
V1_Cat = (Cat.eig - Cat.eig_s)/4
V1_An = (An.eig - An.eig_s)/4
V1_bar = (V1_An + V1_Cat)/2
V2 = 2.16 * hbarsq_over_m / (d**2)
V3 = (Cat.eig - An.eig)/2
alpha_m = (1.11*V1_bar)/sqrt(V2**2 + V3**2)
# Calculate Band gap [(3-43) Harrison 1980 ]
Band_gap = (3.60/3.)*(sqrt(V2**2 + V3**2))*(1-alpha_m)
if verbose:
print("V1_bar = ", V1_bar)
print("V2 = ", V2)
print("alpha_m = ", alpha_m)
print("V3 = ", V3)
return Band_gap
def band_gap_Harrison(anion, cation, verbose=False, distance=None):
"""
Estimates the band gap from elemental data.
The band gap is estimated using the principles outlined in
Harrison's 1980 work "Electronic Structure and the Properties of
Solids: The Physics of the Chemical Bond".
Args:
Anion (str): Element symbol of the dominant anion in the system
Cation (str): Element symbol of the the dominant cation in the system
Distance (float or str): Nuclear separation between anion and cation
i.e. sum of ionic radii
verbose (bool) : An optional True/False flag. If True, additional
information is printed to the standard output. [Defult: False]
Returns :
Band_gap (float): Band gap in eV
"""
# Set constants
hbarsq_over_m = 7.62
# Get anion and cation
An = anion
Cat = cation
d = float(distance)
# Get elemental data:
elements_dict = smact.element_dictionary((An, Cat))
An, Cat = elements_dict[An], elements_dict[Cat]
# Calculate values of equation components
V1_Cat = (Cat.eig - Cat.eig_s) / 4
V1_An = (An.eig - An.eig_s) / 4
V1_bar = (V1_An + V1_Cat) / 2
V2 = 2.16 * hbarsq_over_m / (d**2)
V3 = (Cat.eig - An.eig) / 2
alpha_m = (1.11 * V1_bar) / sqrt(V2**2 + V3**2)
# Calculate Band gap [(3-43) Harrison 1980 ]
Band_gap = (3.60 / 3.) * (sqrt(V2**2 + V3**2)) * (1 - alpha_m)
if verbose:
print("V1_bar = ", V1_bar)
print("V2 = ", V2)
print("alpha_m = ", alpha_m)
print("V3 = ", V3)
return Band_gap
#! /usr/bin/env python
import time
import smact
import itertools
from sys import stdout
from smact.screening import eneg_states_test
from multiprocessing import Pool
element_list = smact.ordered_elements(1, 103)
elements = smact.element_dictionary(element_list)
max_n = 4
neutral_stoichiometries_threshold = 8
include_pauling_test = True
pauling_test_threshold = 0.0
# Number of times to report progress during the counting loop.
count_progress_interval = 100
# Parameters for the threaded version of the code.
mp_use = True
mp_processes = 4
mp_chunk_size = 10
def print_status(text):
"Refresh progress meter on one line"
stdout.write(text + '\r')
#! /usr/bin/env python
import time
import smact
import itertools
from sys import stdout
from smact.screening import eneg_states_test
from multiprocessing import Pool
element_list = smact.ordered_elements(1, 103)
elements = smact.element_dictionary(element_list)
max_n = 4
neutral_stoichiometries_threshold = 8
include_pauling_test = True
pauling_test_threshold = 0.0
# Number of times to report progress during the counting loop.
count_progress_interval = 100
# Parameters for the threaded version of the code.
mp_use = True
mp_processes = 4
mp_chunk_size = 10
def print_status(text):
"Refresh progress meter on one line"
stdout.write(text + '\r')
### Use SMACT to generate a list of sensible chemical compositions ### ### and save in some useful format. ### # Imports from smact.screening import smact_test from smact import Element, element_dictionary import itertools import multiprocessing from functools import partial from pymatgen import Composition from datetime import datetime import pickle # Get a dictionary of all Element objects keyed by symbol all_el = element_dictionary() all_symbols = [k for k, i in all_el.items()] ### === Set up parameters here === ### # Either enter symbols manually as str, or use the element dictionary # that has been imported if there are lots. symbols = all_symbols[:20] symbols_to_ignore = ['O'] symbols = [x for x in symbols if x not in symbols_to_ignore] # Enter elements that must be in every compound, e.g. ['O'] if you # are only interested in oxides. Else leave as None or remove. # These elements should also appear in symbols_to_ignore above. always_include = ['O'] # Set stoichiometry threshold threshold = 4
def compound_electroneg(verbose=False, elements=None, stoichs=None,
elements_dict=None, source='Mulliken'):
"""Estimate electronegativity of compound from elemental data.
Uses Mulliken electronegativity by default, which uses elemental
ionisation potentials and electron affinities. Alternatively, can
use Pauling electronegativity, re-scaled by factor 2.86 to achieve
same scale as Mulliken method (Nethercot, 1974)
DOI:10.1103/PhysRevLett.33.1088 .
Geometric mean is used (n-th root of product of components), e.g.:
X_Cu2S = (X_Cu * X_Cu * C_S)^(1/3)
Args:
elements: A list of elements given as standard elemental symbols.
Optional: if not used, interactive input of space separated
elemental symbols will be offered.
stoichs: A list of stoichiometries, given as integers or floats.
Optional: if not used, interactive input of space separated
integers will be offered.
verbose: An optional True/False flag. If True, additional information
is printed to the standard output. [Default: False]
elements_dict: Dictionary of smact.Element objects; can be provided to
prevent multiple reads of data files
source: String 'Mulliken' or 'Pauling'; type of Electronegativity to
use. Note that in SMACT, Pauling electronegativities are
rescaled to a Mulliken-like scale.
Returns:
Electronegativity: Estimated electronegativity as a float.
Electronegativity is a dimensionless property.
Raises:
(There are no special error messages for this function.)
"""
if elements:
elementlist = elements
if stoichs:
stoichslist = stoichs
# Get elements and stoichiometries if not provided as argument
if not elements:
elementlist = list(raw_input(
"Enter elements (space separated): ").split(" "))
if not stoichs:
stoichslist = list(raw_input(
"Enter stoichiometries (space separated): ").split(" "))
if not elements_dict:
elements_dict = smact.element_dictionary(elements)
# Convert stoichslist from string to float
stoichslist = map(float, stoichslist)
# Get electronegativity values for each element
if source == 'Mulliken':
elementlist = [get_mulliken(elements_dict[el])
for el in elementlist]
elif source == 'Pauling':
elementlist = [2.86 * get_pauling(elements_dict[el])
for el in elementlist]
else:
raise Exception("Electronegativity type '{0}'".format(source),
"is not recognised")
# Print optional list of element electronegativities.
# This may be a useful sanity check in case of a suspicious result.
if verbose:
print "Electronegativities of elements=", elementlist
# Raise each electronegativity to its appropriate power
# to account for stoichiometry.
for i in range(0, len(elementlist)):
elementlist[i] = [elementlist[i]**stoichslist[i]]
# Calculate geometric mean (n-th root of product)
prod = product(elementlist)
compelectroneg = (prod)**(1.0/(sum(stoichslist)))
if verbose:
print "Geometric mean = Compound 'electronegativity'=", compelectroneg
return compelectroneg
def band_gap_Harrison(verbose=False, anion=None, cation=None,
distance=None, elements_dict=None):
"""
Estimates the band gap from elemental data.
The band gap is estimated using the principles outlined in
Harrison's 1980 work "Electronic Structure and the Properties of
Solids: The Physics of the Chemical Bond".
Args:
Anion (str): Element symbol of the dominant anion in the system.
Cation (str): Element symbol of the the dominant cation in the system.
Distance (float or str): Nuclear separation between anion and cation
i.e. sum of ionic radii.
verbose: An optional True/False flag. If True, additional information
is printed to the standard output. [Defult: False]
elements_dict (dict): Element symbol keys with smact.Element
objects values. This may be provided to prevent
excessive reading of data files.
Returns (float): Band gap in eV.
"""
# Set constants
hbarsq_over_m = 7.62
# Get anion and cation
if anion:
An = anion
if cation:
Cat = cation
if not anion:
An = raw_input("Enter Anion Symbol:")
if not cation:
Cat = raw_input("Enter Cation Symbol:")
if distance:
d = float(distance)
if not distance:
d = float(raw_input("Enter internuclear separation (Angstroms): "))
# Get elemental data:
if not elements_dict:
elements_dict = smact.element_dictionary((An, Cat))
An, Cat = elements_dict[An], elements_dict[Cat]
# Calculate values of equation components
V1_Cat = (Cat.eig - Cat.eig_s)/4
V1_An = (An.eig - An.eig_s)/4
V1_bar = (V1_An + V1_Cat)/2
V2 = 2.16 * hbarsq_over_m / (d**2)
V3 = (Cat.eig - An.eig)/2
alpha_m = (1.11*V1_bar)/sqrt(V2**2 + V3**2)
# Calculate Band gap [(3-43) Harrison 1980 ]
Band_gap = (3.60/3)*(sqrt(V2**2 + V3**2))*(1-alpha_m)
if verbose:
print "V1_bar = ", V1_bar
print "V2 = ", V2
print "alpha_m = ", alpha_m
print "V3 = ", V3
return Band_gap
