def __init__(self):
formula = 'FeO'
formula = dictionarize_formula(formula)
self.params = {
'name': 'Wuestite',
'formula': formula,
'equation_of_state': 'slb3',
'F_0': -242000.0,
'V_0': 1.226e-05,
'K_0': 1.79e+11,
'Kprime_0': 4.9,
'Debye_0': 454.0,
'grueneisen_0': 1.53,
'q_0': 1.7,
'G_0': 59000000000.0,
'Gprime_0': 1.4,
'eta_s_0': -0.1,
'n': sum(formula.values()),
'molar_mass': formula_mass(formula, atomic_masses)}
self.property_modifiers = [
['linear', {'delta_E': 0., 'delta_S': 12., 'delta_V': 0.}]]
self.uncertainties = {
'err_F_0': 1000.0,
'err_V_0': 0.0,
'err_K_0': 1000000000.0,
'err_K_prime_0': 0.2,
'err_Debye_0': 21.0,
'err_grueneisen_0': 0.13,
'err_q_0': 1.0,
'err_G_0': 1000000000.0,
'err_Gprime_0': 0.1,
'err_eta_s_0': 1.0}
burnman.Mineral.__init__(self)
def __init__(self):
formula = 'Fe1.0S1.0'
formula = dictionarize_formula(formula)
self.params = {
'name': 'lot',
'formula': formula,
'equation_of_state': 'hp_tmt',
'H_0': -102160.0,
'S_0': 60.0,
'V_0': 1.818e-05,
'Cp': [50.2, 0.011052, -940000.0, 0.0],
'a_0': 4.93e-05,
'K_0': 65800000000.0,
'Kprime_0': 4.17,
'Kdprime_0': -6.3e-11,
'n': sum(formula.values()),
'molar_mass': formula_mass(formula, atomic_masses)}
self.property_modifiers = [
['landau_hp', {'P_0': 100000.0,
'T_0': 298.15,
'Tc_0': 420.0,
'S_D': 10.0,
'V_D': 0.0}],
['landau_hp', {'P_0': 100000.0,
'T_0': 298.15,
'Tc_0': 598.0,
'S_D': 12.0,
'V_D': 4.1e-7}]]
burnman.Mineral.__init__(self)
def __init__(self):
formula = 'Fe1.0S1.0'
formula = dictionarize_formula(formula)
self.params = {
'name': 'lot',
'formula': formula,
'equation_of_state': 'hp_tmt',
'H_0': -102160.0,
'S_0': 60.0,
'V_0': 1.818e-05,
'Cp': [50.2, 0.011052, -940000.0, 0.0],
'a_0': 4.93e-05,
'K_0': 65800000000.0,
'Kprime_0': 4.17,
'Kdprime_0': -6.3e-11,
'n': sum(formula.values()),
'molar_mass': formula_mass(formula)}
self.property_modifiers = [
['landau_hp', {'P_0': 100000.0,
'T_0': 298.15,
'Tc_0': 420.0,
'S_D': 10.0,
'V_D': 0.0}],
['landau_hp', {'P_0': 100000.0,
'T_0': 298.15,
'Tc_0': 598.0,
'S_D': 12.0,
'V_D': 4.1e-7}]]
burnman.Mineral.__init__(self)
def __init__(self, name, atoms, formula, sites, comp, H, S, V, Cp, a, k, flag, od):
if flag != -1 and flag != -2 and k[0] > 0:
formula = dictionarize_formula(formula)
self.params = OrderedDict([('name', name),
('formula', formula),
('equation_of_state', 'hp_tmt'),
('H_0', round(H * 1e3, 10)),
('S_0', round(S * 1e3, 10)),
('V_0', round(V * 1e-5, 15)),
('Cp', [round(Cp[0] * 1e3, 10),
round(Cp[1] * 1e3, 10),
round(Cp[2] * 1e3, 10),
round(Cp[3] * 1e3, 10)]),
('a_0', a),
('K_0', round(k[0] * 1e8, 10)),
('Kprime_0', k[1]),
('Kdprime_0', round(k[2] * 1e-8, 15)),
('n', sum(formula.values())),
('molar_mass', round(formula_mass(formula), 10))])
if flag == 1:
self.landau_hp = OrderedDict([('P_0', 1e5),
('T_0', 298.15),
('Tc_0', od[0]),
('S_D', round(od[1] * 1e3, 10)),
('V_D', round(od[2] * 1e-5, 10))])
if flag == 2:
self.bragg_williams = OrderedDict([('deltaH', round(od[0] * 1e3, 10)),
('deltaV', round(od[1] * 1e-5, 15)),
('Wh', round(od[2] * 1e3, 10)),
('Wv', round(od[3] * 1e-5, 15)),
('n', od[4]),
('factor', od[5])])
def __init__(self):
formula = 'FeO'
formula = dictionarize_formula(formula)
self.params = {
'name': 'Wuestite',
'formula': formula,
'equation_of_state': 'slb3',
'F_0': -242000.0,
'V_0': 1.226e-05,
'K_0': 1.79e+11,
'Kprime_0': 4.9,
'Debye_0': 454.0,
'grueneisen_0': 1.53,
'q_0': 1.7,
'G_0': 59000000000.0,
'Gprime_0': 1.4,
'eta_s_0': -0.1,
'n': sum(formula.values()),
'molar_mass': formula_mass(formula)}
self.property_modifiers = [
['linear', {'delta_E': 0., 'delta_S': 12., 'delta_V': 0.}]]
self.uncertainties = {
'err_F_0': 1000.0,
'err_V_0': 0.0,
'err_K_0': 1000000000.0,
'err_K_prime_0': 0.2,
'err_Debye_0': 21.0,
'err_grueneisen_0': 0.13,
'err_q_0': 1.0,
'err_G_0': 1000000000.0,
'err_Gprime_0': 0.1,
'err_eta_s_0': 1.0}
burnman.Mineral.__init__(self)
def __init__(self):
formula='H2'
formula = dictionarize_formula(formula)
self.params = {
'name': 'hydrogen gas',
'formula': formula,
'equation_of_state': 'cork',
'cork_params': [[5.45963e1,-8.63920e0], [9.18301e-1], [-3.30558e-2,2.30524e-3], [6.93054e-4,-8.38293e-5]],
'cork_T': 41.2,
'cork_P': 0.0211e8,
'H_0': 0.,
'S_0': 130.7,
'Cp': [23.3, 0.004627, 0.0, 76.3]}
Mineral.__init__(self)
def __init__(self):
formula='S2'
formula = dictionarize_formula(formula)
self.params = {
'name': 'sulfur gas',
'formula': formula,
'equation_of_state': 'cork',
'cork_params': [[5.45963e1,-8.63920e0], [9.18301e-1], [-3.30558e-2,2.30524e-3], [6.93054e-4,-8.38293e-5]],
'cork_T': 1314.00,
'cork_P': 0.21000e8,
'H_0': 128.54e3,
'S_0': 231.0,
'Cp': [37.1, 0.002398, -161000.0, -65.0]}
Mineral.__init__(self)
def __init__(self):
formula='H2S'
formula = dictionarize_formula(formula)
self.params = {
'name': 'hydrogen sulfide',
'formula': formula,
'equation_of_state': 'cork',
'cork_params': [[5.45963e1,-8.63920e0], [9.18301e-1], [-3.30558e-2,2.30524e-3], [6.93054e-4,-8.38293e-5]],
'cork_T': 373.15,
'cork_P': 0.08937e8,
'H_0': 128.54e3,
'S_0': 231.0,
'Cp': [47.4, 0.010240, 615900., -397.8]}
Mineral.__init__(self)
def __init__(self):
formula='O2'
formula = dictionarize_formula(formula)
self.params = {
'name': 'oxygen gas',
'formula': formula,
'equation_of_state': 'cork',
'cork_params': [[5.45963e1,-8.63920e0], [9.18301e-1], [-3.30558e-2,2.30524e-3], [6.93054e-4,-8.38293e-5]],
'cork_T': 0.,
'cork_P': 1.0e5,
'H_0': 0.,
'S_0': 205.2,
'Cp': [48.3, -0.000691, 499200., -420.7]}
Mineral.__init__(self)
def __init__(self):
formula='CO2'
formula = dictionarize_formula(formula)
self.params = {
'name': 'carbon dioxide',
'formula': formula,
'equation_of_state': 'cork',
'cork_params': [[5.45963e1,-8.63920e0], [9.18301e-1], [-3.30558e-2,2.30524e-3], [6.93054e-4,-8.38293e-5]],
'cork_T': 304.2,
'cork_P': 0.0738e8,
'H_0': -393.51e3,
'S_0': 213.7,
'Cp': [87.8, -2.644e-3, 706.4e3, -998.9]}
Mineral.__init__(self)
def __init__(self):
formula='CH4'
formula = dictionarize_formula(formula)
self.params = {
'name': 'methane',
'formula': formula,
'equation_of_state': 'cork',
'cork_params': [[5.45963e1,-8.63920e0], [9.18301e-1], [-3.30558e-2,2.30524e-3], [6.93054e-4,-8.38293e-5]],
'cork_T': 190.6,
'cork_P': 0.0460e8,
'H_0': -74.81e3,
'S_0': 186.26,
'Cp': [150.1, 0.002063, 3427700., -2650.4]}
Mineral.__init__(self)
def __init__(self):
formula = 'Re1.0O2.0'
formula = processchemistry.dictionarize_formula(formula)
self.params = {
'name': 'ReO2',
'formula': formula,
'equation_of_state': 'hp_tmt',
'H_0': -445140.0,
'S_0': 47.82,
'V_0': 1.8779e-05,
'Cp': [76.89, 0.00993, -1207130.0, -208.0],
'a_0': 4.4e-05,
'K_0': 1.8e+11,
'Kprime_0': 4.05,
'Kdprime_0': -2.25e-11,
'n': sum(formula.values()),
'molar_mass': processchemistry.formula_mass(formula)}
burnman.Mineral.__init__(self)
def __init__(self):
formula = 'Re1.0'
formula = processchemistry.dictionarize_formula(formula)
self.params = {
'name': 'Re',
'formula': formula,
'equation_of_state': 'hp_tmt',
'H_0': 0.0,
'S_0': 36.53,
'V_0': 8.862e-06,
'Cp': [23.7, 0.005448, 68.0, 0.0],
'a_0': 1.9e-05,
'K_0': 3.6e+11,
'Kprime_0': 4.05,
'Kdprime_0': -1.1e-11,
'n': sum(formula.values()),
'molar_mass': processchemistry.formula_mass(formula)}
burnman.Mineral.__init__(self)
def __init__(self):
formula = 'Re1.0'
formula = processchemistry.dictionarize_formula(formula)
self.params = {
'name': 'Re',
'formula': formula,
'equation_of_state': 'hp_tmt',
'H_0': 0.0,
'S_0': 36.53,
'V_0': 8.862e-06,
'Cp': [23.7, 0.005448, 68.0, 0.0],
'a_0': 1.9e-05,
'K_0': 3.6e+11,
'Kprime_0': 4.05,
'Kdprime_0': -1.1e-11,
'n': sum(formula.values()),
'molar_mass': processchemistry.formula_mass(formula)
}
burnman.Mineral.__init__(self)
def __init__(self):
formula = 'Re1.0O2.0'
formula = processchemistry.dictionarize_formula(formula)
self.params = {
'name': 'ReO2',
'formula': formula,
'equation_of_state': 'hp_tmt',
'H_0': -445140.0,
'S_0': 47.82,
'V_0': 1.8779e-05,
'Cp': [76.89, 0.00993, -1207130.0, -208.0],
'a_0': 4.4e-05,
'K_0': 1.8e+11,
'Kprime_0': 4.05,
'Kdprime_0': -2.25e-11,
'n': sum(formula.values()),
'molar_mass': processchemistry.formula_mass(formula)
}
burnman.Mineral.__init__(self)
def __init__(self):
formula='Mg3Al6O12'
formula = dictionarize_formula(formula)
self.params = {
'name': 'manal',
'formula': formula,
'equation_of_state': 'hp_tmt',
'H_0': -6796630.0 ,
'S_0': 250.0 ,
'V_0': 0.00011166 ,
'Cp': [600.0, 0.018756, -8989200.0, -2665.2] ,
'a_0': 1.93e-05 ,
'K_0': 1.84e+11 ,
'Kprime_0': 4.0 ,
'Kdprime_0': -2.2e-11 ,
'n': sum(formula.values()),
'molar_mass': formula_mass(formula, atomic_masses)}
self.uncertainties = {
'err_H_0': 5120.0 }
Mineral.__init__(self)
def __init__(self):
formula='SiO2'
formula = dictionarize_formula(formula)
self.params = {
'name': 'stv',
'formula': formula,
'equation_of_state': 'hp_tmt',
'H_0': -876820.0 ,
'S_0': 24.0 ,
'V_0': 1.401e-05 ,
'Cp': [68.1, 0.00601, -1978200.0, -82.1] ,
'a_0': 1.58e-05 ,
'K_0': 3.09e+11 ,
'Kprime_0': 4.6 ,
'Kdprime_0': -1.5e-11 ,
'n': sum(formula.values()),
'molar_mass': formula_mass(formula, atomic_masses)}
self.uncertainties = {
'err_H_0': 420.0 }
Mineral.__init__(self)
def __init__(self):
formula='NaMg2SiAl5O12'
formula = dictionarize_formula(formula)
self.params = {
'name': 'nanal',
'formula': formula,
'equation_of_state': 'hp_tmt',
'H_0': -6610270.0 ,
'S_0': 280.0 ,
'V_0': 0.00011322 ,
'Cp': [672.7, 0.000106, -5992800.0, -4539.9] ,
'a_0': 2.01e-05 ,
'K_0': 1.84e+11 ,
'Kprime_0': 4.0 ,
'Kdprime_0': -2.2e-11 ,
'n': sum(formula.values()),
'molar_mass': formula_mass(formula, atomic_masses)}
self.uncertainties = {
'err_H_0': 5120.0 }
Mineral.__init__(self)
def __init__(self):
formula='Mg2SiO4'
formula = dictionarize_formula(formula)
self.params = {
'name': 'mwd',
'formula': formula,
'equation_of_state': 'hp_tmt',
'H_0': -2138080.0 ,
'S_0': 93.9 ,
'V_0': 4.051e-05 ,
'Cp': [208.7, 0.003942, -1709500.0, -1302.8] ,
'a_0': 2.37e-05 ,
'K_0': 1.726e+11 ,
'Kprime_0': 3.84 ,
'Kdprime_0': -2.2e-11 ,
'n': sum(formula.values()),
'molar_mass': formula_mass(formula, atomic_masses)}
self.uncertainties = {
'err_H_0': 620.0 }
Mineral.__init__(self)
def __init__(self):
formula='MgAl2O4'
formula = dictionarize_formula(formula)
self.params = {
'name': 'macf',
'formula': formula,
'equation_of_state': 'hp_tmt',
'H_0': -2246420.0 ,
'S_0': 80.0 ,
'V_0': 3.614e-05 ,
'Cp': [200.0, 0.006252, -2996400.0, -888.4] ,
'a_0': 1.93e-05 ,
'K_0': 2.12e+11 ,
'Kprime_0': 4.0 ,
'Kdprime_0': -1.7e-11 ,
'n': sum(formula.values()),
'molar_mass': formula_mass(formula, atomic_masses)}
self.uncertainties = {
'err_H_0': 1080.0 }
Mineral.__init__(self)
def __init__(self):
formula='Fe1.0'
formula = dictionarize_formula(formula)
self.params = {
'name': 'BCC iron',
'formula': formula,
'equation_of_state': 'hp_tmt',
'H_0': 9149.0 ,
'S_0': 36.868 ,
'V_0': 7.09e-06 ,
'Cp': [21.09, 0.0101455, -221508., 47.1947] ,
'a_0': 3.56e-05 ,
'K_0': 1.64e+11 ,
'Kprime_0': 5.16 ,
'Kdprime_0': -3.1e-11 ,
'n': sum(formula.values()),
'molar_mass': formula_mass(formula, atomic_masses),
'curie_temperature': [1043., 0.0] ,
'magnetic_moment': [2.22, 0.0] ,
'magnetic_structural_parameter': 0.4 }
Mineral.__init__(self)
def __init__(self):
formula='Fe1.0'
formula = dictionarize_formula(formula)
self.params = {
'name': 'FCC iron',
'formula': formula,
'equation_of_state': 'hp_tmt',
'H_0': 7973.0 ,
'S_0': 35.907 ,
'V_0': 6.93863394593e-06 ,
'Cp': [22.24, 0.0088656, -221517., 47.1998] ,
'a_0': 5.13e-05 ,
'K_0': 1.539e+11 ,
'Kprime_0': 5.2 ,
'Kdprime_0': -3.37e-11 ,
'n': sum(formula.values()),
'molar_mass': formula_mass(formula, atomic_masses),
'curie_temperature': [201., 0.0] ,
'magnetic_moment': [2.1, 0.0] ,
'magnetic_structural_parameter': 0.28 }
Mineral.__init__(self)
def __init__(self):
formula='CaAl2O4'
formula = dictionarize_formula(formula)
self.params = {
'name': 'cacf',
'formula': formula,
'equation_of_state': 'hp_tmt',
'H_0': -2325600.0 ,
'S_0': 87.6 ,
'V_0': 3.976e-05 ,
'Cp': [191.9, 0.009563, -3211300.0, -640.2] ,
'a_0': 1.93e-05 ,
'K_0': 1.9e+11 ,
'Kprime_0': 4.0 ,
'Kdprime_0': -2.1e-11 ,
'n': sum(formula.values()),
'molar_mass': formula_mass(formula, atomic_masses)}
self.uncertainties = {
'err_H_0': 10240.0 }
Mineral.__init__(self)
def __init__(self):
formula='CaMg2Al6O12'
formula = dictionarize_formula(formula)
self.params = {
'name': 'canal',
'formula': formula,
'equation_of_state': 'hp_tmt',
'H_0': -6840000.0 ,
'S_0': 257.6 ,
'V_0': 0.00011159 ,
'Cp': [591.9, 0.022067, -9204100.0, -2417.0] ,
'a_0': 1.93e-05 ,
'K_0': 1.77e+11 ,
'Kprime_0': 4.0 ,
'Kdprime_0': -2.2e-11 ,
'n': sum(formula.values()),
'molar_mass': formula_mass(formula, atomic_masses)}
self.uncertainties = {
'err_H_0': 5120.0 }
Mineral.__init__(self)
def __init__(self):
formula='NaAlSiO6'
formula = dictionarize_formula(formula)
self.params = {
'name': 'nacf',
'formula': formula,
'equation_of_state': 'hp_tmt',
'H_0': -1965550.0 ,
'S_0': 110.0 ,
'V_0': 3.631e-05 ,
'Cp': [272.7, -0.012398, 0.0, -2763.1] ,
'a_0': 2.1e-05 ,
'K_0': 1.85e+11 ,
'Kprime_0': 4.6 ,
'Kdprime_0': -2.5e-11 ,
'n': sum(formula.values()),
'molar_mass': formula_mass(formula, atomic_masses)}
self.uncertainties = {
'err_H_0': 3440.0 }
Mineral.__init__(self)
def __init__(self):
formula='MgMg2Si3Mg3O12'
formula = dictionarize_formula(formula)
self.params = {
'name': 'msnal',
'formula': formula,
'equation_of_state': 'hp_tmt',
'H_0': -6172380.0 ,
'S_0': 272.5 ,
'V_0': 0.00011061 ,
'Cp': [639.9, 0.00807, -4231200.0, -4487.7] ,
'a_0': 2.1e-05 ,
'K_0': 1.85e+11 ,
'Kprime_0': 4.0 ,
'Kdprime_0': -2.2e-11 ,
'n': sum(formula.values()),
'molar_mass': formula_mass(formula, atomic_masses)}
self.uncertainties = {
'err_H_0': 5120.0 }
Mineral.__init__(self)
def __init__(self):
formula='Al2O3'
formula = dictionarize_formula(formula)
self.params = {
'name': 'cor',
'formula': formula,
'equation_of_state': 'hp_tmt',
'H_0': -1675250.0 ,
'S_0': 50.9 ,
'V_0': 2.558e-05 ,
'Cp': [139.5, 0.00589, -2460600.0, -589.2] ,
'a_0': 1.8e-05 ,
'K_0': 2.54e+11 ,
'Kprime_0': 4.34 ,
'Kdprime_0': -1.7e-11 ,
'n': sum(formula.values()),
'molar_mass': formula_mass(formula, atomic_masses)}
self.uncertainties = {
'err_H_0': 700.0 }
Mineral.__init__(self)
def __init__(self):
formula='MgO'
formula = dictionarize_formula(formula)
self.params = {
'name': 'per',
'formula': formula,
'equation_of_state': 'hp_tmt',
'H_0': -601570.0 ,
'S_0': 26.5 ,
'V_0': 1.125e-05 ,
'Cp': [60.5, 0.000362, -535800.0, -299.2] ,
'a_0': 3.11e-05 ,
'K_0': 1.616e+11 ,
'Kprime_0': 3.95 ,
'Kdprime_0': -2.4e-11 ,
'n': sum(formula.values()),
'molar_mass': formula_mass(formula, atomic_masses)}
self.uncertainties = {
'err_H_0': 260.0 }
Mineral.__init__(self)
def __init__(self):
formula='Fe2SiO4'
formula = dictionarize_formula(formula)
self.params = {
'name': 'fwd',
'formula': formula,
'equation_of_state': 'hp_tmt',
'H_0': -1467920.0 ,
'S_0': 146.0 ,
'V_0': 4.321e-05 ,
'Cp': [201.1, 0.01733, -1960600.0, -900.9] ,
'a_0': 2.73e-05 ,
'K_0': 1.69e+11 ,
'Kprime_0': 4.35 ,
'Kdprime_0': -2.6e-11 ,
'n': sum(formula.values()),
'molar_mass': formula_mass(formula, atomic_masses)}
self.uncertainties = {
'err_H_0': 900.0 }
Mineral.__init__(self)
def __init__(self):
formula='Mg2SiO4'
formula = dictionarize_formula(formula)
self.params = {
'name': 'mscf',
'formula': formula,
'equation_of_state': 'hp_tmt',
'H_0': -2061130.0 ,
'S_0': 87.5 ,
'V_0': 3.649e-05 ,
'Cp': [213.3, 0.00269, -1410400.0, -1495.9] ,
'a_0': 2.01e-05 ,
'K_0': 1.85e+11 ,
'Kprime_0': 4.0 ,
'Kdprime_0': -1.7e-11 ,
'n': sum(formula.values()),
'molar_mass': formula_mass(formula, atomic_masses)}
self.uncertainties = {
'err_H_0': 1340.0 }
Mineral.__init__(self)
def __init__(self):
formula='FeFe2Si3Fe3O12'
formula = dictionarize_formula(formula)
self.params = {
'name': 'fsnal',
'formula': formula,
'equation_of_state': 'hp_tmt',
'H_0': -4146000.0 ,
'S_0': 440.2 ,
'V_0': 0.00011856 ,
'Cp': [543.3, 0.055578, -8301600.0, -1581.3] ,
'a_0': 2.1e-05 ,
'K_0': 1.85e+11 ,
'Kprime_0': 4.0 ,
'Kdprime_0': -2.2e-11 ,
'n': sum(formula.values()),
'molar_mass': formula_mass(formula, atomic_masses)}
self.uncertainties = {
'err_H_0': 10240.0 }
Mineral.__init__(self)
def __init__(self):
formula='FeO'
formula = dictionarize_formula(formula)
self.params = {
'name': 'fper',
'formula': formula,
'equation_of_state': 'hp_tmt',
'H_0': -262240.0 ,
'S_0': 58.6 ,
'V_0': 1.206e-05 ,
'Cp': [44.4, 0.00828, -1214200.0, 185.2] ,
'a_0': 3.22e-05 ,
'K_0': 1.52e+11 ,
'Kprime_0': 4.9 ,
'Kdprime_0': -3.2e-11 ,
'n': sum(formula.values()),
'molar_mass': formula_mass(formula, atomic_masses)}
self.uncertainties = {
'err_H_0': 680.0 }
Mineral.__init__(self)
def __init__(self):
formula='Fe2SiO4'
formula = dictionarize_formula(formula)
self.params = {
'name': 'fscf',
'formula': formula,
'equation_of_state': 'hp_tmt',
'H_0': -1405500.0 ,
'S_0': 143.4 ,
'V_0': 3.914e-05 ,
'Cp': [181.1, 0.018526, -2767200.0, -527.1] ,
'a_0': 2.01e-05 ,
'K_0': 1.85e+11 ,
'Kprime_0': 4.0 ,
'Kdprime_0': -1.7e-11 ,
'n': sum(formula.values()),
'molar_mass': formula_mass(formula, atomic_masses)}
self.uncertainties = {
'err_H_0': 10240.0 }
Mineral.__init__(self)
def __init__(self):
formula='MgSiO3'
formula = dictionarize_formula(formula)
self.params = {
'name': 'mcor',
'formula': formula,
'equation_of_state': 'hp_tmt',
'H_0': -1468000.0 ,
'S_0': 59.3 ,
'V_0': 2.635e-05 ,
'Cp': [147.8, 0.002015, -2395000.0, -801.8] ,
'a_0': 2.12e-05 ,
'K_0': 2.11e+11 ,
'Kprime_0': 4.55 ,
'Kdprime_0': -2.2e-11 ,
'n': sum(formula.values()),
'molar_mass': formula_mass(formula, atomic_masses)}
self.uncertainties = {
'err_H_0': 880.0 }
Mineral.__init__(self)
def __init__(self, name, atoms, formula, sites, comp, H, S, V, Cp, a, k,
flag, od):
if flag != -1 and flag != -2 and k[0] > 0:
formula = dictionarize_formula(formula)
self.params = OrderedDict([('name', name), ('formula', formula),
('equation_of_state', 'hp_tmt'),
('H_0', round(H * 1e3, 10)),
('S_0', round(S * 1e3, 10)),
('V_0', round(V * 1e-5, 15)),
('Cp', [
round(Cp[0] * 1e3, 10),
round(Cp[1] * 1e3, 10),
round(Cp[2] * 1e3, 10),
round(Cp[3] * 1e3, 10)
]), ('a_0', a),
('K_0', round(k[0] * 1e8, 10)),
('Kprime_0', k[1]),
('Kdprime_0', round(k[2] * 1e-8, 15)),
('n', sum(formula.values())),
('molar_mass',
round(formula_mass(formula), 10))])
if flag == 1:
self.landau_hp = OrderedDict([('P_0', 1e5), ('T_0', 298.15),
('Tc_0', od[0]),
('S_D', round(od[1] * 1e3, 10)),
('V_D', round(od[2] * 1e-5, 10))])
if flag == 2:
self.bragg_williams = OrderedDict([
('deltaH', round(od[0] * 1e3, 10)),
('deltaV', round(od[1] * 1e-5, 15)),
('Wh', round(od[2] * 1e3,
10)), ('Wv', round(od[3] * 1e-5,
15)), ('n', od[4]),
('factor', od[5])
])
mt = minerals.HP_2011_ds62.mt()
qtz = minerals.HP_2011_ds62.q()
FMQ = [fa, mt, qtz]
for mineral in FMQ:
mineral.set_state(P, T)
'''
Here we find chemical potentials of FeO, SiO2 and O2 for
an assemblage containing fayalite, magnetite and quartz,
and a second assemblage of magnetite and wustite
at 1 GPa, 1000 K
'''
component_formulae = ['FeO', 'SiO2', 'O2']
component_formulae_dict = [
processchemistry.dictionarize_formula(f) for f in component_formulae
]
chem_potentials = chemical_potentials.chemical_potentials(
FMQ, component_formulae_dict)
oxygen = minerals.HP_2011_fluids.O2()
oxygen.set_state(P, T)
hem = minerals.HP_2011_ds62.hem()
MH = [mt, hem]
for mineral in MH:
mineral.set_state(P, T)
print('log10(fO2) at the FMQ buffer:',
np.log10(chemical_potentials.fugacity(oxygen, FMQ)))
print('log10(fO2) at the mt-hem buffer:',
for c in components
]
print(' {0}\n {1} (atoms, {2} oxygen basis)\n'.format(
components, af, float(n_O)))
# Let's do something a little more complicated.
# When we're making a starting mix for petrological experiments,
# we often have to add additional components.
# For example, we add iron as Fe2O3 even if we want a reduced
# oxide starting mix, because FeO is not a stable stoichiometric compound.
# Here we show how to use BurnMan to create such mixes.
# We start with a fayalite starting composition
print('\n3) Fayalite starting mix calculations:\n')
composition = Composition(dictionarize_formula('Fe2SiO4'), 'molar')
# The first step is to split the desired starting mix into a set of starting oxides
# (alternatively, we could have initialised the
# composition with a dictionary of these oxides)
composition.change_component_set(['FeO', 'SiO2'])
# Let's check the molar composition of this composition
composition.print('molar', significant_figures=4, normalization_amount=1.)
# Here we modify the bulk composition by adding oxygen to the
# starting mix equal to one third the total FeO (on a molar basis)
# This is equivalent to adding FeO as Fe2O3 (1/2 Fe2O3 = FeO + 1/2 O)
print('')
print(
'FeO doesn\'t exist as a stoichiometric compound, but we can create\n'
