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'