Note
Go to the end to download the full example code.
Calculator: Liquid Properties#
This notebook calculates the activity of endmembers within a liquid. It replaces the functionality previously implemented by the MELTS Supplemental Calculator (https://melts.ofm-research.org/CalcForms/)
This calculator is a work in progress – please let us know if you find any errors!
Open this code in an executable MyBinder instance (MyBinder links may be slow to load– please be patient!):
User Input#
Input liquid composition in wt% oxides, temperature, pressure, and log(fO2) below
Once you have input your data in the cell above, click “Run” –> “Run All Cells” at the top of the notebook. This will run the entire notebook and produce the output table at the bottom of the file.
oxide_wt_dict = {
'SiO2': 48.4012,
'TiO2': 0.9208,
'Al2O3': 14.9349,
'FeO': 9.0825,
'MnO': 0.1587,
'MgO': 8.1285,
'CaO': 14.1368,
'Na2O': 1.3124,
'K2O': 0.1462,
'P2O5': 0.001
}
TK = 1500 + 273.15 # temperature value in K
Pbar = 15000 # pressure value in bar
logfO2 = None # can replace this with a value for absolute logfO2 (not relative to a buffer). Otherwise, calculates with given Fe2O3 value.
Calculations#
The user does not need to modify this code– it will run automatically when “Run All Cells” is triggered.
###-----------------------------------------------------------------------------------------
### 0. Import modules
###-----------------------------------------------------------------------------------------
import numpy as np
import pandas as pd
from thermoengine import model, equilibrate, chemistry
from thermoengine.core import chem
from thermoengine import redox
###-----------------------------------------------------------------------------------------
### 1. Calculate oxide moles
###-----------------------------------------------------------------------------------------
oxide_moles = chem.format_mol_oxide_comp(oxide_wt_dict, convert_grams_to_moles=True)
oxide_moles_ser = pd.Series(oxide_moles, index=chemistry.OXIDES)
oxide_dict_for_fO2 = {'Liq': oxide_moles}
###-----------------------------------------------------------------------------------------
### 2. Adjust composition to be consistent with log fO2 input
###-----------------------------------------------------------------------------------------
if logfO2 is not None:
ln_Fe_oxide_ratio = redox.redox_state(TK, Pbar, oxide_comp=oxide_dict_for_fO2, logfO2=logfO2,
phase_of_interest='Liq', method='Kress91')
Fe2O3_FeO = np.exp(ln_Fe_oxide_ratio)
oxide_moles_ser = redox.impose_redox_ratio(Fe2O3_FeO, oxide_moles_ser)
###-----------------------------------------------------------------------------------------
### 3. Create liquid phase instance
###-----------------------------------------------------------------------------------------
liquid = model.Database(database_name="MELTS_v1_2").get_phase('Liq')
liq_end = liquid.calc_endmember_comp(oxide_moles_ser.values, method='least_squares',
output_residual=False, normalize=False,
decimals=10)
###-----------------------------------------------------------------------------------------
### 4. Calculate Gibbs Free Energies of Formation
###-----------------------------------------------------------------------------------------
end_array = np.identity(liquid.endmember_num)
G_array = np.zeros(liquid.endmember_num)
for i in range(liquid.endmember_num):
G = liquid.gibbs_energy(TK,Pbar,mol=end_array[i,:])
G_array[i] = G
###-----------------------------------------------------------------------------------------
### 5. Calculate Activities
###-----------------------------------------------------------------------------------------
activities = liquid.activity(TK, Pbar, mol=liq_end)
###-----------------------------------------------------------------------------------------
### 6. Combine and display data
###-----------------------------------------------------------------------------------------
data = {'Endmember': liquid.endmember_names, 'Gibbs Energy (kJ)': G_array/1000, 'Activity': activities}
endmember_df = pd.DataFrame(data)
pd.set_option('display.max_rows', None)
endmember_df
Total running time of the script: (0 minutes 0.021 seconds)