This page was generated from docs/Examples/Other_features/fo2_to_Fe3FeT.ipynb. Interactive online version: .

Converting back and forth from Fe3Fet to different redox buffer positions.

You can download the spreadsheet here: https://github.com/PennyWieser/Thermobar/blob/main/docs/Examples/Other_features/Redox_Conversions.xlsx

[1]:

# Loading various python things
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import Thermobar as pt

Load in data

No suffix in file, so add here to say they are liquids

[15]:

load=pt.import_excel('Redox_Conversions.xlsx', sheet_name="Liqs", suffix='_Liq')
Liqs=load['Liqs']
Liqs.head()

[15]:

	SiO2_Liq	TiO2_Liq	Al2O3_Liq	FeOt_Liq	MnO_Liq	MgO_Liq	CaO_Liq	Na2O_Liq	K2O_Liq	P2O5_Liq	H2O_Liq	Sample_ID_Liq
0	51.456179	2.601690	13.529073	11.114610	0.185873	6.698477	10.974609	2.406926	0.483801	0.248535	0.508277	0
1	51.462403	2.641448	13.717522	11.175642	0.189570	6.497934	10.814571	2.451116	0.493423	0.253478	0.518386	1
2	51.491657	2.771451	13.666925	11.521905	0.200504	6.275374	10.459901	2.509225	0.520502	0.268098	0.548285	2
3	51.508276	2.872896	13.569897	11.795709	0.208908	6.138356	10.217900	2.543802	0.541088	0.279336	0.571268	3
4	51.506960	3.058952	13.350351	12.214913	0.223782	5.856971	9.977521	2.592645	0.577148	0.299224	0.611940	4

Example 1: Calculating Fe3Fet for a series of liquid compositions

Remember, Fe3Fet_Liq to buffer positions is very dependent on temperature, so first we need to choose a thermometer

[16]:

# Calculate temperature
T_HT87=pt.calculate_liq_only_temp(liq_comps=Liqs, equationT='T_Helz1987_MgO')

1a: Using a value for logfo2

[17]:

logfo2=-7.58429552677443

# Calculate oxides using Kress 1991 and 3 kbar, and
myLiquids_Fe3_Kress_norm=pt.convert_fo2_to_fe_partition(liq_comps=Liqs, T_K=T_HT87,
                            P_kbar=3, fo2=10**logfo2, model="Kress1991", renorm=True)
myLiquids_Fe3_Kress_norm.head()

[17]:

	SiO2_Liq	TiO2_Liq	Al2O3_Liq	Fe2O3_Liq	FeO_Liq	MnO_Liq	MgO_Liq	CaO_Liq	Na2O_Liq	K2O_Liq	P2O5_Liq	Fe3Fet_Liq
0	51.573474	2.607633	13.559981	2.813568	8.606944	0.186298	6.713780	10.999680	2.412425	0.484906	0.249103	0.227286
1	51.582033	2.647602	13.749479	2.869927	8.617879	0.190011	6.513072	10.839765	2.456826	0.494572	0.254069	0.230563
2	51.620474	2.778399	13.701184	2.993012	8.856176	0.201006	6.291105	10.486121	2.515515	0.521807	0.268770	0.233184
3	51.644329	2.880498	13.605809	3.084121	9.050289	0.209461	6.154600	10.244940	2.550534	0.542520	0.280075	0.234673
4	51.654905	3.067754	13.388765	3.261699	9.313550	0.224426	5.873824	10.006230	2.600105	0.578808	0.300085	0.239613

[19]:

plt.plot(myLiquids_Fe3_Kress_norm['MgO_Liq'], myLiquids_Fe3_Kress_norm['Fe3Fet_Liq'], '-r')
plt.xlabel('MgO Liq')
plt.ylabel('Fe3Fet Liq')

[19]:

Text(0, 0.5, 'Fe3Fet Liq')

../../_images/Examples_Other_features_fo2_to_Fe3FeT_8_1.png

1b: At a known buffer (here, QFM)

[21]:

# Calculate oxides using Kress 1991 and 3 kbar, and
myLiquids_Fe3_Kress_norm_QFM=pt.convert_fo2_to_fe_partition(liq_comps=Liqs, T_K=T_HT87,
                            P_kbar=3, fo2="QFM", model="Kress1991", renorm=True)
myLiquids_Fe3_Kress_norm_QFM.head()

[21]:

	SiO2_Liq	TiO2_Liq	Al2O3_Liq	Fe2O3_Liq	FeO_Liq	MnO_Liq	MgO_Liq	CaO_Liq	Na2O_Liq	K2O_Liq	P2O5_Liq	Fe3Fet_Liq
0	51.621424	2.610058	13.572588	1.881698	9.456264	0.186471	6.720022	11.009907	2.414668	0.485357	0.249335	0.151860
1	51.632661	2.650201	13.762974	1.886144	9.514574	0.190198	6.519464	10.850404	2.459237	0.495057	0.254318	0.151373
2	51.675308	2.781350	13.715738	1.928249	9.827054	0.201220	6.297788	10.497260	2.518187	0.522361	0.269056	0.150063
3	51.702115	2.883721	13.621032	1.962512	10.073308	0.209695	6.161487	10.256404	2.553387	0.543127	0.280389	0.149155
4	51.718628	3.071538	13.405281	2.025025	10.442040	0.224702	5.881070	10.018574	2.603312	0.579522	0.300455	0.148573

[22]:

plt.plot(myLiquids_Fe3_Kress_norm_QFM['MgO_Liq'], myLiquids_Fe3_Kress_norm_QFM['Fe3Fet_Liq'], '-r')
plt.xlabel('MgO Liq')
plt.ylabel('Fe3Fet Liq')

[22]:

Text(0, 0.5, 'Fe3Fet Liq')

../../_images/Examples_Other_features_fo2_to_Fe3FeT_11_1.png

1c: At buffer with offset (here NNO+1)

[24]:

# Calculate oxides using Kress 1991 and 3 kbar, and
myLiquids_Fe3_Kress_norm_NNO1=pt.convert_fo2_to_fe_partition(liq_comps=Liqs, T_K=T_HT87,
                            P_kbar=3, fo2="NNO", fo2_offset=1, model="Kress1991", renorm=True)
myLiquids_Fe3_Kress_norm_NNO1.head()

[24]:

	SiO2_Liq	TiO2_Liq	Al2O3_Liq	Fe2O3_Liq	FeO_Liq	MnO_Liq	MgO_Liq	CaO_Liq	Na2O_Liq	K2O_Liq	P2O5_Liq	Fe3Fet_Liq
0	51.546390	2.606264	13.552860	3.339932	8.127207	0.186200	6.710254	10.993904	2.411158	0.484651	0.248972	0.269955
1	51.557365	2.646336	13.742904	3.349248	8.180990	0.189920	6.509957	10.834581	2.455651	0.494335	0.253947	0.269205
2	51.598076	2.777193	13.695239	3.427946	8.459594	0.200919	6.288375	10.481571	2.514423	0.521581	0.268654	0.267191
3	51.623335	2.879327	13.600278	3.491627	8.678603	0.209376	6.152098	10.240776	2.549497	0.542300	0.279962	0.265793
4	51.637241	3.066705	13.384186	3.604510	9.000728	0.224349	5.871815	10.002808	2.599216	0.578610	0.299982	0.264891

[25]:

plt.plot(myLiquids_Fe3_Kress_norm_NNO1['MgO_Liq'], myLiquids_Fe3_Kress_norm_NNO1['Fe3Fet_Liq'], '-r')
plt.xlabel('MgO Liq')
plt.ylabel('Fe3Fet Liq')

[25]:

Text(0, 0.5, 'Fe3Fet Liq')

../../_images/Examples_Other_features_fo2_to_Fe3FeT_14_1.png

1d: With different normalization routines:

So far, we used Norm=True, this renormalizes the other oxides to account for the changing FeO and Fe2O3 amount, can also put false, doesn’t affect the Fe3FeT but affects the oxide concs. You can see this by comparing the other oxide contents

[29]:

logfo2=-7.58429552677443
print('Original')
display(Liqs.loc[[0]])

# No renormalizatoin
myLiquids_Fe3_Kress_nonorm=pt.convert_fo2_to_fe_partition(liq_comps=Liqs.loc[[0]], T_K=T_HT87.loc[[0]],
                            P_kbar=3, fo2=10**logfo2, model="Kress1991", renorm=False)
print('No Norm')
display(myLiquids_Fe3_Kress_nonorm)


# With renormalization
myLiquids_Fe3_Kress_norm=pt.convert_fo2_to_fe_partition(liq_comps=Liqs.loc[[0]], T_K=T_HT87.loc[[0]],
                            P_kbar=3, fo2=10**logfo2, model="Kress1991", renorm=True)
print('Renorm')
display(myLiquids_Fe3_Kress_norm)

Original

	SiO2_Liq	TiO2_Liq	Al2O3_Liq	FeOt_Liq	MnO_Liq	MgO_Liq	CaO_Liq	Na2O_Liq	K2O_Liq	Cr2O3_Liq	P2O5_Liq	H2O_Liq	Fe3Fet_Liq	NiO_Liq	CoO_Liq	CO2_Liq	Sample_ID_Liq
0	51.456179	2.60169	13.529073	11.11461	0.185873	6.698477	10.974609	2.406926	0.483801	0.0	0.248535	0.508277	0.0	0.0	0.0	0.0	0

No Norm

	SiO2_Liq	TiO2_Liq	Al2O3_Liq	FeOt_Liq	MnO_Liq	MgO_Liq	CaO_Liq	Na2O_Liq	K2O_Liq	Cr2O3_Liq	P2O5_Liq	H2O_Liq	Fe3Fet_Liq	NiO_Liq	CoO_Liq	CO2_Liq	Sample_ID_Liq	FeO_Liq	Fe2O3_Liq	XFe3Fe2
0	51.456179	2.60169	13.529073	11.11461	0.185873	6.698477	10.974609	2.406926	0.483801	0.0	0.248535	0.508277	0.227286	0.0	0.0	0.0	0	8.589075	2.807726	0.147152

Renorm

	SiO2_Liq	TiO2_Liq	Al2O3_Liq	Fe2O3_Liq	FeO_Liq	MnO_Liq	MgO_Liq	CaO_Liq	Na2O_Liq	K2O_Liq	P2O5_Liq	Fe3Fet_Liq
0	51.573474	2.607633	13.559981	2.813568	8.606944	0.186298	6.71378	10.99968	2.412425	0.484906	0.249103	0.227286

Converting from FeO and Fe2O3 proportions to fo2

This function goes the other way, it takes a liquid with FeO and Fe2O3, and a temperature and pressure, and converts to a buffer position/delta fo2 vlaue

[41]:

## The inversion isn't quite perfect, but is very close
calc_fo2=pt.convert_fe_partition_to_fo2(liq_comps=myLiquids_Fe3_Kress_norm_NNO1,
                                        T_K=T_HT87, P_kbar=3, model="Kress1991", renorm=False)

[42]:

calc_fo2

[42]:

	DeltaQFM	DeltaNNO	fo2_calc	SiO2_Liq	TiO2_Liq	Al2O3_Liq	Fe2O3_Liq	FeO_Liq	MnO_Liq	MgO_Liq	CaO_Liq	Na2O_Liq	K2O_Liq	P2O5_Liq	Fe3Fet_Liq
0	1.587252	0.980283	7.999607e-08	51.546390	2.606264	13.552860	3.339932	8.127207	0.186200	6.710254	10.993904	2.411158	0.484651	0.248972	0.269955
1	1.587349	0.980431	7.139051e-08	51.557365	2.646336	13.742904	3.349248	8.180990	0.189920	6.509957	10.834581	2.455651	0.494335	0.253947	0.269205
2	1.587300	0.980439	6.284887e-08	51.598076	2.777193	13.695239	3.427946	8.459594	0.200919	6.288375	10.481571	2.514423	0.521581	0.268654	0.267191
3	1.587231	0.980406	5.807824e-08	51.623335	2.879327	13.600278	3.491627	8.678603	0.209376	6.152098	10.240776	2.549497	0.542300	0.279962	0.265793
4	1.586615	0.979863	4.928451e-08	51.637241	3.066705	13.384186	3.604510	9.000728	0.224349	5.871815	10.002808	2.599216	0.578610	0.299982	0.264891
5	1.586086	0.979386	4.382653e-08	51.638351	3.199578	13.221434	3.682642	9.209909	0.234892	5.673066	9.879096	2.629078	0.603989	0.314080	0.264593
6	1.585330	0.978706	3.698529e-08	51.634502	3.398218	12.978289	3.796698	9.516734	0.250723	5.387579	9.701648	2.668614	0.641860	0.335248	0.264151
7	1.584851	0.978275	3.316046e-08	51.628396	3.530278	12.816809	3.870774	9.716984	0.261292	5.205129	9.588480	2.691642	0.666987	0.349380	0.263860
8	1.584167	0.977661	2.831006e-08	51.614145	3.727939	12.575476	3.979141	10.011395	0.277175	4.942417	9.425986	2.721464	0.704516	0.370618	0.263425
9	1.583734	0.977274	2.556757e-08	51.601373	3.859495	12.415173	4.049654	10.203931	0.287788	4.774137	9.322264	2.738345	0.729436	0.384809	0.263138
10	1.583119	0.976725	2.205359e-08	51.577516	4.056607	12.175604	4.152968	10.487474	0.303752	4.531307	9.173226	2.759398	0.766683	0.406155	0.262708
11	1.582732	0.976380	2.004672e-08	51.558600	4.187924	12.016501	4.220276	10.673160	0.314429	4.375443	9.078035	2.770713	0.791434	0.420430	0.262423
12	1.582732	0.976380	2.004672e-08	51.558600	4.187924	12.016501	4.220276	10.673160	0.314429	4.375443	9.078035	2.770713	0.791434	0.420430	0.262423
13	1.582544	0.976214	1.913018e-08	51.548269	4.253568	11.937139	4.253476	10.765036	0.319778	4.299228	9.031643	2.775586	0.803787	0.427583	0.262280
14	1.582362	0.976051	1.826626e-08	51.537371	4.319209	11.857907	4.286379	10.856281	0.325135	4.224120	8.986032	2.779949	0.816127	0.434746	0.262138
15	1.582183	0.975893	1.745137e-08	51.525916	4.384849	11.778808	4.318990	10.946905	0.330500	4.150092	8.941187	2.783811	0.828454	0.441920	0.261996
16	1.582009	0.975739	1.668222e-08	51.513916	4.450493	11.699847	4.351312	11.036914	0.335874	4.077119	8.897096	2.787183	0.840768	0.449106	0.261855
17	1.581827	0.975579	1.589241e-08	51.529100	4.496905	11.625147	4.382480	11.122869	0.341191	3.998756	8.848689	2.792709	0.854256	0.456956	0.261735
18	1.581695	0.975511	1.375841e-08	52.612734	4.263861	11.713650	4.246476	10.710464	0.327012	3.766118	8.463650	2.870163	0.979760	0.463878	0.262946
19	1.581520	0.975392	1.214620e-08	53.545497	4.063865	11.790118	4.128805	10.357587	0.314846	3.566451	8.133268	2.936798	1.087593	0.469841	0.263994
20	1.581327	0.975246	1.094722e-08	54.320717	3.898105	11.853887	4.030598	10.065866	0.304765	3.400949	7.859484	2.992153	1.177063	0.474801	0.264868
21	1.581123	0.975083	9.993273e-09	54.998878	3.753437	11.909834	3.944379	9.811827	0.295969	3.256496	7.620568	3.040558	1.255220	0.479143	0.265636
22	1.580911	0.974907	9.198004e-09	55.614102	3.622435	11.960703	3.865888	9.582234	0.288004	3.125681	7.404243	3.084456	1.326045	0.483083	0.266334
23	1.580231	0.974324	7.416449e-09	57.204632	3.284890	12.092753	3.661803	8.992664	0.267487	2.788582	6.846957	3.197883	1.508776	0.493280	0.268149
24	1.579221	0.973432	5.683154e-09	59.154871	2.871874	12.255080	3.408360	8.274897	0.242386	2.376084	6.165149	3.336912	1.732547	0.505790	0.270403
25	1.578437	0.972719	4.846800e-09	60.316296	2.627669	12.352587	3.256571	7.852786	0.227552	2.132128	5.762176	3.419607	1.865233	0.513254	0.271747
26	1.577633	0.971978	4.206919e-09	61.346095	2.412078	12.439490	3.121347	7.481528	0.214461	1.916728	5.406509	3.492877	1.982573	0.519881	0.272940
27	1.576543	0.970962	3.560534e-09	62.556232	2.160024	12.542227	2.961789	7.049199	0.199161	1.664854	4.990808	3.578904	2.120038	0.527678	0.274342
28	1.575718	0.970186	3.184888e-09	63.363583	1.992753	12.611191	2.855025	6.763360	0.189011	1.497674	4.715018	3.636246	2.211458	0.532887	0.275275
29	1.574891	0.969404	2.877135e-09	64.098829	1.841131	12.674334	2.757645	6.505031	0.179815	1.346111	4.465098	3.688427	2.294479	0.537637	0.276122
30	1.574065	0.968618	2.621649e-09	64.771438	1.703098	12.732418	2.668493	6.270519	0.171445	1.208111	4.237641	3.736124	2.370207	0.541988	0.276893
31	1.572966	0.967569	2.343280e-09	65.583633	1.537408	12.803026	2.560853	5.989896	0.161403	1.042426	3.964702	3.793663	2.461326	0.547249	0.277817
32	1.572146	0.966783	2.170925e-09	66.136981	1.425242	12.851474	2.487602	5.800502	0.154609	0.930241	3.780003	3.832823	2.523170	0.550840	0.278441
33	1.571302	0.965970	2.020282e-09	66.659137	1.320178	12.897561	2.418719	5.623593	0.148248	0.825132	3.607073	3.869732	2.581271	0.554235	0.279022
34	1.570115	0.964823	1.845036e-09	67.320571	1.188397	12.956564	2.331963	5.402444	0.140275	0.693250	3.390294	3.916410	2.654442	0.558545	0.279746
35	1.569236	0.963970	1.736422e-09	67.764932	1.100791	12.996645	2.274078	5.255923	0.134980	0.605547	3.246275	3.947716	2.703295	0.561449	0.280221
36	1.568370	0.963128	1.643674e-09	68.168968	1.021921	13.033462	2.221829	5.124396	0.130216	0.526562	3.116695	3.976137	2.747456	0.564096	0.280645
37	1.567206	0.961992	1.539031e-09	68.657179	0.928027	13.078620	2.159486	4.968416	0.124551	0.432482	2.962573	4.010397	2.800356	0.567305	0.281140
38	1.566354	0.961159	1.473449e-09	68.983138	0.866257	13.109207	2.118394	4.866183	0.120829	0.370557	2.861274	4.033219	2.835374	0.569456	0.281459
39	1.565521	0.960342	1.417047e-09	69.277768	0.811201	13.137225	2.081729	4.775369	0.117516	0.315335	2.771067	4.053804	2.866770	0.571406	0.281738
40	1.564441	0.959282	1.353801e-09	69.626379	0.747242	13.170940	2.039103	4.670311	0.113672	0.251141	2.666395	4.078091	2.903531	0.573723	0.282053
41	1.563655	0.958509	1.313931e-09	69.857694	0.705689	13.193732	2.011406	4.602379	0.111179	0.209403	2.598487	4.094157	2.927632	0.575268	0.282251
42	1.562891	0.957756	1.279569e-09	70.065498	0.669123	13.214572	1.987043	4.542868	0.108990	0.172645	2.538813	4.108545	2.949032	0.576662	0.282419
43	1.562148	0.957023	1.250000e-09	70.251670	0.637130	13.233607	1.965748	4.491067	0.107078	0.140454	2.486686	4.121392	2.967954	0.577917	0.282560
44	1.561192	0.956077	1.217011e-09	70.469170	0.600944	13.256412	1.941707	4.432888	0.104923	0.103998	2.427862	4.136333	2.989668	0.579393	0.282708
45	1.560499	0.955392	1.196463e-09	70.611226	0.578222	13.271741	1.926656	4.396676	0.103574	0.081069	2.391034	4.146039	3.003551	0.580365	0.282794
46	1.559812	0.954711	1.179003e-09	70.737740	0.558946	13.285850	1.913944	4.366299	0.102436	0.061577	2.359909	4.154628	3.015600	0.581238	0.282857
47	1.558883	0.953788	1.159793e-09	70.886236	0.538023	13.303220	1.900261	4.333956	0.101211	0.040344	2.326343	4.164613	3.029184	0.582277	0.282910
48	1.557488	0.952397	1.144100e-09	71.036962	0.523079	13.323848	1.890969	4.313347	0.100377	0.024876	2.303243	4.174388	3.040906	0.583383	0.282883

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