The Development of New Perovskite-Type Oxygen Transport Membranes Using Machine Learning

被引:7
作者
Schlenz, Hartmut [1 ,2 ,3 ]
Baumann, Stefan [1 ,3 ]
Meulenberg, Wilhelm Albert [1 ,3 ,4 ]
Guillon, Olivier [1 ,3 ,5 ]
机构
[1] Forschungszentrum Juelich, IEK 1 Mat Synth & Proc, Inst Energy & Climate Res IEK, Wilhelm Johnen Str, D-52425 Julich, Germany
[2] Univ Bonn, Inst Geosci, Div Geochem & Petrol, Meckenheimer Allee 139, D-53115 Bonn, Germany
[3] Juelich Aachen Res Alliance JARA Energy, D-52425 Julich, Germany
[4] Univ Twente, Fac Sci & Technol, Inorgan Membranes, POB 217, NL-7500 AE Enschede, Netherlands
[5] Rhein Westfal TH Aachen, Inst Mineral Engn, Dept Ceram & Refractory Mat, D-52064 Aachen, Germany
关键词
ceramic; perovskite; oxygen separation membrane; mixed ionic-electronic conducting membrane MIEC; valence bond calculations; machine learning; !text type='python']python[!/text] programming; Pecon; py; BOND-VALENCE PARAMETERS; ELECTRICAL-CONDUCTIVITY; SOLID ELECTROLYTES; IONIC-CONDUCTIVITY; FUEL-CELL; SRTIO3; PREDICTION; OXIDES; STABILITY; VACANCIES;
D O I
10.3390/cryst12070947
中图分类号
O7 [晶体学];
学科分类号
0702 ; 070205 ; 0703 ; 080501 ;
摘要
The aim of this work is to predict suitable chemical compositions for the development of new ceramic oxygen gas separation membranes, avoiding doping with toxic cobalt or expensive rare earths. For this purpose, we have chosen the system Sr<INF>1-x</INF>Ba<INF>x</INF>(Ti<INF>1-y-z</INF>V<INF>y</INF>Fe<INF>z</INF>)O<INF>3-delta</INF> (cubic perovskite-type phases). We have evaluated available experimental data, determined missing crystallographic information using bond-valence modeling and programmed a Python code to be able to generate training data sets for property predictions using machine learning. Indeed, suitable compositions of cubic perovskite-type phases can be predicted in this way, allowing for larger electronic conductivities of up to sigma<INF>e</INF> = 1.6 S/cm and oxygen conductivities of up to sigma<INF>i</INF> = 0.008 S/cm at T = 1173 K and an oxygen partial pressure p<INF>O<INF>2</INF></INF> = 10-15 bar, thus enabling practical applications.
引用
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页数:17
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