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(736a) Oxygen Non-Stoichiometry and Defect Models of Brownmillerite-Structured Ca2MnAlO5+? for Chemical Looping Air Separation

Tian, Y. - Presenter, North Carolina State University
Luongo, G., ETH Zürich
Müller, C., Swiss Federal Institute of Technology
Westmoreland, P., North Carolina State University
Li, F., North Carolina State University
The brownmillerite-structured Ca2MnAlO5+δ has demonstrated excellent oxygen storage capacity that can be used for chemical looping air separation (CLAS), a potentially efficient approach to produce high-purity oxygen from air. In order to effectively utilize this material as an oxygen sorbent in CLAS, it is necessary to comprehensively understand its thermodynamic properties and the structure-performance relationships in the operating range of interest. In this work, the oxygen non-stoichiometry (δ) of Ca2MnAlO5+δ was systematically measured by thermal gravimetric analysis (TGA) in the temperature ranging from 440-600ºC and under oxygen partial pressure 0.01-0.8 atm. The partial molar enthalpy and entropy for oxygen releasing reaction were calculated using van’t Hoff Equation with an averaged value of 146.5 ± 4.7 kJ/mol O2 and 162.7 ± 5.1 J/K mol O2, respectively. The experimentally measured non-stoichiometry (δ) was well-fitted by a point defect model applied in two regions divided by the predicted equilibrium P-T curve. The equilibrium constants for appropriate defects reactions were also determined. The thermochemical parameters, molar enthalpy and entropy for the main reaction, obtained from the defect model were 141.7 kJ/mol O2 and 139.1 J/K mol O2 respectively, showing agreement with the aforementioned values. It thus demonstrated the constancy on theoretical calculations as well as the high fidelity of the selected defect model. The resulting defect model was also applied to higher oxygen partial pressure environment in the range from 1-4 atm and exhibited satisfactory fitting quality. The experimental studies on oxygen non-stoichiometry combined with the defect-structure modeling provide useful insights on the fundamental understanding of the oxygen sorbents’ redox performances and helpful information for the design and optimization of oxygen sorbents in CLAS.