Predicting grain size distributions in perovskite-structured Ba0.5Sr0.5Co0.8Fe0.2O3–δ oxygen transport membranes

Li Wang; Rui Dou; Gong Wang; Yizhe Li; Mingwen Bai; David Hall; Ying Chen

doi:10.1080/17436753.2018.1434955

Predicting grain size distributions in perovskite-structured Ba_0.5Sr_0.5Co_0.8Fe_0.2O_3–δ oxygen transport membranes

Li Wang, Rui Dou^*, Gong Wang, Yizhe Li, Mingwen Bai, David Hall, Ying Chen

^*Corresponding author for this work

Materials Engineering

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Abstract

This study is conducted over a 3 × 3 time–temperature matrix on Ba_0.5Sr_0.5Co_0.8Fe_0.2O_3−δ (BSCF) ceramics, and sintered bodies above 93% dense are obtained. The electron backscatter diffraction band contrast micrographs of the polished sintered samples are analysed for characterising the grain size distributions (GSDs). This study develops an algorithm for predicting the GSDs of BSCF dependence of sintering condition (time and temperature). In addition, the GSDs predicted by the algorithm agree reasonably with those experimentally observed. When individual grain size is non-dimensionalised by the median grain size, the GSDs data of all BSCF samples reduce to a single self-similar GSD curve. The median grain size is predicted by the classical kinetics equation, Dⁿ= tK₀exp(−Q/RT).

Original language	English
Pages (from-to)	354-360
Number of pages	7
Journal	Advances in Applied Ceramics
Volume	117
Issue number	6
Early online date	13 Feb 2018
DOIs	https://doi.org/10.1080/17436753.2018.1434955
Publication status	Published - 1 Aug 2018

Keywords

BSCF
grain size distribution
grain-growth kinetics
microstructure

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10.1080/17436753.2018.1434955

Wang-2018-2-AAC-AAMbAccepted author manuscript, 2.47 MB

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title = "Predicting grain size distributions in perovskite-structured Ba0.5Sr0.5Co0.8Fe0.2O3–δ oxygen transport membranes",

abstract = "This study is conducted over a 3 × 3 time–temperature matrix on Ba0.5Sr0.5Co0.8Fe0.2O3−δ (BSCF) ceramics, and sintered bodies above 93% dense are obtained. The electron backscatter diffraction band contrast micrographs of the polished sintered samples are analysed for characterising the grain size distributions (GSDs). This study develops an algorithm for predicting the GSDs of BSCF dependence of sintering condition (time and temperature). In addition, the GSDs predicted by the algorithm agree reasonably with those experimentally observed. When individual grain size is non-dimensionalised by the median grain size, the GSDs data of all BSCF samples reduce to a single self-similar GSD curve. The median grain size is predicted by the classical kinetics equation, Dn = tK0exp(−Q/RT).",

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AU - Wang, Li

AU - Dou, Rui

AU - Wang, Gong

AU - Li, Yizhe

AU - Bai, Mingwen

AU - Hall, David

AU - Chen, Ying

PY - 2018/8/1

Y1 - 2018/8/1

N2 - This study is conducted over a 3 × 3 time–temperature matrix on Ba0.5Sr0.5Co0.8Fe0.2O3−δ (BSCF) ceramics, and sintered bodies above 93% dense are obtained. The electron backscatter diffraction band contrast micrographs of the polished sintered samples are analysed for characterising the grain size distributions (GSDs). This study develops an algorithm for predicting the GSDs of BSCF dependence of sintering condition (time and temperature). In addition, the GSDs predicted by the algorithm agree reasonably with those experimentally observed. When individual grain size is non-dimensionalised by the median grain size, the GSDs data of all BSCF samples reduce to a single self-similar GSD curve. The median grain size is predicted by the classical kinetics equation, Dn = tK0exp(−Q/RT).

AB - This study is conducted over a 3 × 3 time–temperature matrix on Ba0.5Sr0.5Co0.8Fe0.2O3−δ (BSCF) ceramics, and sintered bodies above 93% dense are obtained. The electron backscatter diffraction band contrast micrographs of the polished sintered samples are analysed for characterising the grain size distributions (GSDs). This study develops an algorithm for predicting the GSDs of BSCF dependence of sintering condition (time and temperature). In addition, the GSDs predicted by the algorithm agree reasonably with those experimentally observed. When individual grain size is non-dimensionalised by the median grain size, the GSDs data of all BSCF samples reduce to a single self-similar GSD curve. The median grain size is predicted by the classical kinetics equation, Dn = tK0exp(−Q/RT).

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Predicting grain size distributions in perovskite-structured Ba_0.5Sr_0.5Co_0.8Fe_0.2O_3–δ oxygen transport membranes

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