Abstract
Macroporous ceramics exhibit an intrinsic strength variability caused by the random distribution of defects in their structure. However, the precise role of microstructural features, other than pore volume, on reliability is still unknown. Here, we analyze the applicability of the Weibull analysis to unidirectional macroporous yttria-stabilized-zirconia (YSZ) prepared by ice-templating. First, we performed crush tests on samples with controlled microstructural features with the loading direction parallel to the porosity. The compressive strength data were fitted using two different fitting techniques, ordinary least squares and Bayesian Markov Chain Monte Carlo, to evaluate whether Weibull statistics are an adequate descriptor of the strength distribution. The statistical descriptors indicated that the strength data are well described by the Weibull statistical approach, for both fitting methods used. Furthermore, we assess the effect of different microstructural features (volume, size, densification of the walls, and morphology) on Weibull modulus and strength. We found that the key microstructural parameter controlling reliability is wall thickness. In contrast, pore volume is the main parameter controlling the strength. The highest Weibull modulus () and mean strength (198.2 MPa) were obtained for the samples with the smallest and narrowest wall thickness distribution (3.1 m) and lower pore volume (54.5%).
Highlights
Macroporous ceramics are used in applications such as solid oxide fuel cells (SOFC), oxygen transport membranes (OTM), bone replacement, filters, and thermal insulation [1]
S1 and S4 exhibited the characteristic compressive behavior of highly porous materials. As it has been reported in isotropic [35] and anisotropic [36] porous materials, the shifting behavior of the failure mode is mainly caused by the increase in pore volume
The mechanical reliability of ice-templated specimens was measured in compression in different pore structures through a Weibull analysis
Summary
Macroporous ceramics are used in applications such as solid oxide fuel cells (SOFC), oxygen transport membranes (OTM), bone replacement, filters, and thermal insulation [1]. Since the strength of a material is described by a distribution rather than a single value, mechanical reliability must be characterized using a probabilistic approach. This is important in applications like SOFC or OTM where hundreds or thousands of individual macroporous elements must be combined and the failure of a single element could cause the entire module to fail
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