Cu and Gd co-doped BaCeO3 proton conductors: Experimental vs SEM image algorithmic-segmentation results

• Novel algorithmic evaluation method of image resolution using SEM data.
• Microstructure description and electrical conductivity evaluation via algorithmic segmentation of SEM images.
• The method permits to divide the volume resistance and grain-boundary resistance at any temperature range.
• Total conductivity and mean grain size of the ceramics as a function of Cu content.

Segmentation algorithms for the quantitative description of the surface microstructure and the evaluation of the grain-boundary conductivity of ceramic materials surface using SEM microphotographs analysis was developed and applied in the present work for first time in barium cerate based solid solutions. To this purpose novel polycrystalline ceramic materials based on Cu and Gd co-doped BaCeO3 proton conductors exhibiting high proton conductivity have been prepared and characterized. The influence of copper oxide as a dopant on the microstructure and the electrical properties of BaCe0.9–xGd0.1CuxO3–δ (0≤x≤0.1) have been examined in detail. It is shown that the dependence of the electrical conductivity is correlated with the average oxide grain diameter variation in air at various temperatures. Moreover, it was found that the algorithmic segmentation evaluation results are in good agreement with the experimental ones, verifying the considerable contribution of the grain-boundary conductivity to the electrical transport of Cu and Gd co-doped BaCeO3 proton conductors.

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