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Sm0.2Ce0.8O1.9‐ 30% Na2CO3 (Sm doped ceria (SDC)‐30N) nano‐composite electrolytes were densified in a single step via cold sintering process (CSP). At 200°C and 450 MPa of uniaxial pressure, samples up to 97% of their theoretical density could be obtained. The effect of processing parameters, such as temperature, uniaxial pressure, processing duration, and moisture content, on the densification of the nano‐composite electrolytes was investigated. The thermal, microstructural, and electrical properties of nano‐composites were investigated by differential scanning calorimetry, X‐ray diffractometer, scanning electron microscope, and EIS analysis. SDC crystallite sizes were found to be around 25 nm, barely coarsened after CSP by which the true nano nature of the nano‐composite could be preserved. Because, by conventional processing high density values could not be attained and high processing temperatures in excess of 600°C had to be used, promoting particle coarsening. The highest total electrical conductivity was found to be 2.2 × 10−2 S cm−1 at 600°C, with an activation energy of 0.83 eV for SDC‐30N nano‐composites. The present investigation revealed that the implementation of cold sintering technique resulted in significant enhancements in the densification of nano‐composite electrolytes, thereby rendering them suitable for efficient utilization in SOFC applications, as compared to the conventional production methods.

This study proposes a hybrid approach for the selection of students employed part-time at the various departments of a university. There are both qualitative and quantitative criteria for the selection of students. Thus, to handle the subjective assessment in the decision-making process, this study considers developing DEMATEL-modified ANP and MULTIMOORA. An empirical case study applied at Metallurgical and Materials Engineering Department in Turkey is exhibited to test the effectiveness of the proposed decision-making method, which provides a fair selection considering three main and seven sub-criteria. These criteria are determined in accordance with the previous experience of the commission members and the principles which are listed in the Administration Guideline of the university. One among five candidates is selected by a novel hybrid approach. The obtained results and all scenarios in sensitivity analysis based on the changing of the decision makers’ weights and the changing of the dimension weights indicate that the S3 student remains the most preferred alternative, and the S4 student mostly is the most suitable alternative, respectively.

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