Computational engineering of the oxygen electrode-electrolyte interface in solid oxide fuel cells

The Ce0.8Gd0.2O2−δ (CGO) interlayer is commonly applied in solid oxide fuel cells (SOFCs) to prevent chemical reactions between the (La1−xSrx)(Co1−yFey)O3−δ (LSCF) oxygen electrode and the Y2O3-stabilized ZrO2 (YSZ) electrolyte. However, formation of the YSZ–CGO solid solution with low ionic conductivity and the SrZrO3 (SZO) insulating phase still happens during cell production and long-term operation, causing poor performance and degradation. Unlike many experimental investigations exploring these phenomena, consistent and quantitative computational modeling of the microstructure evolution at the oxygen electrode–electrolyte interface is scarce. We combine thermodynamic, 1D kinetic, and 3D phase-field modeling to computationally reproduce the element redistribution, microstructure evolution, and corresponding ohmic loss of this interface. The influences of different ceramic processing techniques for the CGO interlayer, i.e., screen printing and physical laser deposition (PLD), and of different processing and long-term operating parameters are explored, representing a successful case of quantitative computational engineering of the oxygen electrode–electrolyte interface in SOFCs.

Artificial Intelligence in Gravitational-Wave Science

Artificial intelligence gaining popularity not only in the computational engineering industry but also in fundamental science. For the realization of artificial intelligence, numerous machine learning algorithms have been introduced and tested for their applicability. Even in the field of gravitational-wave science, the application of machine learning has been widely studied to enhance conventional analyses in all disciplines from searching for gravitational-wave signals to characterizing noise transients. In this article, I briefly introduce the current status of gravitational-wave science and summarize research topics in which machine learning is applied to each discipline of gravitational-wave science.

Computational engineering of surface layer ground Al2O3‒TiC ceramic. Systematic analysis

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