The models of solid oxide fuel cells (SOFCs), which are available in the open literature, may be categorized into two non-overlapping groups: microscale or macroscale. Recent progress in computational power makes it possible to formulate a model which combines both approaches, the so-called multiscale model. The novelty of this modeling approach lies in the combination of the microscale description of the transport phenomena and electrochemical reactions’ with the computational fluid dynamics model of the heat and mass transfer in an SOFC. In this work, the mathematical model of a solid oxide fuel cell which takes into account the averaged microstructure parameters of electrodes is developed and tested. To gain experimental data, which are used to confirm the proposed model, the electrochemical tests and the direct observation of the microstructure with the use of the focused ion beam combined with the scanning electron microscope technique (FIB-SEM) were conducted. The numerical results are compared with the experimental data from the short stack examination and a fair agreement is found, which shows that the proposed model can predict the cell behavior accurately. The mechanism of the power generation inside the SOFC is discussed and it is found that the current is produced primarily near the electrolyte–electrode interface. Simulations with an artificially changed microstructure does not lead to the correct prediction of the cell characteristics, which indicates that the microstructure is a crucial factor in the solid oxide fuel cell modeling.

A flower-like BiVO₄ microsphere photocatalyst was synthesized with a simple template-free homogeneous precipitation method at 60 °C for 24 h. The purpose of this study is to explore a low-cost, simple method of synthesizing the self-assembled 3D structure in order to enhance photocatalytic performance under visible light irradiation (λ > 420 nm). In this study, the morphology, structure, and photo-absorption of flower-like BiVO₄ microspheres were characterized, and the effects of photocatalysis were analyzed. The results indicate that the size of the flower-like microspheres was about 2 μm to 4 μm and they were composed of several nanosheets. The mechanism of hierarchical microsphere formation has been proposed as the Ostwald ripening process and the self-assembled process. The obtained samples were calcined under different temperatures (300 °C, 400 °C, 500 °C and 600 °C) to study the effects of calcination on the structure and on photocatalysis. The photocatalytic process was then evaluated by decolorization of methylene blue dye under visible-light irradiation.

Methane steam reforming is the foremost method for hydrogen production, and it has been studied through experiments and diverse computational models to enhance its energy efficiency. This study focuses on employing an artificial neural network as a model of the methane steam reforming process. The proposed data-driven model predicts the output mixture’s composition based on reactor operating conditions, such as the temperature, steam-to-methane ratio, nitrogen-to-methane ratio, methane flow, and nickel catalyst mass. The network, a feedforward type, underwent training with a comprehensive dataset augmentation strategy that augments the primary experimental dataset through interpolation and theoretical simulations of the process, ensuring a robust model training phase. Additionally, it introduces weights to evaluate the relative significance of different data categories (experimental, interpolated, and theoretical) within the dataset. The optimal artificial neural network architecture was determined by evaluating various configurations, with the aim of minimizing the mean squared error (0.00022) and maximizing the Pearson correlation coefficient (0.97) and Spearman correlation coefficient (1.00).

A superheated steam fluidized bed dryer (SSFBD) in a self-heat recuperative configuration has a great potential of improving thermal efficiency of a lignite-fired power plant by recovering both of latent heat of vaporization of water kept in the fuel and part of sensible heat during the fuel processing. However, the optimal design of the dryer requires the fundamental knowledge of drying characteristics in respect to the individual properties of the utilized fuel. Experimental investigation to determine the correlation between a specific coal properties originated from geological background and its drying characteristics is thus the major concern in this paper. The investigated lignite is a representative of Turoszow deposit in Poland. Experimental attempts unveiling drying kinetics were carried out for 5 mm and 10 mm diameter spherical samples in the superheated steam atmosphere in the temperature range of 110 °C–170 °C. Simultaneous and continuous measurements of changes in weight, surface and interior temperatures and appearance on each tested sample were carried out for describing drying behavior. Analytical investigation was applied to explain the drying characteristics, which are strongly affected by the individual properties of coal and the inherent ash composition.