• Energy Research

High-temperature electrolysis using solid oxide electrolysis cells (SOECs) is an innovative technology to temporarily store unused electrical energy from renewable energy sources. However, they show continuous performance loss during long-term operation, which is the main issue preventing their widespread use. In this work, we have performed the long-term stability tests up to 1000 h under steam and co-electrolysis conditions using commercial NiO-YSZ/YSZ/GDC/LSC single cells in order to understand the degradation process. The electrolysis tests were carried out at different temperatures and fuel gas compositions. Intermittent AC- and DC- measurements were performed to characterize the single cells and to determine the responsible electrode processes for the degradation during long-term operation. An increased degradation rate is observed at 800 °C compared to 750 °C under steam electrolysis conditions. Moreover, a lower degradation rate is noticed under co-electrolysis operation in comparison to steam electrolysis operation. Finally, the post-test analyses using SEM-EDX and XRD were carried out in order to understand the degradation mechanism. The delamination of LSC is observed under steam electrolysis conditions at 800 °C, however, such delamination is not observed during co-electrolysis operation. In addition, Ni-depletion and agglomeration are observed on the fuel electrode side for all the cells.

Physics-based models have proven to be effective tools for predicting the electrochemical behavior of Li-ion batteries. Among the various physics-based models, the Doyle-Fuller-Newman (DFN) model has emerged as the most widely employed. In response to certain limitations of the DFN model, the multiple particle-Doyle-Fuller-Newman (MP-DFN) model was introduced. The MP-DFN model utilizes multiple electrode particle sizes, addressing internal concentration heterogeneities and more realistically simulate diffusion processes in the electrodes. However, the model requires relatively high computational cost. This work introduces the Padé approximation for the MP-DFN model, resulting in the simplified MP-DFN model, leading to a faster simulation time. However, depending on battery design and operation conditions, this solution shows to have lower accuracy compared to the MP-DFN. To overcome these challenges, this study also introduces a hybrid MP-DFN model. This model uses a novel approach aimed at striking a balance between accuracy and computational speed. The hybrid MP-DFN model integrates both the finite difference method (FDM) and Padé approximation to effectively address the challenges posed by multiple particle sizes within the electrodes. The choice between FDM or the approximations for a specific particle in the electrode is determined by the scaled diffusion length.

The evaluation and enhancement of Li‐ion battery chemistries relies on detailed knowledge of the chemical processes occurring. Undesired side reactions have to be identified and correlated with used materials and operation/storage conditions, which requires suitable analytical tools, especially for minor and reactive species. Herein, a complementing experimental and theoretical method based on pulse electron paramagnetic resonance and density functional theory is presented using vanadyl ions as sensors for the chemical battery environment. The sensor is endogenously formed via cathode dissolution during battery operation. Probing the ligand sphere of the sensor, decomposition products of the electrolyte salt LiPF6are identified, which are proposed to comprise P(+V) and P(+III) constituents. Extensive conformational flexibility of the ligands is observed, which is investigated in terms of structural parameters and holistically with molecular dynamics simulations.

Perspective on recent improvements in experiment and theory towards realizing lithium metal electrodes with liquid electrolytes.

Ni-gadolinia-doped ceria (GDC) based electrode materials have drawn significant attention as an alternative fuel electrode for solid oxide cells (SOCs) owing to mixed ionic conductivity of GDC and high electronic and catalytic activity of Ni. Moreover, the catalytic activity and electrochemical performance of the Ni-GDC electrode can be further improved by dispersing small quantities of other metal additives, such as gold or molybdenum. Therefore, herein, we considered gold and molybdenum modified Ni-GDC electrodes and focused on the upscaling; hence, we prepared 5 × 5 cm2 electrolyte-supported single cells. Their electrochemical performance was investigated at different temperatures and fuel gas compositions. The long-term steam electrolysis test, up to 1700 h, was performed at 900 °C with −0.3 A·cm−2 current load. Lastly, post-test analyses of measured cells were carried out to investigate their degradation mechanisms. Sr-segregation and cobalt oxide formation towards the oxygen electrode side, and Ni-particle coarsening and depletion away from the electrolyte towards the fuel electrode side, were observed, and can be considered as a main reason for the degradation. Thus, modification of Ni/GDC with Au and Mo seems to significantly improve the electro-catalytic activity of the electrode; however, it does not significantly mitigate the Ni-migration phenomenon after prolonged operation.

Exploring the effects of cyclooctane dilution, deposition temperature, process duration, and precursor amount on a-Si:H film properties deposited from liquid trisilane in an atmospheric pressure CVD system.

AbstractBattery modeling has become increasingly important with the intensive development of Li‐ion batteries (LIBs). The porous electrode model, relating battery performances to the internal physical and (electro)chemical processes, is one of the most adopted models in scientific research and engineering fields. Since Newman and coworkers’ first implementation in the 1990s, the porous electrode model has kept its general form. Soon after that, many publications have focused on the applications to LIBs. In this review, the applications of the porous electrode model to LIBs are systematically summarized and discussed. With this model, various internal battery properties have been studied, such as Li+ concentration and electric potential in the electrolyte and electrodes, reaction rate distribution, overpotential, and impedance. When coupled with thermal, mechanical, and aging models, the porous electrode model can simulate the temperature and stress distribution inside batteries and predict degradation during battery operation. With the help of state observers, the porous electrode model can monitor various battery states in real‐time for battery management systems. Even though the porous electrode models have multiple advantages, some challenges and limitations still have to be addressed. The present review also gives suggestions to overcome these limitations in future research.