Modeling the effect of sulfur loading on the electrochemical performance of a lithium-sulfur battery
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Date
2023
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Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2023.
Abstract
Lithium-sulfur (Li-S) batteries are a promising solution for the efficient energy storage demand due to their high theoretical specific energy. Also, Li-S battery has inexpensive raw materials that are naturally abundant and non-toxic. For these advantages, they are considered an alternative to Li-ion batteries. However, they also have disadvantages, such as low cycle life and considerable self-discharge. The complex electrochemical reactions in Li-S batteries need to be better understood and defining the significant parameters and their effects are required to overcome these challenges. So different studies are focusing on finding the optimum cathode design parameters. This study investigates the effect of one of the critical cathode design parameters, sulfur loading, on the electrochemical performance of a Li-S battery. Although sulfur is an electrochemically active material in the cell, it negatively affects cell performance at high loadings since it is insoluble and insulating. In order to increase the conductivity and surface area, carbon is typically used in the cathode. However, an inert material like carbon can lower the energy density. So, the optimum cathode design for high S utilization and high energy density is still under investigation because of the Li-S battery’s complex mechanisms. For estimating the effect of S loading, computational algorithms were used in this study; simplified zero-dimensional and more complex one-dimensional electrochemical models were selected, and the models' response in predicting the impact of S loading on the discharge performance was compared. The zero- dimensional model could not capture the effect of S loading on the discharge capacity; however, the one-dimensional model successfully predicted the experimental trends. Furthermore, a sensitivity analysis was done on both models for different model parameters to discuss the reasons for the differences between the models.