Lithium peroxide crystallization in lithium-air batteries: A population balance modeling approach to enhance energy storage

Efficient energy storage is essential for maximizing renewable energy utilization. Lithium-air (or Li O 2 ) batteries offer high specific energy capacity, making them promising for large-scale applications. However, their efficiency is hindered by lithium peroxide (Li 2 O 2 ) buildup over the carbon-based electrode, obstructing the pores and leading to electrode passivation, which results in reduced discharge capacity. The morphology of Li 2 O 2 product, either crystalline or film-like, significantly affects the battery performance, particularly its discharge rate and cyclability. Understanding and predicting these structures is crucial for optimizing battery operation and minimizing reliance on costly additives, such as redox mediators that can degrade lithium anodes. This study employs population balance modeling and a statistical evaluation to analyze Li 2 O 2 crystallization during battery discharge, identifying reactant concentration and battery capacity as key factors influencing the process. The findings reveal that the interaction of these variables also impacts the final Li 2 O 2 concentration. By focusing on the toroid morphology, the study provides valuable insights into how the application of population modeling can be a powerful tool in understanding the formation of the Li 2 O 2 product during Li O 2 battery discharge mode. Therefore, these results contribute to advancing energy storage technologies by offering strategies to control crystallization and enhance the overall battery performance. • Lithium peroxide buildup obstructs the electrode pores; therefore, its morphology can affect the battery discharge cycle. • Predicting the formation and morphology of lithium peroxide is crucial for optimizing battery operation. • Population balance modeling is a powerful methodology to predict lithium peroxide formation during the battery discharge. • Population modeling that focuses on toroid morphology is influenced by reactant concentration and battery capacity.