Model-based design of sustainable post-Li-ion batteries

In this contribution, we present a recently developed modelling framework used to screen safe, low-cost aqueous electrolyte materials and simulate their dynamic spatiotemporal performance in post-Li-ion battery cells. Li-ion batteries have enabled the green shift towards a renewable energy infrastructure and sustainable transportation network in Europe, and they will continue to play a central role in the future. However, the ambitions outlined in the European Green Deal cannot be achieved by relying on Li-ion batteries alone. High-energy batteries based on safe and abundant materials like Zn and Mg can help meet the growing demand for electrochemical energy storage. It has been shown that these materials can be combined with mild aqueous electrolytes – including seawater – and oxygen-depolarized cathodes to create low-cost metal-air batteries with high energy density. The promise of such batteries is clear; however, their performance has historically been limited by a host of challenges linked to the degradation of the battery materials and structures. The Battery2030+ Roadmap highlights the need for model-based design tools to better understand the battery interfaces, identify totally new materials, and accelerate the development of new chemistries. Over the past 10 years, cell-level battery models have rapidly improved in both the quality and complexity of the insights they provide. However, these models have been developed mostly to study Li-ion batteries and struggle to resolve all the complex processes occurring in metal-air batteries with aqueous electrolytes. We discuss recent advances in electrochemical continuum modelling and demonstrate how they can be applied to simulate the performance of metal-air batteries with novel electrolyte materials. Pulling from a vast database of material properties, we identify promising novel electrolyte compositions, simulate their performance at the cell-level, and experimentally validate the predictions. The results can be used to implement coupled theoretical-experimental workflows for accelerated battery development.