Nowadays, the usage of most appliances and products would not be possible without portable and affordable electrochemical energy storage (i.e. battery). In this regard batteries are ubiquitous, however, still, further advances in capacity, lifetime, and cost of batteries is required to open up new possibilities and markets. In order to meet the necessary requirements, the replacement of battery components (e.g. graphite) is of imperative importance for future battery development. In our work, we investigate the alternative electrode materials (e.g., Li-metal, Si, SnO2), which are the promising candidate for next-generation electrochemical energy storage.

We use variety of computational methods and techniques, such as ab-initio density functional theory (DFT) calculations, finite element method (FEM) and machine learning.