Molecular modelling of components for rechargeable metal-ion batteries
A. Tadjer*, H. Rasheev*, Y. Danchovsky*, L. Borislavov, N. Ilieva* and R. Stoyanova*
As the steady increase in complexity of human society leads to ever growing energy demands, research for better and cheaper materials for energy storage and conversion is at its highest. In recent years, the global climate change effects are more and more prominent and this places significant emphasis on low(no)-carbon energy and its clean storage. So far, the best technology for small to medium energy storage is the Li-ion battery but concerns like high cost and limited resources, as well as safety issues, are perpetuating new developments in the quest for better materials for all battery components. Computational chemistry can be a valuable ally in the search for new materials for clean energy storage. Molecular modelling can help elucidating the intimate details of the processes occurring in the batteries at the atomistic level and aid the design of novel compounds and architectures offering new perspectives for the next generation batteries production. Machine learning and statistical analysis can be harnessed to speed up the research. The endeavours of our group in modelling components and processes in metal-ion batteries will be overviewed.
The authors from CARiM’s Research