Autonomous Discovery of Materials for Intercalation Electrodes

The development of automated computational tools is required to accelerate the discovery of novel batterymaterials. In this work, we design and implement a workflow, in the framework of Density FunctionalTheory, which autonomously identifies materials to be used as intercalation electrodes in batteries, basedon descriptors like adsorption energies and diffusion barriers. A substantial acceleration for the calculationsof the kinetic properties is obtained due to a recent implementation of the Nudged Elastic Bands (NEB)method, which takes into consideration the symmetries of the system to reduce the number of images tocalculate. We have applied this workflow to discover new cathode materials for Mg-ion batteries, wheretwo of these materials display a threefold increase in the potential of the Chevrel phase, the state-of-the-artcathode in Mg-ion batteries.