Autonomous Discovery of Materials for Intercalation Electrodes

The development of automated computational tools is required to accelerate the discovery of novel battery materials. In this work, we design and implement a workflow, in the framework of Density Functional Theory, which autonomously identifies materials to be used as intercalation electrodes in batteries, based on descriptors like adsorption energies and diffusion barriers. A substantial acceleration for the calculations of 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 to calculate. We have applied this workflow to discover new cathode materials for Mg batteries, where two of these materials display a threefold increase in the potential of the Chevrel phase, the state‐of‐the‐art cathode in commercial prototype Mg batteries. Do the math: A workflow, in the framework of Density Functional Theory, has been designed and implemented that automatically calculates crucial battery properties. The automated calculations include the thermodynamic and mechanical stability, Open Circuit Voltages as well as kinetic barriers obtained through the Nudged Elastic Band method. The workflow was able to discover interesting candidates for magnesium insertion cathode materials without the need of user intervention.