The increasing demand of solid-state energy storage requires improved technologies, such as Mg-ion batteries, to address safety and cost concers as well as the energy density limitations of state-of-the-art Li-ion battery technology, however, the realization of Mg-ion batteries hinges on the discovery of host materials that possess sufficiently high voltage, large energy capacity, and, most importantly, adequate mobility of the Mg2+ to ensure the viable intercalation cycling. To date, there has only been a limited number of examples demonstrating the feasibility of rechargeable Mg-ion batteries, motivating the current investigation to search over more broad chemical spaces for attainable multivalent (Mg2+
) intercalation cathode candidates. In this presentation, we show our detailed work, based on the robust automated high-throughput density functional calculations and the high-quality theoretical data from Materials Project, to systematically evaluate the electrochemical performance as well as the intercalating mobility of multivalent cation over several hundreds of host compounds. We also demonstrate our in-house theoretical approaches (e.g., diffusion path topology analysis) that have been designed and practiced to quantitatively estimate the multivalent cation mobility. Our study suggests that the matching between the intercalant site preference to the diffusion path topology of the host structure plays a decisive role to control mobility more than any other factor. Our “in silico” design and evaluation have found several promising Mg-ion cathode materials that possess improved Mg mobility (migration activation energy lower than 600meV) [2,3], and some of them have been confirmed by experimental research teams recently . The results demonstrate that the data-driven computational materials design is a realistic tool to the successful discover and optimize new materials for energy-dense multivalent batteries.
The work is entirely supported by the Department of Energy as part of the Joint Center for Energy Storage Research (JCESR).
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