Rechargeable Li-ion batteries are the workhorse behind today’s mobile electronics industry, currently powering hundreds of millions of laptops, cameras, and phones worldwide. Unfortunately, we are approaching a limit of what can be achieved with the current Li-ion battery technology. One of the most promising scientific approaches to go beyond Li-ion battery technology is to implement batteries with a multivalent chemistry such as Mg2+, where multiple electrons are transported per ion, achieving, in theory, unprecedented energy density at cheaper cost.
The path to fully functioning and cost competitive Mg-ion batteries starts by untangling a few but complex scientific puzzles. One of the most relevant aspects is understanding the mechanism of reversible plating and stripping of Mg at the metal anode/electrolyte interface during battery operation. So far, reversible Mg plating has been achieved with only a narrow class of electrolytes, inorganic or organic magnesium aluminum chloride salts dissolved in ethereal solutions. The Mg analogues to the commercial Li electrolytes instantaneously decompose and passivate the Mg metal anode surface preventing further electrochemical reaction, consequently blocking the battery. A complete understanding at the atomic scale of the electrochemical processes of plating and stripping at the Mg anode // electrolyte interface is still required to steer the direction of next-generation Mg-based electrolytes that can help realize the underlying promise of Mg-ion batteries.
With this ALCC award, we propose a logical approach to gain a fundamental understanding of the crucial aspects governing both stripping and deposition in Mg-ion batteries using large-scale accurate first principles density functional theory molecular dynamics and rare-event techniques. The atomic complexity involved as well as the energetic accuracy required in these simulations, specifically representing a metal interfacing with salt and solvent molecules under the bias of an applied potential at room temperature, justify the need of large computational infrastructures such as the BG/Q at the Argonne Leadership Computing Facility.
The outcomes of this study will provide important models to support and validate the interpretation of complex experiments undergoing concurrently in the Joint Center for Energy and Storage based at Argonne National Lab and funded by the Department of Energy.
