Rechargeable solid-state lithium-metal batteries (SSLMBs) offer tremendous promise as a safe and energy-dense storage technology for use in electric transportation, robotics, and portable electronics. Lithium argyrodites (e.g., Li7PS6, and its halogen-doped derivatives) have emerged as a lucrative class of solid-state electrolytes (SSEs) for SSMLBs owing to their high Li-ion conductivity (~10-3 S/cm), good elastic stiffness (~30 GPa), and low flammability. Despite their promise, SSMLBs based on sulfide electrolytes remain far from commercialization due to lack of atomic-scale understanding of ion-conduction, charge transport, structural evolution, and interfacial reactions (e.g., dendrite growth, electrolyte decomposition etc.). In this talk, I will demonstrate how a synergistic integration of machine learning, quantum calculations, ab initio/classical reactive molecular dynamics simulations, and synthesis/characterization experiments can pave the path towards advancing such knowledge. Specifically, I will highlight our recent success in utilizing accurate materials modeling to design fluorine-containing argyrodite electrolytes that simultaneously offer enhanced (a) Li-ion conduction facilitated by unique Li- disorder induced by fluorine and other halogen co-dopants, and (b) stability against Li-anode owing to formation of a stable solid-electrolyte interface containing conductive species (Li3P), alongside LiCl and LiF. Subsequently, I will showcase how we leveraged supervised machine learning empowered by genetic algorithms to develop an accurate, robust and transferable classical reactive force field (ReaxFF) for Li-P-S system from an extensive dataset obtained from quantum calculations and/or experiments. Our newly developed ReaxFF can accurately capture ion- transport, structural evolution, chemical reactions, interfacial processes, and effects of applied electric field relevant to SSLMBs. I will discuss these results in the context of accelerating design of novel solid-state electrolytes for long-lived, stable, and high-energy density SSLMBs.

Atomic-scale understanding of ion-transport and interfacial stability in lithium argyrodite electrolytes for solid-state lithium-metal batteries

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ACS Fall 2022

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