Deep learning assisted exploration of superionic states and melting temperatures in Li-Sn superconductors

Abstract

The unique spatial arrangement of Li atoms in Li-rich compounds induces properties on Li-rich compounds, including interstitial quasiatoms, superconductivity, and superionic states. However, the dependence of increasing Li concentration on electron-phonon coupling (EPC) and superionic behavior at high pressure remains inadequately understood. Here, we systematically investigate the crystal structure of the LixSn (x = 1–8) compound at 0–150 GPa using structure prediction and first-principles calculations. Band calculations reveal that the P6/mmm phases of LixSn (x = 1–7) commonly exhibits Dirac points, van Hove singularities, and flat bands. Superconducting critical temperatures (Tc) were also investigated, with LiSn exhibiting a Tc of 9.3 K at 0 GPa. We further analyzed the relationship between superconductivity and EPC strength, phonon softening, linewidth, and density of states. Deep learning molecular dynamics simulations of LiSn, Li2Sn, Li3Sn, and Li4Sn demonstrate that when the Li concentration exceeds twice that of Sn, Li atoms undergo melting while Sn remains solid, indicating the emergence of a superionic state. Among them, Li3Sn exhibits the highest melting temperature of 1013 K. These findings enrich the crystal structure of Li-Sn compounds and provide a theoretical basis for constructing superconductors with a Kagome lattice and superionic states.

Source-reported materials — not catalogue approval

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