Machine learning accelerated discovery of superconducting two-dimensional Janus transition metal sulfhydrates

Abstract

The MoSH monolayer, one of the Janus transition metal sulfhydrates synthesized by stripping the top-layer S of MoS2 and replacing it with H atoms [Wan et al., ACS Nano 15, 20319 (2021)], has been predicted to host strong coupling two-gap superconductivity with a calculated critical temperature Tc of about 28.58 K at atmospheric pressure. In this work, by using machine learning aided high-throughput calculations, we narrow down 180 possible configurations of two-dimensional Janus transition metal sulfhydrates (MXH monolayers, where M=transition metal group elements and X=S, Se, and Te) to 20 stable metals. Among them, we identify six low-energy monolayers that are potential high-Tc superconductors. Notably, the 1T-TiSH monolayer stands out with the highest Tc of approximately 48 K, surpassing the superconducting properties of 1H-MoSH (Tc=28.58 K) and the well-known MgB2 superconductor (Tc=39 K). By solving the anisotropic Migdal-Eliashberg equations, we find that 1T-TiSH naturally exhibits a one-gap superconducting nature with strong electron-phonon coupling (λ=2.79) originating from the interactions of Ti dxz,yz orbitals and in-plane vibrations, which is different from and better than the 1H-MoSH monolayer (λ=1.60). The presented results enrich families of Janus transition metal sulfhydrates and accelerate the design of novel two-dimensional superconductors.

Source-reported materials — not catalogue approval

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