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

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.