Machine learning accelerated discovery of superconducting two-dimensional Janus transition metal sulfhydrates
Jingyu Li, Liuming Wei, Xianbiao Shi, Lan‐Ting Shi, Jianguo Si, Pengfei Liu, Bao‐Tian Wang
Abstract
The MoSH monolayer, one of the Janus transition metal sulfhydrates synthesized by stripping the top-layer S of ${\mathrm{MoS}}_{2}$ 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 ${T}_{c}$ 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 ($MX\mathrm{H}$ monolayers, where $M=\text{transition}$ metal group elements and $X=\mathrm{S}$, Se, and Te) to 20 stable metals. Among them, we identify six low-energy monolayers that are potential high-${T}_{c}$ superconductors. Notably, the $1T$-TiSH monolayer stands out with the highest ${T}_{c}$ of approximately 48 K, surpassing the superconducting properties of $1H$-MoSH (${T}_{c}=28.58$ K) and the well-known ${\mathrm{MgB}}_{2}$ superconductor (${T}_{c}=39$ 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 ($\ensuremath{\lambda}=2.79$) originating from the interactions of Ti ${d}_{xz,yz}$ orbitals and in-plane vibrations, which is different from and better than the $1H$-MoSH monolayer ($\ensuremath{\lambda}=1.60$). The presented results enrich families of Janus transition metal sulfhydrates and accelerate the design of novel two-dimensional superconductors.