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Area of Science:

  • Materials Science
  • Condensed Matter Physics
  • Solid-State Chemistry

Background:

  • Metal borides are promising candidates for phonon-mediated superconductors.
  • Discovering new bulk phases with high superconducting transition temperatures (Tc) beyond MgB2-type structures is challenging.

Purpose of the Study:

  • To propose a new structural prototype for layered borides.
  • To screen a large number of potential boride superconductors using computational methods.
  • To identify stable boride compounds with high Tc.

Main Methods:

  • Developed a novel honeycomb-ruby-honeycomb trilayer boron framework.
  • Employed a machine learning interatomic potential-accelerated high-throughput screening workflow.
  • Utilized first-principles calculations for validation and analysis.

Main Results:

  • Screened over 120,000 candidates, identifying 38 dynamically stable, near-hull compounds.
  • Achieved a maximum superconducting transition temperature (Tc) of 28.9 K for LiTiRuB18.
  • Found a strong positive correlation between Tc and the B-p density of states at the Fermi surface.

Conclusions:

  • Expanded the structural diversity of layered borides.
  • Established an efficient data-driven route for discovering bulk boride superconductors at ambient pressure.
  • Highlighted the role of metal-regulated soft B-M hybrid modes in electron-phonon coupling.