High-Throughput DFT-Based Discovery of Next Generation Two-Dimensional (2D) Superconductors.

Area of Science:

• Condensed Matter Physics
• Materials Science
• Computational Materials Science

Background:

• Conventional superconductors are typically found through systematic searches.
• Two-dimensional (2D) superconductors have garnered recent research interest.
• High-throughput computational methods accelerate materials discovery.

Purpose of the Study:

• To systematically screen 2D materials for superconductivity using high-throughput density functional theory (DFT).
• To identify novel 2D superconducting materials with potential applications.
• To provide a computational and experimental roadmap for 2D superconductor research.

Main Methods:

• Employed a high-throughput DFT workflow to screen over 1000 2D materials from the JARVIS-DFT database.
• Calculated electron-phonon coupling and superconducting transition temperature (Tc) using the McMillan-Allen-Dynes formula for 165 materials.
• Performed experimental measurements of Tc for selected layered superconductors.

Main Results:

• Identified 34 dynamically stable 2D materials with Tc above 5 K.
• Discovered the previously unreported Mg2B4N2 with a calculated Tc of 21.8 K.
• Found other promising materials including W2N3, NbO2, ZrBrO, TiClO, NaSn2S4, and Mg2B4C2.

Conclusions:

• The high-throughput workflow effectively identifies potential 2D superconductors.
• The study provides valuable data to guide future computational and experimental investigations.
• Experimental validation of selected materials aligns with computational predictions, confirming the workflow's utility.