High-throughput screening for boride superconductors
Shiya Chen, Zepeng Wu, Zhen Zhang, Shunqing Wu, Kai-Ming Ho, Vladimir, Antropov, Yang Sun

TL;DR
This study uses high-throughput density functional calculations to identify and predict stable boride superconductors, including new ternary compounds with potential for experimental validation and diverse structural motifs.
Contribution
The paper introduces a rapid computational workflow employing the frozen phonon method to discover and analyze stable boride superconductors, including novel ternary systems.
Findings
23 stable boride candidates identified
Superconductivity confirmed in known systems and predicted in new ternary borides
Ta(MoB)$_2$ exhibits the highest T_c of ~12K
Abstract
A high-throughput screening using density functional calculations is performed to search for stable boride superconductors from the existing materials database. The workflow employs the fast frozen phonon method as the descriptor to evaluate the superconducting properties quickly. 23 stable candidates are identified from the screening. For almost all found binary compounds, the superconductivity was obtained earlier experimentally or computationally. For ternary borides, previous studies are very limited. Our extensive search among ternary systems confirmed superconductivity in known systems and found several new compounds. Among these discovered superconducting ternary borides, Ta(MoB) shows the highest superconducting temperature of ~12K. Most predicted compounds were synthesized previously; therefore, our predictions can be examined experimentally. Our work also demonstrates that…
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Taxonomy
TopicsMachine Learning in Materials Science · Iron-based superconductors research · Inorganic Chemistry and Materials
