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  1. Using a starlike Be 6 Au 7 − cluster as a building block and following the bottom-up strategy, an intriguing two-dimensional (2D) binary s-block metal Be 2 Au monolayer with a P 6/ mmm space group was theoretically designed. Both the Be 6 Au 7 − cluster and the 2D monolayer are global minima featuring rule-breaking planar hexacoordinate motifs (anti-van't Hoff/Le Bel arrangement), and their high stabilities are attributed to good electron delocalization and electronic-stabilization-induced steric force. Strikingly, the Be 2 Au monolayer is a rare Dirac material with two perfect Dirac node-loops in the band structure and is a phonon-mediated superconductor with a critical temperature of 4.0 K. The critical temperature can be enhanced up to 11.0 K by applying compressive strain at only 1.6%. This study not only identifies a new binary s-block metal 2D material, namely Be 2 Au, which features planar hexacoordination, and a candidate superconducting material for further explorations, but also provides a new strategy to construct 2D materials with novel chemical bonding. 
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  2. High-throughput computational screening of materials with targeted thermal conductivity ( κ ) plays an important role in promoting the advancement of material design and enormous applications. The Slack model has been widely applied for the fast evaluation of κ with minimal time and resources, showing the potential capability of high-throughput screening of κ . However, after examining the Slack model on a large set of 353 materials, a huge discrepancy is found between the predicted κ and the correspondingly measured κ in experiments for some materials in addition to the generally overestimated κ by the Slack model. Thus, it is necessary to optimize the Slack model for efficiently and accurately evaluating κ . In this study, based on the high-throughput comparison of the κ predicted by the Slack model using elastic properties and those measured in experiments, an optimized Slack model is proposed. As a result, the κ predicted by the optimized Slack model agrees reasonably with the κ measured in experiments, which is much better than the previous prediction. The optimized Slack model proposed in this study can be used for further high-throughput computational evaluation of κ , which would be helpful for finding materials of ultrahigh or ultralow κ with broad applications. 
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