AI 中文总结
本文利用机器学习原子间势构建1620种金属烯三明治异质结构，筛选出1208种动态稳定结构，明确MoSe₂等的稳定效果，为金属烯合成提供系统指导。
AI 中文摘要
金属烯具有诱人的性能，但将其稳定在单原子层相是合成面临的挑战。近期一项实验表明，范德华挤压法可在MoS₂三明治中稳定特定金属烯，这项开创性工作推动了系统研究，但这类研究实验上不可行，第一性原理建模也难以实现。本文借助通用机器学习原子间势，构建了包含6种不同三明治层和45种金属的1620个金属烯三明治异质结构，通过声子计算发现1208个动态稳定结构。研究发现过渡金属二硫族化合物，尤其是MoSe₂，对金属烯的稳定效果极佳，其中褶皱六方和蜂窝状晶格稳定性最高。本文还通过密度泛函理论分子动力学模拟评估了部分异质结构的室温热稳定性，揭示了金属烯稳定化的物理化学因素，为未来应用的合成提供了系统见解，可指导并加速合成进程。
英文摘要
Metallenes have appealing properties, but stabilizing them in a monolayer phase poses challenges for their synthesis. A recent experiment showed that the van der Waals squeezing method can stabilize certain metallenes in a MoS2 sandwich. This pioneering work motivates systematic studies, but such studies are experimentally impractical, while first-principles modeling remains prohibitive. Here, armed with universal machine-learning interatomic potentials, we constructed 1620 metallene sandwich heterostructures containing 6 different sandwich layers and 45 metals. We performed phonon calculations, which revealed 1208 dynamically stable structures. We found that transition-metal dichalcogenides, particularly MoSe2, are highly effective in stabilizing metallenes. Specifically, buckled hexagonal and honeycomb crystal lattices exhibit the greatest stability. We further evaluated the thermal stability of selected heterostructures with density-functional theory molecular dynamics simulations at room temperature. By uncovering the physical and chemical factors governing the stabilization of metallenes, our results provide systematic insights to guide and accelerate synthesis for future applications.
