Kai Wang, Jun Zhao, Junji Guo, Shanbao Chen, Yapeng Zhao, Jiaye Chen, Yarui Wang, Le Liu, Chaoyong Wang, Zhiqing Liu
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引用次数: 0
摘要
由于在下一代微/纳米电子器件和功能材料中的潜在应用,基于锗(Ge)的磁性团簇正受到越来越多的关注。在这项工作中,我们报告了尺寸为 n = 3-20 的 CrMnGen 的结构、电子和磁性能。铬和锰的过渡金属(TMs)倾向于聚集在一起并被 Ge 原子包围。n≤8的小尺寸晶簇更倾向于采用双锥结构作为图案,多余的Ge原子被吸收到表面。从 n = 9 开始,内部有一个 TM 原子的结构开始出现并一直持续到 n = 16,而对于 n = 17-20 的较大尺寸,两个 TM 原子被 Ge 原子完全包覆,形成内面体结构。Hirshfeld 种群分析表明,除尺寸 3 和 6 外,Cr 原子始终是电子供体,而 Mn 原子始终是受体。这些团簇的平均结合能随团簇大小 n 的增大而增大,与 CrMnSin(n = 4-20)团簇的趋势非常相似,这表明形成大尺寸团簇是有利的。CrMnGen(n = 6、13、16、19 和 20)簇倾向于表现出铁磁性的 Cr-Mn 耦合,而其余簇则是铁磁性的。
Magnetic properties of CrMnGen (n = 3–20) clusters
Due to the potential applications in next-generation micro/nano electronic devices and functional materials, magnetic germanium (Ge)-based clusters are receiving increasing attention. In this work, we reported the structures, electronic and magnetic properties of CrMnGen with sizes n = 3–20. Transition metals (TMs) of Cr and Mn tend to stay together and be surrounded by Ge atoms. Small sized clusters with n ≤ 8 prefer to adopt bipyramid-based structures as the motifs with the excess Ge atoms absorbed on the surface. Starting from n = 9, the structure with one TM atom interior appears and persists until n = 16, and for larger sizes n = 17–20, the two TM atoms are full-encapsulated by Ge atoms to form endohedral structures. The Hirshfeld population analyses show that Cr atom always acts as the electron donor, while Mn atom is always the acceptor except for sizes 3 and 6. The average binding energies of these clusters increase with cluster size n, sharing a very similar trend as that of CrMnSin (n = 4–20) clusters, which indicates that it is favorable to form large-sized clusters. CrMnGen (n = 6, 13, 16, 19, and 20) clusters prefer to exhibit ferromagnetic Cr–Mn coupling, while the remaining clusters are ferrimagnetic.
期刊介绍:
This distinguished journal publishes articles concerned with all aspects of computational chemistry: analytical, biological, inorganic, organic, physical, and materials. The Journal of Computational Chemistry presents original research, contemporary developments in theory and methodology, and state-of-the-art applications. Computational areas that are featured in the journal include ab initio and semiempirical quantum mechanics, density functional theory, molecular mechanics, molecular dynamics, statistical mechanics, cheminformatics, biomolecular structure prediction, molecular design, and bioinformatics.