Abstract: Neutral, anionic, and cationic B3Aln0/−/+ (n = 2–6) clusters were systematically explored using density functional theory and coupled cluster CCSD(T) methods to investigate the structural evolution of small mixed aluminum–boron clusters. The lowest energy structures of these clusters were obtained using an unbiased global minimum search, and their structural growth behaviors are discussed. The three boron atoms in B3Aln0/−/+ preferentially form a stable triangle, with additional Al atoms occupying the periphery of the boron triangle. For small clusters of n ≤ 3, the studied clusters show planar two–dimensional configurations. When n ≥ 4, the clusters prefer three–dimensional configurations. Average binding energies, fragmentation energies, second–order differences, HOMO–LUMO gaps, ionization potentials and electron affinities are discussed in detail. For cationic B3Aln+ (n = 2–6) clusters, the even n systems are more stable than the odd n systems, while the stabilities of neutral B3Aln and anionic B3Aln− clusters do not change significantly with growing n. The infrared spectrum and photoelectron spectroscopy of these clusters are simulated, which will be useful for future experimental research. We also compare the chemical bonding of neutral B3Aln (n = 2–6) clusters with their ionic clusters by AdNDP analysis. Graphic Abstract: [Figure not available: see fulltext.]
Bibliographical noteFunding Information:
L. M. W, D. Z, and L.–M. Y. gratefully acknowledge support from the National Natural Science Foundation of China (21673087, 21873032, 21903032, 22073033), startup fund (2006013118 and 3004013105) from Huazhong University of Science and Technology, and the Fundamental Research Funds for the Central Universities (2019kfyRCPY116). The authors thank the Minnesota Supercomputing Institute (MSI) at the University of Minnesota for supercomputing resources. The work was carried out at LvLiang Cloud Computing Center of China, and the calculations were performed on TianHe-2.
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- AdNDP analysis
- Boron–aluminum mixed clusters
- CCSD(T) method
- Chemical bonding
- Density functional theory (DFT)