文献类型：期刊文献

英文题名：Growth Patterns of Carbon Clusters C n (n=2-60) Identified via ABCluster Searching and DFT Benchmarking

作者：Jia, Liting[1];Wang, Yu[1];Tian, Xu[1];Wang, Siyu[1];Wang, Xiao[1];Zhang, Meng[1]

机构：[1]East China Univ Sci & Technol, Sch Phys, Shanghai 200237, Peoples R China

年份：2024

卷号：128

期号：38

起止页码：8009

外文期刊名：JOURNAL OF PHYSICAL CHEMISTRY A

收录：;EI(收录号：20243817055057);WOS:【SCI-EXPANDED(收录号:WOS:001310818600001)】；

基金：This work is financially supported in part by the University Student Innovation Program of China (Grant No. S202210251102).

语种：英文

外文关键词：Clustering algorithms

摘要：Recently, novel algorithms and enhanced computational capabilities have created unprecedented opportunities to precisely determine the geometric structures of clusters through theoretical calculations. In this study, we extensively investigated and characterized the geometric arrangements of the carbon clusters C-n (n = 2-60), employing the efficient ABCluster algorithm in conjunction with the gradient-corrected PBE and higher-accuracy B3LYP hybrid functional in density functional theory (DFT). New structures and a discernible structural growth pattern have been discovered. We observed a distinct preference in carbon clusters that transform from the linear chains (n = 2-9) to closed single-ring and planar structures (n = 10-27) and finally evolve to carbon cages (n = 28-60). A shortcut to construct the cage clusters was unveiled by inserting or rotating specific atoms within a distinct structural unit. The research results obtained from combining ABCluster with DFT calculations offer valuable new insights into the growth mechanisms and evolutionary trajectories of carbon clusters, providing a crucial theoretical framework for the development of innovative carbon-based materials and their potential applications.