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一种群体智能建模方法揭示了限制在碳纳米管内的稀有气体团簇构型。

A swarm intelligence modeling approach reveals noble gas cluster configurations confined within carbon nanotubes.

作者信息

Owais Cheriyacheruvakkara, John Chris, Swathi Rotti Srinivasamurthy

机构信息

School of Chemistry, Indian Institute of Science Education and Research Thiruvananthapuram (IISER TVM), Vithura, Thiruvananthapuram 695551, India.

出版信息

Phys Chem Chem Phys. 2020 Sep 23;22(36):20693-20703. doi: 10.1039/d0cp03014g.

Abstract

Confinement of atoms and molecules brings forth fascinating properties to chemical systems that are otherwise not known in the bulk. Carbon nanotubes (CNTs) and fullerenes are excellent hosts for probing the confinement effects. Herein, we explore the potential energy surfaces of large noble gas clusters, Ngn (Ng = He, Ne and Ar; n = 10, 20, 30, 40, and 50), in the confines of CNTs of various lengths. Our implementation involves integrating the continuum approximation for CNTs with the well-known swarm intelligence technique, particle swarm optimization (PSO), followed by a deterministic local optimization. Global search techniques such as PSO have been increasingly utilized in recent times to track down minimum energy configurations on highly rugged potential energy surfaces. Aside from the position vectors of the noble gas atoms, we have considered the radius of the CNTs as a design variable. Such an approach enabled us to predict the optimal CNT radii for the encapsulation of each of the clusters. Confined cluster geometries ranging from linear, zig-zag, and double-helical to spiral configurations are obtained on encapsulation, in sharp contrast to their bare cluster geometries. On increasing the CNT length, our approach yielded quasi-linear geometries, suggesting that the length of the CNTs plays a crucial role in determining the stable cluster configurations on confinement.

摘要

原子和分子的受限为化学体系带来了在宏观状态下未知的迷人性质。碳纳米管(CNTs)和富勒烯是探究受限效应的理想主体。在此,我们研究了各种长度的碳纳米管中大型稀有气体团簇Ngn(Ng = He、Ne和Ar;n = 10、20、30、40和50)的势能面。我们的实现方法包括将碳纳米管的连续介质近似与著名的群体智能技术——粒子群优化(PSO)相结合,然后进行确定性局部优化。近年来,诸如PSO之类的全局搜索技术越来越多地被用于在高度崎岖的势能面上寻找最低能量构型。除了稀有气体原子的位置矢量外,我们还将碳纳米管的半径作为一个设计变量。这种方法使我们能够预测封装每个团簇的最佳碳纳米管半径。封装后得到了从线性、锯齿形、双螺旋到螺旋构型的受限团簇几何形状,这与它们的裸团簇几何形状形成鲜明对比。随着碳纳米管长度的增加,我们的方法产生了准线性几何形状,这表明碳纳米管的长度在确定受限状态下稳定的团簇构型中起着关键作用。

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