在碳纳米锥内构建锥形螺旋

IF 2.9 3区 化学 Q3 CHEMISTRY, PHYSICAL
Yuliang Yin, Qinzheng Yu, Hongjin Fu and Yunfang Li
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引用次数: 0

摘要

分子动力学模拟表明,聚对苯乙烯(PPP)链可以在单壁碳纳米锥(cnc)的密闭空间内形成规则的锥形螺旋。结合系统总势能(包括各能量分量)和形成的锥形螺旋结构参数的变化,讨论PPP链的易位位移,深入探讨微观结构演化、驱动力和动力机制。此外,还进一步研究了链长、锥角、温度、苯环链数和连接位置对螺旋包封的影响。该方法可能为聚合物链构造规则的锥形螺旋提供新的途径,并最终应用于电子纳米器件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Constructing conical helices inside carbon nanocones†

Constructing conical helices inside carbon nanocones†

Molecular dynamics simulations demonstrate that regular conical helices of poly(para-phenylene) (PPP) chains can be constructed inside the confined space of single-walled carbon nanocones (CNCs). The translocation displacement of the PPP chain combined with the change of the system total potential energy including each energy component and structural parameters of the formed conical helix is discussed to deeply explore the microstructure evolution, driving forces and dynamic mechanisms. In addition, the influence of chain length, cone angle, temperature, chain number, linked position of benzene rings and the form of Lennard-Jones potential on the helical encapsulation is further studied. The proposed method may provide a new way for constructing regular conical helices from polymer chains, with potential applications in electronic nanodevices.

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来源期刊
Physical Chemistry Chemical Physics
Physical Chemistry Chemical Physics 化学-物理:原子、分子和化学物理
CiteScore
5.50
自引率
9.10%
发文量
2675
审稿时长
2.0 months
期刊介绍: Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.
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