Simulation of a Patterned Core–Shell Double-Walled Carbon Nanotube with an Optimal Heat Capacity as Efficient Thermal Conductivity Modules

Abstract

We performed molecular dynamics simulations to determine the equilibrium configuration of designed double-walled carbon nanotubes (DWCNTs) and bundle carbon nanotubes. With the nanotubes in the zigzag structure, the potential energy of the interaction between the core and shell tubes patterned at different inner-tube sizes was investigated. Thermodynamic properties such as the heat capacity and relative orientation of the inner/outer tubes in DWCNTs were computed and elucidated. Our simulations, consistent with the experimental results, also predicted a particular core−shell configuration with a higher surface energy and, hence, a higher heat capacity (about 2 times) compared to the normal DWCNT configuration. The interaction potential energy between the pair of core and shell tubes predicts a van der Waals depth, spanning a circular path, and indicates the accessibility to a higher number of configurational states as the radius of the inner tube decreases. The final cross sections of the patterned coaxis DWCNTs are distorted, and their shapes lead to asymmetric tubes with oval shapes. These configurations agree with other observations reported in theoretical and experimental investigations. Single-walled and patterned triple-walled carbon nanotubes (SWCNTs and TWCNTs) were simulated to confirm and make a sound baseline for DWCNTs. This was included also the simulation of SWCNTs, DWCNTs, and TWCNTs with metallic and semiconducting features. Technologically made available such core−shell nanotubes materials as conductors of electricity would find efficient usage in the applications like microelectronic devices that are encountered with issues of high heat dissipation and thermal conductivity rates.

Characteristics and Applicability Analysis of Nanomorphological Structures for Chemosensors: A Systematic Review

“…DWCNT (double-walled carbon nanotube)-related studies include energy transfer, neuronal network engineering, optimal heat capacity, high-conductivity flexible electrodes, etc. [88][89][90][91][92][93].…”