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Effect of bending buckling of carbon nanotubes on thermal conductivity of carbon nanotube materials
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View: Figures


Image of FIG. 1.
FIG. 1.

(Color online) A schematic of the simulation process of bending (10, 10) CNT to a bending angle Θ = 60° (a) and snapshots of buckled structures at various values of Θ (b).

Image of FIG. 2.
FIG. 2.

(Color online) An illustration of the definition of the local angle Ψ (a), the dependence of Ψ on the unit cell index p counted from the center of the CNT (b), and the dependence of the buckling angle χ on the bending angle Θ (c). In (a), P and A are the positions of the centers of mass of pth and (p-1)th unit cells, respectively. The error bars show the standard deviation for 50 different configurations at equilibrium.

Image of FIG. 3.
FIG. 3.

(Color online) The dependence of the thermal conductance of the bending buckling kink on the buckling angle predicted for (10,10) CNTs in atomistic simulations. Square symbols show the values found in atomistic simulations performed in the present work and the triangle symbol shows the value recalculated from Ref. 22. Solid curve represents a power law fit to the data points given by Eq. (3).

Image of FIG. 4.
FIG. 4.

(Color online) Schematic sketch of the mesoscopic representation of a nanotube i as a chain of cylindrical segments defined by nodes j (a) and the distribution of temperature along the nanotube in the vicinity of the buckling kink (b). The solid circles show the mesoscopic nodes, with nodes where buckling occurs colored red. In the mesoscopic model, the buckling angle is defined as an angle between axes of segments adjacent to the buckling kink. Buckling kinks and CNT ends divide the nanotubes into several buckling-free parts. Temperature is assumed to be constant within any buckling-free part of the nanotube and exhibits a jump at buckling kinks.

Image of FIG. 5.
FIG. 5.

(Color online) Fraction of nanotubes with a given number of buckling kinks, , in samples A (red open squares) and B (green open circles) (a) and a part of sample A shown in Fig. 6 with positions of buckling kinks marked by dark (red online) color (b). The average number of buckling kinks per buckled nanotube, , and the fraction of buckled nanotubes, , are marked in (a) by the solid red square and green circle for samples A and B, respectively.

Image of FIG. 6.
FIG. 6.

(Color online) Steady-state temperature distribution established in a mesoscopic sample A and used in the calculation of the thermal conductivity of the network structure. The sample has dimensions of 500 × 500 × 100 nm3 and is composed of 7829 (10,10) CNTs with nm and material density of 0.2 g cm−3. The nanotubes are colored by their temperature. The temperature distribution is shown for , but it is visually indistinguishable from the one calculated with .

Image of FIG. 7.
FIG. 7.

(Color online) Ratio of thermal conductivity calculated for different values of constant conductance of buckling kinks (.) to the thermal conductivity calculated with zero thermal resistance of buckling kinks (). The results are shown for samples A ( nm; red squares and solid curve) and B ( nm; green circle and dashed curve).

Image of FIG. 8.
FIG. 8.

(Color online) A part of sample A shown in Fig. 6 with nanotubes colored by their total heat flux sum , Eq. (7), calculated with (a) and (b). and mark two characteristic bundles of CNTs. Bundle splits into many thinner bundles and includes multiple buckled CNTs. As a result, the values of for nanotubes in this bundle are visibly different in panels (a) and (b). Bundle mostly consists of nonbuckled CNTs, and the values of for nanotubes in this bundle exhibit only small difference between panels (a) and (b).

Image of FIG. 9.
FIG. 9.

(Color online) The values of the total heat flux sum averaged over individual nanotubes that have the same number of buckling kinks . The results are calculated for sample B with (red squares) and (green triangles). Data for exhibit strong scattering due to the small number of corresponding nanotubes in the sample. The curves show least-squares quadratic polynomial approximation of data points with .

Image of FIG. 10.
FIG. 10.

(Color online) The results of the calculation of thermal conductivity performed for mesoscopic samples composed of nanotubes of different length with constant values of thermal conductance of the buckling kinks (red squares for and green triangles for GWm−2 K−1) and with angular-dependent thermal conductance given by Eq. (3) (blue circles). The data in (a) are normalized to the thermal conductivity predicted for zero resistance of the buckling kinks (). In panel (b), the corresponding dimensional values of and are plotted. The black dashed line in (b) shows the approximate scaling law obtained in Ref. 21 for the (LT ) dependence. The values of shown by diamonds in (b) are slightly different from the ones in Ref. 21 because of a small difference in the methods used in the calculations of the temperature gradient .

Image of FIG. 11.
FIG. 11.

Probability density function of the thermal conductance of the buckling kinks in sample B ( nm) calculated with the angular dependence of the conductance on the buckling angle, , given by Eq. (3). The dots show the values obtained from the actual distribution of the buckling angles and the curve is least-squares 10th order polynomial approximation of the data points with GWm−2 K−1. σ b max and are the most probable and mean values of the conductance .


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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Effect of bending buckling of carbon nanotubes on thermal conductivity of carbon nanotube materials