3D reconstruction of carbon nanotube networks from neutron scattering experiments

Abstract

PSS). SANS and USANS patterns of the different samples containing 10, 30, and 50 wt% SWCNTs were measured. These curves were then utilized to calculate statistical two-point correlation functions of the nanostructure. These functions along with the geometrical information extracted from SANS data and scanning electron microscopy images were used to reconstruct a representative volume element (RVE) nanostructure. Generated RVEs can be used for simulations of various mechanical and physical properties. This work, therefore, introduces a framework for the reconstruction of 3D RVEs of high volume faction nanocomposites containing high aspect ratio fillers from scattering experiments.

Insight into Geometry-Controlled Mechanical Properties of Spiral Carbon-Based Nanostructures

“…Again, in larger cross-sectional radius or larger semiminor and semimajor of CCNTs, for example, (4,3,4,3) and (6,3,4,3) CCNTs, this study was carried out and similar steps were observed (Figure S4). For these CCNTs to achieve at the same stretching range as latter samples of this group, it is necessary to have a larger inner radius.…”

“…Therefore, there is a significant amplification in tension. Moreover, in this stage, there are some differences in the strain range of (5,3,4,3) and (8,4,6,4) CCNTs, that are from 1 to 2.4 and 1.62 to 3.226 strain, respectively. Also, breaking of bonds was seen only in (8,4,6,4) CCNT.…”

A Generalized and Modular Framework for Digital Generation of Composite Microstructures

“…Indeed, a digital microstructure is often the input into most commonly employed multiscale material simulation toolsets (e.g., micromechanical finite element models [4][5][6] and phase-field models [7,8]). Recent efforts in the generation of digital microstructures have focused on problems such as the generation of a statistically similar ensemble of microstructures given a limited amount of available (reference) experimental observations [9][10][11][12], the generation of representative three-dimensional (3D) volume elements of material microstructures based on statistics gathered from two-dimensional (2D) microscopy scans or images from a sample [13][14][15][16][17][18][19][20][21], and the visualization of microstructures corresponding to a prescribed set of measured or predicted spatial correlations [19,[22][23][24][25][26][27][28].…”

Effective thermal and mechanical properties of short carbon fiber/natural rubber composites as a function of mechanical loading

“…Experimental studies show that CNTs have high thermal conductivity, more than 2000 (W/m.K) for SWNTs and MWNTs [6][7][8][9]. Due to their superior properties, nanocomposites are popular in many engineering fields such as aerospace and biomechanics [10][11][12].…”