On Packing, Connectivity, and Conductivity in Mesoscale Networks of Polydisperse Multiwalled Carbon Nanotubes

Abstract

The formation of different mesoscale networks in multiwalled carbon nanotube (CNT) systems that are realized by the mixing of CNTs of varying lengths and length dispersities is reported. By this mixing process, we introduce competing length scales; hence, we alter the self-organized packing that contributes to the synergistic effects on the functional properties of the networks. The experimental findings show a gradual change of volume fraction and aspect ratio as well as a 2-fold increase in electrical conductivity for such networks at certain specific compositions, hence an average aspect ratio. Quantitative large-area scanning transmission electron microscopy (STEM) imaging indeed revealed the existence of such mesoscale packing distribution variations. These packing observations suggest that these optimized networks of CNTs fit into an electrical conduction model that attributes its behavior to the formation of conduction knots, i.e., high-volume-fraction regions of relatively short CNTs that are connected by relatively long CNTs. If these conduction knots occupied by many short CNTs are distributed evenly with their nearest-neighbor distance being close to the average length of the CNT population, then the total electrical contact resistance in the conduction path will be effectively minimized. This study shows that optimized macroscale functional material properties can be designed into the initial colloidal dispersions by understanding and thus tuning the self-organization behavior of colloidal matter.

Percolation of sticks: Effect of stick alignment and length dispersity

“…The appearance of a percolation cluster in this kind of systems drastically changes their physical properties and is associated with an insulator-to-conductor phase transition. Length dispersity is common for NWs, NTs, and NRs [9][10][11][12]. These works evidenced that the length distributions of NWs, NTs, and NRs are close to representing log-normal distributions.…”

Electrical conductance of two-dimensional composites with embedded rodlike fillers: an analytical consideration and comparison of two computational approaches

“…Length dispersity is common for NWs, NTs, and NRs. [6][7][8][9] These works evidenced that the length distributions of NWs, NTs, and NRs are close to log-normal distributions. Furthermore, alignment of such elongated objects may be produced in different ways.…”

Quantification and optimization of ADF-STEM image contrast for beam-sensitive materials

“…Scanning transmission electron microscopy (STEM) has been extensively used to study the morphology of organic, inorganic and biological materials [ 1 – 3 ]. Yet, it is challenging for today's materials scientists to analyse many multiphase materials like polymer nanocomposites and polymer blends especially on account of (i) sampling, because their morphology extends over multiple length scales [ 4 , 5 ]; (ii) poor contrast , as the atomic number and density of individual components (for instance, carbon nanotubes (CNTs) dispersed in polymer matrix) are quite similar [ 6 , 7 ]; and (iii) beam sensitivity , as the polymer degrades in the electron beam and only a limited number of electrons per area and dose rate can be used for imaging [ 8 – 10 ]. We and others have shown that sampling can be tackled by combining large-area imaging [ 4 , 11 ] and thick sections [ 12 , 13 ], e.g.…”

“…Scanning transmission electron microscopy (STEM) has been extensively used to study the morphology of organic, inorganic and biological materials [1][2][3]. Yet, it is challenging for today's materials scientists to analyse many multiphase materials like polymer nanocomposites and polymer blends especially on account of (i) sampling, because their morphology extends over multiple length scales [4,5]; (ii) poor contrast, as the atomic number and density of individual components (for instance, carbon nanotubes (CNTs) dispersed in polymer matrix) are quite 2018 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.…”