Quantifying alignment in carbon nanotube yarns and similar two-dimensional anisotropic systems

Abstract: The uniaxial orientational order in a macromolecular system is usually specified using the Hermans factor which is equivalent to the second moment of the system's orientation distribution function (ODF) expanded in terms of Legendre polynomials. In this work, we show that for aligned materials that are two‐dimensional (2D) or have a measurable 2D intensity distribution, such as carbon nanotube (CNT) textiles, the Hermans factor is not appropriate. The ODF must be expanded in terms of Chebyshev polynomials and therefore, its second moment is a better measure of orientation in 2D. We also demonstrate that both orientation parameters (Hermans in three dimensional (3D) and Chebyshev in 2D) depend not only on the respective full‐width‐at‐half‐maximum of the peaks in the ODF but also on the shape of the fitted functions. Most importantly, we demonstrate a method to rapidly estimate the Chebyshev orientation parameter from a sample's 2D Fourier power spectrum, using an analysis program written in Python which is available for open access. As validation examples, we use digital photographs of dry spaghetti as well as scanning electron microscopy images of direct‐spun carbon nanotube fibers, proving the technique's applicability to a wide variety of fibers and images

Quantifying alignment in carbon nanotube yarns and similar two‐dimensional anisotropic systems

The uniaxial orientational order in a macromolecular system is usually specified using the Hermans factor which is equivalent to the second moment of the system\u27s orientation distribution function (ODF) expanded in terms of Legendre polynomials. In this work, we show that for aligned materials that are two‐dimensional (2D) or have a measurable 2D intensity distribution, such as carbon nanotube (CNT) textiles, the Hermans factor is not appropriate. The ODF must be expanded in terms of Chebyshev polynomials and therefore, its second moment is a better measure of orientation in 2D. We also demonstrate that both orientation parameters (Hermans in three dimensional (3D) and Chebyshev in 2D) depend not only on the respective full‐width‐at‐half‐maximum of the peaks in the ODF but also on the shape of the fitted functions. Most importantly, we demonstrate a method to rapidly estimate the Chebyshev orientation parameter from a sample\u27s 2D Fourier power spectrum, using an analysis program written in Python which is available for open access. As validation examples, we use digital photographs of dry spaghetti as well as scanning electron microscopy images of direct‐spun carbon nanotube fibers, proving the technique\u27s applicability to a wide variety of fibers and images

A Meta-Analysis of Conductive and Strong Carbon Nanotube Materials.

A study of 1304 data points collated over 266 papers statistically evaluates the relationships between carbon nanotube (CNT) material characteristics, including: electrical, mechanical, and thermal properties; ampacity; density; purity; microstructure alignment; molecular dimensions and graphitic perfection; and doping. Compared to conductive polymers and graphitic intercalation compounds, which have exceeded the electrical conductivity of copper, CNT materials are currently one-sixth of copper's conductivity, mechanically on-par with synthetic or carbon fibers, and exceed all the other materials in terms of a multifunctional metric. Doped, aligned few-wall CNTs (FWCNTs) are the most superior CNT category; from this, the acid-spun fiber subset are the most conductive, and the subset of fibers directly spun from floating catalyst chemical vapor deposition are strongest on a weight basis. The thermal conductivity of multiwall CNT material rivals that of FWCNT materials. Ampacity follows a diameter-dependent power-law from nanometer to millimeter scales. Undoped, aligned FWCNT material reaches the intrinsic conductivity of CNT bundles and single-crystal graphite, illustrating an intrinsic limit requiring doping for copper-level conductivities. Comparing an assembly of CNTs (forming mesoscopic bundles, then macroscopic material) to an assembly of graphene (forming single-crystal graphite crystallites, then carbon fiber), the ≈1 µm room-temperature, phonon-limited mean-free-path shared between graphene, metallic CNTs, and activated semiconducting CNTs is highlighted, deemphasizing all metallic helicities for CNT power transmission applications

Extreme stretching of high G:D ratio carbon nanotube fibers using super-acid

Few-wall carbon nanotube (CNT) textiles with unparalleled graphitic perfection and a solitary, prominent radial breathing mode (RBM) associated with metallic chirality have been mechanically stretched in chlorosulfonic acid (CSA) to a degree so far unseen in CNT textiles (150–250% of original length) with notably little tension required. This dramatically enhanced their microstructural alignment and density and, after most of the residual CSA was removed by a vacuum bake, the de-doped fiber's electrical conductivity was found to be 45% greater than single-crystal graphite – a significant milestone for CNT conductor development towards graphitic intercalation compounds (GICs) and traditional metals. Correlation tables and validated, multivariate statistical models show that conductivity is overwhelmingly linked to stretching degree, although eventually saturates near single-crystal graphite levels, implying the existence of a maximum undoped conductivity. The degree of stretching within CSA is correlated with the original mechanical properties (tenacity, elongation-to-break, and linear density); the Raman G’:G ratio and the upper-end oxidation temperature in thermogravimetric analysis also predict the best results. Less graphenically pristine CNT materials stretch to a lower degree in CSA, similar to previous reports. This study highlights the importance of post-synthesis processing to achieve superior performance in carbon nanotube textile materials

Catalyst‐mediated enhancement of carbon nanotube textiles by laser irradiation: Nanoparticle sweating and bundle alignment

The photonic post-processing of suspended carbon nanotube (CNT) ribbons made by floating catalyst chemical vapor deposition (FC-CVD) results in selective sorting of the carbon nanotubes present. Defective, thermally non-conductive or unconnected CNTs are burned away, in some cases leaving behind a highly crystalline (as indicated by the Raman G:D ratio), highly conductive network. However, the improvement in crystallinity does not always occur but is dependent on sample composition. Here, we report on fundamental features, which are observed for all samples. Pulse irradiation (not only by laser but also white light camera flashes, as well as thermal processes such as Joule heating) lead to (1) the sweating-out of catalyst nanoparticles resulting in molten catalyst beads of up to several hundreds of nanometres in diameter on the textile surface and (2) a significant improvement in CNT bundle alignment. The behavior of the catalyst beads is material dependent. Here, we show the underlying mechanisms of the photonic post-treatment by modelling the macro- and microstructural changes of the CNT network and show that it is mainly the amount of residual catalyst which determines how much energy these materials can withstand before their complete decomposition

Catalyst‐mediated enhancement of carbon nanotube textiles by laser irradiation: Nanoparticle sweating and bundle alignment

The photonic post-processing of suspended carbon nanotube (CNT) ribbons made by floating catalyst chemical vapor deposition (FC-CVD) results in selective sorting of the carbon nanotubes present. Defective, thermally non-conductive or unconnected CNTs are burned away, in some cases leaving behind a highly crystalline (as indicated by the Raman G:D ratio), highly conductive network. However, the improvement in crystallinity does not always occur but is dependent on sample composition. Here, we report on fundamental features, which are observed for all samples. Pulse irradiation (not only by laser but also white light camera flashes, as well as thermal processes such as Joule heating) lead to (1) the sweating-out of catalyst nanoparticles resulting in molten catalyst beads of up to several hundreds of nanometres in diameter on the textile surface and (2) a significant improvement in CNT bundle alignment. The behavior of the catalyst beads is material dependent. Here, we show the underlying mechanisms of the photonic post-treatment by modelling the macro- and microstructural changes of the CNT network and show that it is mainly the amount of residual catalyst which determines how much energy these materials can withstand before their complete decomposition.</jats:p

Enhanced convective heat transfer using graphene dispersed nanofluids

Nanofluids are having wide area of application in electronic and cooling industry. In the present work, hydrogen exfoliated graphene (HEG) dispersed deionized (DI) water, and ethylene glycol (EG) based nanofluids were developed. Further, thermal conductivity and heat transfer properties of these nanofluids were systematically investigated. HEG was synthesized by exfoliating graphite oxide in H2 atmosphere at 200°C. The nanofluids were prepared by dispersing functionalized HEG (f-HEG) in DI water and EG without the use of any surfactant. HEG and f-HEG were characterized by powder X-ray diffractometry, electron microscopy, Raman and FTIR spectroscopy. Thermal and electrical conductivities of f-HEG dispersed DI water and EG based nanofluids were measured for different volume fractions and at different temperatures. A 0.05% volume fraction of f-HEG dispersed DI water based nanofluid shows an enhancement in thermal conductivity of about 16% at 25°C and 75% at 50°C. The enhancement in Nusselts number for these nanofluids is more than that of thermal conductivity