Length Of Carbon Nanotubes Research Articles

Multiscale modeling and numerical analyses of the electric conductivity of CNT/polymer nanocomposites taking into account the tunneling effect

AbstractTunneling effect plays a significant part in the extremely low electric percolation threshold and large conductivity of carbon nanotube (CNT)/polymer nanocomposites, which allows electric conduction between two CNTs separated at nanometric distances. In this work, a numerical model taking into account the nonlinear tunneling effect is proposed to evaluate the effective electric conductivity of CNT nanocomposites. The nonlinear finite element formulation is introduced, as well as the definitions of effective quantities for homogenization. Moreover, the CNTs are modeled by highly conducting line segments in order to avoid meshing the thin cylindrical tubes. With this technique, the percolation behavior of the composites has been simulated, and the effects of barrier height, CNT length distribution, CNT aspect ratio as well as alignment have been estimated. It turns out that the barrier height dominates the maximum electric conductivity, while the CNT aspect ratio determines the percolation threshold value, respectively. In addition, the anisotropic behavior is obtained by aligning the CNTs, which also results in higher percolation threshold compared with randomly distributed CNTs. Finally, the results are validated by available experimental data.

Carbon Nanotube Length Distribution Estimation by One-Dimensional Plasmon Resonance for Solid-State Samples

Carbon Nanotube Length Distribution Estimation by One-Dimensional Plasmon Resonance for Solid-State Samples

Tuning the piezoresistive strain‐sensing behavior of poly(vinylidene fluoride)–CNT composites: The role of polymer–CNT interface and composite processing technique

AbstractIn order to understand the role of polymer–carbon nanotube (CNT) interface and composite processing method on strain‐sensing properties, poly(vinylidene fluoride) (PVDF)‐CNT composites have been prepared by melt‐mixing and solution‐casting methods using pristine and acid‐treated CNTs with CNT content of 0.15–4 wt%. The strain rate applied was in the order of s−1. Besides the improved mechanical properties of the composites over pristine PVDF, the piezoresistivity was also profoundly affected by the gentle acid‐treatment of CNTs and the composite processing method leading to tunable strain‐sensing properties. The stability of the strain‐sensors has been further predicted by employing cyclic piezoresistive tests. Interestingly, the pristine CNT composites showed higher strain‐sensitivity likely due to weak interface with polymer and higher initial resistance than the acid‐treated counterparts; while the acid‐treated CNT composites showed better retention of sensing properties under repeated cycles. On the other hand, composites with larger CNT length showed higher strain‐sensitivity than that having shorter CNTs. The temperature dependence of strain‐sensitivity showed a transition from positive to negative temperature coefficient at ~90°C. Finally, the composites subjected to a large number of bending cycles showed excellent performance and stability of strain‐sensing properties, paving the way for development of robust strain‐sensors for structural health monitoring.

First principle calculation of nonlinear optical response of (D/L)-Alanine in chiral carbon nanotube

Chirality is a fundamental feature of a structure, and chiral systems have been widely applied in many fields. This work mainly paid attention to effects of chiral interaction on molecular nonlinear optical (NLO) response. To this aim, D- or L-type alanine (Ala) with right or left handness respectively were added into chiral single-wall carbon nanotube (CNT) in this work. As a result by theoretical calculation, homo-chiral complex, namely, right-handed CNT with (D)-type Ala (or left-handed CNT with (L)-type Ala) would bring little stronger Ala-CNT interaction and larger first-order static hyperpolarizability βtot. In addition, βtot difference arising from charge transfer transition could be tuned by changing length and (or) chirality of CNT. These consequences were meaningful for further exploration of controlling molecular NLO properties by chirality.

Molecular dynamic insight into aluminum nanoparticles self-encapsulated by CNTs and their oxygen ignition

Metal nanoparticles tend to deactivate due to spontaneous migration-aggregation and continuous surface oxidation. Nanocapsules provide a brand-new strategy to tackle these challenges. In this work, two types of nanocapsules were designed and applied to active aluminum. The self-assembly details between carbon nanotubes (CNTs) and aluminum nanoparticles (ANPs) are elucidated through molecular dynamics methods. The stability and controllability of capsules I-VI consisting of various lengths of CNTs were revealed by means of reactive molecular dynamics simulations. The results indicate that the driving force for the self-assembly of nanocapsules is the vdW interaction. The assembled capsule has excellent stability, and the interaction energy between the tube and ANPs and between the tubes is as high as −599.55 and −1,014.78 kcal/mol, respectively. The opening of the nanocapsules during combustion is dependent on the length of the CNTs and temperature. Above 2000 K, the outer CNT can be opened when the length is greater than 31.73 Å. When used as propellants, pyrotechnics and explosives, these nanocapsules can be triggered remotely by visible/infrared lasers without the need of detonating wires.

A novel electro-mechanical technique for efficient dispersion of carbon nanotubes in liquid media

In this paper, we introduce a method to disperse carbon nanotubes (CNTs) within liquid media, established based on the applied hydrodynamic stress in the alignment process of the CNTs using an electric field. The main novelty of this technique is the capability of CNTs length protection and real-time control of the dispersion degree. Herein, the agglomerates and bundles are frequently induced by switching the field in different directions, and subsequently, the CNTs are separated from the main agglomerates. UV-Vis and dynamic light scattering spectroscopies and optical microscope analysis determined the dispersibility of the presented technique is very satisfying. The CNT's length distribution was assessed by the field emission scanning electron microscope. The results revealed that the shortening of CNTs is approximately 230% less than the well-known ultrasonic and melt mixing process. This is due to the unknown fatigue mechanism in which the required energy for dispersing CNTs is much less than CNT-CNT interaction energy. In addition to the capability of CNTs length protection, this method reduces the post-dispersed CNTs’ structural defects strikingly, certified by Raman spectroscopy. For real-time monitoring of the dispersion, the time-dependent voltage is measured. It was found that more reduction in the voltage corresponds to more dispersion.

Electromagnetic wave absorption properties of Ti3C2Tx nanosheets modified with in-situ growth carbon nanotubes

CNTs/Ti3C2Tx hybrids are prepared with carbon nanotubes (CNTs) are in-situ grown on the surface of the Ti3C2Tx nanosheets by using the method of chemical vapor deposition. Internal effects between micro-morphology and interface polarization have been research. The results show that the dielectric properties of the CNTs/Ti3C2Tx hybrids increase with the increase of the length of CNTs, the growth time is a direct determinant of the length of CNTs. The factors of the micro capacitors formed by CNTs, the dipoles formed by defects on CNTs greatly increase the dielectric loss. When the growth time reaches 45 min and the thickness of the absorber is 2.0 mm, the minimum reflection coefficient is −60.9 dB in X-band, the absorption bandwidth reaches 2.9 GHz. The CNTs/Ti3C2Tx hybrid shows excellent electromagnetic wave absorption properties.

A PSO based optimal repeater insertion technique for carbon nanotube interconnects

ABSTRACT Optimal repeater insertion is important in VLSI(very large scale integration) interconnects to reduce propagation delay and power dissipation. We propose a particle swarm optimisation (PSO)-based optimal repeater number for different lengths of carbon nanotube (CNT) interconnects at 20 nm and 14 nm technology nodes. First, numerical equations for optimal repeaters are modelled. Secondly, a PSO-based algorithm is developed and various input parameters are used to train the PSO. Optimal number of repeaters and the propagation delay for CNT interconnects for lengths ranging from 500 to 2000 µm are found out. Results are compared for both numerical and PSO methods, and it is found that they are within 2% deviation. Although earlier work shows similar findings, we have used CNTFET(carbon nanotube field effect transistor)-based inverters as repeaters in CNT interconnects for the first time. We have carried out the analysis for two values of repeater size, i.e. h = 50 and 75.

Estimating carbon nanotube length from isotropic cloud point of carbon nanotube/chlorosulfonic acid solutions

The information about CNT lengths is essential to realize the unique properties of CNTs at the macroscopic scale. Here, we experimentally demonstrate a short-cut method to characterize the average length of carbon nanotubes (CNTs) based on the isotropic-cloud point (ϕICP) of CNT/chlorosulfonic acid (CSA) solutions. We obtained the empirical relationship between the aspect ratio (AR) of CNTs and the ϕICP of CNT/CSA solutions using CNT forests fabricated to have a nearly-uniform length. This empirical relationship follows the Onsager scaling (ϕICP ∼ AR−1) and covers a wide range of the AR. Using this relationship, the average length of CNTs can be estimated from the measurement of ϕICP. This method is applicable to long CNTs (AR>104). The accuracy of the method is supported by comparing the results calculated from this method to those obtained from SEM images. This simple yet accurate method may contribute to the controlled growth of CNTs and fabrication of CNT materials that have desired properties.

(Invited) Thermal and Electrical Conductivity of Carbon Nanotube Network Materials: Theoretical Analysis and Mesoscopic Simulations

A general framework for theoretical analysis and numerical calculations of the effective thermal and electrical conductivity of homogeneous and isotropic disordered materials composed of carbon nanotubes (CNTs) is developed. The model utilizes similarity in the mathematical description of thermal and electrical transport in nanotube materials. The analysis accounts for both the inter-tube contact conductance and intrinsic conductivity of CNTs, and is performed in a wide space of governing parameters that includes the fiber aspect ratio, Biot number calculated for a single contact between nanotubes, and density ranging from values corresponding to the percolation threshold up to those characteristic of dense fiber networks. For dense networks, exact theoretical equations for the effective conductivity of materials composed of nanotubes with arbitrary aspect ratio and Biot number are derived. The effect of the intrinsic conductivity of nanotubes on the thermal and electrical transport is found to depend on the density of inter-tube contacts and, thus, is usually significant in the dense materials. The theoretical finding are confirmed in large-scale simulations of quasi-two-dimensional CNT films and three-dimensional CNT aerogels, where nanotubes form continuous networks of intertwined bundles. The simulations are performed based on a mesoscopic model of CNT materials, where every nanotube is represented by a curved chain of stretchable cylindrical segments. The dependences of the conductivity on the CNT length, Biot number, and material density predicted in these simulations agree well with the scaling laws derived theoretically. The comprehensive theoretical description developed in this work can facilitate tailoring thermal and electrical conductivity of CNT materials to the needs of practical applications by varying the material density, CNT length, and aspect ratio. Financial support for this work is provided by the National Aeronautics and Space Administration (NASA) through an Early Stage Innovations grant from NASA's Space Technology Research Grants Program (grant NNX16AD99G). A.N.V. also acknowledges support from the National Science Foundation through the CAREER award CMMI-1554589.

Development of an advanced Takayanagi equation for the electrical conductivity of carbon nanotube-reinforced polymer nanocomposites

Currently available models for the conductivity of nanocomposites commonly disregard the roles of interphase and tunneling sections. Here, the interphase and tunneling parts are considered to yield an expanded Takayanagi equation to express a model for the electrical conductivity of carbon nanotubes (CNTs)-reinforced polymer nanocomposites (PCNTs). Invoking the interphase section, the operative filler loading and percolation onset are shown to control the volume fraction of networks. Application of the advanced model allows calculation of the conductivity over disparate ranges of various factors and estimation of the conductivity for real specimens. Experimental data for several examples show good matching with the predictions. Straighter CNTs, a dense interphase region, large nets, large tunneling diameter, low polymer tunneling resistivity, and short tunnels give rise to high conductivity. Conductivity is increased to 3.5 S/m at a CNT radius (R) of 5 nm and a CNT length of 20 μm, whereas an insulating sample is observed at R > 8 nm. A percolation onset (ϕp) below 0.0012 results in a conductivity of 0.13 S/m, but it decreases to 0.1 S/m at ϕp> 0.0044. A high CNT volume fraction of 0.02 raises the conductivity to 0.35 S/m, whereas a low CNT volume fraction of 0.005 lowers it to 0.05 S/m.

Advanced Models for Modulus and Strength of Carbon-Nanotube-Filled Polymer Systems Assuming the Networks of Carbon Nanotubes and Interphase Section

This study focuses on the simultaneous stiffening and percolating characteristics of the interphase section in polymer carbon nanotubes (CNTs) systems (PCNTs) using two advanced models of tensile modulus and strength. The interphase, as a third part around the nanoparticles, influences the mechanical features of such systems. The forecasts agree well with the tentative results, thus validating the advanced models. A CNT radius of >40 nm and CNT length of <5 μm marginally improve the modulus by 70%, while the highest modulus development of 350% is achieved with the thinnest nanoparticles. Furthermore, the highest improvement in nanocomposite’s strength (350%) is achieved with the CNT length of 12 μm and interfacial shear strength of 8 MPa. Generally, the highest ranges of the CNT length, interphase thickness, interphase modulus and interfacial shear strength lead to the most desirable mechanical features.

Defect induced deformation effect on water transport through (6, 6) carbon nanotube

In this work, we have studied the effect of deformation induced by different defects along the length of carbon nanotube (CNT) on water transport. The smooth and nearly frictionless flow of water inside the nanotube is hindered due to the presence of defects. Local deformation induced by the defects near the entrance and exit of the nanotubes has a preeminent effect on the water molecule’s movement through the nanotube due to significant deformation. The formation of large energy barrier inside the nanotube and the breakage of the hydrogen bonds disrupts the smooth flow.

Residence time effect on single-walled carbon nanotube synthesis in an aerosol CVD reactor

• Residence time in aerosol CVD was tuned while nanotube nucleation maintained. • Carbon nanotube length and I G /I D ratio increase with a higher residence time. • The increase in length and defectiveness drops equivalent sheet resistance. • Effect of vortices, diffusion, and thermophoresis on nanotube yield was shown. • SWCNT/HAuCl 4 thin films with equivalent sheet resistance of 51 Ω/□ were obtained. We examine an effect of residence time on the growth of single-walled carbon nanotubes (SWCNTs) in an aerosol (floating catalyst) chemical vapor deposition (CVD) process using CO as a carbon source and ferrocene as a catalyst precursor. The key feature of aerosol CVD reactors, namely stabilization of fine nanoparticles by an extreme dilution, limits the method for catalyst evolution studies. We show an approach to examine the role of the residence time while maintaining all the processes preceding the nanotube growth (catalyst formation, nanotube nucleation). Using the diameter distribution of nanotubes as a fingerprint of the SWCNT nucleation stage, we have proven the latter to be unaffected by changes in the residence time. Using SEM observations, we have revealed a quite intuitive but inspiring correlation between the carbon nanotube length and residence time. We have also found a decrease in the SWCNT yield caused by the drop in the aerosol concentration, which could be attributed to the gas-phase losses as well as the shift in the catalyst activation degree. Nevertheless, the trends observed allowed us to reach a tenfold decrease in an equivalent sheet resistance (sheet resistance of a film with 90% transmittance at 550 nm) by a threefold increase in the residence time at optimal CO 2 concentration. SWCNT films with the equivalent sheet resistance as low as 245 Ω/□ and 51 Ω/□ (for pristine and doped carbon nanotubes, correspondingly) ensure the promising future of the proposed strategy for optimization of both aerosol CVD reactors and SWCNT-based films for optoelectronic applications.

Cutting Methods and Perspectives of Carbon Nanotubes

Short carbon nanotubes have a large potential application value in medicine, electronic devices, and composites. Nevertheless, the length of carbon nanotubes prepared is inconsistent and long, whic...

Length-dependent carbon nanotube film structures and mechanical properties

We investigated the microstructures of carbon nanotube (CNT) films and the effect of CNT length on their mechanical performance. 230 μm-, 300 μm-, and 360 μm- long CNTs were grown and used to fabricate CNT films by a winding process. Opposite from the length effect on CNT fibers, it has been found that the mechanical properties of the CNT films decrease with increasing CNT length. Without fiber twisting, short CNTs tend to bundle together tightly by themselves in the film structure, resulting in an enhanced packing density; meanwhile, they also provide a high degree of CNT alignment, which prominently contributes to high mechanical properties of the CNT films. When CNTs are long, they tend to be bent and entangled, which significantly reduce their packing density, impairing the film mechanical behaviors severely. It has also been unveiled that the determinant effect of the CNT alignment on the film mechanical properties is more significant than that of the film packing density. These findings provide guidance on the optimal CNT length when attempting to fabricate high-performance macroscopic CNT assemblies.

Effect of Shortening Carbon Nanotubes on Carbon Nanotube Dispersion, Damage and Mechanical Behavior of Carbon Nanotube-Metal Matrix Nanocomposites

Carbon nanotube dispersion in metallic matrices has been a challenge for many years. This paper investigates for the first time whether shortened carbon nanotubes as a starting material could promote improved carbon nanotube dispersion and promote less carbon nanotube damage when dispersed in metals. Aluminum-carbon nanotube nanocomposites were prepared using two carbon nanotube lengths (644nm and 10–30 μm). The nanocomposites prepared with shortened carbon nanotubes showed less carbon nanotube damage, higher microhardness, smaller matrix grain size, and improved dispersion of the carbon nanotubes as compared to the nanocomposites prepared with longer carbon nanotubes. Results suggest major implications for the use of even shorter carbon nanotubes for metal matrix composites.

Data-driven machine learning approach for exploring and assessing mechanical properties of carbon nanotube-reinforced cement composites

Traditional experimental investigation on the mechanical properties of cement composites is deprecated due to the intensive time and labor involved. Existing predictive models can hardly map the complicated relationships among mechanical attributes and behavior. This study first adopts machine learning to predict the mechanical properties of carbon nanotube (CNT)-reinforced cement composites. For this purpose, predictive models are trained on the previously published experimental data and results demonstrate that machine learning models present better generalization ability and predictive performance than the traditional response surface methodology. A sensitivity analysis indicates that the factor having the maximum influence on compressive strength is the length of CNTs, whereas that having the maximum influence on flexural strength is the curing temperature. Thus, it can be concluded that compared with the traditional experimental investigation and regression methods, machine learning can efficiently and accurately predict the mechanical properties of CNT-reinforced cement composites.

Development of Ji Micromechanics Model for Electrical Conductivity of Carbon Nanotubes-reinforced Samples

In this paper, Ji model for tensile modulus of nanocomposites is expanded to forecast the conductivity of polymer nanocomposites including carbon nanotubes (CNT) summarized as PCNT. The advanced model undertakes the volume fraction of networked CNT and the inherent resistances of tunneling and interphase sections. CNT loading, CNT size and interphase depth suggest the proportion of networked CNT. In addition, the tunneling confrontation is correlated to tunneling width, tunneling distance and polymer tunneling resistivity. The advanced model is used to express the parameters’ roles in the conductivity. Furthermore, the predictions of advanced model are linked to the experimental results of some examples. The proper impressions of all factors on the conductivity as well as the fine agreements among experimental data and calculations justify the advanced model. The radius and length of CNT mainly handle the conductivity, but CNT conduction is useless. Also, a dense interphase causes desirable conductivity, but the interphase conduction cannot govern the conductivity. Moreover, wide tunnels, deprived polymer tunneling resistivity and minuscule tunneling distance enhance the conductivity.

Resistivity of mesopore-confined ionic liquid determined by electrochemical impedance spectroscopy

Ordered carbon nanotube (CNT) arrays with pore diameter 24.4 ± 4.6 nm formed within anodized aluminum oxide (AAO) bonded to Si were used as electrodes for supercapacitors with neat EMIM-BF4 ionic liquid as the electrolyte. A series of devices with increasing AAO thickness (equal to CNT length) were tested using electrochemical impedance spectroscopy (EIS). Data were fit using the de Levie model of porous electrodes to determine the electrochemically active surface area and the in-pore electrolyte resistivity. The results indicate that uncatalyzed chemical vapor deposition (CVD) of CNTs in AAO can lead to blocked CNTs and reduced active area. The average resistivity of the electrolyte within the pores across the four devices tested was determined to be approximately 383 Ω cm, more than five times higher than the reported bulk resistivity of 70.9 Ω cm. It is possible that the enhanced resistivity is due to hydrophilic surface functionalities on the surface of the CNTs.