Tunneling resistance and its effect on the electrical conductivity of carbon nanotube nanocomposites

Bao, Wurigumula; Meguid, S. A.; Zhu, Zheng H.; Weng, George J.

doi:10.1063/1.4716010

Cited by 248 publications

(152 citation statements)

References 59 publications

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“…Several authors [54,[76][77][78][79][80] have reported that the electrical properties of nanocomposites are governed by electron hopping or tunnelling. Experiments and models revealed that the electron tunnelling results in nonlinear current-voltage behaviour in nanocomposites [81,82]. The resistance between nanotubes is a combination of direct contact resistance and tunnelling resistance [83].…”

Section: (C) Equivalent Resistor Networkmentioning

confidence: 99%

Estimation of the physical properties of nanocomposites by finite-element discretization and Monte Carlo simulation

Spanos

Elsbernd

Ward

et al. 2013

Phil. Trans. R. Soc. A.

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This paper reviews and enhances numerical models for determining thermal, elastic and electrical properties of carbon nanotube-reinforced polymer composites. For the determination of the effective stress–strain curve and thermal conductivity of the composite material, finite-element analysis (FEA), in conjunction with the embedded fibre method (EFM), is used. Variable nanotube geometry, alignment and waviness are taken into account. First, a random morphology of a user-defined volume fraction of nanotubes is generated, and their properties are incorporated into the polymer matrix using the EFM. Next, incremental and iterative FEA approaches are used for the determination of the nonlinear properties of the nanocomposite. For the determination of the electrical properties, a spanning network identification algorithm is used. First, a realistic nanotube morphology is generated from input parameters defined by the user. The spanning network algorithm then determines the connectivity between nanotubes in a representative volume element. Then, interconnected nanotube networks are converted to equivalent resistor circuits. Finally, Kirchhoff's current law is used in conjunction with FEA to solve for the voltages and currents in the system and thus calculate the effective electrical conductivity of the nanocomposite. The model accounts for electrical transport mechanisms such as electron hopping and simultaneously calculates percolation probability, identifies the backbone and determines the effective conductivity. Monte Carlo analysis of 500 random microstructures is performed to capture the stochastic nature of the fibre generation and to derive statistically reliable results. The models are validated by comparison with various experimental datasets reported in the recent literature.

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Section: (C) Equivalent Resistor Networkmentioning

confidence: 99%

Estimation of the physical properties of nanocomposites by finite-element discretization and Monte Carlo simulation

Spanos

Elsbernd

Ward

et al. 2013

Phil. Trans. R. Soc. A.

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“…[102,103] This type of electrical transport is commonly described in the framework of the variable range hopping (VRH) model, [86,95,103] according to which the resistance of a CNT film is given by (12) where E 0 is the activation energy of electron hopping between neighboring tubes, T is the temperature, and β is given by 1/(d+1), where d is the dimensionality of the electrical transport. Accordingly, the TCR of CNT films is given by (13) Based on Eq.…”

Section: Bolometers Based On Swcnt-polymer Compositesmentioning

confidence: 99%

Uncooled Carbon Nanotube Photodetectors

Léonard

Kono

2015

Advanced Optical Materials

154

166

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Photodetectors play key roles in many applications such as remote sensing, night vision, reconnaissance, medical imaging, thermal imaging, and chemical detection. Several properties such as performance, reliability, ease of integration, cost, weight, and form factor are all important in determining the attributes of photodetectors for particular applications. While a number of materials have been used over the past several decades to address photodetection needs across the electromagnetic spectrum, the advent of nanomaterials opens new possibilities for photodetectors. In particular, carbon-based nanomaterials such as carbon nanotubes (CNTs) and graphene possess unique properties that have recently been explored for photodetectors. Here, we review the status of the field, presenting a broad coverage of the different types of photodetectors that have been realized with CNTs, placing particular emphasis on the types of mechanisms that govern their operation. We present a comparative summary of the main performance metrics for such detectors, and an outlook for performance improvements.2

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“…The quantum tunneling mechanism based on the percolation theory has been investigated in black carbon and carbon nanotube polymer Electronic addresses: gc@ecs.soton.ac.uk and sli@mail.xjtu.edu.cn composites. 10,11 We believe that it can also be used to represent the charge conduction in nanodielectrics loaded with metallic oxide. For high loading concentration, the separation distance between the two adjacent nanoparticles is short.…”

mentioning

confidence: 99%

Charge transport model in nanodielectric composites based on quantum tunneling mechanism and dual-level traps

2016

Applied Physics Letters

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Charge transport properties in nanodielectrics present different tendencies for different loading concentrations. The exact mechanisms that are responsible for charge transport in nanodielectrics are not detailed, especially for high loading concentration. A charge transport model in nanodielectrics has been proposed based on quantum tunneling mechanism and dual-level traps. In the model, the thermally assisted hopping (TAH) process for the shallow traps and the tunnelling process for the deep traps are considered. For different loading concentrations, the dominant charge transport mechanisms are different. The quantum tunneling mechanism plays a major role in determining the charge conduction in nanodielectrics with high loading concentrations. While for low loading concentrations, the thermal hopping mechanism will dominate the charge conduction process. The model can explain the observed conductivity property in nanodielectrics with different loading concentrations.

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Tunneling resistance and its effect on the electrical conductivity of carbon nanotube nanocomposites

Cited by 248 publications

References 59 publications

Estimation of the physical properties of nanocomposites by finite-element discretization and Monte Carlo simulation

Estimation of the physical properties of nanocomposites by finite-element discretization and Monte Carlo simulation

Uncooled Carbon Nanotube Photodetectors

Charge transport model in nanodielectric composites based on quantum tunneling mechanism and dual-level traps

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