Carbon Nanotube Polymer Nanocomposites Research Articles

The Electromagnetic Shielding Properties of Biodegradable Carbon Nanotube–Polymer Composites

In this article, the electromagnetic shielding properties of carbon nanotube–polymer nanocomposites are presented. The composite fabrication technique is spray-drying, the usage of which leads to a uniform dispersion of carbon nanotubes (CNTs) in a polymer matrix. Obtaining good filler dispersion is necessary to form a continuous, electrically conductive network of CNTs inside the polymer matrix. In the described nanocomposites, the network of conductive filler particles acts as an electromagnetic radiation barrier. For this reason, developing a highly effective fabrication method is very important. Also, the method should be simple enough to be easily adopted in an industrial environment. The authors shows in this text that both goals mentioned are achieved. The obtained nanocomposite material not only has electrostatic shielding capabilities but comprises electromagnetic shielding properties, which fulfills the main goal of the presented work. It is also worth mentioning that the developed manufacturing method allows for the usage of different fillers and polymers and thus the fabrication of materials capable of meeting a wide range of requirements.

Electric field influence on the non-zero temperature resistance of carbon nanotube polymer nanocomposites with subbands effect

The effective electrical resistivity of carbon nanotubes (CNT)-based polymer nanocomposites is studied using an analytical model based on the percolation theory. The CNTs are considered as rod-like conductors that are aligned or randomly dispersed in the polymer to transport electrons by tunneling. When assessing non-zero temperature electrical resistivity, the tunneling effect considers the thermally energized electron transmission that occurs between each coupled pair of CNTs by the electrical transport model. The modeling technique consists of three steps: identifying the percolating network from the primary formation of CNTs, initial prediction of resistivity by equivalent resistor network, computation of the displacements of CNTs for the resistance change. Taking into consideration the behavior of tunneling in the percolation transition zone, a good agreement is obtained between the model results and experimental data. The verified code is used to investigate the sensitivity for different orientation states, aspect ratios and mode numbers. The results reveal lower sensitivity for higher mode numbers as collateral with the influence of increasing randomness.

Introducing a nano-scale surface morphology parameter affecting fracture properties of CNT nanocomposites

Carbon Nanotube (CNT) particles and membranes improve interlaminar fracture toughness of nanocomposites. The novelty of this study is to introduce the effect of a new nanoscale parameter - CNT network (bundle) size to interphase thickness ratio - on modes I and II interlaminar fracture toughness of CNT Polymer Nanocomposites (PNCs). This investigation includes the stochastic distribution function of CNT bundle size, interphase thickness, and modes I and II fracture toughness of PNCs based on an extensive experimental study at the nano- and macro-scales. The Atomic Force Microscopy PeakForce Quantitative Nanomechanics Mapping technique was used to collect 500 datasets for a low-weight percentage of CNT PNC and 180 datasets for a high-weight percentage of CNT PNC. Each dataset included CNT bundle size and interphase thickness at the nanoscale. Double cantilever beam and end-notched flexure experiments were conducted to collect 600 modes I and II fracture toughness data. Two-, three-, and four-parameter Weibull models were used to simulate the nano- and macro-scale material properties of CNT PNCs. Results indicate that (i) a lower CNT bundle size to interphase thickness ratio improves fracture toughness, and (ii) a four-parameter Weibull model is the most efficient model for simulated data.

Stochastic model for the transfer of gaseous particles in polymer-carbon-nanotube nanocomposites with interfacial regions.

In this work, a stochastic model of gaseous transfer in polymer-carbon-nanotube (CNT) nanocomposites is presented. The model takes into account interfacial areas, i.e., polymer depletion regions. The local regime of transport is controlled by the density of the polymer. In a dense polymer, this regime corresponds to the ordinary diffusion, while in free volume regions, it corresponds to the ballistic transport. The introduction of a free volume and/or a depleted polymer layer near to a CNT wall leads to the emergence of anomalous diffusion. We have demonstrated how the anomalous diffusion regime changes in the presence of nanotubes for different distributions of polymer density. The presented approach allows us to describe the threshold effect in the diffusion coefficient as a function of CNTs density in polymer-CNT nanocomposites.

Effect of carbon nanotube type and length on the electrical conductivity of carbon nanotube polymer nanocomposites

Carbon nanotube (CNT) type and length are two key factors that affect the electrical behavior of CNT/polymer nanocomposites. However, numerical studies that consider these two factors simultaneously are limited. This paper presented a stochastic multiscale numerical model to predict the electrical conductivity and percolation threshold of polymer nanocomposites containing single-walled carbon nanotubes (SWCNTs) and multi-walled carbon nanotubes (MWCNTs). The combined effects of CNT type and length on the electrical conductivity and percolation threshold of the polymer nanocomposites were investigated. The model predictions were validated against experimental data of commercially available CNTs. Our results showed that the effect of CNT type varied based on both the length and aspect ratio of the CNTs. Long SWCNTs exhibited the greatest enhancement of the polymer’s electrical conductivity with the lowest percolation threshold among all the CNT types studied.

Synthesis and characterisation of nickel oxide-carboxylated multiwalled carbon nanotube polymer nanocomposites

Synthesis and characterisation of nickel oxide-carboxylated multiwalled carbon nanotube polymer nanocomposites

Multi-axial elastic–viscoplastic curves of unidirectional carbon nanotube-polymer nanocomposites considering interphase and interface debonding using finite element modeling

This paper aims to predict the elastic-viscoplastic curves of unidirectional carbon nanotube (CNT)-reinforced polymer nanocomposites under the multi-axial tensions, including bi-axial transverse-transverse, bi-axial longitudinal-transverse and tri-axial longitudinal-transverse-transverse loadings by the use of finite element (FE) modeling. The role of the interphase between the CNT and polymer matrix as well as the debonding at the CNT/interphase interface in the stress-strain curves of nanocomposites is investigated. The polymer matrix and interphase region are characterized as elastic-viscoplastic materials, while the CNT behaves as the elastic material. The present results in uni-axial loading are compared to the available numerical outcomes for indicating the accuracy of the FE modeling. The simulation of multi-axial load conditions is based on the three-dimensional representative volume element (RVE) of the unidirectional CNT-polymer nanocomposite. The effect of interface strength on the elastic-viscoplastic stress-strain curves is examined under bi-axial and tri-axial loadings.

Optical and dielectric behaviors of polyvinyl chloride incorporated with MgFe2O4/MWCNTs

Casting and wet chemical methods have been used to produce polyvinyl chloride/magnesium ferrite/multi-walled carbon nanotubes (PVC-MgFe2O4-MWCNTs) polymer nanocomposites. Full characterization was carried out applying x-ray diffraction (XRD), scanning electron microscope (SEM/EDS), and Fourier transform infrared (FTIR) techniques. MWCNTs disclosed high crystalline nature and Rietveld refinement revealed nanostructure for MgFe2O4 with average size 16 nm. Optical properties were inferred by diffused reflectance spectrophotometry, fluorescence (FL), and chromaticity (CIE). Upon loading PVC with MgFe2O4/MWCNT, both direct and indirect bandgaps were reduced, the absorbance was enhanced greatly, while transmittance and reflectance were reduced. The refractive index was reduced except for PVC/MgFe2O4 where it enhanced for λ > 450 nm and increased with incident photon energy. The optical conductivity is highly enhanced for the whole wavelength range. According to FL and CIE results, the FL peak intensity of pure PVC polymer decreased upon loading MgFe2O4 and quenched further upon adding MWCNTs to the polymer. PVC emitted in the blue range while doped PVC emitted in blue-violet regions. The effect of MgFe2O4 and/or MWCNTs on the ac conductivity, electrical dielectric constant and electric modulus of PVC was investigated at room temperature. Based on the characterization data, the synthesized polymer nanocomposites have potential applications in several different optoelectronic settings.

Numerical and analytical modelling of effective thermal conductivity of multi-walled carbon nanotubes polymer nanocomposites including the effect of nanotube orientation and interfacial thermal resistance

Multi-walled carbon Nanotube (MWCNT) fillers are extensively used to improve the thermomechanical properties of polymers. In this study, five different weight fractions (0%, 0.25%, 0.50%, 0.75%, and 1%) of MWCNT-polymer nanocomposites were prepared by the solution mixing technique. The thermal conductivity of MWCNT-polymer nanocomposites was investigated using the laser flash method. The closed-form solution of the modified Mori-Tanaka homogenization method was developed for the accurate estimation of the thermal conductivity of nanocomposite materials after considering the influence of interfacial thermal resistance (ITR). The finite element simulation of RVE modelling was utilized to predict the thermal conductivity of nanocomposites with and without consideration of the interfacial thermal resistance effect. A perfect bond was assumed between MWCNT and polymer for both numerical and analytical studies. The thermal conductivity results obtained from the closed-form solution of the modified Mori-Tanaka method were in good agreement with both the finite element simulation (FEM) and experimental results.

Carbon nanotube polymer nanocomposites coated aggregate enabled highly conductive concrete for structural health monitoring

Recently, we proposed a new strategy to develop a three-dimensional conductive network within a cement mortar by coating sand with graphene. In such a design, the interfacial transition zone (ITZ) was directly embedded in the conductive network, thus resulting in high piezoresistive performance. Considering that the ITZ between coarse aggregate and paste is typically much more vulnerable than that of the ITZ between fine aggregate and paste, here we extend this strategy to concrete, whose piezoresistive property has been rarely reported yet intimately relevant for practical application. Conductive fine and coarse aggregates are readily prepared by dipping coating with carbon nanotube (CNT) polymer slurry. Because of the high volume percentage of aggregates (∼70%) in concrete, the obtained concrete exhibit very high conductivity at low CNT usage of 0.41% (by weight of cement), several orders of magnitude higher than that reported before at similar CNT load. We find that the mixture incorporating conductive aggregates has a 28-day electrical resistivity of 1076 Ω cm with a compressive strength loss of 17.8%. On this basis, we further optimize the high-conductivity concrete by connecting conductive aggregates with a small amount of 0.25 wt% carbon fibre, which demonstrates an outstanding 28-day electrical resistivity of 235 Ω cm and an excellent fractional change in resistivity of ∼80%, more than one order of magnitude higher than those obtained in comparable systems. The experimental results also testify that our smart concrete exhibits acceptable mechanical properties and durability. The simple operation and low-cost benefits make our smart concrete demonstrate great potential for large-scale practical application.

Analytical formulation of the piezoresistive behavior of carbon nanotube polymer nanocomposites: The effect of temperature on strain sensing performance

Carbon nanotubes (CNTs) are incorporated into a stretchable polymer to determine modified thermo-resistive and piezoresistive responses of a nanocomposite under temperature variation and mechanical strain. Monte Carlo simulation is paired with tunneling model to disperse CNTs into the representative volume element and recognize CNT-to-CNT separation distance to predict the resistance change of nanocomposites subjected to strain. The principle of thermo-electrical properties is studied under thermo-mechanical stimulus. Nanotube reorientation model is used to investigate the influence of CNT’s tunneling and state of alignment on the piezoresistive behavior of the nanocomposite. Comparisons between modeling results and experimental data suggested a good agreement. The nearly linear dependence of relative resistance change with strain displayed more sensitivity with shorter CNTs and less sensitivity with higher CNT volume fractions. Relative resistance change with temperature was strongly affected by CNTs’ temperature coefficient of resistance and volume fraction. Such change was more pronounced for the anisotropic nanocomposite.

Effective Conductivity of Carbon-Nanotube-Filled Systems by Interfacial Conductivity to Optimize Breast Cancer Cell Sensors.

Interfacial conductivity and “Lc”, i.e., the least carbon-nanotube (CNT) length required for the operative transfer of CNT conductivity to the insulated medium, were used to establish the most effective CNT concentration and portion of CNTs needed for a network structure in polymer CNT nanocomposites (PCNT). The mentioned parameters and tunneling effect define the effective conductivity of PCNT. The impact of the parameters on the beginning of percolation, the net concentration, and the effective conductivity of PCNT was investigated and the outputs were explained. Moreover, the calculations of the beginning of percolation and the conductivity demonstrate that the experimental results and the developed equations are in acceptable agreement. A small “Lc” and high interfacial conductivity affect the beginning of percolation, the fraction of networked CNTs, and the effective conductivity. Additionally, a low tunneling resistivity, a wide contact diameter, and small tunnels produce a highly effective conductivity. The developed model can be used to optimize breast cancer cell sensors.

A method for determining the distribution of carbon nanotubes in nanocomposites by electric conductivity

Carbon nanotube (CNT) polymer nanocomposites are one of the most promising materials due to their remarkable mechanical properties as well as the electrical conductivity, which offers the capability of monitoring the deformation and damage of composite structures by measuring the related conductivity variations. However, quantifying the distribution of CNTs inside the material remains a challenge with respects to both experimental and numerical works. In the current study, the electrical conductivity was used to determine the microstructure of CNT-reinforced polymer. By introducing a modified parameter related to the polar angle of CNTs, the mechanical properties as well as the electrical conductivity change with respect to deformation of nanocomposites can be replicated. After validation by experimental data from the multi-walled CNT/polymer nanocomposites under tensile loading, the capability of the current method was then studied for composites with various weight fractions of nanotubes.

Formulation of interfacial parameter in Kolarik model by aspect ratio of carbon nanotubes and interfacial shear strength to simulate the tensile strength of carbon‐nanotube‐based systems

AbstractIn this work, we formulate the “A” interfacial parameter in Kolarik model by the features of carbon nanotubes (CNTs) and interface. The formulated “A” is applied to develop the Kolarik model for tensile strength of polymer CNT nanocomposites using CNT concentration, CNT aspect ratio, interfacial shear strength, and interfacial stress transfer factor. The advanced equations are applied to approximate the interfacial properties and sample strength. Moreover, the impacts of all factors on the nanocomposite strength are examined to validate the advanced model. CNT size (length and radius) largely changes the “A” from 0 to 250. Both CNT aspect ratio and interfacial stress transfer factor directly manage the “A” and nanocomposite strength. Too thin and extremely large CNTs result in the significant improvement in the strength of nanocomposites, but thick and short CNTs cannot reinforce the polymer media. Very thin (R = 2 nm) and extremely large CNTs (l = 20 μm) cause 1100% improvement in the strength of nanocomposites, whereas R > 12 nm and l < 10 μm cannot strengthen the polymer medium.

Near-Infrared Laser Direct Writing of Conductive Patterns on the Surface of Carbon Nanotube Polymer Nanocomposites.

Near-infrared (NIR) laser annealing is used to write conductive patterns on the surface of polypropylene/multi-walled carbon nanotube nanocomposite (PP/MWCNT) plates. Before irradiation, the surface of the nanocomposite is not conductive due to the partial alignment of the MWCNT, which occurs during injection molding. We observe a significant decrease in the surface sheet resistance using NIR laser irradiation, which we explain by a randomization of the orientation of MWCNTs in the PP matrix melt by NIR laser irradiation. After only 5 s of irradiation, the sheet resistance of PP/MWCNTs, annealed with a laser at a power density of 7 W/cm2, decreases by more than 4 decades from ∼100 MΩ/sq to ∼1 kΩ/sq. Polarized Raman, TEM, and SEM are used to investigate the changes in the sheet resistance and confirm the physico-chemical processes involved. This allows direct writing of conductive patterns using a NIR laser on the surface of nanocomposite polymer substrates, with the advantages of a fast, easy, and low-energy consumption process.

FEM micromechanical modeling of nanocomposites with carbon nanotubes

Abstract Mechanical properties of carbon nanotube (CNT)-based nanocomposites are broadly discussed in the literature. The influence of CNT arrangements on the elastic properties of nanocomposites based on the finite-element method (FEM) and representative volume element (RVE) approach is presented here. This study is an application of RVE modeling in the characterization of elastic behavior of CNT polymer nanocomposites. Our main contribution is the analysis of the impact of a nanotube arrangement on the elastic properties of nanocomposite to comprehensively determine the material constants. While most of the articles are focused on one distribution, not all material constants are determined. Our FEM analysis is compared with micromechanical models and other results from the literature. The current work shows that nanotube arrangements lead to different results of elastic properties. The analytical micromechanical models are consistent with the numerical results only for axial Young’s modulus and Poisson’s ratio, whereas other elastic constants are lower than the numerical predictions. The results of these studies indicate that FEM can predict nanocomposite mechanical properties with good accuracy. This article is helpful and useful to comprehensively understand the influence of CNT arrangements on the elastic properties of nanocomposites.

Electrical conductivity of interphase zone in polymer nanocomposites by carbon nanotubes properties and interphase depth

AbstractIn this work, carbon nanotubes (CNT) properties and interphase depth define the interphase conductivity in polymer CNT nanocomposites (PCNT). In addition, the operative CNT length and volume portion are linked to the conductivity transportation between CNT and insulated polymer medium to propose a simple model for conductivity. The significances of various terms on the interphase conductivity and conductivity of PCNT are justified and the model's predictions are examined using the experimental outputs of certain examples. Thin CNT and dense interphase obtain the extraordinary conductivity transportation, while CNT length and conductivity are ineffective. Moreover, thin, small, and high‐conductive CNT as well as dense interphase introduce the high interphase conductivity. The estimations of conductivity appropriately follow the experimental data authorizing the established model. This model is capable to substitute the conventional models owing to the assumption of innovative nanocomposite's terms.

A new analytical model for predicting the electrical conductivity of carbon nanotube nanocomposites

In predicting the electrical conductivity (EC) of carbon nanotube (CNT)/polymer nanocomposites (CPCs), previous analytical models did not simultaneously consider the effects of CNT waviness and dispersion state, which exist inevitably for real CPCs. In this work, an effective and comprehensive analytical model is developed to predict the percolation threshold and the EC of CPCs by taking into account the effects of CNT waviness and dispersion, etc. A detailed investigation of the effects of CNT content, conductivity, size, waviness and dispersion is conducted on the EC of CPCs. In particular, it is shown that both CNT waviness and dispersion play significant roles in determining the composite EC. Moreover, the predicted results agree well with the existing experimental results and display a higher prediction accuracy compared with the previous typical models for predicting the composite EC. Analytical results indicate that a high EC can be achieved for CPCs with CNTs of a high conductivity, a large aspect ratio (AR), a perfect dispersion state and a low degree of waviness.

Development of Conventional Paul Model for Tensile Modulus of Polymer Carbon Nanotube Nanocomposites After Percolation Threshold by Filler Network Density

In this paper, Paul’s model is advanced to forecast the tensile modulus of polymer nanocomposites reinforced by carbon nanotubes (CNT) above percolation onset. The developed model assumes the CNT network density by CNT aspect ratio (α), percolation onset and CNT density (n). The experimental results from several samples containing a filler network confirm the predictability of the advanced model. However, undesirable results are reported for the samples without the filler network. Also, both α and n directly manipulate the nanocomposite’s modulus above percolation onset, because they positively influence the polymer-CNT interfacial area and network size. The reasonable effects of α, n and percolation onset on the predicted moduli of nanocomposites validate the developed Paul model.

Influence of polymer type and carbon nanotube properties on carbon nanotube/polymer nanocomposite biodegradation

The interaction of anaerobic microorganisms with carbon nanotube/polymer nanocomposites (CNT/PNC) will play a major role in determining their persistence and environmental fate at the end of consumer use when these nano-enabled materials enter landfills and encounter wastewater. Motivated by the need to understand how different parameters (i.e., polymer type, microbial phenotype, CNT characteristics) influence CNT/PNC biodegradation rates, we have used volumetric biogas measurements and kinetic modeling to study biodegradation as a function of polymer type and CNT properties. In one set of experiments, oxidized multiwall carbon nanotubes (O-MWCNTs) with a range of CNT loadings 0–5% w/w were incorporated into poly-ε-caprolactone (PCL) and polyhydroxyalkanoates (PHA) matrices and subjected to biodegradation by an anaerobic microbial community. For each CNT/PNC, complete polymer biodegradation was ultimately observed, although the rate of biodegradation was inhibited above certain critical CNT loadings dependent upon the polymer type. Higher loadings of pristine MWCNTs were needed to decrease the rate of polymer biodegradation compared to O-MWCNTs, an effect ascribed principally to differences in CNT dispersion within the polymer matrices. Above certain CNT loadings, a CNT mat of similar shape to the initial PNC was formed after polymer biodegradation, while below this threshold, CNT aggregates fragmented in the media. In situations where biodegradation was rapid, methanogen growth was disproportionately inhibited compared to the overall microbial community. Analysis of the results obtained from this study indicates that the inhibitory effect of CNTs on polymer biodegradation rate is greatest under conditions (i.e., polymer type, microbial phenotype, CNT dispersion) where biodegradation of the neat polymer is slowest. This new insight provides a means to predict the environmental fate, persistence, and transformations of CNT-enabled polymer materials.