Multifunctional multi-walled carbon nanotube reinforced natural rubber nanocomposites

Industrial Crops & Products 105 (2017) 63–73

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Multifunctional multi-walled carbon nanotube reinforced natural rubber nanocomposites

MARK

Thomasukutty Josea, Grace Monia, Salini S.a, Ann Jess Rajua, Jinu Jacob Georgeb, ⁎ Soney C. Georgea, a b

Centre for Nano Science and Technology, Amal Jyothi College of Engineering, Koovappally P.O., Kottayam 686518, India Rubber Research Institute of India, Kottayam, Kerala, India

A R T I C L E I N F O

A B S T R A C T

Keywords: Natural rubber Multiwalled carbon nanotubes Transport characteristics Mechanical properties Thermal properties Conductivity

The versatility of natural rubber (NR) as an elastomer is of considerable importance in the current scenario. In order to improve the characteristic properties of the elastomer, reinforcing it with nanofillers that possess multifunctional attributes are of great importance. In the present study, multiwalled carbon nanotube (MWCNT) reinforced natural rubber nanocomposites were prepared by two-roll mixing as a function of filler loading. The dispersion of nanotubes in the matrix was confirmed by Transmission Electron Microscopy and Raman analysis. Thermal, mechanical, dynamic mechanical, and transport properties of the nanocomposites were extensively studied. Nanocomposite with 3.5 phr of filler content showed 55% improvement in tensile strength. The thermal stability of the nanocomposites was evaluated with the aid of TGA and DSC analysis. Conductive properties of the nanocomposites were also studied. As the filler loading reaches the value of 3.5 phr, a percolation transition is observed which is accompanied by an increase in dielectric permittivity value of about 1.6 units. The solvent permeability of the composites was considerably reduced due to its reinforcement with nanotubes, following a mechanism that is very close to Fickian.

1. Introduction Elastomers are of great industrial importance due to their high and reversible deformability. In order to enhance their mechanical, thermal, conductive as well as optical properties, it has been incorporated with the nano, micro or macro counter parts. For the past few decades, nanocomposites have attracted a great deal of attention due to their exceptional enhancement in characteristic properties with the introduction of low loading of reinforcing content. The elastic material that is obtained from the latex sap of trees of the Genera Hevea and Ficus, namely natural rubber, as such, is not suitable for industrial purposes because of its poor resistance to chemicals and oil substances, instability towards long time exposure to heat, light, etc. Various means were developed to improve the properties of natural rubber by its modification, especially by vulcanization and its reinforcement by the introduction of filler component. The reinforcing effects of various fillers such as cellulose, carbon black, clay, graphene, CNT etc to enhance the properties of natural rubber composites were done by several researchers (Abraham et al., 2013; Yaragalla et al., 2015; Abdelmouleh et al., 2007; Alejandro et al., 2007; Frogley et al., 2003; Kueseng and Jacob, 2006; Kin et al., 2006; Razi et al., 2006). Nowa-

⁎

Corresponding author. E-mail address: [email protected] (S.C. George).

http://dx.doi.org/10.1016/j.indcrop.2017.04.047 Received 9 June 2016; Received in revised form 15 March 2017; Accepted 27 April 2017 0926-6690/ © 2017 Elsevier B.V. All rights reserved.

days, the use of multiwalled carbon nanotubes (MWCNT) as reinforcing agent in elastomeric composites attracts a great deal of attention due to its outstanding properties (Alejandro et al., 2007; Frogley et al., 2003; Kueseng and Jacob, 2006; Kin et al., 2006; Razi et al., 2006). The properties like tensile strength, stiffness and electrical conductivity of the elastomeric composites had increased significantly by the incorporation of MWCNTs (Inpil et al., 2011; Zdenko et al., 2010; Arash and Nasser, 2011), that are strongly dependent on the aspect ratio, shape and concentration of the filler (Lucia et al., 2012; Martone et al., 2011; Gavrilov et al., 2013; Ayatollahi et al., 2011). Enormous studies were carried out on the application of CNTs in epoxides, thermoplastics, fibers, and elastomers (Frogley et al., 2003; Kin et al., 2006; Razi et al., 2006; Bokobza, 2007; Bokobza and Belin, 2007; Lopez-Manchado et al., 2004). Considerable improvement in physical properties was reported when MWCNTs were incorporated in natural rubber. Kong and coworkers (Zheng et al., 2010) prepared natural rubber/MWCNT nanocomposites using latex compounding techniques. They reported that the well dispersed MWCNTs generated a remarkable increase in the tensile strength of the NR with very low filler loading. In another work, improvement in tensile and dynamic-mechanical properties was re-

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ported with the addition of 8.3 wt% of MWCNTs due to the exfoliation of nanotubes in the elastomeric matrices (Sanjib et al., 2008). Likewise, several works were done with natural rubber-CNT nanocomposites (Sunil Jose et al., 2010; Sagar et al., 2014; Sikong et al., 2015; Mohamed et al., 2015; Selvan et al., 2016). Conductive fillers such as carbon black, CNT, etc are incorporated with the polymer matrix to make them conductive. The introduction of CNT into the matrix to make it conductive is highly advantageous with respect to the percolation threshold which is attained by lower filler loading, compared to the higher proportion of carbon black required to achieve the same result (Bokobza, 2007). Several works have been done in nanocomposites to study the effect of CNT on electrical conductivity properties (Wang et al., 2008; Le et al., 2015; Bokobza, 2012; Grossiord et al., 2008; George et al., 2015). Transport characteristics of the nanocomposites were studied by several researchers and the diffusion properties of the nanocomposites were also studied in systems with different matrix components (Wilson et al., 2012; Abraham et al., 2015). Introduction of filler component to the elastomeric matrix will improve the properties of the final product depending upon its concentration, size and its characteristic features. Multiwalled carbon nanotubes are one such reinforcing agent with multiple outstanding properties. In the present work, we developed NR/MWCNT nanocomposites as a function of filler loading. The mechanical, dynamic mechanical, thermal, electrical properties of the nanocomposites were analyzed as a function of filler loading. The effects of filler concentration on diffusion parameters such as diffusivity, sorptivity, and permeability were also investigated. The highlight of the present work is that even a small amount of unmodified CNT into NR matrix could enhance the conductivity of the resulting nanocomposite with respect to the percolation threshold, compared to the previous work where a higher amount of CNT/Carbon black or surface modification has been used to achieve the similar results (Bokobza, 2007; Mohamed et al., 2015). These improvements in properties were mainly attributed to the proper dispersion of MWCNT in the NR matrix as confirmed from the TEM analysis. The prepared nanocomposites can find applications where better thermal resistance, barrier and conductive properties are required.

Table 1 Formulation of Mixes in phra. Sample

Natural Rubber

ZnO

Stearic Acid

CBS

Filler (MWCNT)

Sulphur

NR0 NR1 NR2 NR3 NR4

100 100 100 100 100

5 5 5 5 5

2 2 2 2 2

1 1 1 1 1

0 0.5 2 3.5 5

2.5 2.5 2.5 2.5 2.5

a

Parts per hundred rubber.

(Leica Ultracut UCT) at −120 °C with a section thickness of 100 nm. Micro Raman spectroscopy using Horiba Jobin Yvon LabRam HR system at a spatial resolution of 2 mm in a backscattering configuration and 633 nm of He-Ne laser for excitation was also performed to study the dispersion of filler in the polymer matrix. 2.3.2. Mechanical properties The mechanical properties such as tensile strength, tear strength, modulus at 100%, 200%, 300% and hardness of the nanocomposites were studied. The tensile properties of the samples were determined on a Universal Testing Machine, Instron Corporation, series 1X model 1034, using dumbbell sample at a cross head speed of 500 mm min−1 as per ASTM D412-87. Hardness (Shore A) of the samples was measured using Durometer hardness tester. To understand and verify the role of MWCNT in enhancing the modulus and tensile properties of the nanocomposites, the experimental results were compared with the theoretical predictions using Guth-Gold model and Halpin-Tsai model. The change in modulus of the filled elastomers was related to the aspect ratio, f and volume fraction, φ by the Guth and Gold model (Bokobza, 2012):

E m = E 0 [1 + 0.67fφ + 1.62(fφ)2 ]

(1)

Where, Em and E0 are the Young’s modulus of the filled elastomers and matrix respectively. Halpin–Tsai model also predicts the stiffness of the composite as a function of aspect ratio (Grossiord et al., 2008). The longitudinal modulus measured parallel to perfectly oriented fibers is given in the form:

2. Experimental methods 2.1. Materials

Em =

Natural rubber (ISNR-5) used as the matrix component was obtained from Rubber Research Institute of India, Kottayam. The filler material, MWCNT (90% carbon content) was purchased from Nanocyl S.A., Belgium, with tube diameter ranging from 10 to 20 nm and an average length of 1.5 μm. Other compounding ingredients and solvents used were of laboratory grade and used without further purification.

E 0 (1 + 2fηf) 1 − ηφ

(2)

Where η is given by Ef

η=

Ef

Em

−1

E m −2f

Ef is the modulus of the filler. In rubber composites Ef > > E0 so Eq. (2) reduces to

2.2. Preparation of nanocomposites

Em =

Compounding of ingredients was done on a two roll mixing mill according to ASTM D15-627 and the formulation of the mixes is given in Table 1. NR Nanocomposites with 0, 0.5, 2, 3.5 and 5 phr filler loading were prepared and designated as NR0, NR1, NR2, NR3, and NR4 respectively. Uncured rubber compounds were analyzed by Monsanto Rheometer R-100 and curing was carried out in an electrically heated hydraulic press at 150 °C.

E 0 (1 + 2fφ) 1−φ

(3)

2.3.3. Dynamic mechanical thermal analysis and thermogravimetric analysis Dynamic Mechanical Thermal Analysis (DMTA) was performed on Eplexor 150 N (Gabo Qualimeter, Ahlden, Germany) in the tension mode, at a constant frequency of 10 Hz, static load at 1% strain, dynamic load at 0.5% strain, heating rate of 2 K/min under liquid nitrogen flow in the temperature range of −80 to 80 °C. The strain sweep measurements of the samples also have been carried out in the strain range of 0.05–50% at room temperature. Thermogravimetric analysis was performed with a PerkinElmer, Diamond TG/DTA analyzer at a heating rate of 10 °C/min.

2.3. Characterization of NR/MWCNT nanocomposites 2.3.1. Morphological analysis The morphology and dispersion of the nanotubes in the polymeric matrix was investigated using JEM 2010 model transmission electron microscopy. Ultra-thin samples were prepared by ultramicrotomy 64

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⎛ hθ ⎞ D= π ⎜ ⎟ ⎝ 4Q∞ ⎠

2.3.4. Conductivity studies The DC Conductance of the nanocomposite membranes was studied using Keithley Electrometer. All conductance values are measured at a current range −70 to +70 μA with measurable voltage range 10 V. The effect of filler concentration on conductivity of elastomeric composites reinforced with conductive fillers was theoretically explained by Voet model (Voet et al., 1965). The model was based on the possibility of non-ohmic conduction present in the system i.e. by some sort of inter particle contact and electron emission phenomenon in the polymer composites that controls the conductivity. The final equation based on Voet theory is in the form; 1

logσ = kφ 3

Where h is the initial sample thickness. Sorption coefficient (S) is a thermodynamic parameter which depends on the strength of the interaction in the polymer–penetrant mixture. Sorption describes the initial penetration and dispersal of permeate molecule into the polymer matrix. It is calculated from the equilibrium swelling by using the equation (Haroppad and Aminabhavi, 1991)

S=

(4)

2.3.5. Transport characteristics Diffusion experiments were done at room temperature using the circular samples punched out from the molded sheets with the aid of sharp edged steel die. The cut polymer samples were weighed and sorption experiments were performed by immersing them in solvents contained in test bottles with air tight stoppers. The samples were withdrawn periodically and the solvent adhered to the surface of the sample was blotted off from the surface gently and immediately weighed on an electronic balance with an accuracy of 0.0001 g. Weighed samples were then immersed in the diffusion bottle immediately. The process was continued till equilibrium reached. The sorption results were analyzed in terms of number of moles of solvent sorbed by 100 g of rubber. The mole% uptake of the solvent (Qt%) was determined using the formula, Massofthesolventsorbedatagiventime

Molarmassofsolvent

Massofpolymer

× 100

P = DS

The interaction between the matrix and the filler component in an elastomeric nanocomposite can be analyzed from the change in position and intensity of the peaks in Raman spectra. The Raman spectra of NR, MWCNT and nanocomposite with 3 phr of filler content were shown in Fig. 1. MWCNT exhibit two characteristic peaks at 1300 cm−1 and 1600 cm−1 known as the D band and G band respectively. D band represents the significant defects and disorders of the nanostructures whereas the tangential vibration of the carbon atoms is responsible for the G band (Morrell and Blow, 1975; Zhang et al., 2002). From the spectrum it is evident that the intensity of the D band and G band present in MWCNT decreased and broadened when incorporated in NR. This is due to the better interaction and dispersion of nanotubes in the NR matrix.

(5)

3.2. Mechanical properties The influence of carbon nanotubes in altering the mechanical properties of the nanocomposites were studied with filler loading. The modulus at 100%, 200% and 300%, tensile strength, elongation at break (Eb), tear strength and hardness of the nanocomposites were analyzed. Stress-strain curves of the nanocomposites with filler loading were shown in Fig. 2. Stress-strain curves of all samples shown similar trend. In the initial region, stress increases linearly with strain and thereafter showed a rubbery deformation behavior. It can be seen that the stress level increases considerably with filler loading. A good interface between the filler and the matrix is very essential for the nanocomposite to uphold the stress. This is due to the better interaction between MWCNT and NR matrix. The filler material, MWCNT transfer the stress produced evenly into the matrix material due to its better dispersion. Here NR3 showed the maximum value and it further decreases with the concentration of MWCNT because of the agglomeration of filler in the matrix (Fakhru’l-Razi et al., 2006; George et al., 2015). The analyzed mechanical properties are given in Table 2. Tensile strength of the nanocomposites increased with filler loading and correspondingly a decrease in Eb was observed. From Table 2, it is clear that there is considerable increase in the tensile strength of the composites with filler loading. The tensile strength of the samples NR1 and NR3 show about 55% and 50% increase compared to the value of tensile strength of NR0 due to the better dispersion of the carbon nanotubes in the sample. Modulus at 300% was found to be increasing with filler loading.

(6) Q

1 2M c

(7)

Where, Mc is the molar mass between crosslinks. Mc can be determined using Flory–Rehner equation (Flory and Rehner, 1943) 1

Mc =

−ρp VV s r3 2 ln(1 − V) r + Vr + χVr

(11)

3.1. Raman analysis

The slope of the plot of ‘log Q t ’ versus ‘log t’ gives the value of n, ∞ indicating the mechanism of transport and its y-intercept is the value of k, depends upon the structural significance of polymer as well as its interaction with the solvent. Parameters such as crosslink density (υ), Diffusion Coefficient (D), Sorption Coefficient (S), and permeability (P) were analyzed to explicate the transport properties of the nanocomposites. Crosslink density, υ can be calculated using the equation (Subramanian et al., 2011)

ν=

(10)

3. Results and discussion

The Qt % values obtained were then plotted against √time. When equilibrium was reached Qt was taken as Q∞, mole% uptake at infinite time. The transport property of polymeric membranes is studied by using the empirical equation (Flory, 1941).

⎛Q ⎞ log ⎜ t ⎟ = logk + nlogt ⎝ Q∞ ⎠

M∞ M0

Permeability (P) is a combination of sorption and diffusion process. Hence the permeability of solvent molecule into polymer membrane depends upon both diffusivity and sorptivity. P can be determined from the following empirical relation (Sanjib et al., 2008).

where, k is a constant, φ is the volume fraction of filler in the composite and σ is the conductivity of the composite.

Qt % =

(9)

(8)

Where ρp is the density of the polymer, Vs is the molar mass of the solvent, Vr is the volume fraction of rubber in the swollen sample and χ is the Flory- Huggins interaction parameter (Flory, 1941; Flory and Rehner, 1943; Huggins, 1941). To study the diffusivity of nanocomposites diffusion coefficient, D was determined using the standard Fickian relationship (Crank, 1975). 65

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Fig. 1. Raman spectra of the NR, MWCNT and NR/MWCNT nanocomposite.

increases with filler loading and maximum was observed for the nanocomposite with 5phr of MWCNT (NR4). The increase in concentration of the filler enhances the surface properties of the polymeric material, therefore the hardness of the sample increases with MWCNT loading and a maximum is observed for the sample NR4.

Tear strength value is also increased with MWCNT loading and is found to be maximum for NR3 sample. This is attributed to the better dispersion of MWCNT in NR3 sample. The mechanical properties of NR3 sample showed better improvement compared to other samples. Fig. 3 shows the TEM image of the NR3 sample which supports the enhancement in its mechanical properties caused by the better dispersion of MWCNT in the matrix. From the micrograph it is evident that the well dispersion of the nanotubes in the matrix leads to an enhancement in these values. The large surface area enables CNT to evenly transform the applied stress through the matrix and this ability of CNT enhanced the modulus as well as stress strain behavior of the nanocomposites. Above 3.5 phr of filler loading there is agglomeration of the nanotubes in the matrix which act as the failure points and it leads to the significant degradation of mechanical properties of the nanocomposites. The schematic representation portraying the dispersion of nanofiller in the matrix was shown in Fig. 4. The dispersion of CNTs in the NR marrix was observed from the figure, which leads to the enhancement in mechanical properties of 3.5 phr filled nanocomposites. The influence of filler loading on hardness of MWCNT nanocomposites is clear from the Table. It is evident that hardness of sample

3.2.1. Comparison of experimental data with theoretical predictions The theoretical and experimental results obtained were shown in Fig. 5. The experimental results obtained were not in good agreement with the theoretical predictions mostly at higher filler loading. The theoretical models assume well dispersion, complete exfoliation and uniform orientation of the nanotubes in the matrix. The Guth model shows large positive deviation at higher filler loading due to the fact that particle aggregation has a significant effect on the stiffness of the material (Bergstrom and Boyce, 1999). Hence a small decrease in the stress strain properties and modulus were observed. 3.3. Dynamic mechanical analysis To evaluate the dynamic reinforcement, the dynamic-mechanical measurements were performed on natural rubber nanocomposites.

Fig. 2. The stress-strain behavior of NR/MWCNT nanocomposites.

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Table 2 Mechanical properties of the nanocomposites. Sample

NR0 NR1 NR2 NR3 NR4

Tensile strength (MPa)

7.58 ± 0.05 11.78 ± 0.02 11.18 ± 0.07 11.35 ± 0.03 10.63 ± 0.05

Elongation at Break (%)

438 528 517 456 466

± ± ± ± ±

5 8 3 7 4

Modulus at 100% (MPa)

200% (MPa)

300% (MPa)

0.82 0.71 0.85 0.96 1.04

1.48 1.26 1.54 1.89 1.98

2.60 2.14 2.61 3.57 3.56

Tear strength (N/mm)

Hardness (Shore A)

29.40 29.69 27.79 33.46 31.86

34 41 42 45 46

± ± ± ± ±

0.01 0.03 0.01 0.02 0.01

± ± ± ± ±

3 2 5 3 5

Fig. 3. TEM Micrographs of 3 phr loaded NR/MWNT nanocomposites.

storage modulus and after that it slightly decreased due to the aggregation of nanotubes. It is interesting to note that the maximum of tanδ decreases when the matrix material is incorporated with filler component (Fig. 6). This decrease in tanδ value is attributed to the restricted motion of the elastomeric chains in the vicinity of the nanotubes. It can also be said that the loss angle of NR is higher than that of the nanocomposites, because NR is able to absorb more energy than the nanocomposites under an acute strain environment (Fig. 7). This energy absorption causes thermal degradation and reduces the mechanical properties. Hence the thermal stability of the nanocomposites with smaller tanδ

Fig. 6 shows the variation of storage modulus (log E′) as a function of temperature for the various MWCNT concentrations. At glassy region the polymer nanocomposite showed elastic modulus around 3.6 Pa. As temperature increases the storage modulus of the rubber composite suddenly drops down due to the glassy-rubbery transition. It is also clear from the graph that the value of E′ increases significantly with the addition of MWCNT in the rubbery region suggesting a strong polymerfiller interaction due to the better dispersion of nanotubes in the matrix as conformed by the TEM images. At glassy region, 5 phr of MWCNT showed better storage modulus. But beyond the Tg, i.e., in the rubbery region 0.5 phr of MWCNT loading shows significant increases in the

Fig. 4. Schematic representation showing the dispersion of MWCNT in the NR matrix.

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Fig. 5. Theoretical modeling of Youngs Modulus and comparison with experimental data. Fig. 7. Variation of loss factor of the NR/MWCNT nanocomposites with temperature.

will be higher than that of pure NR (Peng et al., 2010). This similar behavior is observed with activated carbon nanotube in NR (Sanjib et al., 2008) and cellulose whiskers in natural rubber (Samir et al., 2005) Typical glass transition was observed in the case of NR and NR/ MWCNT nanocomposites. The glass transition temperature (Tg) for NR0 was at −43.6 °C and there is slight shift of 2.8 °C in Tg for NR3. The shifting of Tg towards lower temperature region at higher filler loading indicates the domination of filler–filler interaction over the filler-polymer interaction. In most cases it’s found that Tg increases when the fillers are added due to the better rubber-filler interaction, but in this case the value of Tg decreases. This might be due to the graphitic structure of MWCNT that is energetically not favorable for the adsorption of macromolecular chains. The tan δ peak heights of all the composites are lower than that of pure NR samples, which supports the above statement.

3.4. Thermogravimetric analysis

Fig. 8. Weight loss TGA curve of the NR/MWCNT nanocomposites with temperature.

The thermal stability of the polymer and the nanocomposites were examined by thermogravimetric analysis under nitrogen atmosphere. TGA curves for NR- CNT are shown in Fig. 8. From the curves it is evident that natural rubber with filler content exhibited relatively good thermal stability compared to the gum sample. It is due to the ability of

the MWCNT to prevent the thermal degradation of the matrix material by its better dispersion into the matrix. The sample NR3 showed superior thermal stability due to its ability to stabilize the matrix component with respect to temperature. The better dispersion of

Fig. 6. variation of storage modulus (log E′) as function of temperature for the various MWCNT concentrations.

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near percolation threshold is due to the micro capacitor effect. The agglomeration of nanotubes was pronounced above 3.5 phr of filler loading and hence conductivity of the nanocomposites decreased.

Table 3 Thermogravimetric analysis data of the nanocomposites. Sample

Tonset

TMAX

NR NR NR NR NR

309 354 317 352 357

366 399 360 389 394

0 1 2 3 4

3.6. Direct current (DC) electrical conductivity The change in DC conductivity with weight fraction of the nanotubes in the nanocomposites is shown in Fig. 10(a). From Fig. it is clear that with low filler loading itself a striking improvement in conductivity was observed. As the weight fraction varies from 0 to 0.03 the DC conductivity value increased from −3.1 × 108 to −1.2 × 108 S/m. Comparing with the neat sample about three fold increment in the conductivity value was observed. This increase in conductivity is attributed to the high aspect ratio and unique graphitic structure of the nanotubes. Moreover the uniform dispersion of nanotubes in the matrix enabled the formation of a smooth conducting path that contributed significantly to the enhanced conductivity.

MWCNT on NR matrix for NR3 sample was also clear from the TEM micrographs (Fig. 3). The results of TGA are given in Table 3. TG studies showed that thermal degradation occurs at higher temperature for all the nanocomposites than neat rubber.

3.5. Electrical conductivity of NR-MWCNT nanocomposites The effect of filler loading on the electrical properties of the nanocomposites was analyzed. Nanocomposites with even a small amount of filler showed significant improvement in electrical properties which make them superior to those conventional fillers. Fig. 9(a) shows the variation of AC conductivity with frequency. With increasing the MWCNT content the conductivity of the nanotube reinforced composites increased significantly. When MWCNT is incorporated with the matrix, the conductive property of the filler is transferred to the insulating NR matrix by the formation of a continuous conducting network. Optimum σAC conductivity value was observed for the NR3 sample with 3.5 phr of filler loading. Since the nanotube has high aspect ratio it leads to the sudden rise in its conductivity value. Conductivity decreases with further filler loading due to the agglomeration of nanotubes in the NR matrix. The change in dielectric permittivity (ε‫ )׳‬value with frequency was shown in Fig. 9(b). A trend of slow decrease in ε‫ ׳‬value with frequency was observed for the samples at lower filler loading. Percolation theory states that the concentration at which a conductive path is formed in the composite that convert it from an insulator to conductor is known as the percolation threshold (Sandler et al., 2003; Li et al., 2007). The nanocomposite with 3.5 phr of filler content showed optimum value of ε‫׳‬. As the filler loading reaches the value of 3.5 phr a percolation transition is observed which is accompanied by an increase in ε‫ ׳‬value of about 1.6 units. This is due to the presence of the conductive nanotubes which generates lots of micro capacitors throughout the polymer matrix by its better dispersion. Dang et al. (2007) suggested that this increment in ε‫ ׳‬value of the conductive filler-polymer systems

3.6.1. Correlation of theoretical modelling with experimental results 1

According to the Voet Model, a plot of log σ vs ϕ 3 should be a straight line for conductive composites. Fig. 10(b) shows the plot of log 1

σ with ϕ 3 for the NR/MWCNT nanocomposites. In the present study a steady increase in log conductivity was observed with lower filler loading. DC values increased up to the critical concentration of MWCNT and then decreased further. It is also formed a straight line which confirmed that the system was conducting with 0.5, 2.5 and 3.5 phr of filler loading. This is because of the percolation phenomena present in the system. Thus, up to 3.5 phr of filler loading the system behaves as conductive and beyond that a decrease in conductive property due to the agglomeration of nanotubes in the matrix. 3.7. Transport characteristics The effect of concentration of MWCNT on the equilibrium solvent uptake in toluene was studied and represented in Fig. 11. Filler loading have significant influence on the diffusion process. As the concentration of nanotube in the composite increases, the diffusion of solvents through the polymeric material reduced due to the tortuous path created by the nanotubes. It was observed that the equilibrium solvent uptake decreases with increase in concentration of MWCNT. It is evident from Fig. 11 that the solvent uptake of natural rubber varies with filler loading. Natural rubber with 5 phr and 0.5 phr of MWCNT showed the lowest and the highest uptake respectively. The better dispersion of nanotube in the rubber matrix restricts the

Fig. 9. (a) Variation of AC conductivity of the NR/MWCNT nanocomposites with the frequency, (b) Variations of dielectric permittivity of the NR/MWCNT nanocomposite with frequency.

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Fig. 10. (a) Variation of DC conductance of NR/MWCNT nanocomposite with filler loading, (b) Theoretical prediction of the conduction with Voet model.

transport of the solvent through the sample and thereby decreases the sorption. This can also be explained on the basis of crosslink density (υ) of the sample. Crosslink density of the nanocomposites were calculated using Eq. (7) and is given in Table 4. Crosslink density is lowest for NR0 and highest for NR3 in toluene. Thus the solvent uptake decreases in the order NR0 > NR1 > NR2 > nNR4 > NR3. The important factor that influences swelling is the availability of free volume in the sample. The unfilled sample showed increased solvent uptake since it has higher free volume. As the concentration of the filler in the matrix increases, free volume decreases and the equilibrium solvent uptake decreases. NR3 sample showed lowest solvent uptake since it exhibits better matrix–filler interaction compared to other samples as evident from the TEM micrograph (Fig. 3). Here the enhanced interaction of the filler and the NR matrix is attributed to the higher surface area of nanofiller. Due to the enhancement of polymer − filler interaction, the polymer gets reinforced upon the addition of fillers. The reinforcement of natural rubber matrix can be analyzed from Kraus plot. The Kraus equation is given by Flory and Rehner (1943)

⎛ f ⎞ Vr0 = 1 − m⎜ ⎟ ⎝ 1−f ⎠ Vrf

Table 4 The values of degree of crosslinking of the nanocomposites. Sample

Mc

υ × 104 (mol/cc)

NR0 NR1 NR2 NR3 NR4

5204 3399 3359 3100 3108

0.96 1.47 1.48 1.61 1.60

fraction of rubber phase in the unfilled sample and is given by d

Vr0 =

d

ρp

ρp

+

As

ρs

(13)

Where d is the deswollen weight of the sample, ρp is the density of the polymer, ρs is the density of the solvent and As is the amount of solvent sorbed by the sample. Vr 0 is a constant for a particular system. Vrf is the volume fraction of rubber in the swollen sample and is calculated using the equation

(12)

(d−fw)

Vrf = A plot of Vm/Vrf against f/(1–f) shows the extent of reinforcement caused by the filler in polymeric materials. Where Vr0 is the volume

ρp

⎡ (d−fw) ⎤ As ⎢ ρ p ⎥ + ( ρs ) ⎣ ⎦

Fig. 11. Effect of MWCNT on the equilibrium solvent uptake of nanocomposites.

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(14)

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has the large molecular size. This behavior can also be attributed to the difference in solubility parameter between the solvent and the polymer. Generally, as the solubility parameter difference decreases, solvent uptake increases, and is due to the increase in solvent–polymer interaction. The difference in solubility parameter for benzene, toluene, xylene and mesitylene with NR were 1.25, 1.01, 0.95 and 0.9 respectively. It is evident from Fig. 13 that the solvent uptake is maximum for benzene but the difference in solubility parameter between benzene and NR is also the maximum. Therefore by this study it is seen that sorption mainly depends on the penetrant size rather than solubility parameter difference of the solvent and the polymer. Thus the highest solvent uptake was shown by benzene and the lowest by mesitylene. The values of ‘n’ obtained from Eq. (8) are used to distinguish between the basic modes of transport. If n = 0.5, the diffusion is Fickian. In that case the rate of diffusion of permeant molecule is much less than the polymer segmental mobility. If n = 1, the mechanism is non-Fickian. In this case the permeate diffusion rates are much faster than the polymer segmental mobility. And if ‘n’ lies between 0.5 and 1, then the mechanism of sorption follows an anomalous trend. Here, the permeant mobility and the polymer segmental relaxation rates are similar. By regression analysis, the values of ‘n’ and ‘k’ are obtained as slope and intercept respectively and are given in Table 5. The correlation coefficient values are found to be 0.999. It is evident from Table 5 that the value of ‘n’ ranges from 0.3 to 0.4 and it is clear that the values are close to Fickian. The values of ‘k’ are found to be increasing with the concentration of nanotube and penetrant size. As the mechanisum of transport is close to Fickian, the Fickian relationship i.e. Eq. (9) was used for evaluating the diffusion coefficient (D). The diffusivity of the nanocomposites decreases with increase in the concentration of MWCNT (Table 6). The increase in filler content decreases the free volume and thus reduces the diffusion rate of the solvent through the nanocomposites. The reduction in free volume affects the rate of diffusion of solvent molecules through the NR matrix. The NR3 samples showed optimum rate of diffusion in benzene and mesitylene. The diffusion rate showed same trend in toluene and xylene because of the better solvent- polymer interaction. The values of sorption coefficient and permeability were determined using the Eqs. (10) and (11) respectively for the different nanocomposites in different solvents and are given in Table 6. D, S and P values decreases from NR0 to NR4 as the free volume available for the penetration of the solvent molecules decreases irrespective of the solvents used. Those values were found to be lowest when mesitylene

Fig. 12. Kraus Plot of NR/MWCNT nanocomposites.

‘f’ is the volume fraction of the filler and ‘w’ is the weight fraction of the filler. The Kraus plot of MWCNT filled NR is shown in Fig. 12. Since Eq. (12) is in the form of a straight line, a plot of Vr 0 as a function of f 1 −f Vrf should give a straight line. The slope of the line obtained is a direct measure of the reinforcing ability of the filler. According to Kraus theory, a negative slope value indicates a better reinforcement effect. The Kraus plot in Fig. 12. shows a downward direction therefore it exhibits a negative slope which indicates a better NR–MWCNT interaction in the composites. Thus the theoretical predictions agree well with the experimental results and it supports the presence of pronounced polymer −filler interaction in the nanocomposites.

3.7.1. Effect of penetrant size on diffusion behavior The penetrants; benzene, toluene, xylene and mesitylene were used to study the effect of molecular size on diffusion characteristics. The influence of penetrant size on the sorption behavior of the composite with 5phr filler loading is shown in Fig. 13. The molecular size of the penetrant affects the solvent uptake and the maximum solvent uptake decreases with increase in the molecular size of the penetrant. The migration rate was reduced by the presence of bulky groups in the penetrant. The interaction between the polymer and the solvent decreases due to this bulkier groups and thus reduces the solvent uptake. The lowest solvent uptake was observed with mesitylene, which

Table 5 Mechanism of Transport − The values of n and k. Solvent

Sample

n

k × 102 (min−1)

Benzene

NR0 NR1 NR2 NR3 NR4 NR0 NR1 NR2 NR3 NR4 NR0 NR1 NR2 NR3 NR4 NR0 NR1 NR2 NR3 NR4

0.37 0.35 0.38 0.38 0.33 0.39 0.34 0.22 0.34 0.41 0.38 0.36 0.35 0.35 0.35 0.37 0.42 0.38 0.37 0.37

1.58 1.92 1.37 1.68 2.79 1.48 2.42 7.36 2.50 1.36 1.48 1.75 2.08 1.92 2.13 1.40 1.07 1.32 1.33 1.47

Toluene

Xylene

Mesitylene

Fig. 13. Effect of penetrant size on the sorption behavior of natural rubber with 5phr filler loading.

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References

Table 6 Diffusivity, Sorptivity and Permeability values of the nanocomposites. Solvent

Sample

D × 105 (cm2/s)

S (g/g)

P × 105 (cm2/s)

Benzene

NR0 NR1 NR2 NR3 NR4 NR0 NR1 NR2 NR3 NR4 NR0 NR1 NR2 NR3 NR4 NR0 NR1 NR2 NR3 NR4

5.98 5.68 5.48 5.39 5.60 6.75 6.55 6.26 5.70 5.22 6.01 5.75 5.47 5.28 5.08 4.32 4.26 4.08 3.93 4.05

4.19 3.44 3.43 2.83 2.86 4.28 3.24 3.18 2.97 2.94 4.27 3.21 3.14 2.92 2.92 3.92 2.93 2.88 2.67 2.69

25.05 19.54 18.83 15.28 16.04 28.87 21.26 19.91 16.95 15.34 25.67 18.44 17.17 15.38 14.83 16.97 12.52 11.74 10.49 10.93

Toluene

Xylene

Mesitylene

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is used as the diffusing agent. This is obviously due to its trisubstituted ring structure and large penetrant size. It is also evident from Table 6 that permeability of the solvents through the nanocomposites decreases with filler loading. This decrease in permeability is due to the dispersion of MWCNT in the NR matrix and thereby reduction in free volume and increased polymer–solvent interaction was observed.

4. Conclusion The influence of MWCNT on the NR matrix in terms of mechanical, dynamic mechanical, conductive and transport properties was investigated as a function of filler loading. The morphology of the nanocomposites was analyzed by TEM and Raman spectroscopic techniques and it confirms the dispersion of filler in the matrix. The tensile properties of the composites increased with MWCNT loading. Nanocomposite with 3.5 phr of filler loading showed about 55% increase in tensile strength and enhanced Young’s modulus compared to the neat sample. Thermal stability of the nanocomposites was analyzed by TGA and it is found to be stable up to 350 °C. The AC and DC conductive properties of the nanocomposites were analyzed. Nanocomposite with 3.5 phr of MWCNT content showed enhancement in those properties. The percolation threshold was overcome by small amount (3.5 phr) of the filler content. The sorption behavior of the nanocomposites on aromatic solvents such as benzene, toluene, xylene and mesitylene were also examined. It was found that penetration of solvent through the nanocomposites depends on the penetrant size rather than the difference in solubility parameter of the solvent. The diffusion of the solvent molecules through the composites showed Fickian mechanism. The permeability of the solvent was reduced mostly with the NR3 sample. This is in agreement with the TEM images of NR3 samples in which MWCNT was well dispersed in the NR matrix. Optimum properties were shown by the nanocomposites with 3.5 phr MWCNT loading. The incorporation of MWCNT to NR matrix enhanced the mechanical, dynamic mechanical and transport properties as well as the conductive properties of the composites to a great extent. The prepared nanocomposites can find applications where better thermal resistance, barrier and conductive properties are required. Further work is in progress to enhance the intrinsic properties of the nanocomposites. Thus the utilization of NR can be increased with its enhanced properties.

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