Conducting aluminum-filled nylon 6 composites

Conducting Aluminum-Filled Nylon 6 Composites

GABRIEL PINTO’ and ANA JIMENEZ-MARTjN2

‘Departamento de Ingenieria Quimica Industrial y del Medw Ambiente ETSl Industriales, Universidad Politecnim de Madrid

Madrid, Spain

2Departamento de Ingenieria Ekctronica, ETSl Tekcomunicacwn Universidad Politecnica de Madrid

Madrid, Spain

This work is concerned with the preparation and characterization of composite materials prepared by compression molding of a mixture of aluminum flakes and nylon 6 powder. The electrical conductivity, density, hardness and morphology of composites were investigated. The electrical conductivity of the composites is < lo-’ S/cm unless the metal content reached the percolation threshold, beyond which the conductivity increased markedly by as much as loll. The volume fraction of conductive filler at the percolation threshold was calculated from experimental data, by fits to functions predicted by the percolation theory. Decreasing the average particle diameter of filler leads to increased percolation threshold (it varies from 23 to 34 vol% for the three different fillers studied] and decreased maximal conductivity of composites. The density of the composites was measured and com- pared with values calculated assuming different void levels within the samples. Furthermore, it is shown that for certain sizes of particle filler, the hardness decreases initially with the increase of metal concentration, possibly because of poor surface contact with the nylon matrix, but, starting from a certain value, there is a hardness increase. For the smallest particle filler, the hardness of samples is not influenced by the presence of the filler.

INTRODUCTION

onductive polymer composites have had a signifi- C cant influence on modem technology because of their numerous high technological electrical and electronic applications in a variety of areas such as self regulating heaters, over-current and over-temperature protection devices and materials for electromagnetic/ radio frequency interference (EMI/RFI) shielding in electronic devices (computer and cellular housings for example) (1-9). Increasing the electrical conductivity of typically insulating polymers, such as polyethylene terephtalate (PET) and nylon, has the potential of greatly increasing the market for these materials.

Several methods have been proposed and developed to prepare conductive polymer composites (10- 151, e.g., a hot compaction of a mixture of a polymer powder and carbon black or metal filler.

In general, the percolation theory is used to de- scribe the electrical conductivity of extrinsic conductive polymer composites. Hence, it is generally known that the electrical conductivity for polymer composites does not increase continuously with increasing

electroconductive filler content, but there is a critical composition (percolation concentration) at which the conductivity increases some orders of magnitude from the insulating range to values in the semiconductive or metallic range (2). For efficiency, in order to decrease the difficulty of the process and economic costs, the amount of the conductive phase for achiev- ing materials with high conductivity should be usually as small as possible. A huge number of different models have been proposed for the estimation of the conductivity (or inverse resistivity) vs. filler concentration curves ( 16-25).

This paper reports further developments in previous reported investigation of properties and influence of processing parameters of composites made of copper powder and carbon black embedded in nylon 6 (26-28). We present an experimental study about the influence of filler concentration on the electrical conductivity of composites produced by hot compaction by means of the compression molding of a mixture of aluminum powder and nylon 6 powder. We focus mainly on the estimation of the percolation concentration and its variation with filler sizes and aspect ratio.

POLYMER COMPOSITES, FEBRUARY 2001, Vol. 22, No. 1 65

Gabriel Pinto and Ana Jirnenez-Martin

These data may be helpful in developing theoretical models to better understand the variation of electrical properties of such materials.

Void levels within the samples that greatly influence the electroconductivity, were calculated from the density of the composites.

To check if the percolation phenomenon can be also seen in other characteristic parameters, and in order to complete the characterization of these materials, the density and hardness of the composites, as example of properties, have been investigated.

EXPERIMENTAL

Materials

The matrix polymer used in our experiments was a commercial grade nylon 6 (used mainly for manufacturing fishing nets) supplied in the form of powder by Poliseda. The appropriate properties according to the supplier sheet are shown in Table 1. The cumulative size distribution of the nylon 6 powder, that has particles with a dendritic shape, was reported in previous works (26, 27).

The electrical conducting filler used was aluminum flakes powder, delivered by Panreac, with different mean diameters. Three particle sizes, selected by means of a sieve, were used: A (200 to 500 pm), B (75 to 200 km), and C (25 to 75 km). Table 2, taken from Hufnagel (29). shows the appropriate properties of aluminum, and Table 3 shows the average particle size, obtained by the sieves, and the average particle size, obtained by microscopic analysis, of the three kinds of filer used in this work.

Both, the polymer and the metal powders were thor- oughly dried before use (48 h at SOT).

Composite Preparation

Aluminum filled nylon 6 composites were fabricated by mixing the polymer and the filler powders for 2 h in an internal mixer, followed by compression molding in a specially designed mold with three cavities of 30 mm diameter and 3 mm thickness each one. The molding parameters were 20 MPa and 2 15°C for 15 min. The fabrication conditions for these composites were suggested by previous experience with this polymer (26-28). Samples with filler contents in the range 0 to 80 wtYo were prepared. In order to improve the finishing of the samples their surfaces were polished with sandpaper. Samples were cooled to room temperature in about 30 min.

Table 1. Properties of Nylon 6.

Weight average molecular weight 24,500 Glass transition temperature -50°C Melting temperature -225°C Density 1.1 3 g/cm3 Electrical conductivity at 20°C - 1 o-l3 S/cm

66

Table 2. Characteristics of Aluminum.

Density 2.7 g/cm3

Electrical conductivity at 20°C Purity 99.5%

4 x lo5 S/cm

Table 3. Geometrical Characteristics of Aluminum Flakes.

Average Particle Average Aspect Size (pm) Ratio

Filler A 200 - 500 3: 1 Filler B 75 - 200 2: 1 Filler C 25 - 75 1.5:l

Composite Characterization Techniques

Sample thickness (necessary for the calculation of conductivity) was determined using a micrometer, Schmidt model J 50, to an accuracy of 0.01 mm. Thickness measurements were taken at five locations and averaged. This magnitude varied between 0.35 cm and 0.65 cm.

The electrical conductivity was determined since the resistance values that were measured using a two- point arrangement. Three specimens of each composition were tested, taking four data points on each sample. From this, the medium value of the twelve measurements was determined. In order to decrease the contact resistance, the sample surfaces were coated with silver paint.

Measurements of volume electrical resistance high- er than lo3 ohm were made using a programmable megohmeter (Quadtech model 1865). Measurements of low resistance were made using a digital multimeter (Leader model 856). A constant voltage of 100 V was supplied to the samples and the resistance of the samples was measured after one minute, using a test cycle consisting of 20 s charge, 20 s dwell, 20 s measure, and 20 s discharge. Before starting a new test, the electrodes were short-circuited for 5 min to eliminate any effect of the previous electrification. The procedure used to estimate conductivity, u, from resistance, in the present study was similar to those reported earlier (26-28) for the volume resistivity, p. Significant differ- ences among different specimens with the same composition were not apparent, ensuring homogeneity in the manufacturing process. The reproducibility in the values of u was better than one order of magnitude.

The density of the composites were measured in accordance with ASTM D 792-9 1, by difference of weight in the air or with the sample immersed in ethanol of 96% purity as the liquid of known density (0.810 g/cm3), at 23"C, using a Mettler A J 100 balance equipped with a density determination kit.

The hardness of the samples was determined at 23°C using a durotronic model 1000 Shore D hardness tester, in accordance with ASTM D 2240-68. Five data points were taken on each sample and no difference was found between hardness measurements on both faces of each specimen.

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Conducting Aluminum-Filled Nylon 6 Composites

The microstructures of the samples were observed by reflection by means of a Leitz Aristomet optical microscope.

RESULTS

The electrical conductivity of the composites vs. filler contents for the samples with different geometrical characteristics, i.e. A, B, and C (see Table 3) is illustrated in Ftg. 1 . All concentrations are expressed in weight percentages.

Ftgure 2 shows the comparison between the calculated and measured density/fUler concentration curves for the system under investigation. These curves were calculated assuming different extent of void fraction in the samples, as explained in previous works (26, 27). where more details were included.

Figure 3 shows the dependence of shore D hardness of the different specimens on the filler content. The data obtained for filler C were not shown because, for these samples, the Shore D hardness was approximately constant within the range from 73 to 79 units.

Ftgures 4 to 6 show micrographs of different composites, for the three studied fillers. In each case is shown the structure of composite samples before (a) and after (b) reaching the conductive character.

DISCUSSION

The electrical conductivity of the composites studied vs. filler weight percentage is illustrated in F@. 1 . As

0 20 40 60 80 Filler content (wt - YO)

Fig. 1 . Variation of the electrical conductivities of nylon 6/A1 composites with weight fraction of Aluminum for dflerent particle sizes. Lines represent the best fits, in accordance with Eq 2.

expected, the electrical conductivity of the composites increases dramatically when the aluminum content reaches the percolation threshold. We can see from Ftg. I that the percolation threshold is very sensitive to the geometrical characteristics of the filer.

The morphology of the composites was investigated by optical microscopy. Figures 4a and b show the micrographs of the composite containing 30 wt% and 60 wto/o of filler A, respectively. It is very clear that in Fig. 4a there is no extensive contact between particles of filler, which explains that the sample is not electroconductive. In Fig. 4b, on the other hand, there are particles of filler in direct contact or separated by very small distances, which justifies the electroconductive behavior. F@ures 5a and b, and 6a and b, show similar properties for the fillers B and C, respectively. From Figs. 4, 5 and 6, the decrease in average aspect ratio of filler particles can be appreciated.

As mentioned in the Introduction, many models have been proposed to explain the electrical conductivity of conductive composites. The percolation theory, used extensively (24, 30). predicts a conductivity (u) dependence of the form:

u = uo * ( P - Pc)( (1)

where u is the electrical conductivity of the composite, o0 is the electrical conductivity of the conductive filler particles, P is the volume fraction of the conductive fillers, P, is the volume fraction of conductive filler at

0,8 ! 0 20 40 60 80

Filler content (wt - %)

Fig. 2. Measured density for different filer particles sizes. and calculated density/filler concentration curves for a n overall volume of voids accounts for -: Ooh; . . . . : 10%; - - - -: 2G%.

POLYMER COMPOSITES, FEBRUARY 2001, Vol. 22, No. 1 67

Gabriel Pinto and Ana Jidnez-Martin

I

A - 200-500 pm

78

6 76- 2 2 .

7241

* -

2 74- v ) . A v

a . c

- . A A* A A 70-

681 A A

66 I t I I

0 20 40 60 80 Filler content (wt - %)

Fig. 3. Shore D hardness for composites made with dtfferent particle sues.

the percolation threshold, i.e., the volume fraction below which the conductivity falls to a very small value, and t is an exponent determining the power of the electrical conductive increase above Pc.

Assuming the values of densities referred at Tables 1 and 2, values for the volume fraction can be obtained from the weight percentage. By using a log-log plot of the electrical conductivity vs. the excess of conductive filler volume fraction (P-P,) the best fits were obtained with the values of Pc shown in Table 4.

Nevertheless, as pointed out by Mamunya e t al. (191, Eq 1 is valid only very near to the percolation threshold. Following the normalized percolation equa- tion proposed by Mamunya et aZ. (23), the variation of electrical conductivity with the filler volume fraction can be described by:

P - P , u = uo + (a, - ao) - (-)

F - Pc

where u, is the maximal conductivity reached by the composite, F is the maximal value of the filler volume fraction and the other parameters are the same as in Eq 1.

Values for Pc obtained from Eq 2 are shown in Table 4. As it can be observed, these values are similar to those obtained from Eq 1.

The variation of Pc with average particle diameter of the filler disagrees with that observed in a previous work (26) with copper as filler, but it is obvious that, apart from size, the geometry of the filler, in particular the aspect ratio, plays an important influence. In this way, it is well known that the percolation concentration, that is, the concentration of conductive fillers to produce a continuous network, goes down very sharply with increasing in the anisotropy of the shape of the filler particles, i.e., in increase in their aspect ratio (7, 30) and our results corroborate this view.

In addition, it was observed (see Fig. 1) that the maximum value of conductivity reached by composites decreases with the decreasing of particle size.

(b) JYg. 4. Optical microscopy micrographs of the aluminum-filled nylon 6 composites containing (a) 30 WE% of filer A and [b) 60 wt% offiller A.

This is probably due to the increasing of volume of voids, as explained below.

The data shown in FWJ. 2 reflect that all the measured densities fall into the range between an almost totally void free sample and a situation in which an overall volume voids accounts for 18% of the sample volume. The average fraction voids in volume was 5 2 3% for filler A, 7 2 2% for filler B, and 12 2 5% for filler C. This variation may explain the decrease in the maximum value of the conductivity reached by the composites in the order of increasing fraction voids.

The hardness/filler concentration data, shown in Fig. 3, reveal that there is no sharp change as is seen in the electrical conductivity curves. Nevertheless, for fillers A and B, a variation in hardness analogous at that found for copper filled nylon composites (26) was measured. Hardness initially decreases with the increase of metal concentration, possibly owing to poor surface contact with the nylon matrix, but, starting

68 POLYMER COMPOSITES, FEBRUARV2001, Vol. 22, No. 1

Conducting Aluminum-F'illed Nylon 6 Composites

(b) Fig. 5. Optical microscopy micrographs of the aluminum-$lled nylon 6 composites containing (a) 40 wt?? offiller B and (b) 62 WWO of3lZer B.

from a certain value there is a hardness increase. The Shore D hardness is approximately constant with filler concentration for filler with the smallest average particle filler diameter (filler C).

CONCLUSIONS

In this article we have described an experimental study about the effects of the filler content and filler size effects on the electrical resistivity, density and

Table 4. Values of Percolation Threshold (in Volume Fraction) for the Composites.

_ _ _ _ _ _ _ _ ~

P, from Eq 1 P, from Eq 2

Filler A 0.235 2 0.002 0.23 2 0.01 Filler B 0.300 2 0.005 0.304 2 0.005 Filler C 0.340 2 0.003 0.34 i- 0.01

____ ~ ~~

POLYMER COMPOSITES, FEBRUARY 2001, Vol. 22, No. 1

Fg. 6. Optical microscopy micrographs of the aluminum-frtted nylon 6 composites containing (a) 9 wt% offiller C and (b) 70 wt?? offiller C.

hardness of composites of aluminum flakes powder embedded in nylon 6 prepared by compression molding. From the results obtained, the following conclusions can be shown:

1.

2.

3.

The electrical conductivity of composites increases by as much as eleven orders of magnitude for a given range of filler concentration, showing the typical percolation transition. The percolation threshold concentration oc- curred between 23% and 34% in volume for the different fillers and increased with a decrease in the aspect ratio of filler particles. There is no distinct break in the density/filler concentration relationship. From density measurements it can be observed that the fraction of voids increases with the decrease in medium particle filler diameter.

69

Gabriel Pinto and Ana Jiminez-Martin

4. The Shore D hardness is approximately constant with filler concentration for filler with the smallest average particle filler diameter. For the other fillers, this property shows a certain percolation transition in the hardness/filler concentration plots.

ACKNOWLEDGMENT We wish to thank Prof. Victoria Machuca for help

given in the preparation of this manuscript and to the reviewers for their valuable suggestions. The authors are also grateful to Raul Serrano from Laboratoire MSSMAT (Micanique des Sols, Structures et Materi- am). Ecole Centrule de Paris, for recording the optical microscopy micrographs.

NOMENCLATURE

u = volume electrical conductivity.

conductive filler particle.

composite.

uo = volume electrical conductivity of the

am = maximal conductivity reached by the

p = volume electrical resistivity. F = maximal value of the fdler volume fraction. P = volume fraction of the conductive fillers.

Pc = volume fraction of the conductive fillers at the percolation threshold.

electrical conductivity increase above Pc. t = exponent determining the power of the

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Conducting aluminum-filled nylon 6 composites