Research Article | Open Access
Dielectric and AC Conductivity Studies in PPy-Ag Nanocomposites
Polypyrrole and silver nanoparticles have been synthesized at 277 K by chemical route. Nanoparticles of polypyrrole-silver (PPy-Ag) composites were prepared by mixing polypyrrole and silver nanoparticles in different weight percentages. Dielectric properties as a function of temperature in the range from 300 K to 550 K and frequency in the range from 50 Hz to 1 MHz have been measured. Dielectric constant decreased with increase in frequency and temperature. Dielectric loss decreased with increase in frequency and increased with increase in temperature. Using dielectric data AC conductivity has been determined. Conductivity was found to be in the order of 10−3 (Ω−1 m−1) and it increased with increase in temperature. Temperature variation of conductivity data has been analyzed in the light of Mott’s polaron hopping model. Activation energy for conduction has been determined. Activation energy was determined to be in the order of meV and it has increased with increase in frequency and Ag nanoparticles content. This is the first time that PPy-Ag nanocomposites have been investigated for dielectric properties and AC conductivity and data analyzed thoroughly.
Polypyrrole (PPy) and silver (Ag) are two different types of conductors. PPy is an organic polymer exhibiting semiconductivity and Ag is a metal. Mixture of PPy and Ag particles is called hybrid composites because they combine different electrical features of the parent constituents. Both PPy and Ag display a variety of morphologies on the nanoscale. The properties of metal nanoparticles and conducting polymers instigated an interest in many researchers to synthesis and study nanocomposite materials [1–6]. Silver nanoparticles have applications in conductive inks and adhesives for various electronic components. The composites made of a metal and an organic semiconductor are expected to exhibit a good level of conductivity as well as tunable physical and chemical properties . Among them, the composites made of polypyrrole (PPy) and silver nanoparticles are the best example. Synthesis and size control of PPy nanoparticles have been studied and reported that PPy nanoparticles can be effectively dispersed due to large surface area and they exhibit good conductivity [8–10].
Silver nanoparticles exhibit semiconductor nature due to decrease in size and the optical band gap of silver nanoparticles was estimated using UV-visible spectra . The room temperature conductivity of PPy-Ag composite nanoparticles has been reported to be 4.9 × 10−2 Ω−1 m−1 . PPy-Ag composites exhibited a good ammonia gas sensing . Silver nanoparticles coated with PPy showed improved stability and functionality and measured enhanced conductivity . The combination of polyaniline with silver produced many functional materials that have showed enhanced electrical properties and varied dielectric properties . There are not many research reports on PPy-Ag composites studied for dielectric and AC conductivity properties as a function of temperature and frequency over wide ranges. In this communication, we present dielectric studies carried out on PPy-Ag nanocomposites. Using dielectric data, AC conductivity has been determined. Conductivity data has been analyzed in the light of Mott’s small polaron hopping model .
Highly pure analytical grade pyrrole, ammonium peroxidisulphate, methanol, acetone, silver nitrate, and sodium borohydride were used in the preparation of PPy nanoparticles and silver nanoparticles. Preparation of PPy nanoparticles was carried out at a temperature of 277 K. Aqueous solution of pyrrole was prepared and stirred for 30 minutes to attain homogeneity. Aqueous ammonium persulphate (APS) solution has been added dropwise to the pyrrole solution. After addition of few drops of APS, the solution turned into green indicating the formation of polypyrrole nanoparticles in the colloidal solution. On further addition of APS, the solution became black. The reaction has been carried out for eight hours. The colloidal solution was filtered and washed with double distilled water, methanol, and acetone several times to remove unreacted pyrrole and ammonia. The powder was collected, dried, and ground .
To prepare silver nanoparticles, the chemical reduction method was followed in which aqueous solution of silver nitrate (AgNO3) was added dropwise to ice-cooled aqueous solution of sodium borohydride (NaBH4). Thus silver ions were reduced and clustered to form monodispersed nanoparticles as a transparent sol in the aqueous medium [18, 19]. The solution was filtered and washed with distilled water and acetone several times. The collected powder was dried and ground.
Polypyrrole-silver (PPy-Ag) composite nanoparticles were prepared by mechanical mixing of polypyrrole and silver nanoparticles in the weight percentages defined as , where the weight percentage = 10%, 20%, 30%, 40%, and 50% and are labeled as PPy-AG1, PPy-AG2, PPy-AG3, PPy-AG4, and PPy-AG5, respectively. The results of SEM and XRD studies have been already published . Dielectric properties as a function of temperature and frequency have been investigated in Wayne Kerr Precision Impedance Analyzer (model number 6500B) in the frequency range from 50 Hz to 1 MHz and temperature range from room temperature to 550 K.
3. Results and Discussions
3.1. Dielectric Properties
The dielectric properties have been studied for all the PPy-Ag nanocomposites. Figure 1 shows the variation of dielectric constant with frequency for all the five composites. From this figure, we can note that decrease with frequency for all the samples. Dielectric loss factor variation with frequency for all the five composites is plotted in Figure 2. The nature of variation of with frequency is same as that of with frequency. Figure 2 shows that dielectric loss decreases with increase in frequency and at the higher frequency loss becomes almost constant and similar behavior was observed in . Temperature variation of for PPy-AG1 is shown in Figure 3. From Figure 3, we note that decreases with increasing temperature for small . Similar nature of variation of with temperature has been observed for the remaining composites. The change in with temperature for PPy-AG1 is shown in Figure 4. Similar behavior of with temperature has been observed in the case of other samples of the presented series.
3.2. Electrical Conductivity
Conductivity was estimated using dielectric data as per the following expression : where is the angular frequency and = 8.85 × 10−12 Fm−1 permittivity of free space. Error on the conductivity was estimated to be within 2%. Conductivity variation with temperature for different frequencies of the composite PPy-AG1 is shown in Figure 5. It can be seen in Figure 5 that conductivity increases with increasing temperature indicating semiconducting type of behavior.
It also increased with increasing frequency. But increase in conductivity with frequency is not appreciable at low frequencies. All the present composites behaved in the same fashion. Conductivity was found to be in the order of 10−3 (Ω−1 m−1).
Conductivity variation with Ag content for different frequencies at the temperature of 473 K is shown in Figure 6. From Figure 6, it is clear that conductivity increases with increasing silver content. This result reveals that a higher number of polarons (electrons) are getting added to the conducting pool in the composites as the Ag content is increased. Also, conduction mechanism in these composites appeared to be getting expedited with increasing frequency. This could be due to the fact that increase in frequency enhances polaron hopping frequency.
The temperature variation of conductivity has been fit to conductivity expression derived by Mott originally for the case of small polaron hopping (SPH) in noncrystalline semiconductor solids. It can be noted that, in the absence of a good quantitative theory for explaining conduction mechanism in conducting polymer composites which behave like semiconductors, here we use Mott’s SPH model. According to this model, the conductivity in the nonadiabatic region is given by where is the preexponential factor and the activation energy for small polaron hopping. The plots of versus () were made as per (2) for the composite of PPy-AG1 and shown in Figure 7. The linear lines were fit to the data in the high temperature region where the data appeared linear. The slopes were used to determine the activation energy for AC conduction.
Activation energy versus Ag content determined for the present composites for different frequencies is plotted in Figure 8. From Figure 8, one can note that decreases with increase of frequency. Also, increased with increase in Ag nanoparticles content. It may be that addition of Ag nanoparticles to the PPy network contributes more to the scattering of polarons such as grain boundary scattering.
Polypyrrole and silver nanoparticles have been synthesized at 277 K by chemical route. Nanoparticles of polypyrrole-silver (PPy-Ag) composites were prepared by mixing polypyrrole and silver nanoparticles in different weight percentages. Dielectric properties as a function of temperature and frequency have been measured over wide ranges. Dielectric constant decreases with increase in frequency and temperature. Dielectric loss decreases with increase in frequency and increases with increase in temperature. Using dielectric data, conductivity has been deduced. Conductivity was found to increase with increase in temperature and frequency. By employing Mott’s small polaron hopping model expression for conductivity, activation energy has been obtained. Activation energy was found to be increased with increase in frequency and Ag content. From these results, it can be predicted that, by embedding silver nanoparticles in polymer matrix, the electrical properties of the nanocomposites can be improved. It can also be concluded that the mechanical mixing method might be effective and could be used for a large-scale preparation of the PPy-Ag nanocomposites.
Conflict of Interests
The authors declare that there is no conflict of interests regarding the publication of this paper.
One of the authors, K. Praveenkumar, acknowledges the financial support from UGC, New Delhi, under UGC-BSR fellowship.
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