Relaxation Dynamics in Superionic Molybdate Glass Nanocomposites

Mar 4, 2010 - by melting the mixtures of the chemicals AgI, AgNO3, and MoO3 and ... particular, AgI-doped silver molybdate glasses4-9 are interesting...
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J. Phys. Chem. C 2010, 114, 5745–5750

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Relaxation Dynamics in Superionic Molybdate Glass Nanocomposites Embedded with r-AgI Nanoparticles S. Bhattacharya and A. Ghosh* Department of Solid State Physics, Indian Association for the CultiVation of Science, JadaVpur, Kolkata-700032, India ReceiVed: October 13, 2009; ReVised Manuscript ReceiVed: January 1, 2010

We have prepared silver molybdate glass nanocomposites of compositions xAgI-(1 - x)(yAg2O-(1 - y)MoO3) by melting the mixtures of the chemicals AgI, AgNO3, and MoO3 and quenching the melts. High-resolution transmission electron micrographs have been employed to detect the R-AgI nanoparticles present in the composites. We have studied relaxation dynamics of silver ions in these nanocomposites as a function of frequency and temperature. It has been observed that the variation of the average size of the R-AgI nanoparticles embedded in these nanocomposites and also the dilation of the glass network with AgI doping are responsible for the variation of the conductivity and hopping frequency with composition. The conductivity spectra have been analyzed using the power law model. We have observed that the power law exponent is almost independent of composition. The variation of the conductivity as well as the crossover frequency depends on the modifier to former ratio. We have estimated the concentration of mobile Ag+ ions from the Nernst-Einstein relation, which is found to be almost independent of temperature. We have further observed that only 20-23% of the total Ag+ ions contribute to the conduction process. I. Introduction Ion conducting superionic glasses and nanocomposites are recently under investigation for their technical application as solid electrolytes in electrochemical devices such as batteries, sensors, electrochromic displays, etc., due to their high ionic conductivity (∼10-2 Ω-1 cm-1) as well as for the academic interest to understand the nature of the ion transport process.1,2 These materials offer many advantages over polycrystalline ceramic electrolytes. One of the main scientific challenges is to explain how the disorder structure of glasses is related to high ionic conductivity achieved at ambient temperatures.3 In particular, AgI-doped silver molybdate glasses4-9 are interesting because of the anomaly in their structure as well as in their intensive properties, when compared with silver borate and silver phosphate glasses.4,10,11 Recent X-ray diffraction and transmission electron microscopic studies indicate the presence of R-AgI nanocrystals in molybdate glasses containing high AgI content.12 Although a few studies on the electrical properties of AgI-doped molybdate glasses have been reported,12-14 the role of AgI nanoparticles on the dynamics of silver ions in these nanocomposites has not been studied. The studies of the electrical properties and relaxation of AgI-doped iodomolybdate glass nanocomposites are very interesting not only from their technical application but also from the academic point of view. In order to determine the mechanism of ionic conductivity, it is necessary to separate the contribution of ionic concentration and mobility from the measured conductivity.15 A few methods have been suggested16 to determine the contributions of these two terms separately. Unfortunately, it has not been successful so far. Electrical conductivity spectroscopy is a well-established method for characterizing the hopping dynamics of ions. The frequency and temperature dependences of the conductivity spectra are often described using power law models, and the power law exponents obtained thereby are interpreted.17-20 * Corresponding author, [email protected].

In this paper, we have studied relaxation dynamics of silver ions in glass nanocomposites of compositions xAgI-(1 x)(yAg2O-(1 - y)MoO3) as a function of temperature and frequency. II. Experimental Procedures Three series of samples of compositions xAgI-(1 x)(yAg2O-(1 - y)MoO3), where y ) 0.2, 0.4, and 0.6, were prepared by quenching the melts. The x values are 0.1-0.5 for y ) 0.2, 0.1-0.7 for y ) 0.4, and 0.2-0.6 for y ) 0.6. The appropriate amounts of reagent grade powders AgI, AgNO3, and MoO3 (Aldrich Chem. Co.) were thoroughly mixed and preheated in a platinum crucible at 400 °C for 2 h for denitrogenation of AgNO3. The mixtures were then melted at temperatures in the range from 700 to 800 °C depending upon the composition. The melts were equilibrated for 2 h and finally quenched between two aluminum plates. Transparent samples of thickness ∼1 mm were obtained. Density of the samples was measured using Archimedes’ method. Molar volume was determined from composition and density. Formation of R-AgI nanocrystals in the prepared samples was confirmed from transmission electron microscopic (JEOL JEM 2010) studies. Glass transition temperatures of the samples were determined from differential scanning calorimetric measurements (PerkinElmer, DSC 7) in a nitrogen atmosphere. For electrical measurements both sides of the samples were painted with silver paste to serve as the electrode. Electrical measurements, such as capacitance and conductance, were carried out in the frequency range 10 Hz to 2 MHz and in the temperature range 100-303 K using an LCR meter (QuadTech, model 7600) and a closed cycle cryocooler (Janis Inc., model CCS-450), respectively. We have estimated the ionic part of the conductivity, using the Wagner polarization technique21 and observed that ionic contribution of the conductivity dominated (99.9%) over the electronic counterpart.

10.1021/jp909815t  2010 American Chemical Society Published on Web 03/04/2010

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Figure 2. Variation of the average size of R-AgI nanoparticles with AgI content for different compositions shown in the inset.

Figure 1. (a) TEM images showing distribution of nanocrystals, (b) their high-resolution TEM (HR-TEM), and (c) selected area electron diffraction (SAED) pattern for the 0.5AgI-0.5(0.4Ag2O-0.6MoO3) glass nanocomposite.

TABLE 1: d Values Obtained from SAED Patterns and ASTM Data Sheet for the Compositions xAgI-(1 x)(0.4Ag2O-0.6MoO3) compositions

d value (nm) from TEM

d value (nm) from ASTM data sheet22

x ) 0.10 x ) 0.20 x ) 0.30 x ) 0.40 x ) 0.50 x ) 0.60 x ) 0.70

0.40 (R-AgI) 0.22 (R-AgI) 0.20 (R-AgI) 0.40 (R-AgI) 0.22 (R-AgI) 0.20 (R-AgI) 0.40 (R-AgI)

0.38 0.23 0.21 0.38 0.23 0.21 0.38

III. Results and Discussion Panels a-c of Figure 1 show a transmission electron microscopic (TEM) image, a high-resolution transmission electron microscopy (HR-TEM) image, and the selected area electron diffraction (SAED) pattern of the 0.5AgI-0.5(0.4Ag2O-0.6MoO3) sample, respectively. The micrograph in Figure 1a demonstrates the distribution of nanoparticles (∼100 nm) dispersed in the glassy matrix. The lattice spacing (d value) was calculated from Figure 1c. The d values are in good agreement with those of R-AgI obtained from ASTM data sheet22 as shown in Table 1. The different d values (Table 1), calculated from the SAED patterns of different compositions, correspond to different (hkl) planes of AgI crystals. Figure 2 shows the variation of the average particle size of the R-AgI nanoparticles with AgI content in the compositions for different series. It is observed in Figure 2 that as the Ag2O/ MoO3 value increases, the size of the R-AgI nanocrystals become smaller. We have calculated the lattice strain at the interface between the nanocrystals and the glass matrix using the method described elsewhere23 and observed that the lattice strain becomes larger, when AgI content in the compositions is higher and this larger lattice strain leads to the reduction of size of the nanoparticles with the increase of AgI content in the compositions. The glass transition temperatures for several compositions for the series xAgI-(1 - x)(0.4Ag2O-0.6MoO3) are shown in Figure 3a as a function of AgI content. It is clear from the figure that as

Figure 3. (a) Variation of glass transition temperature (Tg) with AgI content for the series xAgI-(1 -x)(0.4Ag2O-0.6MoO3). (b) The variation of the molar volume for three glass series shown.

the AgI content increases in the compositions the glass transition temperature decreases. This result suggests that the glass structure becomes expanded increasing the free volume as the AgI content is increased. We have observed similar behavior for the other series also. The molar volume of different compositions is also shown in Figure 3b for the series. It is noted in the figure that the molar volume increases with the increase of AgI content in the compositions, supporting the above conclusion. The dc conductivity at different temperatures for all compositions was computed from the complex impedance plots. The variation of the dc conductivity with reciprocal temperature for the series xAgI-(1 - x)(0.2Ag2O-0.8MoO3) is shown in Figure 4a, while Figure 4b shows the same for the samples with fixed AgI content for the three series. Figure 4 indicates that the dc conductivity σdc for all compositions exhibits Arrhenius relation: σdcT ) σ0 exp(-Eσ/kT), where Eσ is the activation energy and σ0 is a pre-exponential factor. The values of the activation energy Eσ for different compositions were obtained from the leastsquares straight line fits. The dependence of the dc conductivity at 303 K and the activation energy on AgI content for all the compositions are shown in parts a and b of Figure 5, respectively. We note in Figure 5a that the conductivity increases with the increase of the AgI content for each series. In Figure 5b it is observed that the activation energy Eσ shows opposite trends.

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Figure 4. (a) dc conductivity of xAgI-(1 - x)(0.2Ag2O-0.8MoO3) glass nanocomposites shown as a function of reciprocal temperature. (b) dc conductivity of 0.4AgI-(1 - x)(yAg2O-(1 - y)MoO3) glass nanocomposites shown as a function of reciprocal temperature.

The variation of the dc conductivity at 163 K with average particle size for the series xAgI-(1 - x)(0.2Ag2O-0.8MoO3) is shown in Figure 6a. It is observed from Figure 6a that the conductivity decreases with the increase of the average particle size of R-AgI nanoparticles. We have observed similar results for other series also. The variation of the dc conductivity at 163 K with the glass transition temperature for the same series is shown in Figure 6b. It may be noted in Figure 6b that as AgI content increases, the dc conductivity increases and glass transition temperature (Tg) decreases. Thus, as AgI content increases, the structure of the glass nanocomposites becomes less compact and hence Tg decreases and the conductivity increases. The frequency dependence of the ac conductivity at a fixed temperature for the compositions with different modifier to former ratio is shown in Figure 7a and that for a particular composition at various temperatures is illustrated in Figure 7b. For each composition the conductivity is independent of frequency at low frequencies and corresponds to the dc conductivity. At high frequency, the ac conductivity shows dispersion. It may be further noted that the composition dependence of the conductivity is strong at low frequencies, while at higher frequencies the dependence is not significant. To study the ac conductivity data presented in Figure 7, we have used a power law model,14 according to which the frequencydependent conductivity can be described by the following power law expression

σ′(ω) ) σdc[1 + (ω/ωc)n]

(1)

Figure 5. (a) dc conductivity at 163 K shown as a function of AgI content in the glass compositions xAgI-(1 - x)(yAg2O-(1 - y)MoO3). (b) Activation energy shown as a function of AgI content for the same glass compositions as in (a).

Figure 6. (a) Variation of the dc conductivity at 163 K with average particle size for the series xAgI-(1 - x)(0.2Ag2O-0.8MoO3). (b) Variation of the dc conductivity at 163 K with the glass transition temperature for the same compositions as in (a).

which is the sum of the dc conductivity (σdc) and a fractional power law dependent dispersive conductivity with power law exponent n. Here ωc is a characteristic crossover frequency from the dc to

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Figure 7. (a) ac conductivity spectra at a fixed temperature (163 K) for the glass nanocomposites 0.3AgI-0.7(yAg2O-(1 - y)MoO3) and (b) ac conductivity spectra at different temperatures for the glass nanocomposites 0.4AgI-0.6(0.6Ag2O-0.4MoO3).

TABLE 2: Density, Activation Energy for dc Conductivity, Crossover Frequency at 163 K, Activation Energy for Crossover Frequency, Activation Energy for Mobile Ag+ Ion Concentration, and Frequency Exponent for the 0.3AgI-0.7(yAg2O-(1 - y)MoO3) Glass Nanocomposites y

density (g cm-3)

Eσ (eV) ((0.01)

log10 [ωc (rad s-1) ] ((0.02) at T ) 163 K

Ec (eV) ((0.01)

EN (eV) ((0.01)

n ((0.01)

0.2 0.4 0.6

6.22 6.44 6.63

0.37 0.35 0.32

3.22 3.50 3.80

0.36 0.35 0.32

0.04 0.05 0.05

0.66 0.68 0.67

the dispersive conductivity.15 Recently, the above model has been widely used to get insights into ion dynamics in ion conducting glasses.16,17 The validity of the power-law conductivity has been also observed in borate and phosphate glasses.24 The experimental data for the ac conductivity for various temperatures were fitted to eq 1, as illustrated in Figure 7. Three parameters σdc, ωc, and n were obtained at different temperatures. The quality of curve fitting is considered good, as the agreement between the fit and the data is within 1-2% in the entire frequency and temperature ranges. The different parameters obtained from the above fits are shown in Table 2 for a composition of each series. It is observed in Table 2 that the values of the power law exponent n for all compositions are approximately 2/3. Similar values of the exponent (nearly equal 2/3) were also obtained for borate and phosphate glasses.24,25 These values of the exponent also correspond to threedimensional conduction25 in the present nanocomposites. The variation of the crossover frequency at 163 K, obtained from the above fits, with AgI content is shown in Figure 8a. It is evident from Figure 8a that the composition with Ag2O/MoO3 ) 2/8 exhibits lowest crossover frequency. The values of the crossover frequency are found to increase with the increase of AgI content of each composition with different Ag2O/MoO3 ratio. It is observed in Figure 8b that the crossover frequency exhibits

Figure 8. (a) Variation of the crossover frequency at 163 K and (b) activation energy for the crossover frequency with AgI content in the glass nanocomposites.

Arrhenius behavior with activation energy (Ec) shown in Table 2. It may be noted in Table 2 that the activation energy for the conductivity and the crossover frequency is almost close to each other within experimental error. Thus the dc conductivity and the crossover frequency behave similarly. The concentration (Nc) of mobile Ag+ ions was estimated from the Nerst-Einstein relation

σdc ) q2d2NcωH /12πkT

(2)

where Nc is mobile ion concentration, q is the total charge, d is the average jump distance, and ωH is the hopping frequency of the mobile ions. In the calculation it is assumed that the hopping frequency is equal to the crossover frequency. This assumption has been verified recently.26 The reciprocal temperature dependence of the mobile Ag+ ions contributing to the transport process is shown in Figure 9a. We note that the concentration of mobile Ag+ ions is almost independent of temperature. The activation energy EN (Table 2) for the concentrations of mobile ions is very small. It may be noted that the mobile ion concentration and hopping frequency is related to the conductivity by σ ) Ncqµ, where µ is the mobility of silver ions. Since the mobility is proportional to the hopping frequency, it can be concluded that the variation of the conductivity is mainly due to the variation of mobility. In Figure 9b, the concentration of mobile Ag+ ions is shown as a function of AgI content for all compositions along with the concentration of the total Ag+ ions, which was estimated from the glass composition and density. It is observed in Figure 9b that only 20-23% of the total Ag+ ions contribute to the transport processes.

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Figure 9. (a) Variation of concentration (Nc) of mobile Ag+ ions with reciprocal temperature for the compositions 0.3AgI-0.7(yAg2O-(1 y)MoO3), y ) 0.2-0.6. (b) Variation of mobile Ag+ ion concentration (solid symbols) and total Ag+ ion concentration (open symbols) with AgI content for the same compositions as in (a).

Now according to the structural model of iodomolybdate glass and nanocomposites4,27 the R-AgI nanopartices occupy the position in the conduction pathways of Ag+ ions within the glass structure. As a consequence, as the particle size decreases the mobility of Ag+ ions increases due to less hindrance and hence the conductivity increases, although the concentration of the mobile Ag+ ions is weakly dependent on AgI content. It has been suggested11 that AgI doping causes dilation of the network structure available for Ag+ motion, by decreasing ionic crosslinking of the glass network, which leads to the considerable increase in conductivity. In the present glasses the dilation of the glass network structure is supported by the increase in molar volume with the increase of AgI content (Figure 3b). Thus, the decrease of the particle size accompanied by the dilation of the network structure is responsible for the large variation of the conductivity with the increase of AgI content in the present glass compositions.

IV. Conclusions The dc conductivity and conductivity spectra of Ag+ ions have been studied for a large number of AgI-doped iodomolybdate glass nanocomposites in a wide temperature range. The decrease of the average size of R-AgI nanoparticles in the glass matrix is the probable reason for the variation of the conductivity as well as the crossover frequency with the increase of AgI content. The dilation of the network structure with the increase of AgI content is also responsible for the increase of the conductivity. Both the dc conductivity and the crossover frequency obtained from the power law model show activated behavior with the same activation energy. The power law exponent is almost independent of AgI doping content. The mobile Ag+ ion concentration is independent of temperature and AgI content in the glass nanocomposites. Further, 20-23% of the total Ag+ ions contribute to the transport process. The conductivity spectra reveal that the relaxation dynamics of Ag+

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ions is independent of temperature and composition. The mobility of Ag+ ions increases due to the AgI doping, leading to an enhancement of the crossover frequency as well as the conductivity. Acknowledgment. Financial support by the Council of Scientific and Industrial Research, Government of India via Grant No. 03(1095)/07/EMR-II is thankfully acknowledged. The authors also acknowledge the support provided by the Department of Science and Technology, Government of India under its Nano Science and Technology Initiative. References and Notes (1) Minami, T. J. Non-Cryst. Solids 1985, 73, 273. (b) Angell, C. A. Annu. ReV. Phys. Chem. 1992, 43, 693. (2) Tomasi, C.; Mustarelli, P.; Magistris, A. J. Solid State Chem. 1998, 91, 140. Mustarelli, P.; Tomasi, C.; Magistris, A.; Cutroni, M. J. NonCryst. Solids 1998, 232-234, 532. (3) Tatsumisago, M.; Shinkuma, Y.; Saito, T.; Minami, T. Solid State Ionics 1992, 50, 273. (4) Minami, T.; Tanaka, M. J. Non-Cryst. Solids 1980, 38-39, 289. (5) Kawata, N.; Saito, T.; Tatsumisago, M.; Minami, T.; Kawamura, J. J. Non-Cryst. Solids 2003, 324, 79. (6) Hemlata, S.; Sarode, P. R.; Rao, K. J. J. Non-Cryst. Solids 1983, 54, 313. (7) Kawata, N.; Saito, T.; Tatsumisago, M.; Minami, T.; Kawamura, J. Solid State Ionics 2004, 175, 679. (8) Dalvi, A.; Awasthi, A. M.; Bharadwaj, S.; Shahi, K. J. Phys. Chem. Solids 2005, 66, 783.

Bhattacharya and Ghosh (9) Matsuo, S.; Yugami, H.; Ishigame, M. Phys. ReV. B 1993, 48, 15651. (10) Swenson, J.; McGreevy, R. L.; Borjesson, L.; Wicks, J. D.; Howells, W. S. J. Phys: Condens. Matter 1996, 8, 3545. (11) Wicks, J. D.; Borjesson, L.; Bushnell-Wye, G.; Howells, W. S.; McGreevy, R. L. Phys. ReV. Lett. 1995, 74, 726. (12) Keen, D. A.; McGreevy, R. L. Nature 1990, 344, 423. (13) Moyamoto, Y.; Itoh, M.; Tanaka, K. Solid State Commun. 1994, 92, 895. Schutt, H. J. Solid State Ionics 1996, 70, 505. (14) Almond, D. P.; Duncan, G. K.; West, A. R. Solid State Ion. 1983, 8, 159. (1983) 9-10, 277,Hairetdinov, E. F.; Uranov, N. F.; Patel, H. K.; Martin, S. W. Phys. ReV. B 1994, 50, 13259. (15) Sidebottom, D. L. Phys. ReV. B 2000, 61, 14507. (16) Ghosh, A.; Pan, A. Phys. ReV. Lett. 2000, 84, 2188. (17) Bhattacharya, S.; Ghosh, A. Phys. ReV. B 2006, 74, 184308. (18) Bhattacharya, S.; Ghosh, A. J. Phys.: Condens. Matter 2005, 17, 5655. (19) Adams, St.; Hariharan, K.; Maier, J. Solid State Ionics 1995, 75-, 193. (20) Kawamura, J.; Oyama, Y. Solid State Ionics 1989, 35-, 311. (21) Hariharan, K.; Kaushik, R. J. Mater. Sci. 1987, 22, 3335. (22) American Society for Testing Materials, Powder Diffraction File, Set: 1-5, 6-10, P-401, JCPDS Card: 08-0473, 75-1505, 72-1689. (23) Hall, W. H. J. Instrum. Methods 1950, 75, 1127. Bhattacharya, S.; Ghosh, A. Phys. ReV. B 2007, 75, 092103. (24) Cutroni, M.; Mandanici, A.; Raimondo, A. Phys. Chem. Glasses 2006, 47, 388. Cutroni, M.; Mandanici, A.; Mustarelli, P. J. Non-Crys. Solids 2002, 307, 963. (25) Sidebottom, D. L. Phys. ReV. Lett. 1999, 83, 983. (26) Ahmad, M. M.; Yamada, K.; Okuda, T. Solid State Ion. 2004, 167, 285. (27) Bhattacharya, S.; Ghosh, A. Appl. Phys. Lett. 2006, 88, 133122.

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