Electrical Transport Properties of Ion-Conducting Glass Nanocomposites

C H A P T E R

8 Electrical Transport Properties of Ion-Conducting Glass Nanocomposites S. Bhattacharya Siliguri Institute of Technology, Darjeeling, West Bengal, India

O U T L I N E 8.1 Introduction 8.2 Ion-Conducting Glass Nanocomposites 8.2.1 Molybdate Glass Nanocomposites 8.2.2 Selenite Glass Nanocomposites

182 183 183 185

8.3 Theory of Ion Conduction and Relaxation in Glasses and Glass Nanocomposites 185 8.3.1 Strong-Electrolyte Theory 186 8.3.2 Weak-Electrolyte Theory 187 8.3.3 AC Relaxation 187 8.3.3.1 Almond-West Formalism 187 8.3.3.2 Electric Modulus Formalism 188 8.4 Preparation of Ion-Conducting Glass Nanocomposites 8.4.1 Melt Quenching Followed by Heat Treatment

Glass Nanocomposites http://dx.doi.org/10.1016/B978-0-323-39309-6.00008-0

189 189

8.4.2 Chemical Route 8.4.3 Template Assisted Growth

190 190

8.5 Characterization Techniques 190 8.5.1 X-ray Diffraction 190 8.5.2 Field Emission Scanning Electron Microscopy and Energy-Dispersive X-ray Spectroscopy 191 8.5.3 Transmission Electron Microscopy 191 8.5.4 Differential Scanning Calorimetry 191 8.5.5 Fourier Transform Infrared Spectroscopy 192 8.5.6 Density and Molar Volume 192 8.5.7 Magnetic Susceptibility of Semiconducting Samples 192 8.5.8 Experimental Setup for Electrical Measurements 192 8.5.8.1 Sample Preparation for Dielectric and Electrical Measurements 193

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Copyright # 2016 Elsevier Inc. All rights reserved.

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8.6 Properties 193 8.6.1 X-ray Diffraction Study 193 8.6.2 Differential Scanning Calorimetry 194 8.6.3 Field Emission Scanning Electron Microscopy and Energy-Dispersive X-ray Spectroscopy 195 8.6.4 Transmission Electron Microscopy 196 8.6.5 FTIR Study 197 8.6.6 DC Conductivity 197 8.6.7 AC Conductivity 199 8.6.7.1 Conductivity Formalism 200 8.6.7.2 Modulus Formalism 205

8.7 Applications

208

8.8 Conclusions

208

8.9 Future Outlook

209

Exercises

209

Acknowledgments

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References

210

8.1 INTRODUCTION Ionic glass nanocomposites have been paid considerable attention recently due to their potential applications in solid-state electrochemical devices [1,2]. Silver oxide glass nanocomposites are good model systems to make out a relationship between structure and transport properties in disordered materials [3–5]. It has been observed that the oxide glass nanocomposite system containing large concentrations of transition metal oxide like MoO3 exhibit semiconducting behavior due to the presence of Mo ions in two valence states in the glassy matrix [6]. The binary silver molybdate glass nanocomposite system is particularly interesting because of the growing evidence of anomalous structure as well as different intensive properties when compared with binary silver phosphate, borate, and tellurite glassy system [7–9]. Infrared [10,11] and Raman spectroscopic [12] studies on AgI doped molybdate glass nanocomposite systems reveal that the molybdenum species exist as tetrahedral orthomolybdate anion MoO2
4 , while other reports have suggested octahedral molybdenum environment [13]. IR studies [11] on molybdate glass nanocomposite system with composition ratio Ag2O/ MoO3 < 1, reveal the two additional infrared absorption bands at 600 and 450 cm
1, respectively. X-ray photoelectron spectroscopy study [14] shows that the binding energy of molybdenum phosphate system typically increases with an increase in the oxidation state of Mo ions. In addition to these, glassy systems embedded with different nanophases have been the subject of intense research recently because of their unusual physical properties and potential applications [15,16]. The synthesis of nanodots, nanowires, nanobelts, etc., of different materials has posed challenging tasks to materials scientists. Different physical and chemical methods have been used to grow nanomaterials in different forms [17]. Recently, the synthesis of low dimensional metal molybdates such as MoO3 nanorods [18] have attracted a lot of recent interest due to their strong application potential in various fields such as photoluminescence (PL) [19], microwave applications [20], optical fiber [21], humidity sensor [22], etc. Binary silver molybdate glassy system formed with an unconventional network former has a substantial amount of void spaces within it. Nanometer-/micrometer-sized particles can be accommodated in these matrices. Melt-quenching technique has been carried out on selected

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silver molybdate glassy matrix to grow the dispersed phase of Ag6Mo10O33 nanowires, Ag2MoO4 nanoparticles, and Ag2Mo2O7 nanorods of definite geometrical shapes in the host glass matrix [23,24]. In general, a large number of studies on ionic conductivity and relaxation in oxide glass nanocomposite system have been reported [3,23–28]. However, no clear consensus on these processes has emerged so far. In order to determine the mechanism of ionic conductivity in these systems, it is necessary to separate the contribution of ionic concentration and mobility [29]. Unfortunately, it is not possible so far to determine ambiguously ionic concentration and mobility separately, although a few attempts [30–34] have been taken to solve the problem. The dependence of the relaxation process on the ionic concentration is another interesting problem. Contradictory results have been reported in the literature [35–40].

8.2 ION-CONDUCTING GLASS NANOCOMPOSITES When in a composite of two or many phases and at least one phase is of the order of nanometer (10
9 m) dimension, the composite material is called a nanocomposite [41]. The precipitation of metals or the formation of cluster in a glass matrix gives birth to glass nanocomposite. The composite thus obtained containing nanoclusters shows different physical properties from those of free atoms and bulk solids having similar chemical composition. Behavior of nanocomposites is sometimes dominated by interphasic interaction and sometimes by the quantum effect associated with the nanostructure. Nanostructured materials have been paid considerable attention because of their novel physical properties exhibited by matter having nanodimensional structure [41]. Oxide superionic glasses have a random network structure with physical void spaces and, therefore, can be exploited as nanotemplates in which distributed nanostructured particles can be generated. These types of oxide glasses containing the distribution of nanoparticles or nanoclusters are designated as glass nanocomposites. The resultant glass nanocomposites exhibit a difference in the electrical conductivity and activation energy from that of the host glass matrix. The understanding of the structure and the transport properties of glass and glass nanocomposites require the recognition of the following aspects (a) Physical structure, which describes the arrangement of atoms with respect to each other. (b) Chemical structure, which describes the nature of bonding (e.g., covalent, ionic, etc.) between three different species (two cations and oxygen anion). (c) Bonding energy structure, which describes the strength of various bonds. (d) Electrical properties that is, conductivity, current-voltage characteristics, etc.

8.2.1 Molybdate Glass Nanocomposites The structure of molybdate glass nanocomposites is constructed from several asymmetric 2
units, mainly MoO2
4 tetrahedra and Mo2O7 ions [42]. Most of the glass nanocomposites containing MoO3, exhibits absorption peaks 875, 780, and 320 cm
1 (ν1, ν2, and ν3 modes of MoO2
4 tetrahedral ions) which are confirmed from the Fourier transform infrared (FTIR) study [42,43].

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Kawamura et al. [44] showed that the progressive change of activation energy observed in the AgI doped molybdate glasses could be attributed to the order-disorder transition in the α-AgI crystal. The ionic conductivity of these glasses occurred due to the cooperative liquid-like motion of the mobile ions and the network structure of glasses probably cause the non-Arrhenius behavior in the rapidly quenched AgI-Ag2O-MoO3 glasses. Eckert et al. [45] demonstrated the local structures of molybdenum species in the glasses in the system AgI-Ag2O-MoO3 using near infrared Fourier transform Raman spectroscopy. They showed that in glasses with the Ag2O/MoO3 ratio of unity, the molybdenum species were present only as tetrahedral monomeric orthomolybdate ions, MoO2
4 . On the other hand, in the glasses with Ag2O/MoO3 molar ratios less than unity, molybdenum species were present as tetrahedral orthomolybdate anions, MoO2
4 . The preponderance of evidence from NMR and vibrational spectroscopy suggests that this unit contains linked MoO4 tetrahedra and MoO6 octahedra. They also showed that the structure of these units was probably similar to the chain ions present in crystalline Na2Mo2O7. Minami and Tanaka [42] showed that glasses with molar ratio Ag2O/MoO3 ¼ 1 contained no condensed macroanions, but only discrete Ag+, I
, and MoO2
4 . In their model, only a part of the silver ions were believed to participate in the conduction process. A recent report [46] on electrical properties of semiconducting tellurium molybdate glasses has adequately been explained using small polaron theory. This report also showed that the glass-forming oxide greatly affected the magnitude of the conductivity and the activation energy for hopping conduction. Ionically conducting glasses and glass nanocomposites containing MoO3 have attracted much attention because of their potential application in many electrochemical devices such as solid-state batteries, electrochromic displays, and chemical sensors [47]. In particular, silver ion conducting glasses are at the focus of current interest, because of their high stability against humidity and their high electrical conductivity in the range of 10
1 S cm
1 at room temperature. Glasses in the system AgI-Ag2O-MoO3, first reported by Minami [42,43], belong to this group of materials, and their glass-forming regions, electrical properties, glass transition temperatures, and local structures have been examined extensively [42,43,47–50].

FIGURE 8.1 Glass-forming region and samples investigated in the system AgI-Ag2O-MoO3; () glassy and (•) crystalline samples.

Agl Series I

80

20 40

Series II

60

60

40

80

Ag2O

20

20

40

60

80

MoO3

Ag2Mo2O7cryst. Ag2MoO4cryst.

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The formation region of the superionic glass nanocomposite system containing MoO3 [51] is shown in Figure 8.1. In particular, the structure of glasses with compositions on the tie line AgI-Ag2MoO4 have been investigated by many researchers, using IR [42,43,52], Raman [53], EXAFS [54], and neutron diffraction [55]. While many studies agree that the in these glass molybdenum species exist as tetrahedral orthomolybdate anion MoO2
4 nanocomposite systems [42,43,53,54], other reports have claimed octahedral molybdenum environment [55,56].

8.2.2 Selenite Glass Nanocomposites The idea of synthesizing selenite glass nanocomposites belongs to Rawson [57] and Stanworth [58] who obtained these in the K2O-SeO2 and SeO2-TeO2-PbO systems. Dimitriev et al. [59] obtained stable homogeneous glasses with high content of SeO2 in combination with other nontraditional network formers, viz., V2O5, TeO2, and Bi2O3. IR spectra show the independence of SeO3 pyramids at νs ¼ 860-810 cm
1 and νd ¼ 720-710 cm
1, participated in the network when the SeO2 concentration is low. As the SeO2 content increases, SeO3 groups became associated into chains which contain isolated Se]O bonds with a vibration frequency at 900-880 cm
1. Satyanarayana et al. [60] studied the differential scanning calorimetry (DSC) for the AgIAg2O-SeO2-V2O5 system. They observed a decrease in Tg with the increase in AgI content. They suggested that a larger number of bonds were destroyed within the network in order to allow its rearrangement to form a more open type thermodynamically stable phase. Venkateswarlu et al. [61] showed that the DC conductivity of AgI-Ag2O-SeO2-V2O5 system increases with the AgI content and exhibited highest conductivity (σ ¼ 2.63  10
2 Ω
1 cm
1) for the 66.67% AgI-23.07% Ag2O-10.26% (0.8SeO2 + 0.2V2O5). In the system with higher AgI content, the conductivity was found to decrease. This type of decrement of conductivity was explained from their structural behavior.

8.3 THEORY OF ION CONDUCTION AND RELAXATION IN GLASSES AND GLASS NANOCOMPOSITES Over the last few years of the millennium, there has been a renewed interest in the electrical properties of various ionic conductors [42,43,62–64]. The room temperature conductivity in these glasses can vary from as little as 10
15 to as much as 10
2 Ω
1 cm
1, which makes them suitable for many electrochemical applications like electrolytes in solid-state batteries or sensor materials for different applications [62–64]. High values of conductivity arise in fast-ionconductors in which the diffusing atoms are charged and carry electric current. Various types of ions can diffuse in glass nanocomposites, which includes the Li+ ion (the smallest) to Ag+ ion (the most deformable) having highest conductivity [42]. Below the glass transition temperature, Tg, the ionic conduction of most ionically conducting glass nanocomposites follows Arrhenius law σ ¼ σ 0 expð
Eσ =kB T Þ II. OXIDE GLASS NANOCOMPOSITES

(8.1)

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where Eσ is the activation energy for conduction, kB is the Boltzmann constant, and T is the absolute temperature. Thus, below Tg the cations can be thought to move in a fixed network and the movement is thermally activated and above Tg, the movement of the ion is facilitated by the cooperative movement of macromolecular chains and the conductivity obeys VogelFulcher-Tammann (VFT) equation given by σ ¼ σ 0 exp½
E0 =kB ðT
T0 Þ

(8.2)

The microscopic mechanisms responsible for ionic conduction in glass nanocomposites, however, are still not well understood due to the difficulty in independently determining the carrier concentration and mobility. The DC conductivity for materials with one type of carrier is given by σ dc ¼ ðZeÞnμ

(8.3)

where Ze is the charge of the carrier, n is the concentration of mobile carriers, and μ is the mobility. Any discussion regarding the mechanism of ion transport in glass nanocomposites must focus on two models, (i) Strong-electrolyte model (Anderson-Stuart model) [65], and (ii) Weak-electrolyte model (Ravaine-Souquet model) [66].

8.3.1 Strong-Electrolyte Theory The strong-electrolyte theory was developed by Anderson and Stuart. The AndersonStuart model [65] is a structural model which considers the activation energy as the energy required to overcome electrostatic forces (ΔEB) plus the energy required to open up “doorways” in the structure large enough for the ion to pass through (ΔES). The first time this model in the atomic level has been successfully utilized by Martin and Angell [67]. According to this model, the total activation energy is given by ΔEact ¼ ΔEB + ΔES

(8.4)

where the binding energy term is given by ΔEB ¼ ZZ0 e2 ½ 1=ðr + r0 Þ
2=λ=ε1

(8.5)

and the strain energy term modified by McElfresh et al. [68] is given by ΔES ¼ πGD λðr
rD Þ2 =2

(8.6)

In effect, ΔEact is the difference between the bottom of the energy well (where the cation normally resides) and the maximum in energy where the cation is poised halfway between neighboring sites. In the above equation, GD is the shear modulus of the system, rD is the interstitial window, r is the mobile cation, and r0 the nonbridging anion radii. λ is the average jump distance, Z and Z0 are the number of charges on the mobile cation and the anion, and e is charge of the electron. The physical and structural parameters necessary to verify the validity

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of the Anderson-Stuart model and the experimental methods required for measuring the following parameters. ΔEact: determined from the reciprocal temperature dependence of ionic conductivity measurements. λ: approximated from the average cation-cation separation calculated from density and composition. ε1: determined from the frequency spectra of dielectric permitivity. GD: computed from acoustic measurements. rD: the interstitial window radius determined from inert gas diffusion studies.

8.3.2 Weak-Electrolyte Theory Ravine and Souquet [66] originally developed the weak-electrolyte model to describe conduction energetics in glass nanocomposites, because of the similarities that exist between aqueous and glassy electrochemistry. It has been hypothesized that, when an alkali oxide modifier (or a dopant salt) is added to a glass nanocomposite, the dissociation of the alkali away from the nonbridging oxygen (or salt ion) is the dominant energetic barrier that the cation experiences in conduction. In this model it is believed that, once a cation has dissociated away from its charge-compensating equilibrium site, the charge carrier is free to migrate until it is trapped by another charge-compensating site.

8.3.3 AC Relaxation The AC electrical relaxation is studied using the conductivity and the electrical modulus formalisms, which are discussed in the next two sections. The first part is a description of the Almond-West model, which relates the DC conductivity to the AC conductivity, and a second part is a discussion of conductivity relaxation in terms of the electrical modulus and conductivity. 8.3.3.1 Almond-West Formalism Jonscher [69,70] proposed the following empirical relationship for the dispersion in the imaginary part of the AC complex dielectric constant (dielectric loss)
a
b
1 ω ω 00 + (8.7) ε ðωÞ∝ ωp ωp where ωp ¼ 2πνp is the dielectric loss peak frequency and m and n are parameters which describe the slope on the high and low side, respectively, of the dielectric loss peak. Similarly, Jonscher showed that a power law relationship (ωn, 0 < n  1) could be used to describe the dispersion in the real part of the conductivity σ 0 (ω). Almond and West [71,72] accounted for the conductivity in both the frequency-independent and -dependent region by combining the DC conductivity with Jonscher’s “universal” power law behavior in a selected frequency regime (10 Hz-2 MHz) σ 0 ðωÞ ¼ σ DC + Aωn II. OXIDE GLASS NANOCOMPOSITES

(8.8)

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where n describes the frequency dependence of the conductivity and A is a temperature dependent parameter. They related the real part of the complex conductivity to the dielectric loss through σ 0 ðωÞ ¼ ωε00 ðωÞ Substituting Eq. (8.7) in Eq. (8.9), Almond and West obtained "

 # ω a ω b
1 0 + σ ðωÞ∝ω ωp ωp

(8.9)

(8.10)

After simplifying Eq. (8.9), σ 00 ðωÞ ¼ σ DC ½1 + ðω=ωHÞn

(8.11)

The conductivity in the low frequency region (10 Hz-2 MHz) obeying Jonscher’s law is due to the ion hopping process as described above and this power law does not obey in the high frequency region (10 MHz-1.8 GHz). The conductivity spectra in the high frequency region (10 MHz-1.8 GHz) can be explained with migration concept [73,74] by Funke. The migration concept provides a means for reproducing experimental conductivity spectra via velocity autocorrelation functions, hv(0)v(t)i. The latter are available from a set of rules for the hopping dynamics of mobile ions. It is useful to introduce the time-dependent correlation factor, W(t), which is the probability for the ion to be (still or again) at its new position at time t after its initial forward hop. W(t) is the normalized integral of hv(0)v(t)i. In order to find the proper shape of W(t), a set of rules was applied for the migration concept [73,74]. These are
W 0 ðtÞ=W ðtÞ ¼
B g0 ðtÞ

(8.12)


g0 ðtÞ=gðtÞ ¼ Γ 0 W ðtÞN ðtÞ

(8.13)

N ðtÞ ¼ N ðαÞ + ðBgðtÞÞλ

(8.14)

Here, it was assumed that the rates of relaxation along the single particle route, with the ion hopping backwards, and on the many particle route, with the other ions rearranging, are both proportional to the same driving force, g(t), and hence proportional to each other. Here, the proportionality constant is called B. The limiting case of B ¼ 0 corresponds to random hopping, the dynamics not being affected by interactions. 8.3.3.2 Electric Modulus Formalism The change over from the frequency-independent (σ DC) to the frequency-dependent [σ(ω)] region signals the onset of the conductivity relaxation phenomena; the transition from longrange ion motion to short range ion motion. As the mechanical modulus of any mechanical system is used to have a measure of the tendency of that system to relax back to its initial state upon the removal of the cause of mechanical distortion, the electric modulus formalism, proposed by Macedo et al. [75,76], is often used to relate the conductivity dispersion to the relaxation of the mobile ions and gives a

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measure of the relaxation of the ions back to their original state on collapsing of the electric field. This formalism is preferred, as it is easier to relate the ion relaxation to other properties, such as the dynamic mechanical modulus, and can be written as a single function of the conductivity. The electric modulus is defined as the reciprocal of the complex dielectric permittivity, i.e., M*(ω) ¼ 1/ε*(ω). The real part of the conductivity is written in terms of the complex electrical modulus M*(ω) as, " # M00 ðωÞ 0 00 (8.15) Reðσ ðωÞÞ ¼ ωε0 ε ðωÞ ¼ ωε0 M0 ðωÞ2 + M00 ðωÞ2 where ε0 is the dielectric permittivity of free space, ε00 is the imaginary component of the complex relative permittivity ε*, and M0 and M00 are the real and imaginary parts of the complex electrical modulus M*. The electrical modulus M*(ω) is related to the time-dependent electrical stress relaxation function φ(t) by 
  ð1 1 dφ ¼ M1 1
dt (8.16) e
jωt M ðωÞ ¼  ε ðωÞ dt 0 where M1 ¼ 1/ε1 and ε1 is the high frequency limit of the real part of the dielectric constant [75,76]. φ(t) is the correlation function that describes the decay in time of an applied electric field in a homogeneous conducting dielectric.

8.4 PREPARATION OF ION-CONDUCTING GLASS NANOCOMPOSITES 8.4.1 Melt Quenching Followed by Heat Treatment An essential prerequisite for “glass nanocomposite” formation from the melt is that the cooling be sufficiently fast to preclude crystal nucleation and growth; the crystalline phase is thermodynamically more stable and crystal growth will always dominate over the formation of the amorphous phase if allowed to take place. The condition for glass nanocomposite formation is that the nucleation rate should be less than a certain value, 10
6 cm
1 s
1. The most rapid melt-quench technique is the “splat-quenching method,” developed specially for metallic glass proposed by Duwez [77] which achieved the cooling rate of 105108 K s
1. When the glassy nanocomposite systems are passed through a heat treatment above their glass transition temperatures, different nanophases are found to grow in the host glass matrix. Tatsumisago et al. [78] prepared the sample 70Li2S-30P2S5 and heated them at 240 °C for 2 h (glass transition temperature was found to be 210 °C) to obtain glass-ceramic samples. They found that the conductivity of the heat-treated samples was much greater than their glassy counterparts. The conductivity enhancement was assumed to be due to the precipitations of highly lithium ion conducting crystals from the Li2S-P2S5 system.

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8.4.2 Chemical Route This approach involves selecting suitable precursor chemicals, which were subjected to heat treatment under different atmospheric conditions. Huber et al. [79] used the pressure injection technique for preparing nanowire arrays of metals (In, Sn, and Al) and semiconductors (Se, Te, GaSb, and Bi2Te3) within the channels of anodic alumina membranes. A novel method for surfactant-assisted growth of crystalline copper sulfide nanowires was reported by Wang et al. [80].

8.4.3 Template Assisted Growth The electrode position inside nanoporous membrane templates has provided a versatile approach to prepare nanowires of metals, semiconductors, and polymers [81]. In comparison to other procedures, template methods are generally inexpensive, allowing deposition of a wide range of nanowire materials, and presenting the ability to create very thin wires (5 nm to 10 μm), with aspect ratios (length over diameter) as high as 1000 [82,83]. Another important advantage of the template method is that the nanowires can be diametercontrollable and well defined, that is, the template provides an effective control over the uniformity, dimensions, and shape). In particular, porous anodic aluminum oxide (AAO) has nanometer size channels (about 5-250 nm in diameter), with high pore densities (up to 1011 pores/cm2), and controllable channel lengths (a few nanometers to hundreds of micrometers). For this reason, AAO can serve as an ideal template for the growth of monodispersive nanowires [84,85]. The diameter and density of the pores are controlled by varying the anodization conditions of high purity aluminum. In addition, the AAO templates are especially suited for use at higher temperatures (thermally stable up to 1000 °C) [85].

8.5 CHARACTERIZATION TECHNIQUES 8.5.1 X-ray Diffraction To ensure the nature of the prepared samples, X-ray diffraction (XRD) was carried out on the powdered glass samples using a Rich-Seifert X-ray diffractometer (Model 3000P) for recording the diffraction traces (2θ vs. intensity) of the powdered samples. In this instrument, Ni filtered CuKα radiation operating at 35 kV and 25 mA in a step scan mode was used. The step size was taken to be of 0.02° in 2θ and a hold time of 2 s per step. The hardware of XRD 3000 systems comprises of the generator ID 3000, the monitor and accessory controller C 3000 and the timer/counter hardware. The diffraction traces were recorded at room temperature. From the diffraction peaks of the XRD pattern, the average particle size of different nanoparticles was determined using Debye-Scherer formula [86] t ¼ 0:89λ=ðβ cos θÞ

(8.17)

where t denotes the average grain size of the particles, λ stands for the X-ray wavelength ˚ ), θ for the Bragg diffraction angle, and β for the peak width in radians at half-height. (1.54 A

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Crystallite size and the lattice strain of the crystal can be evaluated separately from XRD study by Hall’s equation [87], βhkl cos θ=λ ¼ 2η sin θ=λ + K=D

(8.18)

where βhkl is the full width half maximum of a given (hkl) diffraction peak, λ is the wavelength of the X-ray, D is the crystallite size, η is the measure of the heterogeneous lattice strain, θ is the Bragg angle, and K is a constant of 0.9. From the plots between βhkl cos θ/λ and sin θ/λ for the major (hkl) diffraction peaks of different nanocrystals in the samples, the values of βhkl were determined from the Gaussian function which was fitted to the major diffraction peaks. The values of η and the measure of lattice strain were obtained from the slope of the plots.

8.5.2 Field Emission Scanning Electron Microscopy and Energy-Dispersive X-ray Spectroscopy To explore the microstructure and surface morphology of the prepared glass nanocomposites [23,24], field emission scanning electron micrographs (FESEM) of the polished surfaces of the samples were taken in a field emission scanning electron microscope ˚ ) was deposited on the polished surfaces (JEOL JSM-6700F). A thin platinum coating ( 150 A of the samples by vacuum evaporation technique for a conducting layer. The quantitative investigation of the final compositions has been done from energy-dispersive X-ray study of the corresponding FESEM image.

8.5.3 Transmission Electron Microscopy Transmission electron microscopy (TEM) (JEOL JEM2010) is a powerful and unique technique for characterization of the microstructure of the prepared glass nanocomposites. By forming a nanometer-size electron probe, TEM is unique in identifying and quantifying the chemical and electronic structures of individual nanocrystals. The powder sample was sonicated for 15 min in acetone medium to form very fine suspended particles in acetone medium. By pouring a very small droplet of that colloidal solution having fine particles onto carbon coated Cu-grids (400 mesh), grid-preparation was made for transmission electron microscopy. The focused beam of electron is allowed to pass through the samples in the very high vacuum chamber. The final data were recorded using a charge coupled device. Bright and dark field images and selected area electron diffraction (SAED) pattern of the samples [23,24] were taken. The inter planner spacing (dhkl) were found from the SAED patterns and also from the high-resolution transmission electron microscopy (HRTEM).

8.5.4 Differential Scanning Calorimetry To determine the thermodynamic properties such as glass transition temperature (Tg) and crystallization temperature (Tc), DSC of the powder sample is performed in a Perkin-Elmer Differential Scanning Calorimeter (DSC7) operates in the temperature range from
150 to 500 °C in nitrogen atmosphere. In this process fine powder of sample is taken in aluminum pan. Pure Al2O3 in other crucible is used as a reference. The glass transition temperatures (Tg) and the crystallization temperatures (Tc) were determined from the endothermic shoulder and exothermic peak.

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8.5.5 Fourier Transform Infrared Spectroscopy The FTIR spectra of the powder sample in KBr matrices in transmission mode were recorded in a Nicolate FTIR spectrophotometer (Magna IR-750, Series II) in the wave number range of 400-4000 cm
1 at a temperature 25 °C and humidity at 50-60%. Each bonding in the sample has a characteristic frequency of vibration. When IR is transmitting through the sample, the frequency of the bonding of the sample is exactly matched with particular frequency of the IR region, some peaks are found due to resonance of frequency.

8.5.6 Density and Molar Volume The densities of the prepared glass nanocomposite samples were measured by Archimedes principle using acetone as an immersion liquid. Molar volume of a substance is the volume of one mole of that substance. Molar volume of a substance is defined as the ratio of its molecular or atomic weight, whichever is suitable to its density. The relationship between density and composition of an oxide glass nanocomposite system can be expressed in terms of an apparent molar volume of oxygen (VM) for the system, which can be obtained using the formula X VM ¼ xi Mi =ρ (8.19) where xi is the molar fraction and Mi is the molecular weight of the ith component.

8.5.7 Magnetic Susceptibility of Semiconducting Samples The magnetic susceptibility of the semiconducting samples at room temperature was determined using a EG & G Parc (Princeton, NJ) vibrating sample magnetometer (Model 155). The electronic concentration was obtained from the following relation χ ¼ N 2 μ2B p2eff =3RT

(8.20)

where, χ is the paramagnetic susceptibility, Ig is the intensity of magnetization, Hg is the applied magnetic field, M is the molecular weight of the sample under consideration, N is the electronic concentration, μBpeff is the effective magnetic moment in BM unit, R is the universal gas constant.

8.5.8 Experimental Setup for Electrical Measurements The block diagram for the experimental setup for electrical measurements in wide frequency and temperature range is shown in Figure 8.2. The electrical conductivity measurements of the as-prepared samples have been carried out at various temperatures by complex impedance method. For this, the samples of about 1 mm thickness has been used and the measurements were made by the two-probe method. The sample inside the sample holder has been kept in contact with two polished, cleaned, and spring-loaded copper electrodes (JoyCrucible made). The complex impedance measurements were carried out using Hioki LCR tester (Model No. 3532-50) in the frequency range 42 Hz to 5 MHz at various temperatures.

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193

8.6 PROPERTIES

A

PC

TC

R GPIB

RLC meter bridge

Temp controller

Sample holder

Probes

TT

Tab Furnace F Sample Sample holder

FIGURE 8.2 Block diagram for the experimental setup for frequency-dependent electrical measurements using Hioki LCR tester (Model-3532-50).

8.5.8.1 Sample Preparation for Dielectric and Electrical Measurements The prepared glass nanocomposites were shaped rectangular or circular by cutting the samples with a diamond cutter. Gold electrodes were deposited on both surfaces of the polished samples by vacuum deposition technique. The gold-coated samples were then heated at 50-60 °C for 2 h for the stabilization of the electrodes. In some cases, silver paste was painted on the both sides of the fragile sample as electrodes.

8.6 PROPERTIES 8.6.1 X-ray Diffraction Study The XRD patterns of the 0.3Ag2O-0.7(xZnO-(1
x)0.5MoO3) glass nanocomposites with x ¼ 0.05, 0.10, and 0.20 are presented in Figure 8.3a. In these diffractograms, broad diffuse scattering at low angles indicates a long-range structural disorder, which is characteristic of amorphous network. It is observed that (011) peaks due to Ag6Mo10O33 crystal with P1 space group and (112) peak due to Ag2Mo2O7 of P1 space group triclinic symmetry [88,89], respectively. (201) peak due to Ag2MoO4 cubic system of Fd3m space-group structure and (103) peak due to Ag2Mo2O7 [89] are presented in Figure 8.3a. (440) peak due to Ag2MoO4 cubic system is also shown. The (100) peak and corresponding d-values [90] refer to the confirmation of dispersed ZnO nanoparticles in the glass matrix. It is clear from Figure 8.3a that change in heights of the several peaks indicates the variation of polycrystalline nature of the samples. It is also noted that the peak heights except (110) are found to decrease with the increase of ZnO content. Here, ZnO may be acting as stabilizer and it may impel more and more Ag+, Mo6+, and O2
to take part into the structure. The interplaner spacings between two

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8. ELECTRICAL TRANSPORT PROPERTIES OF ION-CONDUCTING GLASS NANOCOMPOSITES

FIGURE 8.3

Intensity (a.u.)

(a) X-ray diffractograms of 0.3Ag2O0.7(xZnO-(1
x)0.5MoO3) glass nanocomposites with different values of x. (b) Histogram of particle distribution for x ¼ 0.05.

10

20

30

(a)

40

50

60

70

80

2q

Particle frequency

4

3

2

1 10

(b)

20

30

40

50

60

70

Particle size (nm)

successive planes (d-values) have been computed from XRD analysis. These d-values are also good agreement with those received from ASTM data sheet [88]. The Particle sizes of ZnO, Ag2MoO4, Ag2Mo2O7, and Ag6Mo10O33 nanoparticles dispersed in glass nanocomposites have been determined from Debye-Scherer formula [86]. The histogram of particle distribution for x ¼ 0.05 is presented in Figure 8.3b and it shows Gaussian in nature. Calculated d-values obtained from TEM, XRD, and ASTM data sheet for xAg2O-(1
x)MoO3 system [24] are presented here.

8.6.2 Differential Scanning Calorimetry The DSC curves of the glass nanocomposites xAg2O-(1
x)MoO3, for x ¼ 0.20, 0.30, and 0.40, respectively, are shown in Figure 8.4a. Figure 8.4b shows the variation of glass transition temperature (Tg) with compositions. The glass transition temperatures for x ¼ 0.20, 0.30, and

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195

8.6 PROPERTIES

450

x = 0.40

400 Tg (⬚C )

x = 0.30

Endo

Exo

xAg2O−(1−x)MoO3

x = 0.20

350 300 250

100

(a)

200 300 T (⬚C )

400

0.2

(b)

0.3 x

0.4

FIGURE 8.4 (a) DSC plots and (b) variation of glass transition temperature (Tg) with x for the compositions xAg2O-(1
x)MoO3.

FIGURE 8.5 FESEM of some glass nanocomposites 0.3Ag2O-0.7(xMoO3-(1
x)SeO2) with (a) x ¼ 0.7 and (b) 0.9, respectively.

0.40 are found to be 290, 250, and 200 °C, respectively, and crystallization temperatures are 415, 350, and 260 °C, respectively.

8.6.3 Field Emission Scanning Electron Microscopy and Energy-Dispersive X-ray Spectroscopy Figure 8.5a and b represent FESEM of as-prepared glass nanocomposites 0.3Ag2O-0.7(xMoO3-(1
x)SeO2) with x ¼ 0.7 and 0.9, respectively. It is observed from surface morphology as shown in Figure 8.5 that each sample contains a globular-like structure [23] of Ag2Mo2O7 and SeO2 of average size 40 nm and flake like structures [57,59] of Ag2Se and SeO2 having 2 μm in length and 80 nm in breadth, respectively. Theses phases were

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8. ELECTRICAL TRANSPORT PROPERTIES OF ION-CONDUCTING GLASS NANOCOMPOSITES

confirmed from XRD studies. It is also observed that in the lower MoO3 content sample, SeO2 has a prominent tendency of agglomeration and formation of more flakes like structures of Ag2Se and SeO2 as shown in Figure 8.5a. As the MoO3 content increases, large particles Ag2Mo2O7 and SeO2 are formed due to agglomerates of much smaller particles. Figure 8.5b shows the Ag2Mo2O7 nanorod-like structure of 300 nm in length and 15 nm in diameter.

8.6.4 Transmission Electron Microscopy The distribution of dispersed CuMoO4 nanoparticles in the xCuI-(1
x)(0.5CuO-0.5MoO3) glass nanocomposites [91] has been confirmed from the transmission electron microscopic (TEM) study as illustrated in Figure 8.6, for a particular sample x ¼ 0.2. The average grain size 20 nm of CuMoO4 nanoparticles has been estimated from TEM study. It is also observed that the density of distribution of CuMoO4 nanoparticles is found to increase with the increase of CuI content. SAED patterns and high-resolution transmission electron microscopic (HRTEM) results of them are presented in Figure 8.6b and c. The inter- planer spacings between two successive lattice planes (d-values) have also been computed from these SAED patterns

(a) TEM image displays the distribution of frozen CuMoO4 nanoparticles for x ¼ 0.2. (b) SAED pattern for x ¼ 0.2. (c) HRTEM for x ¼ 0.2. (d) HRTEM for x ¼ 0.4. Reproduced from Ref. [91] with permission, Copyright# Elsevier.

FIGURE 8.6

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8.6 PROPERTIES

FIGURE

8.7 FTIR spectra in the 1800-400 cm
1 of the glass nanocomposites.

region

0.3 Ag2 O-0.7 (xZn O-(1−x) MoO3)

% Transmittance (a.u.)

x = 0.20

1800

x = 0.10

x = 0.05

1600

1400 1200 1000 800 Wave number (cm–1)

600

400

and HRTEM micrographs. These d-values corresponding to CuMoO4 nanoparticles are in agreement with those values obtained from ASTM data sheet [21].

8.6.5 FTIR Study The room temperature FTIR spectra in the region 1800-400 cm
1 for all glass nanocomposites under investigation are shown in Figure 8.7. It is observed in Figure 8.7 that the most prominent absorption band at 871 cm
1 of crystalline MoO3 due to the symmetric stretching [52] of ModO octahedral unit is shifted toward lower wavenumbers as ZnO is introduced and then increased. This peak shift implies that the bond strength of ModO in compositions becomes weaker with the increases in the ZnO content. This bond weakening in the glass nanocomposites results from the presence of partial covalency [11] in ZndOdMo. The bands at 979 and 745 cm
1, which can be assigned as ν1 and ν3 stretching vibrations of Mo2O2
7 ions, [54] are present in the compositions. The shift of the peaks for all the compositions is likely due to the formation of zinc molybdenum oxide [Zn(MoO4)] and molybdite [MoO3] nanoparticles embedded in the glass matrix, which are confirmed from other studies. The band at 874 cm
1 assigned to be ν1 modes of monomeric tetrahedral orthomolybdate ion [12] MoO2
is not shifted for all compositions due to invariance of 4 ModO bond length. The signature of more number of absorption bands in the glass nanocomposites of higher ZnO content (less MoO3) suggests that, as the ZnO content of the glass nanocomposites is increased, complex structural units containing inter linked octahedral MoO6 and MoO4 species are replaced by the monomeric MoO2
4 ions [12].

8.6.6 DC Conductivity The DC electrical conductivity (σ DC) has been computed from the Cole-Cole plots of resistivity as shown in Figure 8.8a. The plots are similar to each other in shape, with a semicircle

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8. ELECTRICAL TRANSPORT PROPERTIES OF ION-CONDUCTING GLASS NANOCOMPOSITES

80,000

–4.2 0.3Ag2O-0.0175 ZnO-0.6825 MoO3

Z //

60,000

T = 620 K T = 630 K T = 640 K T = 660 K

40,000

20,000

0.30Ag2 O-0.7 (xZnO-(1–x) MoO3)

log10 [s DC (Ω−1cm−1)]

198

–4.8

–5.4

–6.0

–6.6 0 0

(a)

50,000

100,000

Z/

150,000

1.4

(b)

x = 0.025 x = 0.050 x = 0.075 x = 0.100 x = 0.200

1.6

1.8

2.0

1000 / T (K–1)

FIGURE 8.8 (a) Cole-Cole plots of resistivity a particular glass nanocomposites at various temperatures and (b) reciprocal temperature dependence of the DC conductivity of 0.3Ag2O-0.7(xZnO-(1
x) 0.5MoO3) glass nanocomposites.

appearing in the high frequency domain and a straight portion in the low frequency region. The depressed semicircle in the moderate frequency region is attributed to the charge transfer process [92] and the diameters of the semicircles indicate the DC resistance of the samples under investigation. The low frequency region arises from the interaction of grain boundary with bulk materials. The DC resistance is found to decrease with the increase in temperature, indicating thermally activated behavior. Figure 8.8b shows the temperature dependence of the DC conductivity. The DC conductivity for all the samples is found to increase with the increase in temperature. It follows the Arrhenius type of variation σ DC T ¼ σ 0 expð
Eσ =kT Þ, where Eσ is the DC activation energy for glass nanocomposites under investigation, T is the absolute temperature, and k is the Boltzman constant. The solid lines in Figure 8.9 indicate the best fitted straight lines of the DC conductivity data. The Eσ has been computed from the slopes of the straight line fits. The DC conductivity at 600 K and corresponding activation energy of ZnO doped silver molybdate glass nanocomposites have been presented in Figure 8.9a and b, respectively. The activation energy for conduction follows opposite behavior (Figure 8.9b), that is, the system possesses lowest activation energy. The DC conductivity of these glass nanocomposites arises due to random motion of ion diffusion throughout the network. This process has been performed due to repeated hops between charge-compensating sites. The DC conductivity is found to increase up to x ¼ 0.1 and then decreases. It may be explained from the point of view of their structures. It is seen from the X-ray diffractograms that peak heights are found to decrease for x ¼ 0.2 compared to other compositions. This fall in peak heights may be associated with the agglomeration of ZnO, Ag2MoO4, Ag2Mo2O7, and Ag6Mo10O33 nanoparticles dispersed in glass nanocomposites. This agglomeration may enhance the grain boundary resistance, which in turn, resist the conduction pathways of Ag+ ion motion thereby decreasing the conductivity.

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199

8.6 PROPERTIES

FIGURE 8.9 (a) Variation of DC conductivity at T ¼ 600 K

–5.0

and (b) corresponding activation energy with ZnO content.

log10 [s DC (Ω−1 cm−1)]

–5.2 –5.4 –5.6 –5.8 –6.0

(a)

0.30 Ag2 O-0.7 (x ZnO-(1−x)MoO3)

0.6

Eσ (eV)

0.5

0.4

0.3

0.01

(b)

0.05

0.10

0.15

0.20

ZnO content

The temperature dependence of the DC conductivity of CuI doped molybdate glass nanocomposites [91] has also been studied. The DC conductivity for all the samples is found to increase with the increase in temperature. The Eσ of them has been computed from the slopes of the straight line fits. The DC conductivity at 303 K and corresponding activation energy of them has also been computed. The activation energy for conduction follows opposite behavior, that is, the system possesses lowest activation energy. AgI doped vanadate glass nanocomposites [93] are included for comparison. Here the conductivity level is found to increase slightly due to mixed mobile ions Ag+ and Cu2+ compared to the present work. The DC conductivity of these glass nanocomposites arises due to random motion of ion diffusion throughout the network [24]. This process has been performed due to repeated hops between charge-compensating sites.

8.6.7 AC Conductivity The AC conductivity of the present glass nanocomposites has been analyzed using both the conductivity formalism [33,40] and modulus formalism [75,76] because there is a debate on which of these two formalisms gives better description of the data analysis [40].

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8. ELECTRICAL TRANSPORT PROPERTIES OF ION-CONDUCTING GLASS NANOCOMPOSITES

8.6.7.1 Conductivity Formalism To study the AC conductivity data, in the framework of conductivity formalism [33,40], presented in Figures 8.15 and 8.16, a power law model [33] has been used. According to this model, the real part of the frequency-dependent conductivity can be described by σ = ðωÞ ¼ σ DC ½1 + ðω=ωc Þn 

(8.21)

which is the sum of the DC conductivity, σ DC and a fractional power law dependent dispersive conductivity with an exponent n. Here ωc is a characteristic crossover frequency from DC to dispersive conductivity [40]. Both the DC conductivity and the characteristic crossover frequency, above which σ /(ω)αωn, are thermally activated. The above model has been widely used to get an insight into ion dynamics in ion conducting glasses [34]. It may be noted that the value of the frequency exponent n is less than unity and does not depend significantly on composition. The conductivity spectra for 0.3Ag2O-0.7(xZnO-(1
x)0.5MoO3) glass nanocomposites have been studied and they have been presented in Figure 8.11 for a particular composition x ¼ 0.1. The experimental data for different temperatures were then fitted to Eq. (8.21) as illustrated in Figure 8.10. Three parameters, σ DC, ωc, and n were obtained for different temperatures. It was observed that the value of the DC conductivity obtained from the curve fitting agreed well with those obtained from the complex impedance plots. It has been observed that at low frequency, the conductivity becomes flat. This frequency-independent conductivity corresponds to the DC conductivity. The reason of this type of conductivity independent behavior in the low frequency regime may be due to the diffusion of Ag+ ions. At higher frequencies, the AC conductivity shows dispersion and follows a power law nature. This dispersion in the higher frequency region indicates a nonrandom motion of Ag+ ions and the motion is correlated and subdiffusive. It is clear from the literature [19] that this correlated

FIGURE 8.10 Conductivity spectra at various temperatures for x ¼ 0.1. Solid curves indicate the best fitted curves (power law model).

−4.6

log10 [s (Ω−1 cm−1)]

0.30Ag2 O-0.07ZnO-0.63MoO3) T = 593 K T = 603 K T = 613 K T = 623 K T = 633 K T = 653 K

−4.8

−5.0

–5.2 2

4 6 log10 [w (rad s−1)]

8

II. OXIDE GLASS NANOCOMPOSITES

8.6 PROPERTIES

201

motion arises due to interionic interaction which leads to systematic change in power law exponent with ion concentration. The conductivity spectra for xCuI-(1
x)(0.5CuO-0.5MoO3) glass nanocomposites [91] with x ¼ 0.3 have also been studied. It has been observed that at low frequency, the conductivity becomes flat. This frequency-independent conductivity corresponds to the DC conductivity. The reason of this type of conductivity independent behavior in the low frequency regime may be due to the diffusion of Cu2+ ions. This may be occurred owing to low frequency ion diffusion on longer timescales and longer length scales. At higher frequencies, the AC conductivity shows dispersion and follows a power law nature. This dispersion in the higher frequency region (above crossover frequency) indicates a nonrandom motion of Cu2+ ions and the motion is correlated and subdiffusive. The crossover frequency is found to increase as the temperature is increased, in agreement with a thermally activated behavior. The ion hopping behavior above the crossover frequency of the present glass nanocomposites may be ascribed due to localized hopping motion of Cu2+ ions, occurring on shorter timescales and shorter length scales. This correlated motion may indicate a preference on the part of ions that has hoped away to return its original position [91]. Different models have been proposed to shed some light in the mechanism responsible for electrical relaxation in crystalline and glassy materials [27,63,64]. According to Ngai [29,38,39], some form of inter ionic interaction (ion coupling) offers correlated and subdiffusive motion, leading to systematic change of observed power law exponent with ion concentration. The variation of ωH with temperature of 0.3Ag2O-0.7(xZnO-(1
x)0.5MoO3) glass nanocomposites is presented in Figure 8.11a, which also shows Arrhenius nature. Composition dependence of the hopping frequency and the corresponding activation energy of all the glass nanocomposites under investigation have been shown, respectively, in Figure 8.11b and c. Figure 8.12 shows that the value of the frequency exponent n is less than unity and does not depend significantly on composition up to x ¼ 0.1. Due to some differences in structure, n value is slight high. It is also noted that the activation energy for σ DC and ωH are almost same. It is clear from the literature [94] that the exponent n is independent of both ion concentration and temperature and it is also related to the dimensionality of the free ion conduction space. The calculated value of n ¼ 0.60 for the present system indicates three-dimensional [94] Ag+ ion motion in the glassy nanocomposites. It is also noted that the activation energy for σ DC and ωH are almost same. The concentration of mobile Ag+ ions has been estimated from the Nernst-Einstein relation given by σ DC ¼ q2 d2 Nc ωH =12πkT

(8.22)

where Nc is the mobile ion concentration, q is the charge, d is the average jump distance, and ωH is the hopping frequency of charge carriers. It is assumed that the hopping frequency in Eq. (8.22) is equal to the crossover frequency in Eq. (8.21). The validity of this assumption has been verified experimentally [34]. The average distance between Ag+ ions was estimated as the value of d. The concentration of mobile Cu2+ ions (Nc) with temperature for xCuI-(1
x)(0.5CuO0.5MoO3) glass nanocomposites [91] has been presented in Figure 8.13, which shows

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8. ELECTRICAL TRANSPORT PROPERTIES OF ION-CONDUCTING GLASS NANOCOMPOSITES

8

x = 0.025 x = 0.050 x = 0.075 x = 0.100 x = 0.200

Log10 [w H(rad s–1)]

6

4

2 0.30Ag2 O-0.7(x ZnO-(1−x)MoO3)

(a)

1.4

1.6

1.8 1000/T (K–1)

2.0

2.2

0.7 T = 600 K

7.0

6.5

EH(eV)

Log10 [w H(rad s–1)]

0.6

0.5

0.4

6.0 0.3 5.5

(b)

0.2 0.05

0.10 0.15 ZnO content

0.20

0.05

(c)

0.10 0.15 ZnO content

0.20

FIGURE 8.11 (a) Variation of hopping frequency with reciprocal temperature (solid lines indicate the best fitted lines). (b) Variation of hopping frequency with ZnO content. (c) Variation of activation energy corresponding to hopping frequency with ZnO content.

temperature-independent behavior. Here, the average distance between Cu2+ ions (d) is assumed to be 3  10
8 cm [91]. Total concentration (N) of Cu2+ ions has been estimated from the glass composition and density. It is also noted that the values of Nc is only 15-20% of the total Cu2+ ion concentration, contributing to the electrical conduction processes. Previously, it was observed that activation energies corresponding to DC conductivity and hopping frequency, respectively, were almost the same. This implies that the mobile ion

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203

8.6 PROPERTIES

FIGURE 8.12 Variation of frequency exponent with ZnO content of 0.3Ag2O-0.7(xZnO-(1
x) 0.5MoO3) glass nanocomposites.

1.0

0.8

n

0.6

0.4

0.2

0.0 0.05

0.10

0.15

0.20

ZnO content

FIGURE 8.13 Variation of mobile ion concentration with reciprocal temperatures.

x Cul-(1−x)(0.5CuO-0.5MoO3)

log10 [Nc (cm–3)]

15

x = 0.1 x = 0.2 x = 0.3 x = 0.4

10

5

3

4

5

6

1000 / T (K–1)

concentration is independent of temperature and the conductivity is mainly depends upon mobility of charge carriers [34]. Also we know that σ ¼ Ncqμ, where μ is the mobility of the charge carrier. This statement suggests that mobility is the main important parameter for ion conduction process in the glass matrix, since conductivity increases with temperature. The scaling of the conductivity spectra at different temperatures and compositions for all the glasses and glass nanocomposites has been considered. The scaling of the conductivity spectra has been performed using the procedure outlined elsewhere [95]. The results at different temperatures for xCuI-(1
x)(0.5CuO-0.5MoO3) glass nanocomposites [91] are shown in Figure 8.14a. The near perfect overlap of the spectra at different temperatures indicates that

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8. ELECTRICAL TRANSPORT PROPERTIES OF ION-CONDUCTING GLASS NANOCOMPOSITES

2.0

1.5

log10 (s / sDC)

FIGURE 8.14 (a) Temperature scaling of conduc-

x CuI-(1−x)(0.5 CuO-0.5MoO3) x=0.1

tivity spectra for x ¼ 0.1, various temperatures are shown. (b) Composition scaling of conductivity spectra of xCuI-(1
x)(0.5CuO-0.5MoO3) glass nanocomposites at T ¼ 240 K. Reproduced from Ref. [92] with permission, Copyright # Elsevier.

T = 180 K T = 200 K T = 220 K T = 240 K T = 260 K T = 280 K T = 300 K

1.0

0.5

0.0

–0.5 –2

–1

(a)

0 log10 (w /w H)

1

2

2

log10 (s /sDC)

x CuI-(1−x)(0.5 CuO-0.5MoO3) T = 240 K

1

x = 0.1 x = 0.2 x = 0.3 x = 0.4

0

–3

(b)

–2

–1

0

1

2

log10(w /w H)

the glass nanocomposites obey the time-temperature superposition principle. The scaling results for different compositions of xCuI-(1
x)(0.5CuO-0.5MoO3) glass nanocomposites at a particular temperature are shown in Figure 8.14b. In Figure 8.14a, it has been noted that all the conductivity spectra for all compositions are also properly scaled. Similar results were also obtained for other investigated temperatures and also for other compositions. The perfect overlap of the spectra at different temperatures follows the time-temperature superposition principle. In the composition scaling at a particular temperature as presented in Figure 8.15b, it has been noted that all the conductivity spectra for all compositions are not properly scaled. It directly indicates that the relaxation process of Cu2+ ions is independent of temperature, but dependent on CuI content.

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205

8.6 PROPERTIES

0.05

0.04

161 K 180 K 200 K 220 K 240 K 260 K 280 K 300 K 320 K 340 K 360 K

0.2Cul-0.4CuO-0.4MoO3

M⬘

0.03

0.02

0.01

0.00

2

(a)

3

4

5

log10 w (rad

M⬙

0.01

0.020

0.2Cul-0.4CuO-0.4MoO3

0.015

x Cul-(1-x)(0.5CuO-0.5MoO3) T = 180 K x= 0.10 x= 0.20 x= 0.30 x= 0.40

0.010

M⬙

161 K 180 K 200 K 220 K 240 K 260 K 280 K 300 K 320 K 340 K

6

s–1)

0.005

0.000 0.00 2

(b)

4 5 3 log10 w (rad s–1)

2

6

(c)

3 4 5 log10 w (rad s–1)

6

FIGURE 8.15 (a) Real (M/) parts of the modulus spectra for a particular composition x ¼ 0.2 at various temper-

atures. (b) Imaginary (M//) parts of the modulus spectra for a particular composition x ¼ 0.2 at various temperatures. (c) Imaginary (M//) parts of the modulus spectra for different compositions at a particular temperature T ¼ 180 K. Reproduced from Ref. [91] with permission, Copyright # Elsevier.

8.6.7.2 Modulus Formalism The modulus formalism [75,76] has also been adopted for the analysis of the electrical impedance data. An electric modulus M* at a particular frequency ω and temperature is defined in terms of reciprocal of complex dielectric permittivity ε* as

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8. ELECTRICAL TRANSPORT PROPERTIES OF ION-CONDUCTING GLASS NANOCOMPOSITES

M ðωÞ ¼ 1=ε ðωÞ

(8.23)

The real and imaginary modulus spectra have been presented at different temperatures for all the glass nanocomposites xCuI-(1
x)(0.5CuO-0.5MoO3) in Figure 8.15a and b, respec00 , which corresponds tively [75,76]. The imaginary modulus M00 exhibits a maximum Mmax 00 to the conductivity relaxation frequency ωm. It is further noted that the position of Mmax shifts / to higher frequencies as the temperature is increased. The real modulus M increases with the increase in frequency and shows saturation at high frequencies. The imaginary parts of modulus spectra M00 , for all the glass nanocomposites under investigation at a fixed temperature 180 K have been illustrated in Figure 8.15c. It is noted in Figure 8.15c that conductivity relaxation frequency ωc decreases with the increase of CuI content up to x ¼ 0.3 and its value is slightly increased for x ¼ 0.4, which indicates that ionic relaxation starts at higher frequencies for x ¼ 0.4. The above mentioned fact may be, in turn, depends upon its structure. Size of the CuMoO4 nanoparticles plays an important role for offering greater resistive paths for conduction of Cu2+ ions for x ¼ 0.4. The electric modulus can be expressed as the Fourier transform of a relaxation function ϕ(t) [75,76]:   ð1 dt expð
iωtÞð
dφ=dtÞ (8.24) M ðωÞ ¼ M1 1
0

where M1 is the reciprocal of high frequency dielectric constant εα and the function ϕ(t) gives the time evolution of the electric field within the materials and is usually taken as KohlrauschWilliams-Watts function, given by [75,76] h i 8.25 ϕðtÞ ¼ exp
ðt=τm Þβ , 0 < β  1 where β is the stretched exponent, whose value tends to unity for Debye type relaxation and τm is the conductivity relaxation time. The stretched exponent β and the conductivity relaxation time τm were obtained from the fits of the experimental modulus data to Eqs. (8.24) and (8.25). The variation of relaxation time (τm) with temperature for all glass nanocomposites has been presented in Figure 8.16a. τm exhibits an activated behavior obeying the following Arrhenius relation τm ¼ τ0 expðEτ =kT Þ

(8.26)

where Eτ is the activation energy for the conductivity relaxation. In Figure 8.16b, the dependence of the conductivity relaxation time τc on the CuI content has been shown at room temperature. It is observed that τc is found to increase with CuI content and shows a maximum value for x ¼ 0.2. After that τc decreases gradually, indicating enhancement of ionic conductivity level. It is also noted from Figure 8.16b that the nature of variation of Eτ is same as that of τm. The stretched exponent (β), discussed in Eq. (8.25), has been computed from the relation β ¼ 1.14/w [76], where w being the full-width at half-maximum (FWHM) and it is 1.14/w for Debye relaxation. It has been observed that β is independent of temperature. But it depends upon compositions. It is noted in Figure 8.16c that the stretched exponent β decreases with

II. OXIDE GLASS NANOCOMPOSITES

207

8.6 PROPERTIES

–3

x CuI-(1−x )(0.5CuO-0.5MoO3)

x = 0.10 x = 0.20 x = 0.30 x = 0.40

log10 [t c (S–1)]

–4

–5

–6

–7

–8 3

5 4 1000 / T (K–1)

(a) –6.6

x = 0.10 x = 0.20 x = 0.30 x = 0.40

x CuI-(1−x )(0.5CuO-0.5MoO3)

0.8 0.7

0.3

–7.4

0.2

b

–7.2

0.1

0.4 0.0 0.0 0.1 0.2 0.3 0.4 X

–7.8 0.0

0.6 0.5

–7.6

(b)

7

–7.0

Et (eV)

log10 [t c (S–1)]

–6.8

T = 303K

6

0.1

0.2

0.3 X

0.4

0.3 0.5

0.1

(c)

0.2

0.3

0.4

X

FIGURE 8.16 (a) Arrhenious nature of conductivity relaxation time (τc) with reciprocal temperature. (b) Compositional dependence of conductivity relaxation time (τc) at a fixed temperature. Compositional dependence of corresponding activation energy is shown in the inset. (c) Compositional dependency of stretched exponent parameter (β).

CuI content up to x ¼ 0.3 and then increases for x ¼ 0.4. The lowering of β values with CuI content can be strongly related with their structure. The values of β indicate that the conductivity relaxation process is highly nonexponential. It is found that phosphate glassy system possesses fixed of β value ( 0.50) [67]. This might arise from structural differences between the phosphate glassy system and the present glass nanocomposites. The decoupling index Rτ (Tg) [96] is also calculated. It is defined as the ratio of the structural relaxation time, τs (Tg), to the average conductivity relaxation time, τm (Tg) at the glass

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transition temperature Tg. This quantity, Rτ (Tg) determines the extent to which the motion of the ions is decoupled from the viscous motion of the glassy network. For the structural relaxation time it is assumed that τs (Tg) ¼ 200 s [96]. It is also noteworthy that the decoupling index increases with increase of Ag2O content in the compositions so that the motion of Ag+ ions is more decoupled from the viscous motion of the glass nanocomposites.

8.7 APPLICATIONS Device exploitation of these systems requires a thorough knowledge of the physical mechanisms involved for the peculiar electrical and structural characteristics of these materials and an extensive database in order to optimize the device performance. Very few works on the electrical and structural properties of the AgI doped glasses and glass nanocomposites have been reported from our country. In the international context, the study of the frequencydependent conductivity and relaxation behavior in the AgI doped system is also very limited. In these glassy electrolytes, Ag+ ions contribute to the conduction process and offer many interesting features. Besides these ionic systems, polaron-hopping in semiconducting glass nanocomposites containing transition metal ions are also very interesting not only for academic interest, but also for the application in optical switching, display devices, etc. As such, a thorough investigation of the electrical transport in both ion-conducting and semiconducting glasses and glass nanocomposites will be significant for the better understanding of the conduction and relaxation processes in these technical materials.

8.8 CONCLUSIONS XRD study of 0.3Ag2O-0.7(xZnO-(1
x)0.5MoO3) glass nanocomposites reveals the formation of ZnO, Ag2MoO4, Ag2Mo2O7, and Ag6Mo10O33 nanoparticles dispersed in 0.3Ag2O-0.7(xZnO-(1
x)0.5MoO3) glass nanocomposites. We have shown that the doping of ZnO to silver molybdate glass nanocomposites causes changes to the structure and conductivity relaxation of the host glassy system. The FTIR studies of the samples suggest a symmetric stretching of the ModO octahedral units. The peak shift in the FTIR spectra implies that the bond strength of ModO in compositions becomes weaker with increases in the ZnO content. Conductivity relaxation time, τc is found to decrease with ZnO content and shows a minimum for x ¼ 0.1. After that τc decreases gradually, indicating enhancement of ionic conductivity level. The motion of Ag+ ions is decoupled more and more from the viscous motion of the glassy matrix with the increase of ZnO content in the glass compositions. The ionic conductivity of CuI doped copper molybdate glass nanocomposites has been studied compared with others works and presented. The copper molybdate (CuMoO4) nanoparticles have been identified from XRD and HRTEM studies. AC conductivity data have been analyzed in a wide frequency and temperature range on the frame work of power law model. The DC conductivity and the hopping frequency show thermally activated behavior. The power law exponent is found to be almost independent of CuI doping content. The mobile Cu2+ ion concentration is independent of temperature, but slightly depends upon compositions. The scaling behavior of the conductivity spectra is well-described. This indicates the

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temperature-independent relaxation process of Cu2+ ions. Conductivity relaxation time, τc is found to increase with CuI content and shows a maximum for x ¼ 0.2. After that τc decreases gradually, indicating enhancement of ionic conductivity level. The values of β indicate that the conductivity relaxation in these glass nanocomposites is highly nonexponential. The lowering of β values with CuI content can be strongly related with their structure. From the temperature and composition scaling it may be concluded that the relaxation dynamics of Cu2+ ions is independent of temperature but it depends on the doping level of CuI content. The conductivity and the conductivity relaxation of xAg2O-(1
x)MoO3 glasses and their heat-treated counterparts with varying Ag2O content have been studied in wide frequency and temperature ranges. The DC conductivity and the activation energy of these glasses and their heat-treated samples were compared and it has been observed that the conductivity of the heat-treated samples decreases in comparison with their glassy counterparts due to formation of different nanophases in the glass matrices. The concentration of mobile Ag+ ions is not thermally activated and only 10-25% of the total Ag+ ions contribute to the dynamic processes. The conductivity relaxation process is highly nonexponential. The motion of Ag+ ions is decoupled more and more from the viscous motion of the glassy matrix with the increase of Ag2O content in the glass compositions and for the heat-treated glass nanocomposites, the motion of Ag+ ions is less decoupled from the viscous motion for them compared to their glassy counterparts. In brief, this chapter provides the understanding of general features of ionic conduction and structural models of conduction in glass nanocomposites. It also makes possible, in designing semiconducting and fast ion conducting glass nanocomposites, preparation of nanoparticles, nanorods, and nanowires by exploiting the silver molybdate glass matrix through annealing technique. Finally, it draws the correlation between structure and transport properties of glass nanocomposites.

8.9 FUTURE OUTLOOK Multifunctional zinc oxide (ZnO) is one of the most important materials used for industrial applications. As an n-type semiconductor with a wide band gap of 3.37 eV [97–99], it is widely used in many fields, including electrical and optical devices [100,101], electro-luminescent devices [102,103], gas sensors [104], transparent conducting films [100,105], etc. Hence, synthesis of semiconducting ZnO nanoparticle system can be done by the chemical route with respect to enhancement of their band gaps. In this regard, the PL can also be carried out. The electrical conductivity and the conductivity relaxation in ZnO as well as ZnO doped semiconducting systems can also be studied in a wide temperature and frequency range. Similarly other nanocomposite systems can also be explored with respect to both academic and industrial interest.

EXERCISES 1. What factor does influence the fast ion conduction in oxide glass nanocomposites? 2. Do the present models of DC conductivity and AC relaxation mechanism agree with the experimental data?

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3. How is the mobile ion concentration is related to the conductivity and how does it vary with temperature and composition? 4. How do the frequency exponents (in the low and high frequency regime) vary with temperature and composition? 5. Does the variation of the microscopic parameters with composition obtained from conductivity and modulus formalism tally? 6. Does the relation between the nonexponential parameter β and the frequency exponent parameter n follow the relation proposed by Ngai? 7. Do the relaxation dynamics in these systems depend on temperature or composition? 8. What factor does influence the formation of different nanophases in the oxide glass nanocomposites? 9. Does the as-prepared glass nanocomposites may behave like nanotemplates? 10. How does the complicated structure of glass nanocomposites conduct Ag2+ or Cu2+ ions? 11. How does the dimensionality of ion transport in these glass nanocomposites depend upon the structure? 12. How does a different nanophase grow in the glass matrices? 13. What factor does influence the motion of Ag2+ or Cu2+ ions? 14. Why the DC conductivity levels differ for Ag2+ or Cu2+ ions? 15. Does the ionic radius of Ag2+ or Cu2+ ions play any role for ion motion in glass nanocomposites under study? 16. Does the mobile ion concentration influence on the conductivity? 17. Does the mobility influence on the conductivity? 18. Is there any effect of controlled annealing of the as-prepared glass nanocomposites on conductivity and ionic relaxation process? 19. “Formation of nanoparticles, nanorods, and nanotubes in the glass matrices may restrict the three dimensional ion motion.” Explain. 20. Which one is more reliable to calculate crystallite sizes, “XRD” and “HRTEM”? 21. What is the role of ZnO in zinc molybdate glass nanocomposites?

Acknowledgments The Council of Scientific and Industrial Research (CSIR), India (Sanction No. 03 (1286)/13/EMR-II) is thankfully acknowledged for partial financial assistance.

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II. OXIDE GLASS NANOCOMPOSITES