Lithium ion conductivity in Li2O–P2O5–ZnO glass-ceramics

Lithium ion conductivity in Li2O–P2O5–ZnO glass-ceramics

Accepted Manuscript Lithium ion conductivity in Li2O–P2O5–ZnO glass-ceramics Sanjib Bhattacharya, Amartya Acharya, Anindya Sundar Das, Koyel Bhattacha...

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Accepted Manuscript Lithium ion conductivity in Li2O–P2O5–ZnO glass-ceramics Sanjib Bhattacharya, Amartya Acharya, Anindya Sundar Das, Koyel Bhattacharya, Chandan Kumar Ghosh PII:

S0925-8388(19)30237-3

DOI:

https://doi.org/10.1016/j.jallcom.2019.01.284

Reference:

JALCOM 49322

To appear in:

Journal of Alloys and Compounds

Received Date: 2 October 2018 Revised Date:

16 January 2019

Accepted Date: 19 January 2019

Please cite this article as: S. Bhattacharya, A. Acharya, A.S. Das, K. Bhattacharya, C.K. Ghosh, Lithium ion conductivity in Li2O–P2O5–ZnO glass-ceramics, Journal of Alloys and Compounds (2019), doi: https://doi.org/10.1016/j.jallcom.2019.01.284. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT Lithium ion conductivity in Li2O–P2O5–ZnO glass-ceramics

Sanjib Bhattacharya1, *, Amartya Acharya1, Anindya Sundar Das2, Koyel Bhattacharya3 and

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Composite Materials Research Laboratory,

Department of Engineering Science and Humanities,

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Chandan Kumar Ghosh4

Siliguri Institute of Technology, Darjeeeling-734009, West Bengal, India

Department of Electronics and Communication Engineering

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2

Swami Vivekananda Institute of Science & Technology, Dakshin Gobindapur, Kolkata-

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700145, India 3

Department of Physics, Kalipada Ghosh Tarai Mahavidyalaya, PO: Bagdogra, District: Darjeeling, Pin-734014, West Bengal, India 4

Department of Electronics and Communication Engineering

Dr. B..C. Roy Engineering College, Durgapur-713026, West Bengal, India. ABSTRACT

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A series of new glass-ceramic samples containing Li2O has been prepared to explore their electrical transport properties. XRD patterns of them reveal the formation of different types of nanocrystallites, dispersed in amorphous glassy matrices. Study of dc conductivity (σdc) of

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them shows their thermally activated nature. Formation of more non-bridging oxygen in the compositions may enhance their ionic conductivity. Conductivity spectra at various temperatures have been studied and interpreted using Jonscher's universal power-law and

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Almond-West formalism to shed some light on transport mechanism. The frequency independent conductivity (plateau region) in low-frequency zone is caused by diffusion of Li+ ions. Moreover, in the high-frequency dispersive region, the conductivity is because of correlated and pseudo-three-dimensional motion of Li+ ions in percolating networks. In consequence, the power-law exponent values become greater than 1 and exhibit super-linear and/or NCL (nearly constant loss) nature. Correlated barrier hopping (CBH) model is modified to some extent, which yields a better fit to experimental results. Here, ion hopping and characteristic relaxation times have been correlated with electrical conductivity with good precision. The master curve in conductivity scaling analysis reveals that conductivity

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ACCEPTED MANUSCRIPT relaxation process in the present system are independent of temperature as well as composition.

Keywords: Glass-ceramics; Composite materials; X-ray diffraction; Ionic conductivity; Li+

*Corresponding author’s email: [email protected]

Introduction

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1.

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ion migration.

In recent days, lithium is supposed to be a key component of rechargeable batteries,

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which may be used in electric vehicles, smart phones and mobile computers, with the promise of renewable energy storage [1, 2]. Recent review work [3] reveals that traditional lithiumion batteries are not good enough because of some safety issues, arising due to incorporate here highly flammable organic liquid electrolytes or polymer electrolytes. To thoroughly

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address the safety issues, organic liquid electrolytes have been replaced by inorganic solid electrolytes that have high thermal stability, high energy density and better electrochemical stability [4]. Lithium is indispensable to every glass-ceramic, because of its responsibility for

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the products’ zero expansion, ensuring their use in high temperature ranges without voltage breakage [5]. Veeraiah etal [6] extensively studied the influence of silver ion concentration

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on dielectric properties of Li2O doped glassy system and predicted that higher values of dielectric constant were due to larger contribution from space charge polarization. A group of researchers [7] have tried to improve the electrochemical performance of lithium-rich oxide layer material with Mg and La co-doping. Recent work on electrical transport of Li doped composites [8] exhibited the existence of highly-resistive lithium-depleted layer due to the very low mobile-ion concentration.

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ACCEPTED MANUSCRIPT The glassy solid electrolytes have other advantages over their polycrystalline counterparts owing to more free volume open structure [9] and flexibility of size and shape at a satisfactory limit [10]. Now-a-days, glassy system is the most promising candidate for inorganic solid electrolytes, which can be prepared over a wide range of compositions,

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allowing for better control of properties [11], which have an irregular network that makes for variable-sized channels. Recent work on PEO-based inorganic-polymer composite membrane points to the direction for achieving a promising electrolyte for new lithium batteries with

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high energy density and power density [12]. Solid-state sodium-ion batteries with the hexagonal P2 structure have been well demonstrated [13]. Path breaking research work on

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hybrid Li ion-conducting solid electrolyte explores next generation solid-state lithium battery with high stability [14]. A novel free-standing cathode material has already been fabricated for the high-temperature all-solid-state lithium-vanadium battery [15]. Investigation of electrical transport properties of new glass-ceramic lithium ion

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conductor is expected to reveal their structural information, which is essential for the knowledge of conduction mechanism. In the present communication, electrical conductivity behavior of Li2O doped glassy electrolyte is discussed. The results are expected to be

Experimental procedure

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2.

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interesting not only for technological applications but also for academic interest.

A series of glass ceramics, xLi2O–(1-x) (0.5ZnO–0.5P2O5) with x = 0.1, 0.2, 0.3, 0.4 and 0.5 was prepared using familiar melt quenching technique with high purity (≥ 99%) precursors Li2O, ZnO and P2O5. These chemicals were weighed properly and the mixture was taken in alumina crucible. It was melted in a high-temperature electric muffle furnace in the temperature range 800 K to 850 K depending on the concentration of Li2O (x). The melts were equilibrated by stirring to ensure homogeneous mixing. The homogeneous melts were then instantly quenched at room temperature (300K) by pouring it in between two aluminium 3

ACCEPTED MANUSCRIPT plates. As a consequence, glassy ceramics of thickness ~ 1mm were formed. The glassceramic flakes were gently crushed to get fine powder. X-ray diffraction (XRD) patterns were recorded using a Seifert (model 3000P) X-ray diffractometer. The size and distribution of different nanocrystallites, grown in the glassy matrices have been confirmed from the XRD-

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peaks. The differential scanning calorimetry (DSC) scans have been done using NETZSCH DSC 214. The conducting silver paste was placed on both sides of the glass-ceramic flakes, which acts as electrodes. The values of conductance (G), capacitance (C) and dielectric loss

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tangent (tanδ) of all glass-ceramic samples were measured using a high precision programmable automatic LCR meter (HIOKI, model no. 3532-50) at various temperatures

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and in the frequency range 42Hz–5MHz.

The dc conductivity of the samples was determined from the complex impedance plots. For a particular temperature, the real and imaginary parts of the complex impedance, Z∗(ω) = Z/ + iZ// at frequency ω were determined from the following relations:

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Z' = G(ω)/(G2(ω)+ω2(C(ω)-C0)2)

Z'' = ω(C(ω)-C0)/(G(ω)2+ω2(C(ω)-C0)2)

(1) (2)

where, C is the capacitance, G is the conductance of the samples, C0 is the capacitance of the

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sample cell without sample. From the complex impedance plots, the dc resistance R was

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calculated at different temperatures and then dc conductivity was calculated using the relation σdc = (t/A)×(1/R)

(3)

where, t and A are the thickness and area of the samples respectively. The frequency dependent ac conductivity σ/(ω) at frequency ω was determined from the following relation

σ/(ω) = (t/A)G(ω)

(4)

To check electrochemical stability of the resultant composite, cyclic voltammetry study has been conducted in the 0-2 volt window (Model: CHI700E). Here, a three electrode setup was used with a glassy carbon as working electrode, a platinum wire as a counter electrode and a 4

ACCEPTED MANUSCRIPT Ferrocenium/Ferrocene (Fc+/Fc) as pseudo-reference electrode. While the current flowed between the working and counter electrodes, the reference electrode was used to accurately measure the applied potential relative to a stable reference reaction. In case of present experiment, the used solvent was Aceto-Nitryl, which had an electrochemical stability of 0-2

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volt window.

Results and discussion

3.1

Study of X-ray diffraction and differential scanning calorimetry (DSC)

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3.

X-ray diffraction patterns of all the glass-ceramic samples have been presented in Fig. 1.

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The presence of many sharp peaks, signifying long-range order or crystallinity, has been disclosed from Fig. 1. Thus, it can be asserted that the present glass-ceramic compositions are of mixed-phased or polycrystalline in nature. With the help of available literature data, the dispersed nanophases within the amorphous matrices have been recognized from different

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Bragg’s angle (2θ) peaks. A few unidentified peaks, probably owing to impurities or mixed phases, have also been observed with lower intensity. The sizes of nanocrystallites have been estimated using Debye-Scherer relation [16, 17] .



(5)

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d =

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Here, β is the full width at half maximum (FWHM), θ is the Bragg's diffraction angle and λ is the wavelength (1.54 Å) of the CuKα X-ray radiation. The values of strain (ε) of each nanocrystallite have been computed using the broadening of diffraction line as defined by Williamson and Hall [18, 19]. The imperfection and distortion of crystallites should induce the broadening of the diffraction line and lattice strain, which may be evaluated by the relation:

ε =  

(6)

5

ACCEPTED MANUSCRIPT where, ε is the micro-strain and β is the peak breadth or FWHM due to strain, which have been developed owing to the formation of nanocrystallites in the present glass matrices. The inter-planar spacing (D) concerning the lattice planes has been estimated using the familiar Bragg's law 2Dsinθ = nλ. The evaluated values of the nanocrystallite sizes (dc) and inter-

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planar distances (D) are presented in Table 1. Table 1 also presents the different nanocrystallites, dispersed in the glass-ceramic matrices. These nanocrystallites have been identified as LiZn(PO4) [20], LiPO3 [21], Li3(PO4) [22], Zn2P2O7[23], ZnP4O11 [24], Li2O

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[25], ZnO [26] and P2O5 [27], which are also included Table 1. The variation of the mean crystallite sizes (dC) and the lattice-strain (ε) with reference to the concentration of Li2O (x)

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have been depicted in Fig. 2, which made a correlation between lattice strain and mean size of the nanocrystallites. It represents that as the lattice strain of the glass-ceramics increases, mean size of the nanocrystallites is found to decrease. The dissimilarity of the lattice-strain (ε) values may be caused due to the modification of glass-ceramic structure and development

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of new nanocrystallites.

Estimated values of glass-transition temperatures (Tg) and crystallization temperatures

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(Tc) are presented in Table 2. The notable feature of the DSC scans is the change in heat flow at the glass transition, which is proportional to the change in the heat capacity at Tg. It is also

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noted that this change in heat capacity as well as Tg are found to decrease with addition of more lithium content to the composites. Furthermore, transition is spread over a far larger temperature range, which indicates its greater stability for various applications in a wide range of temperature. 3.2

Study of ionic conductivity Analysis of frequency dependent ionic conductivity at several temperatures of the solid

electrolytes under investigation reveals some important facts: ion hopping frequency, temperature dependency of conductivity, dc conductivity and also thermally activated nature 6

ACCEPTED MANUSCRIPT of mobile ions [28-31]. Fig.3 (a) exhibits frequency dependent conductivity plot for x = 0.1. Ac conductivity (σac) spectra at a particular temperature for all the glass-ceramics are illustrated in Fig. 3(b). The prime observations in Figs. 3(a) and (b) above room temperature are as follow: (i) the high frequency dispersive region (ac conductivity) on account of the

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increment of the probability of short-range ionic motion, and (ii) the low frequency plateau or flat region, which corresponds to dc conductivity and is caused by diffusion of Li+ ions [32, 33]. Here, the nature of conductivity spectra indicates that the effect of non-neutral defects

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and enormous interrelating vacancies cannot be ignored [34]. The characteristics of conductivity at high-frequency dispersion and low-frequency flat regions can be analyzed



σ ω = σ  1 + 





!

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using Almond-West formalism relation [33, 34]

(7)

Here, σdc is the frequency-independent conductivity (dc conductivity), ωim is ion migration

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frequency separating plateau region from the dispersive conduction regime (hopping/ crossover frequency), which indicates the beginning of the conductivity relaxation process, and n is the frequency exponent. The frequency and temperature dependent conductivity (σ

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(ω)) data, shown in Fig. 3(b) have been best fitted with Eq. (7), which explores three parameters: σdc, ωim and n. The conductivity spectra for other samples have also been

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analysed using Eq. (7) and similar parameters are obtained. The average value of the frequency exponent (n) of all glass-ceramic samples are found in the range 1.11 to 1.33. It is noted from Jonscher’s report [35] that the high-frequency conductivity dispersion corresponds to the non-zero values of n, which is the result of the energy stored in the collective movement of ions in short-range order. The higher value of n corresponds to the greater energy, stored in such collective movements of ions [35]. It may be concluded from the above-mentioned facts that conduction of Li+ ions takes place via diffusion of individual Li+ ions from one crystal lattice site to another through interrelated diffusion channels in the 7

ACCEPTED MANUSCRIPT crystal structural framework [36]. In this process, the transportation of mobile Li+ ions may occur through the different nanocrystallite-energy territory where, the highest energy of the energy territory along the diffusion path regulates the ionic diffusion energy barrier [37]. It is interestingly noted that at ion migration frequency (crossover/ hopping frequency), the

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conductivity spectra show dispersion [9, 32], which are shifted towards higher frequencies with rise in the temperature. Here, the possible reasons of the above-mentioned facts may be due to enhancement of kinetic energy and vibrational frequency of Li+ ions [9, 32].

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Moreover, it is observed from the analysis of Fig.3 that both dc conductivity and onset ion migration frequency are thermally activated with different values of activation energy.

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Fig. 4(a) illustrates linear relationship of dc conductivity (σdc) with reciprocal temperature, which shows thermally activated nature. It is also noted in Fig. 4(a) that σdc is found to increase with increase in Li2O content. To analyze Fig. 4(a), Arrhenius relation [38-40] has been employed to describe the process of thermally activated ion-transport conductivity as: '

σ T = σ exp − * () ,

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+

(8)

where, σ0 is the pre-exponential factor, Edc is the activation energy corresponding to dc

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conductivity, which is the energy necessary to overcome the electrostatic force and the potential wells during the jump or hop, KB is the Boltzmann constant and T is the absolute

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temperature. The values Edc, estimated from the least square straight-line fits using Eq. 8 (shown by solid lines in Fig. 4(a)) are presented in the inset of Fig. 4(a). Room temperature dc conductivity of all glass-ceramics has been extrapolated from Fig. 4(a) and presented in Table 3. It is asserted from Fig.4 (a) and Table 3 that as the Li2O content in the composition increases, σdc increases and Edc decreases. Variation of ion hopping frequency (ωim) with reciprocal temperature of all the samples is presented in Fig. 4(b). To analyze the reciprocal temperature dependence of ωim as shown in Fig. 4(b), thermally activated ion migration frequency (ωim) is considered as [41]: 8

ACCEPTED MANUSCRIPT ω-. = ω/ exp 

'0

(11)

*+ ,

Here, ωe is the pre-exponential factor of migration frequency, and EM is the amount of free energy required for mobile ion migration. The free energy of ion migration (EM) values have

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been computed from the slope of the plots as observed by solid lines in Fig. 4(b) and the EM values are presented in the inset of Fig. 4(b) as well. It is worth noting in Fig. 4(b) that EM value drops down as the conductivity of the present glass-ceramics are found to increase. Thus, it is emphasized that the variation of conductivity arises due to the temperature

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dependency of the hopping rate of mobile Li+ ions [41, 42]. It is explored from Figs. 4(a) and

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(b) that the values of Edc are higher than those of EM, which indicates that conduction of charge carriers in the present system is partially controlled by ion-hopping process [42]. Fig. 5(a) presents the variation σdc with Edc, which shows non-linear relationship, which asserts that the conductivity improvement should be, related to the increasing mobility of the charge carriers [39]. It is interestingly noted from Fig. 5(b) that σdc increases with the

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increase in Li2O content as Edc decreases. This result indicates that higher conductive samples with higher Li2O content require less energy necessary to overcome the electrostatic force and the potential wells during the jump or hop of lithium ion. To shed some light on transport

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mechanism of Li+ ion conductor, in-depth conduction process in Li2O-doped glass-ceramics

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has to be incorporated, which is the consequence of the sequential three-dimensional diffusion of Li+ ions from one non-bridging oxygen to the next [39]. It requires the description of some essential parameters [39, 40] like non-bridging oxygen number, Li+ ion concentration and the spacing between two Li+ ions, which must affect the conductivity process effectively. The Li-ion concentration in the glass-ceramic structure can be computed using the following expression [40]: 4 5/ 6/7/ 8  .6 --  9 : 9 <

; N2-3-  = =>/7?/ . 5/@57 A/-?B 8  .6 -- 

9

(9)

ACCEPTED MANUSCRIPT Here, NA is the Avogadro number and ρ is the density of the present sample. To estimate the spacing between Li+ ions, the following relation [40] has been employed R 2-3-  = :

D

D/K

(10)

EFGHI

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The estimated values of N2-3-  and R 2-3-  with Li2O content are presented in double column plot of Fig. 5(b). It is observed in Fig. 5(b) that Li-ion concentration increases with the rise in Li2O content in the composition. In the ion hopping process [39, 40], the spacing between Li+ ions must affects the activation energy for conduction and thus dc electrical

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conductivity, which indicates a strong dependency between the spacing of Li+ ions and the

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activation energy for conduction [40]. It is clearly noted in Fig. 5(b) that Li+ ion spacing reduces with a rise in Li2O content in the composition, which causes dc conductivity to increase. However, it has been found [41] that as the content of Li2O increases in the composition, the Li+ ion solubility acting as a charge compensator is exceeded. As a consequence [41], some of the comparatively stronger P–O and Zn–O bonds in the glass

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network may be replaced by weak ionic Li+–O– bonds, which manifests the reducing nature of Edc and the increasing nature of σdc.

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Fig. 6(a) depicts the plot of reciprocal temperature dependence of total ac conductivity (σtotal) at various frequencies of glass-ceramic with x = 0.2, where dc

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conductivity values are included for comparison. The values of corresponding activation energy (Eac) are also presented in the inset of Fig. 6(a). It is observed in Fig. 6(a) that the value of Eac reduces as the frequency increases. The reduction of Eac may force Li+ ions to migrate from one favourable lattice site to another [41]. As a result of Coulomb interaction, the ion hopping time is not infinitely short [34]. Fig. 6(b) represents the ac conductivity (σac) with reciprocal temperature of all the as-prepared glass-ceramics at a fixed frequency 3 MHz. Activation energy corresponding to ac conductivity (Eac) has been computed from the best fitted straight line fits as shown in Fig. 6(b). It is observed from Fig. 6(b) that Eac decreases as 10

ACCEPTED MANUSCRIPT the content of Li2O increases, which shows the opposite nature of ac conductivity. As the size of different nanocrystallites are found to decrease with Li2O (Fig. 2), diffusion mechanism is expected to be greatly influenced by the structural rearrangement of the present system, which may result the increment of ac conductivity. It is also predicted that as Li2O content

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increases in the composition, the structure of present glass-ceramics becomes more open due to the formation of more non-bridging oxygen ions, which may be suitable for migration of Li+ ions [34]. It is also obvious from the previous discussion that as the value of Li+ ion

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spacing decreases, more suitable sites to occupy Li+ ions are available in the system, which may enhance the conjoining conduction pathways of the percolation [43]. The reduction of

effectively with Li2O content [44, 45].

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interphase resistance due to the above-mentioned facts should enhance the ac conductivity

A.K. Jonscher has proposed the dispersive behavior of ac conductivity (σac) of ionic materials, which shows dependency on the angular frequency ω of the form [46]: (12)

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σ ω = A ω-.

where, A is the pre-factor and the s is the power-law exponent, which lies normally in the range 0 < s < 1. For highly disordered materials, e.g., ionically conducting glasses and

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amorphous semiconductors, such conductivity has been commonly observed, which is

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recognized as the “universal dynamic response” [46, 47]. The power-law exponent (s) has been derived from the slope of the dispersive region of the ac conductivity (σac) plot. The values of the power-law exponent are found to be greater than 1 for the present system, which may be regarded as super-linear power-law exponent [48] or NCL (nearly constant loss) regime [48]. Structural disorder in the present system may be the possible reason for formation of NCL regime [49, 50], where the localized hopping movement of Li+ ions is expected to be taken place within fairly small clusters of LiZn(PO4). In Li+ ion conducting glass-ceramics, the NCL may originate from the relaxation of asymmetric double-well

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ACCEPTED MANUSCRIPT potentials (ADWP) with a broad distribution of relaxation times [49]. The asymmetric double-well potential (ADWP) model describes that at higher frequencies or temperatures, the low-energy excitations instigate the system to relax over an energy barrier, which separates two different energy minima [50]. The hopping or non-hopping process of the

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glass-ceramics can be verified using the nature of variation of (log A)/s with temperature plot [48, 51]. Here, the value of the constant (A) can be extracted from Eq.12 as A = σdc x ωim– s [48]. It is already reported that the values of (log10 A)/s is independent of temperature and

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composition [48]. Another work on Ag+ ion conducting glasses [51] exhibits the composition and temperature dependency of (log10 A)/s. Fig. 7 shows the variation of (log10A)/s as a

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function of temperature, which clearly indicates that the ratio (log10A)/s depends on temperature for all the samples. This result signifies that the temperature advancement of log10A is not comparative to the temperature advancement of S and the conduction process may be predicted as hopping [48, 51]. The variation of power-law exponent (s) with

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temperature of all the glass-ceramics is presented in Fig. 8. Theoretically, there are singleparticle hopping models, concerning random barriers and/or trapping sites to facilitate the movement of Li+ ions in percolating networks [52-54]. Similarly, there are the theories of

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many-particle interactions in hopping mechanism, which involve the motion of Li+ ions with

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influence of relaxation of its neighbourhood [55]. Thus, the value of s may be treated as the consequence of the accumulative effect of the distribution of relaxation path, the mechanism on the structural disorder and the degree of interaction of the dispersed nanocrystallites in amorphous glassy matrices. The estimated values of the power-law exponent (s) (Fig. 8) are found to be greater than 1 over the entire temperature range, which may be due to the percolation [52-54] or pseudo-three-dimensional [28, 51, 56] motions of Li+ ions. In addition, the value of power-law exponent (s) is found to decrease with temperature for all the glassceramic compositions, which implies that correlated barrier hopping (CBH) model is the

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ACCEPTED MANUSCRIPT most suitable ion conduction mechanism [55]. It may be concluded from the previous discussion that conduction may occur via ion hopping process, where Li+ ions instantaneously hop over the potential barrier in a complex energy landscape [51]. In this way, Coulomb wells [57] of dispersed nanocrystallites may overlap for adjacent locations for

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a suitable separation (R). This anticipation may result to go down the effective height of energy barrier from Wm to W for individual ion hopping, which may be expressed as [57]:  /O

W = W. – P Q Q

(13)

R S

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Here, Wm is the maximum ion hopping energy, W is the potential energy barrier for ion

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hopping after lowering of effective barrier (Wm) due to overlapping of Coulomb wells. ε and ε0 is the dielectric constant of material and permittivity of free space respectively, R is the separation between the ion hopping sites and n is the number of ions involved in hopping process. The power-law exponent (s) as per CBH model is stated as [55] U *+ ,

 W *+ , 9 5   X R 

(14)

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s = 1 − V

It is observable from Eq. 14 that the value of s decreases with temperature. Wm is the energy necessary to hop over the crystallites’ potential wells and τ0 is the characteristic relaxation

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time. To fit the experimental data with good precision, existing CBH model should be modified as the value of s> 1. The modified CBH model [57] can be presented as: U *+ ,3,R 

(15)

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s = 1 − V

 W *+ ,3,R  ∗ 5   X R 

The values of maximum hopping energy (Wm), τ0 and T0 (ideal glass transition temperature) have been computed from the fitting using Eq. 15. The black solid lines in Fig. 8 shows nonlinear curve fits to the experimental values of power-law exponent (s) as a function of temperature (T). The values of fitting parameters Wm, τ0 and T0 are, shown in the inset of Fig. 8. Here, the computation is done at a fixed frequency, f = 100 KHz. It is noted in Fig. 8 that

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ACCEPTED MANUSCRIPT the values of Wm, τ0 and T0 are decreased with Li2O content, which agrees with ionic conductivity results. In ac conductivity spectra (Fig. 3(a) and (b)), the existence of strong frequency dispersion above the characteristic ion hopping frequency (ωH) is observed. It is also noted that ωH

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shifts towards higher values with temperature. In addition, it is perceived that the frequency range of the low-frequency plateau region of ac conductivity spectra depends strongly on temperature. These two observations recommend that multiple σac isotherms can be super-

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imposed to form a single master curve in a process known as the time-temperature superposition principle (TTSP) or scaling [42, 58, 59]. In the present study, “Ghosh and Pan”

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scaling approach [60-62] is adopted successfully. According to linear response theory, electrical conductivity is related to the time-dependent displacement of the mobile ions in thermal equilibrium and ion dynamics are represented by a non-random forward-backward hopping process, which predicts that long-time regime requires random walker of ions [59].

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The temperature-scaling and composition-scaling for conductivity spectra using “Ghosh and Pan” scaling approach [60] for present glass-ceramic compositions are shown in Fig. 9(a) and (b) respectively. A small deviation can be observed in the high-frequency region, caused by

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the strong interaction of ions with the surrounding environment, which is confirmed with

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higher values of the power-law exponent (s>1). The superposition of ac conductivity spectra into a master curve signifies that the conductivity relaxation behaviour is independent of temperature and composition. In these glass-ceramics, the localized movements of Li+ ions are correlated with the long-range ion transport mechanism and thus the conductivity spectra obey time-temperature superposition principle (TTSP). 3.3

Study of Cyclic Voltammetry (CV):fs The traces of cyclic voltammograms for x = 0.2 and 0.4 are shown in Fig. 10 (a) and

(b) respectively. Each trace contains an arrow indicating the direction in which the potential

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ACCEPTED MANUSCRIPT is scanned to record the data. The arrow indicates the beginning and sweep direction of the first segment [63]. It is observed from Fig. 10 (a) and (b) that the apparent oxidation of the samples with x = 0.2 and 0.4 starts at about 1.0 v. The subsequent cathodic scan indicates the oxidation reaction is not observed in the traces of higher scans as no oxidation peaks are

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observed in the higher cycle. The maximum current of ~2 µA in Fig. 10(a) indicates that only a small amount of sample is oxidized, but maximum current of ~9 µA in Fig. 10(b) indicates that a large amount of sample is oxidized. So, it can be concluded that electrochemical

4.

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stability may be disturbed as the lithium content of the resultant composite increases. Conclusion

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A series of Li2O-doped glass-ceramics have been prepared using the conventional melt quenching route. The XRD patterns confirm the presence of different type and size of nanocrystallites over the amorphous glass-ceramic matrices. The mean crystallite size reduces with increasing Li2O content. The study of dc ionic conductivity-temperature relation

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shows that all the glass-ceramic samples obey the Arrhenius law. The higher concentration of Li+ ion opens the Li+ transport pathway more, i.e., conduction channels for Li+ ion hopping become wider, which causes lower the dc activation energy (Edc) and higher dc ionic

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conductivity (σdc). The temperature and frequency dependence of ac conductivity is well

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fitted to Jonscher’s universal power-law and Almond-West formalism. The chemically and structurally more heterogeneous glass-ceramics facilitates the formation of low energy percolating Li+ ions conduction pathways and thereby increasing the ac conductivity. The fitting of modified CBH model to s versus T data reveal that Wm and τ0 values are found to decrease with ionic conductivity. “Ghosh and Pan” scaling approach is used to explore the effect of temperature and composition on the ion conduction relaxation mechanism and it is found that the ion conduction relaxation mechanism is independent of temperature as well as composition. It is clear from CV studies that the present system shows well electrochemical

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ACCEPTED MANUSCRIPT stability with lower lithium content. Therefore, further investigations on such glass-ceramics might pave the way for the development of high conductive solid electrolytes with high stability for application of solid-state lithium rechargeable batteries. Acknowledgement

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The financial assistance for the work by the Council of Scientific and Industrial Research (CSIR), India via sanction No. 03(1411)/17/EMR-II is thankfully acknowledged. Authors also thankfully acknowledge Dr. Achintesh Narayan Biswas, Department of Chemistry, NIT

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Sikkim for providing Cyclic Voltammetry traces of the samples under investigation.

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Figure captions

Fig.1. X-ray diffraction patterns of xLi2O–(1-x)(0.5ZnO–0.5P2O5) glass-ceramics with different values of x. Fig. 2. The variation of mean crystallite size and strain as function of composition (x). Fig. 3. (a) Temperature and frequency dependent conductivity of 0.1Li2O–0.9 (0.5ZnO– 0.5P2O5) glass-ceramic, solid lines indicate best-fitted curves using Almond-West formalism, 21

ACCEPTED MANUSCRIPT (b) the comparative study of ac conductivity at 683K for all the glass-ceramics with different values of x. Fig.4. (a)The reciprocal temperature dependence of dc ionic conductivity of all the glass ceramic compositions with different values of x, (b) Variation of ion hopping frequency with

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reciprocal temperature. Fig. 5 (a) Variation of dc conductivity (σdcT) with dc activation energy (Edc), (b) Variation of spacing between Li+ ions and Li-ion concentration with Li2O content.

Fig. 6. (a) The variation of ac conductivity at different frequencies for x = 0.2 with reciprocal

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temperature, (b) The reciprocal temperature dependent ac conductivity of all samples at f =

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3MHz

Fig.7. Variation of (log10A)/s as a function of temperature.

Fig. 8. s–T plot fitted with modified-CBH model of all the glass-ceramic samples. From bottom to up: x = 0.1, 0.2, 0.3, 0.4 and 0.5 respectively.

Fig. 9 (a) Temperature scaling of ac conductivity spectra of the glass-ceramic for x = 0.2 at

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various temperatures, (b) composition scaling of ac conductivity spectra at 653 K for all the

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Fig.10. The traces of cyclic voltammograms for (a) x = 0.2 and (b) 0.4 respectively.

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Table captions Table 1

0.1

2θ (degree)

dC (nm) (D-S)

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The values of diffraction peak (2θ), crystallite size using Debye-Scherrer (D-S) equation (dC), crystalline phases, Miller indices (hkl), and interplanar distances (D) of the dispersed phases of all the glass-ceramic samples.

25.06 25.64 27.70 28.38 30.12 33.76 34.90 36.64 47.28 48.65 52.03 56.29 71.65

44.82 40.56 42.94 44.30 42.95 43.17 43.67 39.06 38.19 26.34 55.35 33.97 58.91

Phase

h

k

l

LiPO3 LiPO3 LiZn[PO4] LiZn[PO4] ZnP4O11 Li2O Li3 [PO4] LiZn[PO4] ZnO LiPO3 Li3[PO4] Li2O P2O5

2 2 2 4 1 1 4 0 1 5 2 2 2

1 1 2 0 6 1 0 4 0 2 3 2 10

-4 1 -4 2 -1 1 0 0 2 -5 1 0 2

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Interplanar Distance(D) (A)

7.103 6.943 6.437 6.285 5.930 5.306 5.138 4.902 3.842 3.740 3.513 3.266 2.632

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6

2

2

LiPO3 LiPO3 LiZn[PO4] LiZn[PO4] ZnP4O11 Li2O Li3[PO4] LiZn[PO4] ZnO LiPO3 Li3[PO4] Li2O P2O5 Li3[PO4]

2 2 2 4 1 1 4 0 1 5 2 2 2 6

1 1 2 0 6 1 0 4 0 2 3 2 10 2

-4 1 -4 2 -1 1 0 0 2 -5 1 0 2 2

LiPO3 LiPO3 LiZn[PO4] LiZn[PO4] ZnP4O11 LiZn[PO4] Li2O Li3[PO4] LiZnPO4 ZnO LiPO3 Li3[PO4] Li2O P2O5 Li3[PO4]

2 2 2 4 1 2 1 4 0 1 5 2 2 2 6

1 1 2 0 6 2 1 0 4 0 2 3 2 10 2

-4 1 -4 2 -1 -5 1 0 0 2 -5 1 0 2 2

Zn2P2O7 LiPO3 LiPO3 LiZn[PO4] LiZn[PO4] ZnP4O11 LiZn[PO4] Li2O Li3[PO4] LiZn[PO4] ZnO LiPO3 Li3[PO4] Li2O P2O5 Li3[PO4]

0 2 2 2 4 1 2 1 4 0 1 5 2 2 2 6

2 1 1 2 0 6 2 1 0 4 0 2 3 2 10 2

1 -4 1 -4 2 -1 -5 1 0 0 2 -5 1 0 2 2

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2.547 4.827 7.126 6.961 6.452 6.295 5.936 5.316 5.152 4.906 3.846 3.745 3.512 3.271 2.639 2.548 4.836 7.098 6.939 6.433 6.281 5.923 5.657 5.298 5.136 4.900 3.841 3.739 3.505 3.265 2.632 2.546 4.880 7.512 7.112 6.948 6.441 6.295 5.936 5.669 5.308 5.145 4.906 3.842 3.734 3.509 3.268 2.639 2.548 5.051

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Li3[PO4]

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Mean Value 0.2 24.97 25.58 27.63 28.33 30.09 33.70 34.80 36.61 47.23 48.59 52.05 56.21 71.45 74.41 Mean Value 25.07 25.66 0.3 27.71 28.40 30.15 31.61 33.81 34.92 36.66 47.30 48.67 52.15 56.31 71.67 74.47 Mean Value 0.4 23.67 25.02 25.63 27.68 28.33 30.09 31.54 33.75 34.85 36.61 47.28 48.74 52.10 56.26 71.45 74.41 Mean Value

27.75 41.57 50.57 47.11 47.00 48.54 46.75 44.33 47.53 42.04 41.85 29.61 31.79 41.33 27.17 25.11 40.77 30.71 30.46 47.63 47.67 43.26 34.00 29.01 44.95 36.04 36.11 46.00 23.21 39.23 35.73 25.68 36.65 39.79 35.83 34.70 36.44 37.16 37.88 36.89 36.45 36.12 35.89 33.98 21.97 23.60 30.47 25.93 24.23 32.96

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ACCEPTED MANUSCRIPT Zn2P2O7 LiPO3 LiPO3 LiZn[PO4] LiZn[PO4] ZnP4O11 LiZn[PO4] Li2O Li3[PO4] ZnO LiPO3 Li3[PO4] Li2O P2O5 Li3[PO4]

0 2 2 2 4 1 2 1 4 1 5 2 2 2 6

2 1 1 2 0 6 2 1 0 0 2 3 2 10 2

1 -4 1 -4 2 -1 -5 1 0 2 -5 1 0 2 2

7.497 7.093 6.930 6.429 6.277 5.920 5.657 5.300 5.138 3.838 3.735 3.508 3.265 2.631 2.546 5.051

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Mean Value

36.57 28.72 31.49 27.26 27.93 29.28 35.49 43.26 28.93 34.69 21.45 24.59 27.31 35.08 27.04 30.61

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23.72 25.09 25.69 27.73 28.42 30.17 31.61 33.80 34.90 47.33 48.72 52.11 56.31 71.68 74.49

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Table 2:

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Glass-transition temperatures (Tg) and crystallization temperatures (Tc) for xLi2O–(1x)(0.5ZnO–0.5P2O5) glass-ceramics.

Tg ( ̊C)

Tc ( ̊C)

610 590 585 575 570

670 665 662 660 658

Table 3:

Room temperature dc conductivity of xLi2O–(1-x)(0.5ZnO–0.5P2O5) glass-ceramics.

x

σdc (Ω Ω-1cm-1)

0.1 0.2 0.3

3.54x10-20 2.63x10-16 2.62x10-15 25

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√ Ac conductivity spectra of Li2O based glassy ceramics √ Almond-West formalism

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√ Temperature and composition dependency of conductivity

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√ Higher values of the power-law exponent indicates strong interaction of ions with the surrounding