Structural defects characterization of silver-phosphate glass nanocomposites by positron annihilation and related experimental studies

Journal Pre-proof Structural defects characterization of silver-phosphate glass nanocomposites by positron annihilation and related experimental studies

Dipankar Biswas, Anish Rajan, Soumyajyoti Kabi, Anindya Sundar Das, Loitongbam Surajkumar Singh, P.M.G. Nambissan PII:

S1044-5803(19)30809-5

DOI:

https://doi.org/10.1016/j.matchar.2019.109928

Reference:

MTL 109928

To appear in:

Materials Characterization

Received date:

24 March 2019

Revised date:

9 August 2019

Accepted date:

10 September 2019

Please cite this article as: D. Biswas, A. Rajan, S. Kabi, et al., Structural defects characterization of silver-phosphate glass nanocomposites by positron annihilation and related experimental studies, Materials Characterization (2018), https://doi.org/10.1016/ j.matchar.2019.109928

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© 2018 Published by Elsevier.

Journal Pre-proof

Structural defects characterization of silver-phosphate glass nanocomposites by positron annihilation and related experimental studies

Dipankar Biswas

a, b

, Anish Rajan c, Soumyajyoti Kabi d, Anindya Sundar Das

e, *

,

Loitongbam Surajkumar Singh b, P.M.G. Nambissan f

Department of Electronics & Communication Engineering, Regent Education and Research Foundation,

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f

a

Barrackpore, Kolkata-700121, India b

Department of Electronics & Communication Engineering, National Institute of Technology Manipur,

c

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Langol, Imphal-795004, India

Department of Physics, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Majhitar, Sikkim

e-

737136, India

Department of Physics, Hijli College, Kharagpur 721306, India

e

Department of Electronics & Communication Engineering, Swami Vivekananda Institute of Science &

Pr

d

Technology, Dakshin Gobindapur, Kolkata-700145, India

Applied Nuclear Physics Division, Saha Institute of Nuclear Physics, Kolkata-700064, India

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Abstract

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The structural defects and their role in the formation and properties of the metal oxide glass nanocomposite xAgI–(1-x) (0.65Ag2O–0.35P2O5) have been studied using several sensitive spectroscopic techniques. The nanocomposite samples have been prepared by conventional melt-quenching method and the formation of nanocrystallites over the amorphous glassy matrices has been verified from X-ray diffraction and transmission electron microscopy studies. The optical band gap energies were determined from Tauc’s plots of UV-Vis absorption spectra taken from a spectrophotometer. Special emphasis on the defect characterization and defects-mediated stages of evolution is made possible through positron annihilation lifetime (PAL) and coincidence Doppler broadening spectroscopic (CDBS)

Journal Pre-proof measurements, which further helped in the investigation of the growth of defects, especially the Ag+ ion vacancies, within the nanocomposites. A defect-specific positron lifetime is identified to represent positron trapping in the interfacial gaps between nanocrystallites and the amorphous glass matrices besides the vacancies of Ag+ ions. The longest positron lifetime component occurs due to the formation of orthopositronium in free volume holes of small sizes and it increased as an effect of agglomeration of the free volume holes within the amorphous glassy matrices at increased incorporation of AgI. The CDB spectra revealed the

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changing proximities of the Ag+ ion vacancies to the surrounding oxygen ions. The positron annihilation characteristics were especially indicative of the importance of the choice of

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stoichiometry in the formation of the nanocomposite and its exhilarating properties.

Keywords: Defects and Vacancies; Nanocomposites; Positron annihilation; Transmission

Corresponding author:

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*

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electron microscopy; UV-Vis absorption; X-ray diffraction.

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E-mail address: [email protected] (A.S. Das)

1. Introduction

Phosphate-based glass nanocomposites have been extensively studied already as they have great applications in optical data transmission, solid-state batteries and laser technologies [1-3]. The favourable properties of these composites for the said applications included, to mention a few, their high thermal expansion coefficient, low glass transition temperature and high electrical conductivity [1-6]. Phosphate glass nanocomposites also have the prodigious potential for use as biomaterials [7-9]. Phosphate glasses exhibit ionic conductivity when comprised of Li+, Na+, Cu+ and Ag+ ions [10]. Among these, Ag+ ion containing phosphate glasses are very useful in optical fibre amplifiers and fibre photonic

Journal Pre-proof devices [11, 12]. Moreover, phosphate glass nanocomposites containing silver ions are well utilized as antibacterial constituents [13] and also more recently in technological applications like photonics and laser optical data recording [14, 15]. It is reported that the glassy network of the P2O5-based glasses is formed using PO4 tetrahedral unit connecting through P–O–P bonds and forming a polymeric chain structure [1 - 6]. In phosphate glasses, P2O5 acts as the glass network former and these glasses can be synthesized remarkably by melt-quenching technique at relatively low temperatures [16, 17].

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The inclusion of modifier such as oxide or iodide alters the physical bond of the glassy network from the random three-dimensional network to one of the linear phosphate chains.

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In terms of the number of oxygen atoms bridging with PO 4 tetrahedron [4], the structures of

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phosphate groups pass from meta-phosphate to pyrophosphate and then to orthophosphate [1

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- 6]. With increasing modifier oxide or iodide concentration, the three-dimensional long phosphate chains may possibly reduce in number, resulting in a collapse of the glassy

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network coherency [1 - 6, 17]. It is therefore felt interesting to explore the minute details of

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defect microstructure development at the different stages of nanocomposite formation and

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evolution and emphasize the necessity to account for the defects-aided formulation of properties at nanometric and atomic scales. The analysis of macroscopic properties and the microscopic structure of the material is a foremost topic in materials science. The existence of defects or free volumes owing to the static and dynamic disorder of the structure affects the properties such as structural relaxation, physical aging, viscosity [18], electrical transport [19], mobility etc. The dynamical free volume concept can provide a comprehensive understanding of the molecular material since free volume defects play an influential role in the determination of the physical and mechanical properties of the nanocomposites. Thus, to interpret the presence of defects or free volume properly, quantitative measurements are required

Journal Pre-proof including the sizes, concentrations, structure and distribution of free volume defects and their local elemental surroundings. There are several structural characterization techniques available for examining the structure of glass nanocomposites such as, for example, X-ray diffraction (XRD), transmission electron microscopy (TEM), atomic force microscopy (AFM), field emission scanning electron microscopy (FESEM) and so on. Nevertheless, these experimental techniques cannot investigate the deficiency of atoms and the existence of free volume defects within the structure, especially in the nanometer range of sizes.

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Positron annihilation spectroscopy (PAS) is recognized as the most informative and nondestructive tool for the study of free-volume defects in solids, which is an application based

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on the physical phenomenon of the interaction of the electron with positron in matter [20,

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21].

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This work describes the types of structural defects present in xAgI-(1-x)(0.65Ag2O0.35P2O5) glass nanocomposite systems using positron annihilation lifetime (PAL) and

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coincidence Doppler broadening spectroscopic (CDBS) techniques in addition to the

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conventional methods such as X-ray diffraction, UV-Vis absorption spectroscopy and

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transmission electron microscopy (TEM). The wisdom behind the choice of PAL and CDBS lies in the ability of these techniques to focus on to the defect-specific aspects of the microstructural variation as the concentration of AgI is stoichiometrically varied to identify the stages of evolution and detect the prominent species of defects at each stage. That precisely constituted the main interest behind this work and a few similar studies already reported in literature further provided motivation to undertake this investigation in depth and detail [22-24]. 2. Experimental procedure 2.1 Materials and synthesis

Journal Pre-proof Using the process of melting at high temperature followed by rapid-quenching, silver iodide-doped ionic glass nanocomposite samples of the composition xAgI–(1-x)(0.65Ag2O– 0.35P2O5) for x = 0.0, 0.1, 0.2, 0.4, 0.6, and 0.8 have been synthesized from reagent grade chemicals. Appropriate amounts of AgI, Ag2O, and P2O5 (all of purity 99.5% and obtained from Loba Chemie, Mumbai, India) have been accurately weighed and assorted in an agate mortar as per the necessary stoichiometry of the composites. The assortments were then taken into an alumina crucible and heated at a rate of 5°C/min and continuously observed

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cautiously to note down the melting temperature. After melting of the compositions, the temperature was raised by 10-20°C to obtain better fluidity of the melt and held at that

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temperature for half an hour to enhance the homogeneity of the melt. Details of

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stoichiometry of the compositions and melting temperature of all the samples are presented

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in tabular form in the Electronic Supplementary Information S1. During the heat treatment process, the samples or the melt was kept in the furnace at atmospheric air environment and

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atmospheric air pressure. In this case, the melts have been cooled rapidly by pressing the

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melt between two highly polished aluminum plates to obtain the glass nanocomposite flakes

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and then smoothly grinded them to fine powder form. 2.2. Characterization – X-ray diffraction and other studies X-ray diffraction (XRD) measurements have been performed on the powdered samples to describe the structure of nanocomposites using a Rigaku TTRAX-III rotating anode X-ray diffractometer, which operates in a step scan mode using Ni-filtered CuKα radiation of wavelength 1.54 Å. The step size is 0.02° at 2θ (Bragg angle) ranging from 15o to 90o and at a hold time of 2 sec per step. The determination of the presence of nanophases with their size, strain and lattice parameters within the samples and the measure of the degree of crystallinity or amorphousness of the samples have been performed from the XRD patterns.

Journal Pre-proof The outcome of XRD patterns have been compared with high-resolution TEM (HR-TEM) images, and TEM micrographs of nanocomposites, which have been obtained using a JEOL JEM-2010 facility with 300 keV electrons. The identification of the degree of crystallinity or amorphousness of the as-quenched samples have also been observed using selected area electron diffraction (SAED) patterns. Since finite size effects like changes in band gap are known to happen in wide band gap semiconductor oxides at extreme low nanoscales, UVVis absorption measurements on the nanocomposite samples have been carried out at 300K

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using PerkinElmer Lambda-750 spectrophotometer in a wide range of wavelength (190–750 nm). The colloidal suspensions essential for the absorption have been prepared using the

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probe sonicator (Takashi SK-500F).

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finely powdered samples dissolving in ethanol and homogenizing it using an ultrasonic

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For defect characterization, positron annihilation measurements have been performed using a positron source, i.e., radioactive isotope

22

Na (~10 μCi), which is in the form of

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deposition on a thin (~ 2m Ni-foil), folded and kept embedded at the centre of the column

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of finely powdered sample taken in a glass tube. The source is surrounded by the sample

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from all sides in adequate thicknesses to capture and annihilate all the emitted positrons within it. The assembly of positron source and the sample are always held in moisture-free conditions by uninterruptedly evacuating (P ~ 10–3 mbar) the glass tube to remove air and absorbed gases and permitting the particles to relax under their own weight. After the positron emission, the daughter nucleus (22Ne) emits an energetic 1.28 MeV photon within 3 picoseconds, which thus can be considered as the birth of the position and is used to start the lifetime clock. Positron first slows down by losing the kinetic energy and gets annihilated by an electron within the material. Two 0.511 MeV gamma-quanta are released, out of which one is detected to end the positron lifetime clock. The time delay between the positron birth signal (1.28 MeV) and the annihilation gamma ray (0.511 MeV)

Journal Pre-proof is the positron lifetime that provides the local electron density information. The measurements are performed using a slow-fast gamma-gamma coincidence spectrometer setup [25]. The source-sample assembly is kept between two scintillation detectors (BaF2) coupled with fast photomultiplier tubes (PMT- XP2020Q) to detect the gamma rays. In order to obtain the complete positron lifetime spectrum, more than 106 counts have been recorded, and the data have been analyzed using the PALSfit program [26]. In this work, we could perform successful three-component fitting of the positron lifetime spectra without any

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constraints, and the obtained positron lifetimes are denoted as τ1, τ2 and τ3 (ns) with relative intensities I1, I2, and I3 (%) respectively.

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In order to conserve the linear momentum of the annihilating electrons, the annihilation

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γ-rays are Doppler shifted. The measurement of 0.511E MeV annihilation γ-rays energies

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enables to perform coincidence Doppler broadening spectroscopy (CDBS) to obtain the electron momentum distribution in the samples. The measurement of the Doppler

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broadening effect has been carried out using two high-purity Germanium (HPGe) detectors

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with very good energy resolutions (1.27 keV and 1.33 keV at 0.511 MeV). The LAMPS

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software developed by Pelletron Division, Tata Institute of Fundamental Research, Mumbai has been utilized to acquire, store, and analyze the CDBS data [27]. In each Doppler broadening measurement, nearly two million events are collected under the CDB spectrum. The Doppler broadened spectrum is further characterized in terms of the line shape (S) and wing (W) parameters, which represent the low and high momentum distribution of the annihilated electrons respectively. The positron annihilation states within the materials or solids can be identified by simultaneous analysis of S and W-parameter and the S-W correlation [28]. The correlated measurement of S and W-parameters is sensitive to the type and the nature of trapping site or defects in the material. Similar studies have been carried out earlier and further details can be seen in some of the references [29, 30].

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3. Results and discussion 3.1 Study of X-ray diffraction patterns

The XRD patterns of all the as-prepared glass nanocomposite samples are presented in Fig. 1, which indicate a few well-defined peaks in all the patterns featuring the presence of

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nanocrystallites and revealing prominence to the long-range order over the short-range order of amorphous glassy matrices. The individual diffraction peaks with finite widths have been

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identified through proper assessment and the values of Miller indices have been validated

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from the available literature data (JCPDS Card numbers 78-0641 (AgI), 43-0997 (Ag2O),

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87-0952 (P2O5), 11-0637 (Ag4P2O7), 87-7399 (Ag3PO4), 33-1186 (Ag3P2O11) and so on). The sizes of nanocrystallites (dc) are estimated by the Debye-Scherrer (D-S) equation [31] 0.89 λ 𝛽 cos 𝜃

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𝑑c =

(1)

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Here 2θ is the Bragg diffraction angle, λ is the wavelength (1.54 Å) of the Cu-Kα X-ray

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radiation, and β is the full width at half maximum (FWHM). The microstructural properties were investigated and discussed by using the line profile analysis (LPA) method, in accordance with Gaussian distributions [32]. Moreover, the integral width was calculated by determining the area under each peak divided by the highest intensity in accordance with Gaussian distributions [32]. The corrections for instrument broadening were carried out in the estimation of the sizes of the crystallites. The X-ray profile of a standard crystalline silicon of high purity was used to estimate the instrumental broadening. The correct broadening of any observed peak for any sample, βcorrected, results from the subtraction of two factors, i.e., the observed broadening, βobserved, and the instrumental broadening,

Journal Pre-proof βinstrumental. The FWHM (β) used in eq. (1) was thus corrected for the instrumental broadening effect and the value of β used in the calculations has been taken as [33] 1/2

 = 𝛽corrected = (𝛽observed 2 − 𝛽instrumental 2 )

(2)

The Ag4P2O7 [34], Ag3PO4 [35], Ag3P2O11 [36], P2O5 [37], P2O3 [38], P4O7 [39], AgI [40], Ag2O [41] nanophases have been identified, which are superposed over the amorphous glassy matrices. The values of Bragg angle of diffraction and the values of Miller indices are

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presented in Table 1 along with the sizes of the nanocrystallites in the respective samples. By employing the Bragg’s law of diffraction nλ = 2Dsinθ, the inter-planar spacing (D)

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relating to each of the nanocrystallite phases has been estimated, and these values are also

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presented in Table 1. The amount of amorphousness of all the samples are determined by

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computing the relative percent crystallinity of each nanophase. There are several methods available to estimate this quantity and one of the methods is to perform deconvolution of the

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amorphous and crystalline peaks in the diffraction pattern. Percent crystallinity as

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originating from X-ray diffraction measurements is generally determined by the ratio of the intensity of the crystalline peaks to the sum of the amorphous and crystalline peak

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intensities. This can be written mathematically as [42]

Percent crystallinity = Icrystalline / (Icrystalline + Iamorphous)

(3)

Moreover, according to Ruland [43], the relative percent crystallinity can also be determined by deducting the contribution of amorphousness from the X-ray diffraction spectra by an amorphous standard. The selection of an amorphous standard is an immense challenge since it stipulates that the standard chosen normally should be almost similar to the amorphous component in the sample. Thus, the relative percent crystallinity is determined by dividing the total area of any crystalline peaks by the total area under the diffraction pattern

Journal Pre-proof (crystalline plus amorphous peaks). In other words, relative percent crystallinity is calculated as the ratio between the area of the crystalline contribution and the total area [44, 45], which can be written as follows

Area under the crystalline peak

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Crystallinity (%) = Total area under the diffraction curve (crystalline+amorphous) × 100

Fig. 1. X-ray diffraction patterns of the nanocomposite samples.

(4)

Journal Pre-proof The values of the percent crystallinity of each nanophase are shown in Table 1. It can be observed in Table 1 that the amorphousness of all the compositions is much higher than the percent crystallinity. Fig. 1 and Table 1 reveal that percent crystallinity of the samples of x = 0.2, 0.6 and 0.8 are higher than the samples of x = 0.0, 0.1 and 0.4 due to the higher values of the crystalline peak intensity or individual crystalline peak area as the percent crystallinity depends on peak intensity or the area under the crystalline peak. Due to the increment in the total number of crystalline peaks, their corresponding intensity value may also enhance the

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total percent crystallinity of the composites individually. Thus, it can be concluded that all the samples exhibit the existence of a certain amount of crystallinity superposing over

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amorphous glassy matrices.

Fig. 2. The Williamson-Hall (W-H) plots of all the different samples.

Journal Pre-proof The effects of microstrains are as well calculated from the broadening of X-ray diffraction peaks caused by the nanocrystallite sizes using the Williamson-Hall approach as [46] 0.89 λ 𝑑c

) + 4 𝜀 Sin 𝜃

(5)

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Pr

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𝛽 Cos 𝜃 = (

Fig. 3. (a) The comparative study of the crystallite sizes estimated from DebyeScherrer (D-S) equation and Williamson-Hall (W-H) plots; (b) The variations of microstrains (ε) with the concentration of AgI (x) in the nanocomposite samples.

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Fig. 2 presents the Williamson-Hall (W-H) plots of all the compositions. The y-intercepts values are used to estimate the sizes of nanocrystallites (dc) and the values of dc are shown in Fig. 2. In Fig. 3, a comparative study of the average nanocrystallite sizes estimated using WH plots and D-S method is depicted. From Fig. 3, it can be clearly realized that the average dimensions of the nanocrystallites evaluated by the W-H plots (Eq. 5) are consistently higher than the dimensions calculated by the D-S method (Eq. 1). The values of microstrains (ε) are

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attained from the slopes of the W-H plots as specified by Eq. (5). Additionally, the compositional dependence of the microstrain (ε) is shown in Fig. 3 and it is observed that

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microstrain (ε) values are dependent on the size of the nanocrystallites.

0.0

0.1

2θ (degree) 25.86 29.16 30.16 32.66 35.42 39.08

25.32 28.86 30.04 32.62 35.38 39

17.44 25.68 28.94 30.02 32.52 35.24

dC (nm) (D-S) 43.92 44.39 29.22 42.35 35.78 21.03 36.11 (ave) 22.59 26.29 27.05 15.71 34.54 59.39 30.92 (ave) 27.93 29.37 29.59 35.55 28.24 26.79

Phase

h

k

l

Percentage Crystallinity (%)

Interplanar distance (D) (Å)

Ag4P2O7 Ag3PO4 Ag4P2O7 P2O5 Ag3P2O11 Ag3PO4

2 2 0 1 1 3

3 1 8 1 3 0

3 0 1 2 4 0

Ag4P2O7 Ag3PO4 Ag4P2O7 P2O5 Ag3P2O11 Ag3PO4

2 2 0 1 1 3

3 1 8 1 3 0

3 0 1 2 4 0

P2O3 Ag4P2O7 Ag3PO4 Ag4P2O7 P2O5 Ag3P2O11

0 2 2 0 1 1

1 3 1 8 1 3

1 3 0 1 2 4

1.28 1.49 1.67 0.99 0.94 1.16 7.53 (total) 1.33 1.43 1.7 1.01 1.04 0.64 7.15 (total) 1.3 2.51 3.14 3.28 1.69 1.84

13.79 13.83 9.09 13.09 10.98 6.38 11.19 (ave) 10.74 10.96 8.41 20.89 10.60 18.03 13.27 (ave) 13.71 14.51 14.53 11.06 13.33 10.96

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x

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Table 1 The values of diffraction peak (2θ), crystallite size using Debye-Scherrer (D-S) equation (dc), crystalline phases, Miller indices (hkl), percent crystallinity and crystallite size from Williamson-Hall (W-H) plot (dc) (Fig. 2), interplanar distances (D) of the dispersed phases of (1-x)(0.65Ag2O– 0.35P2O5)–xAgI glass nanocomposites.

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Ag4P2O7 Ag2O Ag3PO4 Ag4P2O7 P2O5 Ag3P2O11 Ag3PO4

2 1 2 0 1 1 3

3 1 1 8 1 3 0

3 0 0 1 2 4 0

P4O7 P4O7 P4O7 Ag2O AgI

0 2 2 0 1

1 1 2 1 1

1 -1 -2 1 1

P4O7 AgI P4O7 P4O7 Ag3P2O11 Ag3PO4 Ag2O Ag3PO4 Ag3PO4

0 0 2 2 1 3 2 3 4

1 0 1 2 3 0 1 2 0

2.35 1.78 0.94 0.89 19.72 (total) 1.81 0.61 1.41 1.87 0.81 1.2 0.97 8.68 (total) 3.18 3.05 1.4 1.14 1.22 9.99 (total) 1.72 2.87 1.68 2.23 1.68 2.73 1.73 1.45 1.17 17.26 (total)

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0 -3 2 2

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0 3 0 2

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11.28 23.88 28.06 31.56 35.66 39.36 46.48 56.82 62.44

3 3 2 2

1 16 -1 -2 4 0 1 1 0

3.91 7.20 7.05 8.44 10.47 (ave) 12.60 14.71 11.96 7.99 12.17 14.06 4.80 11.18 (ave) 18.98 17.12 15.39 15.94 14.19 16.33 (ave) 15.31 15.89 16.06 11.71 9.09 11.26 10.59 8.40 7.88 11.80 (ave)

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0.8

11.32 28.1 31.16 38.42 40.38

Ag3PO4 P4O7 AgI Ag3PO4

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0.6

25.86 26.68 29.18 30.14 32.56 35.98 39.1

12.87 24.55 24.34 29.39 26.86 (ave) 25.13 21.71 26.05 25.68 21.10 29.50 15.81 23.56 (ave) 59.23 54.81 49.61 52.40 46.96 52.61 (ave) 51.74 53.81 51.40 37.62 46.27 40.77 61.50 49.10 60.73 50.32 (ave)

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0.4

38.96 48.94 51.9 53.46

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0.2

From Table 1, it is observed that the percent crystallinity depicts an overall increasing trend with the concentration (x) of AgI but for a sudden sharp fall between x = 0.2 and 0.4. From the X-ray diffraction patterns shown in Fig. 1, it is also obvious that a broad peak indicating the onset of amorphization appears at x = 0.1 and develops further at x = 0.4. In between, at x = 0.2, the growth of tiny nanocrystallites of different stoichiometric compositions is also visible in the form of appearance of several new peaks, all of which have been correctly identified and listed in Table 1. Fig. 2 had the illustration of just the average size of the nanocrystallites and the values are therefore reasonably small for x = 0.2 and 0.4. The plots available from the calculations based on Debye-Scherrer and Williamson-

Journal Pre-proof Hall equations are thereby consistent, notwithstanding the slight higher values given by the latter due to the microstrain effects taken into consideration. Alternatively, it may also be argued that x = 0.2 appears to be the optimum stoichiometry for the formation of the newer nanocrystallites, which is a novel observation in this work. 3.2 Study of TEM images The transmission electron microscopy (TEM) images have been recorded and analyzed

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to look for the evidence of the presence of nanocrystallites superposing over amorphous

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glassy matrices to support the findings of the XRD patterns. Fig. 4 depicts the different TEM

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and HR-TEM micrographs and selected area electron diffraction (SAED) patterns. Figs. 4(a) and (b) reveal the distribution of nanocrystallites of different shapes and sizes over the

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amorphous glassy matrices for the samples of x = 0.0 and 0.4 respectively. Fig. 4(a) shows

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that the sizes of different nanocrystallites are in the range of 5nm to 55nm for the sample of x = 0.0. The elemental composition of the nanocomposite samples can be identified by an

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energy dispersive X-ray (EDAX) analysis as shown in Fig. 5. For the sample of x = 0.0, the

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absence of AgI can be noted in Fig. 5(a) and the percentage of the weight of the elements O,

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P and Ag are 39.55%, 51.78% and 8.67% respectively. Whereas Fig. 4(b) reveals that the sizes of different nanocrystallites are in the range of 4nm to 38nm for the sample of x = 0.4. For the sample of x = 0.4, Fig. 5(b) shows the presence of all the composite elements and the percentage of the weight of the elements O, P, Ag and I are 15.28%, 25.27%, 46.27% and 13.19% respectively. Figs. 4(c) and (d) display the HR-TEM images of the samples of x = 0.0 and 0.4 respectively, revealing the presence of nanocrystallites superposing over the amorphous glass matrices. The arrangements of lattice fringes of amorphous glass matrices are random in nature and dislocation of lattice fringes are also observed conspicuously. The presence of the interface between the nanocrystallites and amorphous glass matrix can also be noticed clearly in Figs. 4(e) and (g). The lattice fringes of the nanocrystallites are also

Journal Pre-proof shown in the Figs. 4(e) and (g), which are the zoomed-in version of the area marked by the blue rectangles in Figs. 4(c) and (d). In Fig. 4(e), it is observed that the width of the lattice fringes is 0.11 to 0.14 nm and the interplanar distance is 0.19 nm to 0.32 nm for the sample of x = 0.0. However, in Fig. 4(g), it is seen that the width of the lattice fringes is 0.12 to 0.17 nm and the interplanar distance is 0.15 nm to 0.35 nm for the sample of x = 0.4.

(c)

(e)

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(a)

13 nm

(f)

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17 nm

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(i)

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22 nm

(d)

(g)

(h)

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(b)

(j)

11 nm

Fig. 4. (a) and (b) TEM images; (c), (e), (f), (d), (g) and (h) HRTEM micrographs; (i) and (j) SAED patterns of the nanocomposite samples of x = 0.0 and 0.4 respectively.

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The existence of porous type defects can also be noticeably observed in Figs. 4(c) and (d), which are marked by yellow color oval shapes for the samples of x = 0.0 and 0.4 respectively. To observe the presence of porous type defects clearly, the zoomed-in images of the area marked by the yellow color oval shapes in Figs. 4(c) and (d) are shown in Figs. 4(f) and (h) for the samples of x = 0.0 and 0.4, respectively. Figs. 4(i) and (j) depict the

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SAED patterns of the nanocomposite samples of x = 0.0 and 0.4 respectively, revealing

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concentric circles characteristic of the amorphous nature and bright shining spots over the

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concentric circles featuring the formation of nanocrystallites. This supports the XRD

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patterns as well (Fig. 1). The bright shining spots are due to the presence of silver phosphates (Ag4P2O7, Ag3PO4, and Ag3P2O11), different phosphates (P2O5, P2O3, and P4O7),

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AgI and Ag2O nanocrystallites over the amorphous glassy matrices.

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Fig. 5. EDAX spectra of the nanocomposite samples of (a) x = 0.0 and (b) x = 0.4 respectively.

3.3 Determination of optical band gaps The UV-Vis absorption spectra of all the samples have been recorded and further judiciously scrutinized to estimate the optical band gap energies (Eopt) by employing Tauc's

n

(6)

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αhν = [ B (hν − 𝐸opt )]

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f

plot technique [47, 48] in which Eopt is computed using the relation

Here hν is the incident photon energy and B is a band-tailing parameter. The approach of

e-

electronic inter-band transition usually decides the value of n [49]. For indirect allowed band

Pr

transitions, the value of n should be equal to 2 in Eq. (6). Consequently, the Tauc’s plots

Jo u

rn

al

equivalent to (hν)1/2 against hν variations of all the samples are presented in Fig. 6(a).

Journal Pre-proof

Fig. 6. (a) The Tauc’s plot of all the samples; (b) the optical band gap energies (Eopt) versus concentration of AgI (x). The values of E opt can be computed by the extrapolation of the linear region of the plots to meet the hν axis (x-axis) at (hν)1/2 = 0. Fig. 6(b) illustrates the plot of obtained optical band gap energies (Eopt) with respect to the concentration of AgI (x). Fig. 6(b) reveals that the

oo

f

values of Eopt increase with increasing concentration of AgI (x) up to the sample of x = 0.4 after which Eopt value decreases due to structural alterations. It is further well perceived

pr

from Figs. 3 and 6(b) that the nature of variation of Eopt is opposite to the sizes of the

e-

nanocrystallites and thereby ensuring a correlation of information available from the two techniques.

Pr

Davis and Mott's model [50] states that the increasing nature of the density of defect

al

states or disorder in amorphous solids leads to a decrement of the value of optical band gap

rn

energy (Eopt). The model further proposes that more localized states form near the mobility edge as the degree of disorder or defect states inside the amorphous structure increases. With

Jo u

the inclusion of AgI in the glassy matrix, the number of defect states or disorder probably have decreased, thus the value of Eopt increases [51]. Defect investigation, however, is discussed under the following section on positron annihilation studies and the information can be correlated with the changes in macroscopic properties such as lattice parameters and energy band gaps. 3.4 Positron annihilation studies

The typical peak-normalized PAL spectra of all the nanocomposite samples are shown in Electronic Supplementary Information S2. The long exponential decaying nature of such curves specifies the presence of various types of defects of diverse sizes and concentrations

Journal Pre-proof and other low-electron density sites such as intercrystallite interfaces within the glass matrices [52]. Through a three-component unconstraint fitting of the spectra using the PALSfit program [26], the composition dependent spectra of positron lifetimes (τ1, τ2 and τ3) and their corresponding intensities (I1, I2 and I3) are extracted and presented in Fig. 7. τ1 is the shortest component of positron lifetime, characteristic of annihilations of free positrons within the amorphous glass matrix after thermalization [53]. Fig. 7 reveals that the values of τ1 for all the nanocomposites are in the range of 0.10 ns to 0.13 ns. The lower

oo

f

values of τ1 signify that a fraction of positrons may possibly be captured and annihilated by the electrons of atoms of the amorphous glass matrices. As the average sizes of the

pr

nanocrystallites are in the range of about 20-70 nm and the thermal diffusion wavelength of

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positrons is about 50-110 nm in most of the materials, some of the positrons may possibly

Pr

diffuse from the amorphous glass matrix phase and be trapped on the surfaces or interfaces. The higher value of τ1 for the sample of x = 0.4 is thus a result of the increasing number of

al

positron annihilations in the surfaces or interfaces due to the reduction in the average

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the sample of x = 0.4.

rn

nanocrystalline sizes. It is worth noting that the nanocrystallites are of the lowest sizes for

In vacancies or other similar defects, the lifetime of trapped positrons is longer than that in the perfect lattice since positrons observe lower-than-average electron density in vacancies or defects than that in the bulk and hence a lower annihilation rate [53]. The positron lifetime increases with increasing open volume of the vacancies or defects. At the same time, the fraction of annihilations with core electrons of positrons reduces due to the reduced overlap between the positron wave function with the atomic core electron wave functions [53, 54]. τ2 is interpreted as the positron lifetime originating from the trapping and annihilation of positrons in the interfacial gaps of the nanocrystallites. It also beholds in it the lifetimes of positrons trapped in the vacancies or the vacancy type defects. The

Journal Pre-proof interfacial contribution comes from the fact that the sizes of the nanocrystallites identified here all are less than the typical thermal diffusion lengths of positrons in materials [55]. The values of τ2 of all the glass compositions are in the range from 0.288 ns to 0.321 ns (Fig. 7). Initially, the value of τ2 reduces as the concentration of AgI increases up to the sample of x = 0.2. For the sample of x = 0.4, τ2 value increases owing to the formation of clusters of Ag+ ion vacancies. Subsequently the values of τ2 reduce as positrons get trapped in interfacial gaps of the nanocrystallites. It is also observed in Fig. 7 that the intensities of τ2, (i.e., I2), are

oo

f

higher except for the sample of x = 0.4. Thus, it can be concluded that, for the sample of x = 0.4, the formation of Ag+ ion vacancies dominate and the number of defect states or disorder

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rn

al

Pr

e-

pr

decreases, which makes optical band gap energy higher (Fig. 6).

Journal Pre-proof Fig. 7. The positron lifetimes and relative intensities against the AgI concentration (x) in the different samples.

The bulk positron lifetime (τb) and mean positron lifetime (τm) can be estimated using the following relations [56] to analyze positron-trapping modes in a quantitative way as

1

𝐼

𝐼

= 1 + 2 1

(7)

2

f

b

1 𝐼1 +2 𝐼2 +3 𝐼3 𝐼1+𝐼2 +𝐼3

(8)

e-

pr

m =

oo

and

Here the intensities are expressed in decimal values. Figs. 8(a) and (b) present the variations

Pr

of the bulk positron lifetime τb and the mean positron lifetime τm with respect to AgI

al

concentration (x) respectively. The trapping of positrons within different types of defects is confirmed as τ1 < τb, which can be understood from Figs. 7 and 8(a). The reducing nature of

rn

τm as shown in Fig. 8(b) up to the sample of x = 0.4 suggests positron trapping in vacancies

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of Ag+ ions. (This is because, since τm is a weighted average of the different positron lifetimes, its reducing values indicate the dominance of defects with smaller lifetimes for positrons.) The rise of τm thereafter indicates positron trapping in the porous-type defects or free volume defects within the amorphous glassy matrix. As τm and τb exhibit similar behaviour, the same arguments hold good. Fig. 8(c) presents the difference between defectrelated (τ2) and defect-free (τb) positron lifetimes (τ2 – τb). The decrease of τ2 – τb up to sample x = 0.2 indicates that the vacancy type defects arising from the deficiency of Ag+ ions are smaller in size and it is possible that vacancy clusters or nanovoids have contracted owing to the unfavourable glassy matrix configuration surrounding them. However, for the sample of x = 0.4, τ2 – τb increases, revealing the formation of larger free volume defects or

Journal Pre-proof Ag+ ionic vacancies responsible for positrons trapping [56]. With further increasing concentration of AgI (x), τ2 – τb values reduce due to the contraction of large free volumes within the glass matrix. In nanocrystalline samples, the formation of positronium is possible in free volume spaces and/or at the intercrystallite separation. The longest lifetime component, 3, reduces for the sample of x = 0.2, which is indicative of the formation of porous-type defects within

f

the amorphous glassy matrix. For the sample of x = 0.4, 3 shows a higher value due to the

oo

formation of large free volumes, which forms in consequence of the agglomeration of small

Jo u

rn

al

Pr

e-

pr

free volumes.

Journal Pre-proof Fig. 8. (a) The bulk positron lifetime (τb), (b) the mean positron lifetimes (τm) and (c) τ2 – τb of all the nanocomposite samples as function of the concentration (x) of AgI.

Further, with AgI concentration (x) rise, 3 values reduce further with the contraction of free volumes within the amorphous glassy matrix. A simple relation (Eq. 9) between free volume radius (R) and o-Ps lifetime is proposed by Tao [57] and later modified by Eldrup et al [58].

oo

f

This model states that o-Ps may possibly reside in a spherical or irregular well having an infinite potential barrier of radius R0 with a homogeneous electron layer ΔR in the region

pr

between the irregular hole radius (R) and R0, i.e., R0 = R + ΔR. In this model, it is also

e-

assumed that o-Ps is localized in a finite spherical shaped hole. This model (Eq. 9) also assists to establish a relationship between the o-Ps lifetime τ3 and the mean free-volume

Pr

radius (R). The empirical equation derived by fitting the measured o-Ps lifetime (τ3) in an

as [57, 58] 𝑅

rn

al

infinite potential spherical well model with known cavity sizes is written in a general form

1

𝑅

−1

Jo u

τ3 = 0.5 [1 − 𝑅+∆𝑅 + 2π sin (2π 𝑅+∆𝑅 )]

(9)

rn

al

Pr

e-

pr

oo

f

Journal Pre-proof

Fig. 9. The free volume radius and the free volume fraction with reference to the

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concentration of AgI (x) in the nanocomposite samples.

Here 3 is expressed in ns and the radii in Å. Thus, the positronium lifetime 0.7044 ns can be attributed to free volume pores of radius 1.08 Å. The free-volume fraction (fV) can be estimated using the relation fV = AVf I3 where Vf = (4/3)πR3 is the size of the free volumes and A is a material constant. The value of the constant A depends on the material characteristics. In this case, as quite a few nanocrystallites of divergent structure and phases are involved, the extraction of the accurate value of A seems to be somewhat problematic thus we have used 1/600 as cited in the original works of Tao [57] and Eldrup et al [58]. Therefore, the values of fv are not absolute and only qualitatively used for interpretation. The

Journal Pre-proof variations of the extracted hole radius (R) and free-volume fraction (fV) are shown in Fig. 9, which suggest an overall decrease of the free volume fraction with rising concentration of AgI up to the sample of x = 0.2 followed by an increase with AgI concentration rise. The radius of free volume defects is less than 1.72 Å for the samples of x = 0.1, 0.2, 0.6 and 0.8, which confirms that these defects are the pores within the glassy matrix. The increase of radius of the free volume defects for the samples of x = 0.0 and 0.4 is due to the large free volume defects, which are formed in consequence of the agglomeration of the small porous

oo

f

type defects. The average sizes of the nanocrystallites reduce (Fig. 3(a)) and the values of optical band gap energy (Eopt) increase (Fig. 6(b)) up to the sample of x = 0.4 and

pr

consequently the interfacial defects have become weak in trapping positrons. The overall

e-

increase of the corresponding intensity I3 indicates this transformation.

Pr

The distribution of core electron momenta can be measured by coincidence Doppler broadened spectra, which can analyse the position of atoms near the positron annihilation

al

sites. The thermalized positrons are annihilated with electrons during the diffusion within

rn

the materials. In the centre of mass frame, annihilating γ-photon energy is exactly m0c2 =

Jo u

0.511 MeV (m0 is the rest mass of the positron or electron), and the movement of two γphotons is exactly in opposite directions. But due to the finite electron momentum (pL) longitudinal to the direction of emission of the gamma rays, the 0.511 MeV annihilation γrays are Doppler shifted in energy by an amount ± ∆E = ½ c pL and hence any change to the local electron momentum can be efficiently probed by positrons. The alteration of electron momentum generally occurs at the defect sites, and hence the effect of electron momentum distribution around the defects can be realized using positron annihilation process.

e-

pr

oo

f

Journal Pre-proof

Pr

Fig. 10. The ratio curves generated from the CDB spectra of all the different samples

rn

al

with reference to the spectrum of Al single crystalline samples.

Jo u

Fig. 10 presents the CDB ratio curves [59, 60], which are generated from the spectra of the samples with respect to the CDB spectrum of a pair of pure (99.999%), well-annealed and defect-free Al single crystalline samples. The prominent peak at pL = 9.64  10-3 m0c is identified as the consequence of positron annihilation with the 2p core electrons of oxygen ions surrounding the cationic vacancies and their clusters within the samples. The different samples have generally exhibited identical features about the local electronic environment of vacancies although the relative amplitudes of each curve change from sample to sample. It may be further noted in this context that the positively charged oxygen ionic vacancies cannot trap positrons due to Coulomb repulsion [59, 60].

pr

oo

f

Journal Pre-proof

m0c) against the AgI concentration (x) in the different samples.

al

Pr

3

e-

Fig. 11. The peak CDBS ratio of the major 2p electron annihilation (at pL ~ 9.6410–

rn

Fig. 11 presents the amplitude of the peak at pL ~ 9.64 x 10–3 m0c of the CDB ratio

Jo u

curves against the concentration of AgI. With the incorporation of AgI in the composite, i.e., of the sample of x = 0.1 as compared to the sample of x = 0.0, the reduction of amplitude indicating decreased annihilation process of electron-positron owing to the reducing particle size at this stage, escalates positron annihilation at surface states. The succeeding reduction of amplitudes of the sample of x = 0.2 is the consequence of the formation of porous type defects or smaller size of voids within the glassy matrices. Further increase in the amplitude of the sample of x = 0.4 owes to the low momentum states indicating increased Ag+ vacancy addition. The peak amplitude of CDB spectra of the samples of x = 0.6 and 0.8 decreases in consequence of the agglomeration of small free volumes, which results in larger voids and reduces the number of isolated Ag+ ion vacancies within the amorphous glassy matrices. The

Journal Pre-proof highest amplitude of CDB peak is observed for the sample of x = 0.0 owing to the presence of more Ag+ ion vacancies and a smaller number of agglomerated voids. The Doppler broadened spectrum can be further investigated in terms of the line-shape (S-parameter) and wing parameters (W-parameter), which characterize the portions of low and high momentum electrons annihilated by the positrons respectively. The central portion of the annihilation gamma ray spectrum represents those 0.511 MeV γ-rays, which are less Doppler shifted, i.e., coming from the annihilation of positrons with the low momentum

oo

f

(valence and free) electrons. The ratio of the central area counts of the 0.511 MeV photopeak and the total photo-peak area is abbreviated as S-parameter. Similarly, the wing portion

pr

of the spectrum represents the annihilation γ-rays, which are more Doppler-shifted, i.e.,

e-

coming from the annihilation of positrons with the high momentum (core and bound)

Pr

electrons. The W-parameter signifies the relative fraction of the counts in the wing regions on either side of the annihilation line with respect to that under the whole spectrum. Due to a

al

lower electron density, the distribution of momentum of annihilating valence electron

rn

becomes slightly narrower. Additionally, at a vacancy, the overlap of the wave function of

Jo u

localized positron reduces with ion cores leading to a significant reduction in the annihilation process with high momentum core electrons. Fig. 12 depicts the variation of the S-parameter and W-parameter as a function of the concentration of AgI (x). The line-shape parameter (S) increases due to the enhancement in the concentration of open volume defects in the system. This occurs when relative concentrations of porous type of defects or voids increase in the material. A correlation between the S and W parameters is illustrated and briefly discussed in Electronic Supplementary Information S3.

rn

al

Pr

e-

pr

oo

f

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AgI (x).

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Fig. 12. The variation of S-parameter and W-parameter against the concentration of

Typically, the grain size is a few tens of nanometers for the nanocrystallites and hence many of the positrons may propagate to the surface of the crystallites that are immensely defective in nature [61, 62]. Such interfacial surface regions increase with reducing crystallite size, thereby resulting an increment in the S-parameter. The increasing concentration of vacancy in a sample leads to a greater probability of positron annihilation with low momentum valance electrons. As core electrons are closer to the nucleus and

Journal Pre-proof strongly bound, they have a diminutive possibility of annihilation with positrons within a vacancy like free space.

4. Conclusions The results of spectroscopic investigations using conventional and novel techniques like X-ray diffraction, transmission electron microscopy, UV-Vis absorption and positron

f

annihilation studies on xAgI–(1-x)(0.65Ag2O–0.35P2O5) nanocomposite samples yielded

oo

certain microstructure-specific information on the formation of nanocrystals and amorphous

pr

matrix coexisting with well-defined characteristics. A notable observation in XRD patterns and HR-TEM micrographs is the formation of a certain amount of crystallinity superposing

e-

over the amorphous glassy matrices. The optical band gap energies increased whereas the

Pr

average size of nanocrystallites within the glassy matrices decreased for the samples up to x = 0.4. The formation of different type of defects within the amorphous glassy matrices has

al

been investigated through positron lifetime and coincidence Doppler broadening

rn

measurements. The results indicated the formation of o-Ps within the extended

Jo u

intercrystallite regions as the positron lifetime spectra of all the samples decayed through a third component (τ3) of nanoseconds longevity besides two shorter lifetimes. The porous type defects and interface between nanocrystallite and amorphous matrix could also be observed in the HRTEM micrographs. The agglomeration of porous type defects takes place that makes the size of free volume holes to increase for the samples of x = 0.0 and 0.4. The second positron lifetime component (τ2) is defined as resulting from positron annihilation in interfacial gaps between nanocrystallites and surrounded amorphous matrix. The expansion of interfacial gaps around the nanocrystallites or the formation of more Ag+ ion vacancies within the amorphous matrices of the samples of x = 0.0 and 0.4 assist τ2 to increase. The CDB measurements confirmed that the positron annihilation occurs with the electrons of

Journal Pre-proof ions of different charges and momentum distributions. Positrons get trapped in defects surrounded by O2– 2p electrons and thus the role of cationic defects and their clusters emphasize the properties of the nanocomposites. In addition, the variation of the Sparameters derived from CDB spectra further support the findings from positron lifetime measurements. The evolution of defects with the inclusion of AgI in all the ionic glass compositions has thus provided a clear view of how the structural changes involving electrons can be utilized to provide valuable information on the intrinsic exotic features of

oo

f

metal oxide nanocomposites.

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Acknowledgements

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The authors wish to thank Mr. Anish Karmahapatra and Ms. Soma Roy for their help in the

Pr

X-ray diffraction and UV-Vis absorption measurements respectively. PMGN wishes to acknowledge the involvement of Ms. Aiswarya M.S., Ms. Darshitha P.P. and Mr. Akash

al

Dey in the positron annihilation experiments as part of their project work. The authors

rn

sincerely thank Dr. Debasish Roy, Professor, Department of Mechanical Engineering,

Jo u

Jadavpur University, Kolkata, India for his help and support throughout the work. Data availability

The raw/processed data required to reproduce these findings cannot be shared at this time as the data also forms part of an ongoing study. References [1] J.J. Hudgens, R.K. Brow, D.R. Tallant, S.W. Martin, Raman spectroscopy study of the structure of lithium and sodium ultra-phosphate glasses, J. Non-Cryst. Solids, 223 (1998) 21–31.

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Figure captions Fig. 1. X-ray diffraction patterns of all the nanocomposite samples. Fig. 2. The Williamson-Hall (W-H) plots of all the different samples.

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Fig. 3. (a) The comparative study of the crystallite sizes estimated from Debye-Scherrer (D-

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S) equation and Williamson-Hall (W-H) plots, (b) the variations of microstrain (ε) with the

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concentration of AgI (x) in the nanocomposite samples.

Fig. 4. (a) and (b) TEM images; (c), (e), (f) and (d), (g), (h) HRTEM micrographs; (i) and (j)

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SAED patterns of the nanocomposite samples of x = 0.0 and 0.4 respectively.

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Fig. 5. EDAX spectra of the nanocomposite samples of (a) x = 0.0 and (b) x = 0.4 respectively.

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Fig. 6. (a) The Tauc’s plot of all the compositions; (b) the optical band gap energies (Eopt)

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versus concentration of AgI (x).

samples.

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Fig. 7. The positron lifetimes and relative intensities versus the AgI concentration (x) in the

Fig. 8. (a) The bulk positron lifetime (τb), (b) the mean positron lifetimes (τm) and (c) τ2–τb of all the nanocomposite samples as function of the concentration (x) of AgI. Fig. 9. The free volume radius and the free volume fraction with reference to the concentration of AgI (x) in the nanocomposite samples. Fig. 10. The ratio curves generated from the CDB spectra of all the samples with reference to the spectrum of Al single crystalline sample. Fig. 11. The CDBS ratio of the major 2p electron annihilation peak (at pL ~ 9.6410–3 m0c) against the AgI concentration (x) in the different samples. Fig. 12. The variation of S-parameter and W-parameter against the concentration (x) of AgI.

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Journal Pre-proof Highlights (for review) X-ray diffraction patterns reveal the formation of nanocrystallites superposing over amorphous glass matrix. HR-TEM images support XRD patterns and indicate the formation of porous type defects within the amorphous glass matrix. The optical band gap energies of the samples increase while average crystallite size reduces. Positron lifetimes point out the presence of Ag + ion vacancies defects within the nanocomposite samples.

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CDB spectra reveal the electron momentum distribution around the vacancy type defects.