5.2 Principle of Fourier transform infrared (FTIR...

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119 | Page Chapter V FTIR and UV-Vis studies on α-Fe 2 O 3 and its nanocomposites 5.1 Introduction 5.2 Principle of Fourier transform infrared (FTIR) spectroscopy 5.3 Principle of diffuse reflectance UV-Vis (DRUV) spectroscopy 5.4 FTIR analysis 5.4.1 FTIR spectra of glycine assisted α-Fe 2 O 3 nanoparticles 5.4.2 FTIR spectra of α-Fe 2 O 3 /SnO 2 SNH’s 5.4.3 FTIR spectra of α-Fe 2 O 3 /graphene NC’s 5.5 Diffuse reflectance analysis 5.5.1 DRUV spectra of glycine assisted α-Fe 2 O 3 nanoparticles 5.5.2 DRUV spectra of α-Fe 2 O 3 /SnO 2 SNH’s 5.5.3 DRUV spectra of α-Fe 2 O 3 /graphene NC’s 5.6 Conclusions References

Transcript of 5.2 Principle of Fourier transform infrared (FTIR...

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Chapter V FTIR and UV-Vis studies on α-Fe2O3 and its nanocomposites

5.1 Introduction

5.2 Principle of Fourier transform infrared (FTIR) spectroscopy

5.3 Principle of diffuse reflectance UV-Vis (DRUV) spectroscopy

5.4 FTIR analysis

5.4.1 FTIR spectra of glycine assisted α-Fe2O3 nanoparticles

5.4.2 FTIR spectra of α-Fe2O3/SnO2 SNH’s

5.4.3 FTIR spectra of α-Fe2O3/graphene NC’s

5.5 Diffuse reflectance analysis

5.5.1 DRUV spectra of glycine assisted α-Fe2O3 nanoparticles

5.5.2 DRUV spectra of α-Fe2O3/SnO2 SNH’s

5.5.3 DRUV spectra of α-Fe2O3/graphene NC’s

5.6 Conclusions

References

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Chapter V

FTIR and UV-Vis studies on α-Fe2O3 and its nanocomposites

5.1 Introduction:

Spectroscopy is the study of the interaction of electromagnetic radiation with matter

[1]. Spectroscopy has many applications in the modern world, ranging from nondestructive

examination of materials to medical diagnostic imaging (e.g., MRI, CAT scans). In a

chemical context, spectroscopy is used to study energy transitions in atoms and molecules.

The transitions are interpreted and can serve to identify the molecule or give clues about the

molecular structure. Spectroscopy is a powerful tool for inorganic chemists to identify the

compounds that have been prepared. Interpretation of data plays a crucial role as the

deductive reasoning skills will be challenged when the principles of spectroscopy is applied

to solve chemical problems. When a molecule interacts with electromagnetic radiation,

energy is absorbed and the molecule is promoted, or is said to undergo a transition, to a

higher energy state (excited state). In order for absorption to occur, the energy of the

radiation must match the energy difference between the quantized energy levels of the

molecule. For example, in Fig.5.1, E1 and E2 are the quantized energy levels and ΔE is the

energy difference (ΔE = E2 - E1) that must match the energy of the incident radiation.

ΔE = hυ= hc/λ = νhc

Where, h is the Planck’s constant=6.626×10-34 J·s

C is the speed of light=3×108 m/s

The incident radiation can be characterized by its frequency (υ), its wavelength (λ), or its

wave number ( ν ). The relationships between these quantities are:

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Fig.5.1 Showing the energy difference between the quantized energy levels of the

molecule during transition as it interacts with electromagnetic radiation.

λ(m)

)c(m.s)ν(s

11

= ; cm100

m1

λ(m)

1)(cmν 1

×=−

Although the wave number (cm-1) is not an S.I. unit, it is conventionally used to describe the

transitions in infrared (IR) spectroscopy. The unit of frequency, s-1 ("per second"), is known

as hertz (Hz). This unit is sometimes convenient for very low energy transitions, such as in

nuclear magnetic resonance (NMR) spectroscopy. The wavelength range of optical

spectroscopy extends from 200 nm (UV) to 500 μm (FIR). It is impossible to build one

single spectral instrument capable of covering the region completely and providing

information about the different processes of absorption, emission and scattering of light [2].

Light sources, detectors and other optical components have limited operational ranges,

caused by the underlying physical work principles. The choice of the appropriate instrument

type depends on the application. The interaction process of light with the material and the

spectral interval of interest have to be taken into account. Traditionally, spectrometers for

absorption measurements are optimized for ultraviolet/visible (UV/VIS) (175-700 nm), near-

infrared (NIR) (0.8-2.5μm), mid-infrared (MIR) (2.5-25 μm) and far-infrared (FIR) (25-1000

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μm) ranges. In general, an absorption spectrum is obtained by recording the amount of

radiation absorbed by the sample as a function of frequency or wavelength of the incident

radiation. Each type of spectroscopy focuses upon a specific region of the electromagnetic

spectrum (Fig.5.2). Based on these requirements it is primarily interested with (MIR) (4000 -

200 cm-1) and ultraviolet-visible (UV) (175-700 nm) spectroscopies, since the inorganic

semiconductor nanoarchitechtures synthesized in the present work responds well in these

regions.

Fig.5.2 The schematic overview of electromagnetic spectrum [1].

5.2 Principle of Fourier transform infrared (FTIR) spectroscopy:

Processes of change, including those of vibration and rotation associated with IR

spectroscopy, can be represented in terms of quantized discrete energy levels E0, E1, E2, etc.,

as shown in Fig.5.3 [3]. Each atom or molecule in a system must exist in one or other of

these levels. In a large assembly of molecules, there will be a distribution of all atoms or

molecules among these various energy levels. The latter are a function of an integer (the

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Fig.5.3 Illustration of quantized discrete energy levels.

quantum number) and a parameter associated with the particular atomic or molecular process

associated with that state. Whenever a molecule interacts with radiation, a quantum of

energy (or photon) is either emitted or absorbed and this phenomenon is explained in section

5.1. In each case, the energy of the quantum of radiation must exactly fit the energy gap E1 −

E0 or E2 − E1, etc. The energy of the quantum is related to the frequency by the following:

ΔE = hν (1)

Hence, the frequency of emission or absorption of radiation for a transition between the

energy states E0 and E1 is given by:

ν = (E1 − E0)/h (2)

Associated with the uptake of energy of quantized absorption is some deactivation

mechanism whereby the atom or molecule returns to its original state. Associated with the

loss of energy by emission of a quantum of energy or photon is some prior excitation

mechanism. Both of these associated mechanisms are represented by the dotted lines in

Fig.5.3. Generally, the infrared bands for inorganic materials are broader, fewer in number

and appear at lower wave numbers than those observed for organic materials. If an inorganic

compound forms covalent bonds within an ion, it can produce a characteristic infrared

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spectrum. IR spectroscopy is therefore a very powerful technique which provides fingerprint

information on the chemical composition of the sample. In spectroscopy, it is essential to

know which frequencies are absorbed and which are not. This requires that the radiation

source covers a broad spectral range and the individual frequencies of the radiation are

analyzed.

FTIR spectrometers cannot be built as double-beam instruments [2]. FTIR

spectrometers acquire single channel spectra of sample and reference and their ratio is

calculated afterwards (Fig.5.4). Sample and reference may automatically be replaced by a

sample slider, or the IR beam may be switched between sample and reference by flip-mirrors.

In the case of higher accumulation numbers, the instrument switches repeatedly between

sample and reference scan. The heart of any FT-IR spectrometer is an interferometer. The

Michelson interferometer consists basically of a beam splitter and two flat mirrors. One of

the mirrors is fixed in one interferometer arm; the other mirror is movable in the second

interferometer arm. Most common MIR beam splitters are made of KBr with a multilayer

coating. The beam splitter should have a reflectivity of 50% and no absorption across its

range of use. The functionality of a Michelson interferometer is based on a collimated IR

beam. The latter is directed to the beam splitter, which divides the beam into two parts of

equal intensity (in the ideal case). The divided beams are reflected, by the fixed and the

movable mirrors, back to the beam splitter, where they recombine and interfere. The

displacement of the movable mirror causes changes in the optical path length between the

two beams, so that the conditions for constructive and destructive interference, as well as all

intermediate states between the two, are consecutively met. The recombined IR beam passes

the sample (or the reference) and reaches the detector. The position and movement of the

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Fig.5.4 Showing a simple FTIR spectrophotometer layout.

intermediate states between the two, are consecutively met. The recombined IR beam passes

the sample (or the reference) and reaches the detector. The position and movement of the

movable mirror are controlled by a helium-neon laser (λHeNe=632.8 nm). The interferogram of

the helium-neon laser is used to control the sampling of the IR interferograms in steps down to

λHeNe/2=316.4 nm. The mathematical procedure, which is employed to convert the IR

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interferogram (intensity versus time, also called time domain) to an IR spectrum (intensity

versus frequency, also called frequency domain), is called Fourier transformation. Sample and

reference interferograms are separately transformed. Afterwards, the ratio of both is

automatically calculated and displayed as instrument-independent IR transmission spectrum.

5.3 Principle of diffuse reflectance UV-Vis (DRUV) spectroscopy:

Light incident at optically scattering interfaces (inhomogeneous samples like

powders) with roughness down to the range of the wavelength may be partly reflected

regularly, partly scattered diffusely, and partly enter the substrate [2]. The latter part may

undergo absorption within particles, undergo diffraction at grain boundaries, re-emerge at the

sample surface and intermingle with reflected parts. The measured reflectivity includes

contributions from all mechanisms, see Fig. 5.5. When the dimensions of the particle are

Fig.5.5 Schematic illustration of light trajectories in a scattering sample.

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small compared with the beam cross section but large relative to the light wavelength,

diffraction phenomena also occur because rays striking the crystal and passing by it result in

interferences among elementary waves [4]. In powders of randomly oriented particles of

such size, part of the incident light goes back at all angles into the hemisphere of provenance

of the light. The phenomenon resulting from the reflection, refraction, diffraction, and

absorption by particles oriented in all directions is called diffuse (or volume) reflection, in

contrast with regular (or directional) reflection from a plane phase boundary.

In a DRUV spectrum, the ratio of the light scattered from an infinitely thick layer and

the scattered light from an ideal non-absorbing reference sample is measured as a function of

the wavelength λ [5]. At present, barium sulfate is considered as suitable standard which has

an absolute reflectance of 0.973 to 0.988 in the 380 to 750 nm wavelength range. The

illumination of powdered samples by incident radiation leads to diffuse illumination of the

samples. The incident light is partially absorbed, partially scattered. The scattered radiation,

emanating from the sample is collected in an integration sphere and detected. This is

schematically illustrated in Fig.5.6. The basic equation for the phenomenological description

of diffuse reflection is the radiation transfer equation:

���

�ρ� = I−

"

� (3)

where I is the incident light intensity of a given wavelength; dI/dS the change of the intensity

with the pathlength dS; ρ the density of the medium; k an attenuation coefficient

corresponding with the total radiation loss due to absorption and scattering; j is the scattering

function. Eq. (3) can be solved by introducing simplifications which are related with easily

attainable experimental conditions. These ideas, first suggested by Schuster and later on

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Fig.5.6 Schematic overview of a diffuse reflectance spectrophotometer with integration

sphere.

further developed by Kubelka and Munk, simplify the solution of the radiative transfer Eq.

(3), known as the Schuster-Kubelka-Munk (S-K-M) theory. In this theory, the incident and

scattered light flux are approximated by two fluxes I and J perpendicular to the surface of the

powdered sample, but in the opposite direction. This is illustrated in Fig.5.7. I is the flux of

Fig.5.7 The Schuster-Kubelka-Munk approximation in diffuse reflectance spectroscopy.

The incident and remitted light fluxes are approximated by two opposite fluxes,

perpendicular to the surface of the infinitely thick sample layer.

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monochromatic diffuse illumination, whereas J is the flux of diffusively scattered light. If

the sample is infinitely thick, the diffuse reflection of the sample (R1) is related to an

apparent absorption (K) and apparent scattering coefficient (S) via the Schuster-Kubelka-

Munk (S-K-M) or Kubelka-Munk (K-M) function:

s

k

2R

)R(1)F(R

2

=−

=

∝ (4)

Where F(R∞) is usually termed the remission or Kubelka–Munk (K–M) function, K and S are

the absorption and scattering coefficient of the sample, respectively. The bandgap can be

obtained from the plots of [F(R∞)hυ]1/2 versus hυ, as the intercept of the extrapolated linear

part of the plot at [F(R∞)hυ]1/2 = 0, assuming that the absorption coefficient α is proportional

to the Kubelka–Munk function F(R∞). Eq. (4) is valid under the following conditions:

1. diffuse monochromatic irradiation of the powdered sample;

2. isotropic light scattering;

3. an infinite layer thickness;

4. a low concentration of powders;

5. a uniform distribution of powders;

6. absence of fluorescence.

5.4 FTIR analysis:

KBr discs were prepared by pressing the powdered sample into a wafer between 0.1

and 0.25 mm thick. The samples were finely ground and mixed with dry KBr powder in the

ratio 1:10. Grinding and mixing was done with an agate mortar and pestle. The mixture was

then pressed into a transparent disc in a die for 2 min at a pressure of 3 tons. The disc was

fed directly to a sample holder and the transmittance spectrum was recorded in the

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transmittance mode using a Fourier transform infrared spectrophotometer (FTIR, Perkin

Elmer Spectrum Two), between the spectral range 350-4000 cm-1. Characteristic absorption

bands and the surface absorbed residues can be identified from the transmittance spectrum.

5.4.1 FTIR spectra of glycine assisted α-Fe2O3 nanoparticles:

Vibrational spectra of hematite nanoparticles examined by FTIR spectroscopy in the

frequency range 350–800 cm−1 are shown in Fig.5.8. The two strong distinct absorption

bands appeared at 560 and 475 cm−1 of G1 are ascribed to the perpendicular modes of Fe-O

stretching vibrations in corundum structure [6]. It is interesting to note that, with reduction

of particle size the peaks at 560 and 475 cm−1 showed a systematic red shift toward lower

frequency region, as marked by double arrows in the figure and this shift can be ascribed to

the strong depolarization field effect along c-axis [7]. Moreover the vibration modes at 377,

369 and 363 cm−1 merges as the size declines. It is well known that hematite lattice has six

infrared active modes, in which two modes are associated with the vibrations parallel to c-

axis and other four modes are perpendicular to c-axis. It is concluded that vibration bands in

the frequency range 350–800 cm−1confirm the hexagonal phase of α-Fe2O3. In order to

confirm the formation of α-Fe2O3 nanoparticles several research groups have analyzed the

FTIR spectra in the MIR region. For instance, G. K. Pradhan et al. [8] observed Fe-O

vibrational bands in the range 464-468 cm-1, which assured the hematite phase. X. Hu et al.

[9] identified strong absorption bands in the range 400 to 800 cm-1 and attributed them to the

characteristic lattice vibrations of the hematite phase. R. Ramesh et al. [7] noticed absorption

bands in the range 400-750 cm-1 which represented the Fe-O vibration mode of α-Fe2O3.

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Fig.5.8 Showing the vibrational bands of glycine assisted α-Fe2O3 samples G1-G5.

5.4.2 FTIR spectra of α-Fe2O3/SnO2 SNH’s:

FTIR spectra of the samples (S1-S4) recorded in the region 400–1200 cm−1 are shown

in Fig.5.9. In S1, two broad peaks centered at 450 and 576 cm−1 are assigned to stretching

vibrations of Fe3+–O2− bond in the FeO6 octahedron and FeO4 tetrahedron structures [10].

With the addition of SnO2 (S2), the width of the broad peak centered at 576 cm−1 decreases

slightly. In S3, the broad peaks of α-Fe2O3 collapse slightly and some minor peaks pertaining

to SnO2 appears in the region 400–500 cm−1, as shown in the inset. This is a signature for

the presence of SnO2 and the formation of SNH’s. In S4, the peaks of α-Fe2O3 completely

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Fig.5.9 Showing the vibrational bands of α-Fe2O3/SnO2 SNH’s samples S1-S4.

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disappeared and three peaks corresponding to SnO2 appeared at 500, 675 and 832 cm−1. In

addition to that, number of minor peaks appeared in the region 400–550 cm−1, as shown in

the inset. The above three peaks along with the minor peaks are assigned to Sn-O stretching

vibrations of SnO2 [11]. Thus the FTIR results clearly verify the formation of SNH’s and

they are consistent with XRD and HRTEM results as discussed in chapter III & IV.

5.4.3 FTIR spectra of α-Fe2O3/graphene NC’s:

The Fourier transform infrared spectroscopy (FTIR) transmission spectra of the

samples N1-N4 are shown in Fig.5.10. In the sample N1 the peak located at 1635 cm-1

resulted from the skeletal vibration of benzene ring in graphene, while the peaks observed at

555 and 460 cm-1 could be assigned to the stretching vibration of Fe-O bonds of α-Fe2O3

[8,12-14]. The peak centred at 912 cm-1 is assigned to Fe-O-C bond formed during annealing

process. In N2 three weak peaks at 1639, 1306 and 915 cm-1 are assigned to vibrations of

benzene ring, C-OH groups stretching and Fe-O-C bond respectively. The other two peaks at

566 and 454 cm-1 are assigned to Fe-O stretching vibrations of α-Fe2O3. In N3 two bands

appeared at 1603 and 912 cm-1 are assigned to skeletal vibrations of benzene ring and Fe-O-

C bonds respectively, while the peaks centred at 544 and 444 cm-1 are identified as Fe-O

bonds of α-Fe2O3. In N4 three bands identified at 1646, 1495 and 1051 cm-1 are assigned to

vibrations of benzene ring, COO- stretching and C-O-C bonds [15], while the other two

strong peaks centred at 566 and 430 cm-1 are located as Fe-O bonds in α-Fe2O3. These

observations reveal that the chemical bonds were firmly built between graphene and α-Fe2O3.

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Fig.5.10 Showing the vibrational bands of α-Fe2O3/graphene NC’s samples N1-N4.

5.5 Diffuse reflectance analysis:

Reflectance spectrum was acquired with the assistance of a diffuse reflectance UV–

vis spectrophotometer (Shimadzu UV-2700) in the wavelength range 220-850 nm. The beam

passes through a slit width of 5.0 nm and the spectrum was recorded in the reflectance mode.

Prior to the measurement, the sample and BaSO4 powder were mixed thoroughly by grinding

them with a pestle in a mortar for 2 min. BaSO4 was used as a reference and the mixture was

taken in the ratio 1:10. The resulting powder was pressed into the sample holder hole by a

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thin glass sheet. The sample holder was placed into the sample port, and the spectrum was

recorded.

5.5.1 DRUV spectra of glycine assisted α-Fe2O3 nanoparticles:

Diffuse reflectance spectroscopy in the ultraviolet and visible region is, in principle,

the most versatile spectroscopic technique, as both d-d and charge transfer (CT) transitions

can be probed [16]. The optical absorption properties of the α-Fe2O3 nanostructures were

investigated at room temperature by the DRUV spectra and such absorption is related to the

shape and size of the samples [17]. The reflectance spectra are analyzed using Kubelka–

Munk formalism [18] to determine the band gap energies of α-Fe2O3 nanoparticles.

Reflectance is converted to equivalent absorption coefficient, proportional to the Kubelka–

Munk function F(R∞), given by the equation F(R∞) = (1 − R∞)2/2R∞= K/S. The optical band

gaps are obtained from the intercept of extrapolated linear fit of experimental data by a plot

of [F(R∞)hυ]1/2versus incident photon energy. Fig.5.11 displays the absorption spectra of α-

Fe2O3 nanoparticles, while Fig.5.12 depicts the band gap energies of the samples G1-G5.

With size reduction, the absorption band edge shifts toward the low wavelength region,

indicating a clear blue shift from G1-G3. This increases the optical band gap and the values

of G1-G3 are 1.775(3), 1.889(2) and 1.959(1) respectively. However, for samples G4 and G5

the band gap slightly reduces and the values are 1.949(2) and 1.936(2) eV. The enlargement

of band gap with size reduction can be ascribed to the Burstein-Moss effect which is a crucial

phenomenon in n-type semiconductors [19]. Kennedy et al. [20] have obtained an indirect

band gap of 1.9–2.1 eV by Tauc analysis. Experiments have shown that band gap varies with

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crystallite size and methods of preparation of α-Fe2O3 [21–23]. In the present case, except

G1 all other band gap values are consistent with previous reports. It is believed that the low

Fig.5.11 Displaying the absorption spectra of α-Fe2O3 nanoparticles prepared using

glycine.

band gap of G1 could be possibly due to the bimodal particle size distribution (as evident

from TEM and VSM) formed due to less glycine used in the synthesis. Also in the

absorbance spectra, the intensity of sub-band gap scattering tail from 600 to 850 nm

increases as the size of crystallite increases [17]. Moreover an increase in absorbance with

decline in size occurs at 561, 538, 530, 526 and 518 nm for G1, G2, G3, G4 and G5,

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respectively. It is known that transitions at 535 and 375 nm can be ascribed to ligand field

transition (d–d transition) and ligand-to-metal charge transfer respectively [16]. It is

Fig.5.12 Displaying the band gap energies of α-Fe2O3 nanoparticles prepared using

glycine.

observed that ligand field transition shifts toward the red end of visible spectrum from 529

nm to 564 nm whereas, ligand-to-metal charge transfer is blue shifted from 386 nm to 354

nm as the crystallite size increases. A similar red shift with increase in crystallite size is

reported in α-Fe2O3/SiO2nanomaterials [24]. The enhancement in red shift of the ligand field

transition with size toward longer wavelength region is ascribed to photonic crystal effect, as

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the intrinsically enhanced scattering for large particles was overcome by the photon

localization [24]. This kind of phenomena generally occurs when there is a strong magnetic

coupling between the neighboring Fe3+ cations [25] as discussed in chapter IV.

5.5.2 DRUV spectra of α-Fe2O3/SnO2 SNH’s:

In the case of α-Fe2O3/SnO2 heterostructure the absorption edge should be the

combined contribution of the core and shell. The band gap varies significantly by altering

the core/shell compositions [26-33] and it can be studied by diffuse reflectance UV-Vis

spectroscopy (DRUV). The absorption spectra of the samples S1-S4 are shown in Fig.5.13.

Kubelka–Munk function [18], F(R∞) = (1-R∞)2/2R∞ is used to determine the band gap by

analyzing the DRUV data. The reflectance data are converted to equivalent absorption

coefficient, proportional to the Kubelka–Munk function, F(R∞). The band gap values of S1-

S4 are 1.862(2), 1.9640(6), 1.967(1) and 1.9931(7) eV respectively. In Fig.5.13, it can be

seen that, after coupling SnO2 shells on the surface of the α-Fe2O3 cores, and when the wt.

ratio increases, the absorption band edge shifts toward the blue wavelength region of the

absorption spectrum. This enlarges the band gap energies from 1.862(2) to 1.9931(7) eV as

shown in Fig.5.14. These results are consistent with the lattice mismatch values obtained

from the XRD results as discussed in chapter III. This can be explained by the interactive

strain between the core and shell that alters the optical properties [34]. Strain effect is caused

by the variation in lattice parameter values of SnO2 (a, b = 4.7373 Å, c = 3.1864 Å), smaller

than those of α-Fe2O3 (a, b = 5.0334 Å, c = 13.7458 Å). As a result lattice mismatch occurs,

where the core is subjected to compressive strain, while shell experiences tensile strain.

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From the XRD results, shown in Table 1 of chapter III, compressive strain increases with

increase of SnO2 wt. ratio, thereby enlarging the band gap slightly (weak blue shift) from

Fig.5.13 Displaying the absorption spectra of α-Fe2O3/SnO2 SNH’s.

1.9640(6) (S2) to 1.967(1) (S3). However, when the compressive strain decreases slightly

(S4), the band gap gets blue shifted to 1.9931(7) eV. According to Bao et al. [35], the reason

for blue shift can be explained as follows. As the SNH’s are excited with UV-light, electrons

and holes are spatially separated across the interface, bends the band and modifies the

electron and hole energy levels via stark effect. This leads to the weak blue shift of the

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samples S2 and S3. At high SnO2 wt. ratio (S4), photoexcited electrons and holes occupy the

higher energy sub bands and a band filling effect takes place. This is responsible for the

Fig.5.14 Displaying the band gap energies of α-Fe2O3/SnO2 SNH’s.

blue shift from S3 to S4. Another possible reason for the blue shift is the antiferromagnetic

ordering in the samples, which can be interpreted from ZFC curves of the samples, discussed

in chapter VI. With increase of SnO2 wt. ratio, the Morin transition temperature increases,

which increase the magnetic ordering, thereby increase the band gap energies. It is

concluded that the enlargement of band gap energies is due the combined effects of

compressive strain of the core and magnetic ordering.

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5.5.3 DRUV spectra of α-Fe2O3/graphene NC’s:

Band gap of the samples N1-N4 are studied by diffuse reflectance spectroscopy UV-

Vis (DRUV). The absorption spectra of the samples N1-N4 are shown in Fig.5.15. Kubelka–

Munk function [18], F(R∞) = (1- R∞)2/2R∞ is used to determine the band gap by analyzing the

DRUV data. The reflectance data are converted to equivalent absorption coefficient,

proportional to the Kubelka–Munk function, F(R∞). It is interesting to note that, after

anchoring α-Fe2O3 ND’s on the surface of GN’s the absorption band edge shift towards the

Fig.5.15 Displaying the absorption spectra of α-Fe2O3/graphene NC’s.

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higher wavelength region indicating a clear red shift. The bandgap energies of N1, N2, N3

and N4 are found to be 1.74(2), 1.67(3), 1.63(3) and 1.47(5) respectively, as shown in

Fig.5.16. As evidenced from the band-gap energy estimation of prepared NC’s, the

introduction of GN’s affect the optical absorption property of iron oxide and its presence

shifts the absorption edge of all samples toward the red region. Very recently G. Pradhan

et.al [33] fabricated α-Fe2O3/graphene nanocomposite and found that the absorption edge is

larger when α-Fe2O3 was modified with graphene. Similar kind of band edge shift is also

Fig.5.16 Displaying the band gap energies of α-Fe2O3/graphene NC’s.

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noticed by F. Meng et al. [13]. The reduction of of band gap with graphene composition can

be ascribed to the presence of blackbody properties of GN’s [33]. These interpretations also

suggest that the presence of GN’s modifies the fundamental process of electron-hole pair

formation of α-Fe2O3 ND’s by increasing its surface electric charge during the photochemical

process. The absorption is characterized by a sub band gap scattering tail [17] of 600-850

nm which increases the intensity with graphene composition. Transitions at 535 and 375 nm

have been previously assigned to a ligand field and a ligand-to-metal charge transfer

transitions, respectively [16]. Interestingly, both ligand field and ligand-to-metal charge

transfer transitions are red-shifted in all the samples to higher wavelength region when the

composition of GN’s increases. These observations further reveal that GN’s has strong

influence towards the optical properties of NC’s. Another possible reason for the red shift in

the absorption spectra is the antiferromagnetic ordering in the samples, which can be

interpreted from ZFC curves of the samples as discussed in chapter VI. With increase of

GN’s composition, the Morin transition temperature increases, which increase the magnetic

ordering, thereby reduces the band gap energies.

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5.6 Conclusions:

FTIR and DRUV spectroscopic studies have been carried out for the

nanoarchitectures by means of FTIR and DRUV spectrophotometers. For glycine assisted α-

Fe2O3 nanoparticles the characteristic absorption bands shifted towards low frequency region

with size reduction. DRUV studies showed that the band gap enlarges with size reduction

due to Burstein-Moss effect. In α-Fe2O3 /SnO2 SNH’s the broad peaks of α-Fe2O3 collapses

and some minor peaks pertaining to SnO2 appears in the FTIR spectra when the wt. ratio of

SnO2 increases, thus confirms the formation of SNH’s. A clear blue shift was also noticed in

the absorption spectra and reveals that the band gap enlarges with SnO2 wt. ratio. In α-Fe2O3

/graphene NC’s the vibrational bands pertaining to α-Fe2O3 and graphene were observed in

all the NC’s and ascertains the composite formation. The absorption band edge shifted

towards the red region and indicates that the band gap reduces with graphene composition.

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References:

[1] J. McMurry and R. C. Fay, Chemistry, Prentice Hall: Englewood Cliffs, 1995.

[2] G. Gauglitz and T. Vo-Dinh, Handbook of Spectroscopy, WILEY-VCH Verlag,

Weinheim, 2003.

[3] B. Stuart, Infrared Spectroscopy: Fundamentals and Applications, John Wiley & Sons,

2004.

[4] J. Torrent and V. Barron, Methods of Soil Analysis. Part 5. Mineralogical Methods, Soil

Science Society of America, USA, 2008.

[5] B. M. Weckhuysen and R. A. Schoonheydt, Catal. Today, 49 (1999) 441-451.

[6] S. Hayashi and H. Kanamori, J. Phys. C, 13 (1980) 1529.

[7] R. Ramesh, K. Ashok, G. M. Bhalero, S. Ponnusamy and C. Muthamizhchelvan, Cryst.

Res. Technol., 45 (2010) 965–968.

[8] G. K. Pradhan and K. M. Parida, ACS Appl. Mater. Interfaces, 3 (2011) 317–323.

[9] X. Hu and J. C. Yu, Adv. Funct. Mater., 18 (2008) 880–887.

[10] G. Xia, N. Li, D. Li, R. Liu, C. Wang, Q. Li, X. Lu, J. S. Spendelow, J. Zhang and G.

Wu, ACS Appl. Mater. Interfaces, 5 (2013) 5 8607−8614.

[11] X. Xu, J. Zhuang and X. Wang, J. Am. Chem. Soc., 130 (2008) 12527.

[12] W. Xiao, Z. Wang, H. Guo, Y. Zhang, Q. Zhang and L. Gan, J. Alloys Compds., 560

(2013) 208–214.

[13] F. Meng, J. Li, S. K. Cushing, J. Bright, M. Zhi, J. D. Rowley, Z. Hong, A. Manivannan,

A. D. Bristow and N. Wu, ACS Catal., 3 ( 2013) 746-751.

[14] X. Pan, Y. Zhao, S. Liu, C. L. Korzeniewski, S. Wang and Z. Fan, ACS Appl. Mater.

Interfaces, 4 (2012) 3944−3950.

Page 28: 5.2 Principle of Fourier transform infrared (FTIR ...shodhganga.inflibnet.ac.in/bitstream/10603/93513/10/10_chapter5.pdf · 5.2 Principle of Fourier transform infrared (FTIR) spectroscopy:

146 | P a g e

[15] H. Guo, X. Wang, Q. Qian, F. Wang and X. Xia, ACS Nano, 3 (2009) 2653–2659.

[16] L. A. Marusak, R. Messier and W. B. White, J. Phys. Chem. Solids, 41 (1980) 981.

[17] K. Sivula, R. Zboril, F. L. Formal, R. Robert, A. Weidenkaff, J. Tucek and M. Gratzel,

J. Am. Chem. Soc., 132 (2010) 7436.

[18] P. Kubelka and F. Munk, Z. Tech. Phys., 12 (1931) 593.

[19] Y. H. Yang, X. Y. Chen, Y. Feng and G. W. Yang, Nano Lett., 7 (2007) 3874.

[20] J. H. Kennedy and K. W. Frese, J. Electrochem. Soc., 125 (1978) 709.

[21] A. A. Akl, Appl. Surf. Sci., 233 (2004) 307.

[22] N. Ozer, F. Tepehan and G. Tapehan, Proc. SPIE Int. Soc. Opt. Eng., 3138 (1997) 9.

[23] L. Vayssieres, C. Sathe, S.M. Butorin, D. K. Shuh, J. Nordgren and J. Guo, Adv. Mater.,

17 (2005) 2320.

[24] K. Cheng, Y. P. He, Y. M. Miao, B. S. Zou, Y. G. Wang, T. H. Wang, X. T. Zhang and

Z. L. Du, J. Phys. Chem. B, 110 (2006) 7259.

[25] H. M. Fan, G. J. You, Y. Li, Z. Zheng, H. R. Tan, Z. X. Shen, S. H. Tang and Y. P.

Feng, J. Phys. Chem. C, 113 (2009) 9928.

[26] Y. Shaogui, Q. Xie, L. Xinyong, L. Yazi, C. Shuo and C. Guohua, Phys. Chem. Chem.

Phys., 6 (2004) 659–664.

[27] C. Karunakaran, S. Dasan, S. Raadha, P. Gomathisankar and P. Vinayagamoorthy, RSC

Adv., 3 (2013) 16728–16738.

[28] Y. Shi, H. Li, L. Wang, W. Shen and H. Chen, ACS Appl. Mater. Interfaces, 4 (2012)

4800−4806.

[29] Y. Xia and L. Yin, Phys. Chem. Chem. Phys., 15 (2013) 18627-18634.

Page 29: 5.2 Principle of Fourier transform infrared (FTIR ...shodhganga.inflibnet.ac.in/bitstream/10603/93513/10/10_chapter5.pdf · 5.2 Principle of Fourier transform infrared (FTIR) spectroscopy:

147 | P a g e

[30] W. Chiu, P. Khiew, M. Cloke, D. Isa, H. Lim, T. Tan, N. Huang, S. Radiman, R.

Shukor, M. Azmi Abd. Hamid and C. Chia, J. Phys. Chem. C, 114 ( 2010) 8212–8218.

[31] M. Tamez Uddin, Y. Nicolas, C. Olivier, T. Toupance, L. Servant, M. M. Muller, H.

Kleebe, J. Ziegler and W. Jaegermann, Inorg. Chem., 51 (2012) 7764−7773.

[32] L. Zheng, Y. Zheng, C. Chen, Y. Zhan, X. Lin, Q. Zheng, K. Wei and J. Zhu, Inorg.

Chem. 48 (2009) 1819-1825.

[33] G. K. Pradhan, D. K. Padhi and K. M. Parida, ACS Appl. Mater. Interfaces, 5 (2013)

9101-9110.

[34] W. Chiu, P. Khiew, M. Cloke, D. Isa, H. Lim, T. Tan, N. Huang, S. Radiman, R.

Shukor, M. Hamid and C. Chia, J. Phys. Chem. C, 114 (2010) 8212.

[35] J. Bao, D. Bell and F. Capasso, Nano lett., 8 (2008) 836.