Synthesis of biogenic hematite (α-Fe₂O₃) nanoparticles for antibacterial and nanofluid applications

Abstract

The use of biological products such as microorganisms, plant extracts or plant biomass is a better alternative to chemical and physical methods for the engineering of metal oxide nanoparticles through an environmentally benign route. Hematite (α-Fe₂O₃) nanoparticles have acquired significant attention from researchers for being the most stable iron oxide in air under ambient conditions. Further, they are also known for their extensive applications in diverse fields. In the present work, hematite (α-Fe₂O₃) nanoparticles have been synthesized by the sole use of the extract of guava (Psidium guajava) leaves. The synthesized material has been studied by X-ray diffraction (XRD), UV-visible spectroscopy, Fourier transform infrared (FTIR) spectroscopy, Vibrating Sample Magnetometry (VSM), Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM) techniques. The average diameter of α-Fe₂O₃ nanoparticles is observed to be about 34 nm. Absorption studies of the sample from UV to near IR regions show four absorption bands at 347 nm, 543 nm, 652 nm and 849 nm. The photoluminescence (PL) spectrum shows band edge emission at 688 nm. The FTIR spectrum reveals the role of biomolecules present in the extract in capping the nanoparticles. The VSM study shows the weak ferromagnetic nature of the synthesized nanoparticles. The antibacterial activities of the synthesized nanoparticles against Gram-positive and Gram-negative bacteria have been ascertained through an agar-well diffusion method. Further, the nanoparticles show enhancement in thermal conductivity for the base fluids water and ethylene glycol. The bioefficacy and thermal conductivity enhancement exhibited by the as synthesized nanoparticles may lead to their possible applications in environmental and industrial fields.

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1 Introduction

In recent years, studies on the synthesis of different types of transition metal oxide nanostructures with diverse morphologies have attracted a great deal of attention from researchers due to their unique optical, electrical and magnetic properties. The improved physical and chemical properties of nanostructured transition metal oxides originates owing to factors such as large surface to volume ratio, spatial confinement, reduced dimensions and imperfections in the crystallinity.^1,2 Among the various metal oxide nanomaterials, magnetic nanoparticles have attracted a surge in interest due to their promising applications in drug delivery, hyperthermia treatment, bio-sensors and bio-electronics.^3–7 Different forms of iron oxides (FeO, Fe₂O₃ and Fe₃O₄) in different phases (α-Fe₂O₃, β-Fe₂O₃, γ-Fe₂O₃ and ε-Fe₂O₃) have numerous fundamental, technological and medical applications.^8–11

Due to their abundance, low cost, low toxicity, excellent chemical stability and tunable optical and magnetic properties, α-Fe₂O₃ (hematite) nanoparticles have attracted considerable attention in catalytic reactions, paint manufacturing, lithium–iron batteries,^12,13 gas sensors,¹⁴ biomedical applications,¹⁵ magnetic storage devices¹⁶ and photoelectron chemical splitting of water.¹⁷ Several synthesis techniques for α-Fe₂O₃ nanoparticles with controlled size and shape have been reported including liquid-phase synthesis methods such as hydro-thermal,¹⁸ solvo-thermal,¹⁹ sol–gel²⁰ routes, gas-phase deposition methods,²¹ thermal oxidation and pyrolysis approaches²² and electro-chemical methods.^23,24 α-Fe₂O₃ nanoparticles with diverse morphologies including nanowires,²⁵ nanotubes,²⁶ hollow spheres²⁷ and nano flowers²⁸ can be fabricated via liquid-phase methods. Due to their unique advantages including requirement of a simple equipment, high yield, simplicity of operation and ease of control, liquid-phase methods are widely used for the synthesis of α-Fe₂O₃ nanoparticles.

Darezereshki et al.²⁹ successfully synthesized crystalline α-Fe₂O₃ nanoparticles by direct thermal decomposition of γ-Fe₂O₃ (maghemite) nanoparticles. Al-Gaashani et al.³⁰ reported the synthesis of α-Fe₂O₃ nanostructures with various morphologies via thermal decomposition of iron(III) nitrate 9-hydrate and their optical behavior. Zhang et al.³¹ elucidated the shape dependent optical and magnetic properties of α-Fe₂O₃ nanoparticles by hydrothermal and solvothermal synthesis of spindle, ellipsoid, spherical & quasi-cubic structures. Tailoring of optical band gap and magnetic properties such as coercivity, saturation magnetization and remanence of α-Fe₂O₃ nanoparticles by pulse laser ablation in different aqueous media has been reported by Pandey et al.³² However chemical synthesis routes often involve the utilization of toxic or expensive chemicals and templates and hence the prospect of exploiting natural resources for their synthesis has become competent and environmentally benign. The preparation of highly crystalline and highly mesoporous α-Fe₂O₃ nanoparticles by a simple and one step hydrothermal method using the extract of green tea leaves has been reported by Ahmmad et al.³³

The present work emphasizes a simple method for the synthesis of α-Fe₂O₃ nanoparticles using Psidium guajava (P. guajava) leaf extract. P. guajava is an important food crop and medicinal plant in tropical and subtropical countries which is widely used in folk medicine around the world. Many pharmacological studies have demonstrated the ability of the leaves of this plant to exhibit antioxidant, anti-allergic, antimicrobial, antiplasmodial, cytotoxic, cardioactive, anticough and antidiabetic activities supporting its traditional uses.^34–36 The leaves contain essential oils composed of α-pinene, β-pinene, limonene, menthol, terpinyl acetate, isopropyl alcohol, longicyclone, flavonoids and saponins.^34,37

In the aqueous synthesis of hematite nanoparticles, researchers usually follow chemical precipitation method in which precipitating agents like sodium hydroxide⁹ and ammonium hydroxide²⁹ are added. In addition to this, complicated heat treatment processes with the aid of Teflon-lined autoclave^31,33 are common in the synthesis of hematite nanoparticles. In this context, the current work is quite novel because it does not require additional precipitating agents and autoclaving process. In addition, this method yields environmentally benign α-Fe₂O₃ nanoparticles.

Microbial contamination of food products and emergence of infectious diseases is a matter of serious concern. Thus there is an urgent demand to develop effective antimicrobial agents to eliminate the pathogens and control their spread. Metal based nanoparticles have been widely used as antimicrobial agents because of their supreme abilities for biological functionalization. Various metal oxide nanoparticles in different forms such as powders, coated on cellulose fibres or as part of organic or inorganic nanocomposites have been successfully developed for inactivating a wide range of Gram-positive as well as Gram-negative bacteria.^38,39 The present work includes the study of antibacterial activity of synthesized α-Fe₂O₃ nanoparticles against certain selected pathogens. Application of hematite nanoparticles in enhancing the thermal conductivity of ethylene glycol and water at room temperature is also a novelty of the present work to the best of our knowledge. The synthesized nanoparticles are environmentally benign, without considerable variation in already reported optical and magnetic characteristics which can find applications in preventing bacterial growth. The ability of the material to enhance thermal conductivity may find application in heat transfer systems such as coolants. The catalytic efficacy of the material in the photo degradation of dyes is to be tested for environmental and industrial applications.

2 Materials and methods

Deionized water has been used as the solvent throughout the synthesis. Anhydrous iron(III) chloride (FeCl₃ (>97%)) was procured from Sigma-Aldrich. P. guajava leaves collected from the botanical garden of Mar Ivanios College were used for the study. All the glasswares were washed using aqua regia.

2.1 Preparation of the extract

10 g of healthy leaves are boiled in 100 mL of de-ionized water for about 2 min. The yellow coloured extract is filtered out and cooled to room temperature and has been used in further experiments.

2.2 Synthesis of α-Fe₂O₃ nanoparticles

10 mL of 0.01 M solution of FeCl₃ is prepared and stirred well for 10 min using a magnetic stirrer. The precursor solution is pale yellow in colour. After uniform stirring the solution is boiled for 2 min and to the boiling solution 5 mL of P. guajava leaf extract is added under constant stirring. The solution turns deep brown on the addition of the extract with the ultimate formation of a brownish precipitate. The solution is centrifuged at 10 000 rpm for 10 min and the precipitate is collected. The precipitate is washed several times with deionized water followed by acetone and dried under ambient conditions. Dried precipitate is powdered and annealed at 600 °C for 3 h to obtain deep red coloured α-Fe₂O₃ nanoparticles.

2.3 Characterization

X-ray diffraction is carried out by XPERT PRO diffractometer with Cu-Kα radiation (λ = 1.5406 Å) operating at 30 mA. Transmission Electron Microscope JEOL-JEM 2100 and Scanning Electron Microscope JEOL-JSM 6390LV are used for morphological studies. The optical absorptions by the sample in the ultraviolet, visible and near infrared regions are recorded with UV-Vis-NIR Spectrophotometer Varian Cary 5000. Fourier transform infrared spectra are obtained on IR Prsestige-21 Schimadzu Spectrophotometer. Perkin-Elmer Fluorescent Spectrometer (LF45) is used to record photoluminescence spectrum. Thermal analysis of the sample is carried out by Perkin Elmer Diamond TG/DTA analysis system. Vibrating Sample Magnetometer, Lakeshore VSM 7410 is used for the magnetic studies of the sample.

2.4 Antibacterial efficacy studies

Antibacterial activity of synthesized α-Fe₂O₃ nanoparticles against Gram-negative Escherichia coli (E. coli) and Gram-positive Staphylococcus aureus (S. aureus) is investigated by agar-well diffusion method.⁴⁰ The Mueller Hinton agar medium is prepared by dissolving 33.9 g of commercially obtainable Mueller–Hinton agar medium (Hi Medium) in 1000 mL of distilled water. The dissolved medium is autoclaved at 15 lbs pressure at 121 °C for 15 min. The autoclaved medium is mixed well and 20 mL is poured onto 100 mm Petri-plate. A nutrient broth is also prepared by dissolving 13 g of commercially available nutrient medium (Hi Medium) in 1000 mL distilled water and boiled. When it is dissolved completely, desired quantity of the medium is dispensed and sterilized by autoclaving at 15 lbs pressure and 121 °C for 15 min. The Petri-plates containing Mueller–Hinton agar medium are seeded with 24 hour old broth culture of respective bacterial stains. 10 mm sized wells are made into each Petri-plate using sterile cork borer. The synthesized nanoparticles are dispersed in dimethyl sulfoxide (DMSO) to obtain a uniform suspension with concentration of 1 mg mL⁻¹. Different quantities of the suspension (25, 50 and 100 μL) are added to the wells, incubated at 37 °C for 24 hours. Gentamycin (40 mg mL⁻¹) is used as the positive control. After the incubation period, the zone of inhibition of each well is measured for the eventual antibacterial activity.

2.5 Thermal conductivity measurements of nanofluids

α-Fe₂O₃/water and α-Fe₂O₃/Ethylene Glycol (EG) nanofluids are prepared by dispersing different amounts (0.005, 0.01, 0.015, 0.02 and 0.025 weight%) of synthesized nanoparticles in respective base fluids using an ultrasonication probe. Sonication is carried out for 20 min to obtain a homogeneous suspension. A cooling system maintained at (30 ± 1) °C is employed to avoid the temperature variations. The thermal conductivity of the nanofluids is measured using KD2 Pro instrument (Decagon, Pullman, WA, USA) which works based on the principle of transient hot wire (THW) method.⁴¹ A needle sensor with 1.3 mm diameter and 60 mm length is opted for the measurements, installed in a jacketed beaker, coupled to the cooling system. Nanofluids are placed into the jacketed beaker and their thermal conductivities are observed at a constant temperature.

3 Results and discussion

3.1 X-ray diffraction

The X-ray diffraction pattern of the synthesized product before and after annealing to determine their crystalline phase. Fig. 1(a) shows the XRD pattern of synthesized product before annealing. The diffraction peaks are less intense and broad which are indexed according to JCPDS-ICDD card number 89-0596. Only a few peaks of α-Fe₂O₃ are seen in the pattern which shows that the formation of hematite nanoparticles has not been completed. The crystal phase of the annealed product characterized by X-ray diffraction shows the pattern given in Fig. 1(b). The X-ray diffraction peaks are rather broad, indicating the nanocrystalline nature of the sample. All the intense peaks in the XRD pattern could be indexed with the JCPDS-ICDD card number 89-0596 corresponding to α-Fe₂O₃ with rhombohedral symmetry (space group: R3̄c (167)).⁴² The synthesized sample shows main characteristic peaks of α-Fe₂O₃ at 2θ values of 24.4°, 33.2°, 35.8°, 41.1°, 49.6°, 54.2°, 57.8°, 62.6°, 64.1°, 69.8°, 72.1°, 75.6°, 77.9°, 80.9°, 83.2°, 85.2° and 88.7° corresponding to the reflections from the planes (0 1 2), (1 0 4), (1 1 0), (1 1 3), (0 2 4), (1 1 6), (1 1 2), (2 1 4), (3 0 0), (2 0 8), (1 0 10), (2 1 7), (0 3 6), (1 2 8), (0 2 10), (1 3 4) and (2 2 6) respectively. No trace of additional peaks has been observed in the pattern which indicates that the proposed synthesis method could be employed for the synthesis of high purity α-Fe₂O₃ nanoparticles.

Fig. 1 X-ray diffractogram of synthesized material (a) before and (b) after annealing. (c) Williamson–Hall plot of synthesized hematite nanocrystals.

The average crystallite size normal to the reflection planes for the sample has been estimated using the Scherrer equation,

where ‘k’ is the shape factor, ‘λ’ is the X-ray wavelength, ‘β_hkl’ is full width at half maximum (FWHM) of diffraction peak in radian and ‘θ_hkl’ is the Bragg angle.⁴³ The average crystallite size has been calculated to be ∼34.1 nm which is the average of sizes measured from the intense peaks corresponding to α-Fe₂O₃.

The average values of the lattice parameters has been calculated using the relation,

where a, b and c are lattice parameters, (h k l) are Miller indices and d_hkl is interplanar spacing. Calculated values of lattice parameters are a = 5.03 Å and c = 13.69 Å which are consistent with reported values.⁴⁴ The broadening of XRD lines usually depends on the crystallite size (D) and local lattice strain (ε). In Williamson–Hall method, it has been assumed that the crystallite size and local strain contributions to the broadening are independent of each other.⁴⁵ The W–H equation is usually written aswhere ε is the microstrain allied with the NPs. Eqn (3) embodies a straight line between 4 sin θ_hkl and β_hkl cos θ_hkl.⁴⁶

Williamson and Hall plot has been employed to calculate the microstrain in the synthesized α-Fe₂O₃ nanoparticles (annealed sample) which is shown in Fig. 1(c). The slope of the line gives the strain (ε) and the intercept (kλ/D) of the line on Y-axis gives grain size (D). The crystallite size and microstrain evaluated by W–H method are ∼35.5 nm and ∼7.11 × 10⁻⁴, respectively. The microstrain in the sample is mainly the defects arising from cation (Fe³⁺) and anion (O²⁻) vacancies. The obtained values are comparable with the calculated values (Table 1). The small variation in the value of grain size is due to the fact that in Debye–Scherer's method, broadening of lines due to microstrain has been assumed to be negligible.

Table 1 Average particle size and microstrain values of the sample calculated using Debye–Scherrer formula and W–H method

	Debye–Scherrer formula	W–H method
Particle size (D) (nm)	34.1	35.5
Microstrain (ε)	7.10 × 10^−4	7.11 × 10^−4

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3.2 Optical properties

3.2.1 Absorption in near UV to near IR regions. The absorption spectrum of synthesized α-Fe₂O₃ nanoparticles has been shown in the Fig. 2. The spectrum shows four absorption bands in the near UV, visible and near IR regions. The absorption band in 347 nm results from the ligand to metal charge transfer (LMCT) transition (direct transition).^47,48 Band at 543 nm has been assigned to the double excitation processes ⁶A₁(⁶s) + ⁶A₁(⁶s) to ⁴T₁(⁴G) + ⁴T₁(⁴G) in the range 485–550 nm which is likely to be overlapped by the contributions of ⁶A₁(⁶s) to ⁴E, ⁴A₁(⁴G) ligand field transitions at 430 nm and the charge transfer band tail.⁴⁹ The double excitation process yields the strongest absorption band at 543 nm, which is primarily responsible for the red colour of hematite. Band at 652 nm corresponds to the ⁶A₁(⁶s) to ⁴T₂(⁴G) ligand field transition while absorption at 849 nm has been considered to be the result of ⁶A₁(⁶s) to ⁴T₁(⁴G) ligand filed transition.¹⁷

Fig. 2 The absorption spectrum of synthesized α-Fe₂O₃ nanoparticles in UV to near IR regions.

The optical band gap energy (E_g) of the synthesized sample has been calculated using the eqn (4), and the Tauc plot method from the UV-Vis spectrum.

αhν = (hν − E_g)ⁿ (4)

where hν is the photon energy, α is the absorption coefficient and n is 1/2 for a direct transition and 2 for an indirect transition.³² Zotti et al.⁵⁰ have reported that, α-Fe₂O₃ has an indirect band gap. The reported values of the indirect band gap lie in the range of 1.38–2.09 eV.^51–53 Direct band gap in the range from 1.95 to 2.35 eV have also been reported.^54–56

If the momentum of electrons in the conduction band and holes in the valence band are the same, an electron can directly emit a photon. The energy of photon is equal to the direct band gap energy. While making a transition, if an electron pass through an intermediate state and transfer momentum to the crystal lattice, photon cannot be emitted which is the reason for indirect band gap in a semiconductor. Herein, the observed band gap energy (Fig. 3(a)) of the as synthesized sample has been observed to be 1.71 eV, which shows that the sample has direct band gap occurring in conjunction with indirect band gaps. The existence of direct band gap can be attributed to quantum size effects associated with nanocrystallites.⁵⁷ Further, the obtained band gap (Fig. 3(b)) of 1.56 eV has also been observed to be consistent with earlier reports.

Fig. 3 Tauc plots for (a) direct transition and (b) indirect transition in synthesized α-Fe₂O₃ nanoparticles.

3.2.2 FTIR spectrum of α-Fe₂O₃ nanoparticles. A comparison of the IR spectra of the extract (Fig. 4(a)) and the nanoparticles (Fig. 4(b)) could give information regarding the functional groups of biomolecules responsible for reducing and capping the α-Fe₂O₃ nanoparticles. The prominent bands at 602 cm⁻¹, 545 cm⁻¹ and 465 cm⁻¹ observed in the spectrum (Fig. 4(b)) can be attributed to Fe–O vibrational modes.^58–60 Peak at 993 cm⁻¹ corresponds to =C–H bend of alkenes.⁶¹ Bands at 1100 cm⁻¹ and 1196 cm⁻¹ are assigned to C–O stretching of alcoholic derivatives.⁶² The FTIR spectrum of the hematite nanoparticles shows a peak in the amide (1535 cm⁻¹) region, which is characteristic of proteins and enzymes⁶³ that have been responsible for the reduction of the metal ions from the precursor. O–H bending vibrational modes results in a band at 1670 cm⁻¹.^64,65 This strong band may also be due to C=O group of the biomolecules capping α-Fe₂O₃ nanoparticles. Fig. 4(a) shows FTIR spectrum of P. guajava extract. The prominent band at 1031 cm⁻¹ can be assigned to the absorption of –C–O–C bonds. The band at 1370 cm⁻¹ may be attributed to –C–O stretching mode.⁶⁶ Absorption at 1409 cm⁻¹ should be attributed to C–H vibration of the hydrolyzed products. The weak IR band at 1554 cm⁻¹ arise from the stretching vibrations of C=C chain.⁶⁷ The strong band at 1637 cm⁻¹ results from –C=C–stretching vibration.⁶⁸ The bands corresponding to –C=C–, –C–O–C, –C–O, O–H and C=C bonds are originated from water soluble phyto compounds such as flavonoids, alkaloids and poly phenols present in P. guajava leaf. The results show that some metabolite functional groups such as alcohols, ketones, and carboxylic acids have been involved in the formation of α-Fe₂O₃ nanoparticles.

Fig. 4 FTIR spectra of (a) Psidium guajava leaf extract and (b) synthesized α-Fe₂O₃ nanoparticles.

3.2.3 Photoluminescence of α-Fe₂O₃ nanoparticles. Due to the local d-band transition nature, α-Fe₂O₃ does not show photoluminescent emission in its bulk form.⁶⁹ The PL spectrum (Fig. 5) of the phytosynthesized nanoparticles shows an intense emission when excited with 460 nm radiation. The intense and sharp nature of the band indicates that the emission around 688 nm is band edge emission,⁷⁰ which is possibly corresponding to the optical absorption at 652 nm. The structure model of hematite proposed by Pauling and Hendricks suggests a change in the oxygen atomic coordinates in nanosized α-Fe₂O₃ as well as increase of Fe–O bonding separation, resulting in enhancement of the magnetic coupling of the neighboring Fe³⁺, which is also responsible for the photoluminescence.^71,72

Fig. 5 Photoluminescence spectra of the α-Fe₂O₃ nanoparticles excited by 460 nm and 480 nm lines.

In view of the large Stokes shift of the emission peak in contrast with the excitation wavelength, we can attribute the emission to bound-exciton emission, as observable in other common semiconductor nanoparticles. As reported by Zou et al.,⁷³ capped α-Fe₂O₃ shows stronger emission due to the confinement by ionic surfactants, which prevents nanoparticles from energy exchange with the environment and stops the electron wave function broadening. Therefore, the observed emission peak in the present study is believed to be accountable for the distinctive structure of α-Fe₂O₃, quantum confinement effect and surface state effect in nanoscale and the presence of biomolecules as capping agents. The PL peaks around 688 nm may also be contributed by the surface defects which may arise from the deep trap created due to iron vacancy.

The synthesized sample has four absorption bands in the near UV, visible and near IR regions which is the characteristics of the material. Most of the earlier reports failed to explain these absorption bands. The presence of direct and indirect band gaps could be explained using the Tauc plots. The FTIR spectrum of the sample could shows characteristic peaks at 602 cm⁻¹, 545 cm⁻¹ and 465 cm⁻¹. Photo luminescence spectrum of the sample shows band emission at 688 nm which is in good agreement with observed absorption data. Articles reporting all these information about hematite nanoparticles is very rare.

3.3 Vibrating sample magnetometry studies

VSM studies explain the size and shape dependence of magnetic properties of the sample such as coercivity, remnant magnetization and saturation magnetization. Magnetization measurement has been performed as a function of the magnetic field at room temperature in order to elucidate field dependent magnetic properties of the synthesized hematite nanoparticles. α-Fe₂O₃ is an important magnetic material and shows unusual magnetic behavior due to particle size and morphology of the particles.⁷⁴ Fig. 6 shows magnetic hysteresis loop taken at room temperature. The observed results indicate weak ferromagnetic behavior of the sample.

Fig. 6 Magnetic hysteresis (M–B) curve of synthesized α-Fe₂O₃ nanoparticles.

Earlier works in this field have already reported that the coercivity of α-Fe₂O₃ samples depend on the size, shape and synthetic conditions. Rath et al.⁷⁵ has reported that, a small increase in coercivity can be observed for trapezoidal particles and large increase in coercivity can be found for pseudocubic particles, with their increasing size. Tadic et al.⁷⁶ observed that plate-like α-Fe₂O₃ particles reveal higher coercivity (1140 Oe) in comparison with the hematite nanospheres. This high value of coercivity is due to increased aspect ratio of plate-like structures, i.e. due to an increase of shape anisotropy. In another report, Tadic et al.⁷⁷ points out high coercivity value (4350 Oe) of hematite nanospheres due to their large size (∼150 nm). The synthesized α-Fe₂O₃ nanoparticle has a coercive magnetic field of 771.52 G. This high coercivity can arise due to the large size (∼38 nm) and shape anisotropy in the synthesized particles. Remanent magnetization value is M_r = 0.0369 emu g⁻¹ which is less than previously reported values (0.125 emu g⁻¹ (ref. 76) and 0.731 emu g⁻¹ (ref. 77)). In nano-sized hematite particles, the surface contribution is expected to enhance the magnetization. Due to the increased surface to volume ratio, an increased number of uncompensated surface spins caused by the breaking of large numbers of exchange bonds between surface atoms could be expected to exist at surface of the particles at nano scale. The uncompensated surface spins tend to interact ferromagnetically. It is to be expected that the contribution of such spins to the total magnetization will increase with reduction of nanoparticle size.^78,79 In the present work, the observed saturation magnetization of the synthesized sample is 0.3152 emu g⁻¹. The saturation magnetization is small because, the synthesized hematite nanoparticles are not too small to exhibit enhanced magnetization contributed by surface spin interaction. The small value of saturation magnetization and high value of coercivity can also be due to crystal defects and disorders in the nanostructures.^80,81

3.4 TG-DTG analysis

Thermo Gravimetric (TG) analysis (Fig. 7) shows three stages of weight loss. The first weight loss (−11.1%) corresponds to the superficial water loss while the second loss (−18.1%) is associated with the removal of chemisorbed water. The Differential Thermo Gravimetric (DTG) curve (Fig. 7) also demonstrates the removal of water from the surface of the samples as well as from the interstitial sites of the sample.²⁹ In the TGA curve, it has been observed that a −4.7% of weight loss occur in the temperature range between 400 °C and 650 °C. This can be attributed to the decomposition of mixed phases of iron oxides into α-Fe₂O₃ phase. Further, it has been observed that the synthesized powder has been completely decomposed to α-phase by annealing at 600 °C.

Fig. 7 TGA-DTG curves for the synthesized material in the temperature range 10 °C to 650 °C.

3.5 Morphological characterization of α-Fe₂O₃ nanoparticles

The morphology of the synthesized sample has been initially investigated by Scanning Electron Microscopy (SEM). It has been observed that the synthesized nanoparticles possess a quasi-spherical shape (Fig. 8). The diameter of the poly-dispersed α-Fe₂O₃ nanoparticles has been calculated to be in the range of 20 to 48 nm and the average diameter of NPs is approximately 35 nm. The facets on the surface of the structures are clearly discriminable and appear very smooth.

Fig. 8 (a)–(c) SEM images of the synthesized α-Fe₂O₃ nanoparticles at different magnifications; (d) energy dispersive X-ray spectrum of pure α-Fe₂O₃ nanoparticles.

Energy Dispersive X-ray (EDX) Spectroscopy analysis (Fig. 8(d)) of the sample indicates the presence of Fe and O composition in the synthesized α-Fe₂O₃ nanoparticles. The respective percentage weight of iron and oxygen are 62.55% and 37.45%, respectively. The EDX data displayed only peaks of Fe and O atoms which confirms the absence of impurities during the synthesis of the desired material.

The morphology of the α-Fe₂O₃ NPs has been further investigated by Transmission Electron Microscopy (TEM). The particles (Fig. 9) appear to be irregular in shape with an average size of ∼38 nm. The dimensions of the particles have been consistent with the SEM and XRD observations. The lattice fringe width of 0.27 nm corresponds to (104) facets of the rhombohedral structure.⁸²

Fig. 9 (a) TEM micrograph of α-Fe₂O₃ nanoparticles; (b) high resolution TEM image of a single nanocrystal showing lattice fringes with spacing of 0.27 nm.

3.6 Antibacterial activity of α-Fe₂O₃ nanoparticles

The antibacterial activity of α-Fe₂O₃ nanoparticles against E. coli and S. aureus have been tested and zones of inhibition have been observed in the tested bacterial strains (Fig. 10). An increase in diameter of zone of inhibition could be observed for both organisms on enhancing the concentration of the nanoparticles (Table 2). Analogous results have already been reported on the concentration dependent bacterial inhibition of iron oxide nanoparticles⁸³ and silver nanoparticles.⁸⁴ It has been observed that hematite nanoparticles are more efficient against Gram-positive S. aureus bacterial strain than the Gram-negative E. coli bacteria. Ismail et al.⁸⁵ have also reported a similar result. The different sensitivities of Gram-positive and Gram-negative bacteria against the nanoparticles are presumed to be due to the fact that E. coli has a more negatively charged and more rigid surface than S. aureus.⁸⁶

Fig. 10 Figure illustrates the microbial growth inhibitions by α-Fe₂O₃ nanoparticles against (a) E. coli and (b) S. aureus at different dose concentrations (25, 50 and 100 μL). (c) Comparison of zone of inhibition of both organisms against α-Fe₂O₃ nanoparticles and the positive control chosen.

Table 2 The zone of inhibition (ZOI) for different bactericidal concentrations for both α-Fe₂O₃ NPs and the positive control chosen against E. coli and S. aureus organisms

Concentration of sample (μg μL^−1)	Zone of inhibition (ZOI) (mm)
	E. coli	S. aureus
20 (reference)	29	39
25	0	10
50	10	13
100	12	15

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Earlier studies have reported two possible mechanisms for the interaction between nanoparticles and bacteria. One among them is the production of increased levels of reactive oxygen species (ROS) including hydroxyl radicals (OH⁻), singlet oxygen and hydrogen peroxide (H₂O₂).⁸⁷ When α-Fe₂O₃ nanoparticles with defects are activated by UV or visible light, electron–hole pairs are created. The holes can split H₂O molecules into OH⁻ and H⁺. The addition of electrons transforms dissolved oxygen molecules to superoxide radical anions (O₂⁻). The free radicals O₂⁻ and OH⁻ produced in the reactions can depolymerize polysaccharides, cause DNA strand breaks, inactivate enzymes, and kick off lipid peroxidation leading to death of the bacteria.^88–91 The other feasible mechanism is, the nanoparticle binding to cell membrane of the bacteria or cell membrane proteins through electro-static interactions or accumulation of nanoparticles either in the cytoplasm or in the periplasmic region causing disruption of cellular function and disruption and disorganization of membranes.^87,92

3.7 Thermal conductivity studies

Thermal conductivity enhancement of ethylene glycol-based α-Fe₂O₃ nanofluids and water-based α-Fe₂O₃ nanofluids at room temperature for different weight percentages of the nanoparticles (0.005% to 0.025%) have been investigated. The experimental thermal conductivities of the hematite nanofluids (K_nf) at different weight percentages are presented in Table 3. The enhanced thermal conductivity ratio (K_nf/K₀) and percentage enhancement in thermal conductivity at different weight percentage are also highlighted in the table. The variation of thermal conductivity ratio as a function of weight percentage is demonstrated in Fig. 11. As observed from the figure, thermal conductivity increases with increase in weight percentage of the nanoparticles. An enhancement of thermal conductivity from 1.79% to 29.92% and 1.98% to 33.99% could be observed for water-based and EG-based hematite nanofluids, respectively.

Table 3 (a) The values of enhanced thermal conductivity ratio (K_nf/K₀) and percentage enhancement in thermal conductivity at different weight percentage of nanoparticles in water-based α-Fe₂O₃ nanofluids. (b) The values of enhanced thermal conductivity ratio (K_nf/K₀) and percentage enhancement in thermal conductivity at different weight percentage of nanoparticles in ethylene glycol-based α-Fe₂O₃ nanofluids

Nanoparticles loading weight%	Knf (W m^−1 K^−1)	Knf/K0	Percentage increase of K (%)
(a)
0.005	0.626	1.018	1.79
0.010	0.664	1.079	7.97
0.015	0.708	1.151	15.12
0.020	0.759	1.234	23.41
0.025	0.799	1.299	29.92
(b)
0.005	0.258	1.019	1.98
0.010	0.282	1.115	11.46
0.015	0.304	1.202	20.16
0.020	0.323	1.277	27.67
0.025	0.339	1.340	33.99

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Fig. 11 (a) The enhanced thermal conductivity ratio (K_nf/K₀) and (b) percentage enhancement in thermal conductivity at different weight percentage of nanoparticles in water-based α-Fe₂O₃ nanofluids and ethylene glycol-based α-Fe₂O₃ nanofluids.

All the concentrations of nanofluids exhibit the enhancement in thermal conductivity with increase of weight percentage. A similar trend of thermal conductivity enhancement for alumina (Al₂O₃) nanofluids has been observed by Timofeeva et al.^93,94 for different particle shapes of alumina nanoparticles. Reports of Beck et al.⁹⁵ and Wang et al.⁹⁶ are also in agreement with the observed results. As the thermal conductivity of solid particles is relatively larger than that of base fluids, the suspended particles are expected to enhance the thermal conductivity and hence the heat transfer performance. Many factors such as size, weight percentage and thermal conductivity of the solid particles, temperature, viscosity and thermal conductivity of the base fluids as well as the liquid–solid particle interface influences the thermal conductivity of a nanofluid.⁹⁷ In the case of α-Fe₂O₃ nanofluids, the nature of heat conduction in nanoparticle suspensions and an organized structure of liquid molecule membrane around the nanoparticles are responsible for the nonlinear increase in thermal conductivity with increase of nanoparticles loading.⁹⁸

Xie et al.^99,100 have concluded that, for the same nanoparticles, the enhanced thermal conductivity ratio has been reduced on increasing the thermal conductivity of the base fluid. Similar results could be seen in the present study. Since water has higher thermal conductivity (615 W m⁻¹ K⁻¹) than ethylene glycol (253 W m⁻¹ K⁻¹) at 30 °C,⁹⁷ ethylene glycol-α-Fe₂O₃ nanofluid shows higher thermal conductivity ratio, compared to that of water-α-Fe₂O₃ nanofluid, for same weight percentage of nanoparticles. Since crystalline α-Fe₂O₃ nanoparticles are ordered, the liquid membranes in contact with solid interface have been more ordered than a bulk liquid. This ordered liquid layering has also been expected to lead to a higher thermal conductivity.¹⁰¹ The effect of the Brownian motion could also be a prominent factor for the enhancement in thermal conductivity, as the synthesized hematite nanoparticles are almost spherical structures.⁹⁷

4 Conclusions

The current work suggests a unique approach for the synthesis of highly pure, crystalline and biocompatible hematite nanoparticles through the sole use of P. guajava leaf extract. The average crystallite size calculated by Debye–Scherer's and Williamson–Hall plots is observed to be 34.1 nm and 35.5 nm respectively. The UV-visible absorption shows the existence of indirect and direct band gap energies of α-Fe₂O₃. PL spectrum from the nanoparticle-clusters excited at 460 nm shows emission band at 688 nm due to the band edge emission. VSM study exhibited hysteresis loop at room temperature, which indicates the weak ferromagnetic nature of the synthesized sample. The observed high value of coercive magnetic field is owing to the shape anisotropy. The synthesized material is found to be a very good candidate for thermal conductivity enhancement of conventional base fluids water and ethylene glycol. The antibacterial efficacy of the hematite nanoparticles against Gram-positive as well as Gram-negative bacteria is also established. Further, studies on the size dependent and shape dependent optical and magnetic properties of α-Fe₂O₃ nanoparticles and the mechanism including the contributions of quantum confinement and surface effect remain as future prospects of the present study.

Acknowledgements

The authors gratefully acknowledge NIT Calicut, SAIF STIC Cochin and SAIF IIT Madras for technical support.

References

1. H. Gleiter, Acta Mater., 2000, 48, 1–29.
2. K. S. Upadhyaya, G. K. Upadhyaya and A. N. Pandey, J. Phys. Chem. Solids, 2002, 63, 127–133.
3. J. Chatterjee, Y. Haik and C. J. Chen, J. Magn. Magn. Mater., 2003, 257, 113–118.
4. D. Serantes, K. Simeonidis, M. Angelakeris, O. Chubykalo-Fesenko, M. Marciello, M. P. Morales, D. Baldomir and C. Martinez-Boubeta, J. Phys. Chem. C, 2014, 118, 5927–5934.
5. M. A. Willard, L. K. Kurihara, E. E. Carpenter, S. Calvin and V. G. Harris, Int. Mater. Rev., 2004, 49, 125–170.
6. J. Chatterjee, Y. Haik and C. J. Chen, J. Magn. Magn. Mater., 2001, 225, 21–29.
7. V. Patsula, M. Moskvin, S. Dutz and D. Horák, J. Phys. Chem. Solids, 2016, 88, 24–30.
8. S. K. Maji, N. Mukherjee, A. Mondal and B. Adhikary, Polyhedron, 2012, 33, 145–149.
9. D. K. Kim, Y. Zhang, W. Voit, K. V. Rao, J. Kehr, B. Bjelke and M. Muhammed, Scr. Mater., 2001, 44, 1713–1717.
10. M. Mohapatra and S. Anand, Int. J. Eng. Sci. Res. Technol., 2010, 2, 127–146.
11. S. Upadhyay, K. Parekh and B. Pandey, J. Alloys Compd., 2016, 678, 478–485.
12. X. Zhang and Q. Li, Mater. Lett., 2008, 62, 988–990.
13. Z. H. Jing and S. H. Wu, Mater. Chem. Phys., 2005, 92, 600–603.
14. K. Sivula, F. Le Formal and M. Grotzel, ChemSusChem, 2011, 4, 432–449.
15. S. Cabanas-Polo, M. Distaso, W. Peukert and A. R. Boccaccini, J. Nanosci. Nanotechnol., 2015, 15, 10149–10155.
16. S. Piramana, S. Sundar, R. Mariappana, Y. Y. Kima and K. Min, Sens. Actuators, B, 2016, 234, 386–394.
17. D. A. Wheeler, G. Wang, Y. Ling, Y. Li and J. Z. Zhang, Energy Environ. Sci., 2012, 5, 6682–6702.
18. Z. Li, X. Lai, H. Wang, D. Mao, C. Xing and D. Wang, Nanotechnology, 2009, 20, 245603.
19. H. J. Kim, K. I. Choi, A. Pan, I. D. Kim, H. R. Kim, K. M. Kim, C. W. Na, G. Cao and J. H. Lee, J. Mater. Chem., 2011, 21, 6549–6555.
20. K. Woo, H. J. Lee, J. P. Ahn and Y. S. Park, Adv. Mater., 2003, 15, 1761–1764.
21. Y. Lin, S. Zhou, S. W. Sheehan and D. Wang, J. Am. Chem. Soc., 2011, 133, 2398–2401.
22. H. L. Wang and J. A. Turner, J. Electrochem. Soc., 2010, 157, F173–F178.
23. A. Kleiman-Shwarsctein, M. N. Huda, A. Walsh, Y. F. Yan, G. D. Stucky, Y. S. Hu, M. M. Al-Jassim and E. W. McFarland, Chem. Mater., 2010, 22, 510–517.
24. H. E. Prakasam, O. K. Varghese, M. Paulose, G. K. Mor and C. A. Grimes, Nanotechnology, 2006, 17, 4285–4291.
25. R. Wang, Y. Chen, Y. Fu, H. Zhang and C. Kisielowski, J. Phys. Chem. B, 2005, 109, 12245–12249.
26. Z. Zhang, M. F. Hossain and T. Takahashi, Appl. Catal., B, 2010, 95, 423–429.
27. Z. Wu, K. Yu, S. Zhang and Y. Xie, J. Phys. Chem. C, 2008, 112, 11307–11313.
28. S. Y. Zeng, K. B. Tang, T. W. Li, Z. H. Liang, D. Wang, Y. K. Wang, Y. X. Qi and W. W. Zhou, J. Phys. Chem. C, 2008, 112, 4836–4843.
29. E. Darezereshki, F. Bakhtiari, M. Alizadeh, A. Behradvakylabad and M. Ranjbar, Mater. Sci. Semicond. Process., 2012, 15, 91–97.
30. R. Al-Gaashani, S. Radiman, N. Tabet and A. R. Daud, J. Alloys Compd., 2013, 550, 395–401.
31. X. Zhang, Y. Niu, Y. Li, X. Hou, Y. Wanga, R. Bai and J. Zhao, Mater. Lett., 2013, 99, 111–114.
32. B. K. Pandey, A. K. Shahi, J. Shah, R. K. Kotnala and R. Gopal, Surf. Sci., 2014, 289, 462–471.
33. B. Ahmmad, K. Leonard, Md S. Islam, J. Kurawaki, M. Muruganandham, T. Ohkubo and Y. Kuroda, Adv. Powder Technol., 2013, 24, 160–167.
34. R. M. P. Gutierrez, S. Mitchell and R. V. Solis, J. Ethnopharmacol., 2008, 117, 1–27.
35. W. K. Oh, C. H. Lee, M. S. Lee, E. Y. Bae, C. B. Sohn, H. Oh, B. Y. Kim and J. S. Ahn, J. Ethnopharmacol., 2005, 96, 411–415.
36. P. Jaiarj, P. Khoohaswan, Y. Wongkrajang, P. Peungvicha, P. Suriyawong, M. L. S. Saraya and O. Ruangsomboon, J. Ethnopharmacol., 1999, 67, 203–212.
37. S. Begum, S. I. Hassan, B. S. Siddiqui, F. Shaheen, M. N. Ghayur and A. H. Gilani, Phytochemicals, 2002, 61, 399–403.
38. H. A. Foster, I. B Ditta, S. Varghese and A. Steele, Appl. Microbiol. Biotechnol., 2011, 90, 1847–1868.
39. P. Basnet, G. K. Larsen, R. P. Jadeja, Y. C. Hung and Y. Zhao, ACS Appl. Mater. Interfaces, 2013, 5, 2085–2095.
40. C. Perez, M. Paul and P. Bazerque, Acta Bio. Med. Exp., 1990, 15, 113–115.
41. Sh. Azarfar, S. Movahedirad, A. A. Sarbanha, R. Norouzbeigi and B. Beigzadeh, Appl. Therm. Eng., 2016, 105, 142–150.
42. V. A. Sadykov, L. A. Isupova, S. V. Tsybulya, S. V. Cherepanova, G. S. Litvak, E. B. Burgina, G. N. Kustova, V. N. Kolomiichuk, V. P. Ivanov, E. A. Paukshtis, A. V. Golovin and E. G. Avvakumov, J. Solid State Chem., 1996, 123, 191–202.
43. F. T. L. Muniz, M. A. R. Miranda, C. M. dos Santos and J. M. Sasaki, Acta Crystallogr., 2016, 72, 385–390.
44. C. D. Guerra, L. Perez, J. Piqueras and M. F. Chioncel, J. Appl. Phys., 2009, 106, 104302–104304.
45. G. Madhu, V. C. Bose, K. Maniammal, A. S. A. Raj and V. Biju, Phys. B, 2013, 421, 87–91.
46. G. K. Williamson and W. H. Hall, Acta Metall. Mater., 1953, 1, 22–31.
47. L. A. Marusak, R. Messier and W. B. White, J. Phys. Chem. Solids, 1980, 41, 981–984.
48. D. M. Sherman and T. D. Waite, Am. Mineral., 1985, 70, 1262–1269.
49. Y. P. He, Y. M. Miao, C. R. Li, S. Q. Wang, L. Cao, S. S. Xie, G. Z. Yang and B. S. Zou, Phys. Rev., 2005, 71, 125411–125419.
50. G. Zotti, G. Schiavon and U. Casellato, J. Electrochem. Soc., 1998, 145, 385–389.
51. L. Dghoughi, B. Elidrissi, C. Bernede, M. Addou, M. A. Lamrani, M. Regragui and H. Erguig, Appl. Surf. Sci., 2006, 253, 1823–1829.
52. N. Beermann, L. Vayssieres, S. E. Lindquist and A. Hagfeldt, J. Electrochem. Soc., 2000, 147, 2456–2461.
53. N. Ozer and F. Tepehan, Sol. Energy Mater. Sol. Cells, 1999, 56, 141–152.
54. L. Vayssieres, C. Sathe, S. M. Butorin, D. K. Shuh, J. Nordgren and J. H. Guo, Adv. Mater., 2005, 17, 2320–2323.
55. M. Gartner, M. Crisan, A. Jitianu, R. Scurtu, R. Gavrila, I. Oprea and M. Zaharescu, J. Sol-Gel Sci. Technol., 2003, 26, 745–748.
56. R. N. Goyal, A. K. Pandey, D. Kaur and A. Kumar, J. Nanosci. Nanotechnol., 2009, 9, 4692–4699.
57. S. Sivakumar, D. Anusuya, C. P. Khatiwada, J. Sivasubramanian, A. Venkatesan and P. Soundhirarajan, Spectrochim. Acta, Part A, 2014, 128, 69–75.
58. B. Pal and M. Sharon, Thin Solid Films, 2000, 379, 83–88.
59. Y. Y. Xu, D. Zhao, X. J. Zhang, W. T. Jin, P. Kashkarov and H. Zhang, Phys. E, 2009, 41, 806–811.
60. E. Darezereshki, Mater. Lett., 2011, 65, 642–645.
61. K. Rajendran, V. Karunagaran, B. Mahanty and S. Sen, Int. J. Biol. Macromol., 2015, 74, 376–381.
62. J. Coates, Encyclopedia of Analytical Chemistry, 2000, pp. 10815–10837.
63. S. Gurunathan, K. Kalishwaralal, R. Vaidyanathan, D. Venkataraman, S. R. K. Pandian, J. Muniyandi, N. Hariharan and S. H. Eom, Colloids Surf., B, 2009, 74, 328–335.
64. S. K. Apte, S. D. Naik, R. S. Sonawane and B. B. Kalew, J. Am. Ceram. Soc., 2007, 90, 412–414.
65. L. Song, S. Zhang, B. Chen, J. Ge and X. Jia, Colloids Surf., A, 2010, 360, 1–5.
66. S. S. Shankar, A. Rai, A. Ahmad and M. Sastry, J. Colloid Interface Sci., 2004, 275, 496–502.
67. H. Schulz and M. Baranska, Vib. Spectrosc., 2007, 43, 13–25.
68. J. Huang, Q. Li, D. Sun, Y. Lu, Y. Su, X. Yang, H. Wang, W. Shao, N. He, J. Hong and C. Chen, Nanotechnology, 2007, 18, 105104–105114.
69. A. A. Jahagirdar, N. Dhananjaya, D. L. Monika, C. R. Kesavulu, H. Nagabhushana, S. C. Sharma, B. M. Nagabhushana, C. Shivakumara, J. L. Rao and R. P. S. Chakradhar, Spectrochim. Acta, Part A, 2013, 104, 512–518.
70. H. Fei, X. Ai, M. Gaob, Y. Yang, T. Zhang and J. Shenb, J. Lumin., 1996, 66–67, 345–348.
71. Q. Han, Z. Liu, Y. Xu, Z. Chen, T. Wang and H. Zhang, J. Phys. Chem. C, 2007, 111, 5034–5038.
72. R. Blake, R. Hessevick, T. Zoltai and L. Finger, Am. Mineral., 1966, 51, 123–129.
73. B. Zou and V. Volkov, J. Phys. Chem. Solids, 2000, 61, 757–764.
74. H. Ni, Y. Ni, Y. Zhou and J. Hong, Mater. Lett., 2012, 73, 206–208.
75. C. Rath, K. K. Sahu, S. D. Kulkarni, S. Anand, S. K. Date, R. P. Das and N. C. Mishra, Appl. Phys. Lett., 1999, 75, 4171–4173.
76. M. Tadic, N. Citakovic, M. Panjan, Z. Stojanovic, D. Markovic and V. Spasojevi, J. Alloys Compd., 2011, 509, 7639–7644.
77. M. Tadic, N. Citakovic, M. Panjan, B. Stanojevic, D. Markovic, D. Jovanovic and V. Spasojevi, J. Alloys Compd., 2012, 543, 118–124.
78. L. Kopanja, I. Milosevic, M. Panjan, V. Damnjanovic and M. Tadic, Appl. Surf. Sci., 2016, 362, 380–386.
79. K. V. Manukyan, Y. S. Chen, S. Rouvimov, P. Li, X. Li, S. Dong, X. Liu, J. K. Furdyna, A. Orlov, G. H. Bernstein, W. Porod, S. Roslyakov and A. S. Mukasyan, J. Phys. Chem. C, 2014, 118, 16264–16271.
80. M. Sirena, A. Zimmers, N. Haberkorn, E. Kaul, L. B. Steren, J. Lesueur, T. Wolf, Y. Le Gall, J. J. Grob and G. Faini, J. Appl. Phys., 2010, 107, 113903.
81. D. H. Qin, Y. Peng, L. Cao and H. L. Li, Chem. Phys. Lett., 2003, 374, 661–666.
82. Z. Liua, B. Lv, D. Wu, Y. Sun and Y. Xu, Particuology, 2013, 11, 327–333.
83. E. N. Taylor and T. J. Webster, Int. J. Nanomed., 2009, 4, 145–152.
84. J. S. Kim, E. Kuk, K. N. Yu, J. H. Kim, S. J. Park, H. J. Lee, S. H. Kim, Y. K. Park, Y. H. Park, C. Y. Hwang, Y. K. Kim, Y. S. Lee, D. H. Jeong and M. H. Cho, Nanomedicine, 2007, 3, 95–101.
85. R. A. Ismail, G. M. Sulaiman, S. A. Abdulrahman and T. R. Marzoog, Mater. Sci. Eng., C, 2015, 53, 286–297.
86. R. Sonohara, N. Muramatsu, H. Ohshima and T. Kondo, Biophys. Chem., 1995, 55, 273–277.
87. Y. Yamamoto, N. Imai, R. Mashima, R. Konaka, M. Inoue and W. C. Dunlap, Methods Enzymol., 2000, 319, 29–37.
88. L. C. Chu, Z. W. Zhou, X. F. Duan and L. L. Tang, Mater. Rev., 2003, 17, 84–85.
89. M. Fang, J. H. Chen, X. L. Xu, P. H. Yang and H. F. Hildebrand, Int. J. Antimicrob. Agents, 2006, 27, 513–517.
90. N. Jones, B. Ray, K. T. Ranjit and A. C. Manna, FEMS Microbiol. Lett., 2008, 279, 71–76.
91. D. Touati, Arch. Biochem. Biophys., 2000, 373, 1–6.
92. S. Makhluf, R. Dror, Y. Nitzan, Y. Abramovich, R. Jelinek and A. Gedanken, Adv. Funct. Mater., 2005, 15, 1708–1715.
93. E. V. Timofeeva, A. N. Gavrilov, J. M. McCloskey, Y. V. Tolmachev, S. Sprunt, L. M. Lopatina and J. V. Selinger, Phys. Rev. E, 2007, 76, 061203.
94. E. V. Timofeeva, J. L. Routbort and D. Singh, J. Appl. Phys., 2009, 106, 014304.
95. M. P. Beck, T. Sun and A. S. Teja, Fluid Phase Equilib., 2007, 260–275.
96. X. Wang, X. Xu and S. U. S. Choi, J. Thermophys. Heat Transfer, 1999, 13, 474.
97. Y. Li, J. Zhou, S. Tung, E. Schneider and S. Xi, Powder Technol., 2009, 196, 89–101.
98. S. U. S. Choi, Z. G. Zhang, W. Yu, F. E. Lockwood and E. A. Grulke, Appl. Phys. Lett., 2001, 79, 2252–2254.
99. H. Xie, J. Wang, T. Xi, Y. Liu and F. Ai, J. Appl. Phys., 2002, 91, 4568–4572.
100. H. Xie, H. Lee, W. Youn and M. Choi, J. Appl. Phys., 2003, 94, 4967–4971.
101. K. C. Leong, C. Yang and S. M. S. Murshed, J. Nanopart. Res., 2006, 8, 245–254.

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