Features of metal oxide colloidal nanocrystal characterization

Features of metal oxide colloidal nanocrystal characterization

6

Mohamad Azuwa Mohameda, Zul Adlan Mohd Hir b, Wan Nur Aini Wan Mokthar a, Nur Syazwani Osmanc a Centre for Advanced Materials & Renewable Resources, Universiti Kebangsaan Malaysia, Bangi, Malaysia, bFaculty of Applied Sciences, Universiti Teknologi MARA, Pahang, Malaysia, cDepartment of Chemistry, Universiti Putra Malaysia, Serdang, Malaysia

6.1

Introduction

The metal oxide colloidal nanocrystal is a fascinating material because it has been reported to be the most versatile material that can be applied in various applications such as energy harvesting, environmental pollution control, and medical, electronic, and sensor material, among many more [1–7]. It is believed that the surface chemistry metal oxide colloidal nanocrystal is a crucial enabler for its colloidal nanocrystal applications. By understanding the chemistry of metal oxide colloidal nanocrystals, we can manipulate the composition, size, structure, and shape of individual nanocrystals. Also, its overall physicochemical properties can be applied in the intended application. Therefore, in this chapter, the several characterization techniques are introduced, and the underlying principle is briefly explained. The first part of this chapter mostly explicates on the strategies and advances of microscopy in the characterization of metal oxide colloidal nanocrystals, which involved the use of scanning electron microscopy (SEM), transmission electron microscopy (TEM), and atomic force microscope (AFM). The surface chemistry of the metal oxide colloidal nanocrystal is explored using spectral characterization such as Fourier transform infrared (FTIR), Raman spectroscopy, UV–vis spectroscopy, photoluminescence spectroscopy (PL), X-ray photoelectron spectroscopy (XPS), X-ray fluorescence spectroscopy (XFS), and nuclear magnetic resonance (NMR) spectroscopy. Finally, the probing of nano colloids of metal oxides by diffraction techniques is also discussed to understand the crystal structure of the metal oxide colloidal nanocrystal.

6.2

Strategies and advances of microscopy in the characterization of colloidal metal oxide nanocrystals

The structure and morphology of the colloidal metal oxide nanocrystals can be determined by using microscopy techniques such as scanning electron microscopy (SEM), transmission electron microscopy (TEM), and atomic force microscope (AFM). In this section, Colloidal Metal Oxide Nanoparticles. https://doi.org/10.1016/B978-0-12-813357-6.00008-5 © 2020 Elsevier Inc. All rights reserved.

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the sample preparation of colloidal metal oxide samples and the principle of the microscopy techniques are explained.

6.2.1 Scanning electron microscopy SEM is a type of electron microscope that produces images of a sample by scanning the surface with a high-energy beam of electrons. The interaction between the electrons and atoms in the sample generates various signals that contain information about surface topography, morphology, composition, and crystallographic information. There are two classes of emission sources or electron guns used by SEMs: the thermionic electron gun (TEG) and the field emission gun (FEG). These two emission sources are the main difference between SEM and the field emission scanning electron microscope (FE-SEM). The thermionic emission gun heats a filament until the electrons are emitted. The two most common materials used for filaments are tungsten (W) wire and lanthanum hexaboride (LaB6) crystal. These emission sources have several problems such as relatively low brightness, evaporation of cathode material, and thermal drift during operation. Thus, the most recent emitter is a field emission gun, also known as a cold gun, which extracts electrons away from their atoms by generating a strong electric field. This field emission gun is used to produce an electron beam that is smaller in diameter, more coherent, and has a higher current density or brightness, which significantly increased emitter life and reliability as well as improved the signal-to-noise ratio and spatial resolution. Once the electron beam hits the sample, it emits X-rays and three kinds of electrons: primary backscattered electrons, secondary electrons, and Auger electrons. Detectors collect the secondary electrons and primary backscatter electrons and convert them to a signal that is sent to a viewing screen, similar to the one in an ordinary television, which produces an image. SEM application in colloidal metal oxide nanocrystals provides a better understanding of surface properties as well as surface morphology (shape) and the aggregation and dispersion of the particles. There are various kinds of techniques to prepare for SEM samples, which depend on the physical properties of the samples. This is crucial because it is difficult to stabilize the nanoparticle colloids. Within the many kinds of forces governing the stability of nanoparticle colloids, the van der Waals attraction and the repulsive force are the two forces that balance the nanoparticles. The repulsive force can be electrostatic repulsion from the electric double layer surrounding the nanoparticles. Besides, another stabilization mechanism is based on the steric repulsion between molecules or ions adsorbed on neighboring particles. Aside from the charge and steric stabilization, the effect of the dielectric constant (polarity) of the solvent also needs to be considered. This can be approximated using the Hamaker constant. This is because varying the dielectric constant of the solvent will directly affect the particle-particle pair interactions. Therefore, changing solvents could dissolve the surface species off the surface of the nanoparticles. For instance, in 2018, the morphological and structural characterizations of different metal oxide nanoparticles (ZnO, TiO2, CuO, SnO2, and In2O3) as a suitable metal oxide ink formulation for printed electronics were performed by a high-resolution

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scanning electron microscope (HRSEM) with a JEOL JSM-7500F [8]. For HRSEM sample preparation, inks are dried on silicon wafers; in case of CuO, the powder is attached to carbon tape. The HRSEM images of the chemical vapor synthesized nanoparticles in Fig. 6.1 reveal nearly spherically shaped nanoparticles in case of SnO2 (B), TiO2 (E), and ZnO (D). Fischer et al. [9] reported the new design of a colloidally stable metal oxide/polymer hybrid nanoparticle of cerium, iron, and zinc oxide nanocrystals. They also compared the stability of the hybrid colloid with a different solvent with aqueous and alcoholic dispersions. The samples for SEM observation were prepared by drop casting of diluted dispersions on silicon wafers. For CeO2 in distilled water (aqueous solvent), a dense and homogeneous particle coverage is seen. Meanwhile, to investigate the extension of the method to nonaqueous solvents (alcoholic dispersions), the experiment was further performed for Fe2O3 in 2-propanol and ZnO in methanol. The Fe2O3 hybrid particles obtained from 2-propanol presented a denser coverage than those formed from aqueous solution, whereas ZnO showed a raspberry-like particle coverage that only could be achieved from methanol or other alcoholic solvents. Also, Jafari et al. [10] synthesized Ag and ZnO mixed metal oxide nanocolloidal particles for medical purposes. He and his coresearcher prepared the SEM sample by diluting the nanoparticle suspensions in distilled water before dropping them onto copper stubs. After air drying, the particles were coated with a thin layer of gold under vacuum to make them conductive before scanning by SEM. Meanwhile, Dadashi et al. in their research prepared the iron and iron oxide nanoparticles by pulsed laser ablation in deionized water and acetone [11]. They carried out sample preparation of SEM by dropping of the sample solution and placing on microscopic slides, then drying at room temperature. They observed that the iron oxide nanoparticles prepared in acetone and water are somewhat spherical.

Fig. 6.1 HRSEM images of the CVS synthesized nanoparticles (A) In2O3, (B) SnO2, (C) CuO, (D) ZnO, (E) TiO2 (all images have the same magnification) [8].

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6.2.2 Transmission electron microscopy TEM is a technique that uses the interaction of energetic electrons with the sample and provides morphological, compositional, and crystallographic information. The electron emitted from the filament passes through the multiple electromagnetic lenses and makes contact with the screen, where the electrons are converted into light and an image is produced. A modern TEM is composed of an illumination system, a condenser lens system, an objective lens system, a magnification system, and the data recording system. A set of condenser lens that focuses the beam on the sample and an objective lens collects all the electrons after interacting with the sample. It then forms an image of the sample and determines the limit of image resolution. Finally, a set of intermediate lenses magnifies this image and projects it on a phosphorous screen or a charge coupled device (CCD). The most important feature of TEM is that the wavelength of electrons is much smaller than atomic separations in the solids. Therefore, it is theoretically possible to see crystal details well below the atomic sizes. Meanwhile, high-resolution transmission electron microscopy (HRTEM) is a powerful tool to study the properties of materials on the atomic scale, such as semiconductors, metals, nanoparticles, and sp2-bonded carbon such as graphene and carbon nanotubes. It uses both the transmitted and scattered beams to create an interference image. The image mode in HRTEM allows for direct imaging of the atomic structure of the sample. In this case, the outgoing modulated electron waves at very low angles interfere with themselves during propagation through the objective lens. All electrons emerging from the specimen are combined at a point in the image plane. HRTEM has been extensively and successfully used for analyzing crystal structures and lattice imperfections in various kinds of advanced materials on an atomic resolution scale. It can be used for the characterization of point defects, stacking faults, dislocations, precipitate grain boundaries, and surface structures. There are many techniques and methods to prepare the colloidal samples before analyzing with TEM. Senpan et al. [12] have different techniques to prepare the colloidal iron oxide nanoparticles for TEM analysis. First, the nanoparticles were fixed with 2.5% glutaraldehyde (Electron Microscopy Sciences) for 30 min on ice and were spun at high speed in a tabletop microfuge to form a tight pellet. After rinsing, the pellet was sequentially stained with osmium tetroxide, tannic acid (Sigma-Aldrich), and uranyl acetate; it was then dehydrated and embedded in Polybed 812 (Polysciences). Next, the tissue was thin sectioned on a Reichert-Jung Ultracut and poststained in uranyl acetate and lead citrate before being recorded with Kodak E.M. Film. The TEM images of colloidal iron oxide nanoparticles are displayed in Fig. 6.2. As can be seen in the TEM image, the distribution of colloidal iron oxide nanoparticles demonstrating that the oleate-coated magnetite particles are incorporated into the oil core, and the core is encapsulated with lipid layer (inset B). Salameh et al. compared the TEM images of TiO2 colloidal nanoparticles fresh and after 1 week [13]. The TiO2 sample was prepared by dispersing the powdered sample in ethanol, and the resulting suspensions were deposited on a copper grid coated with a porous carbon film. In the case of the new suspension, a small particle with a mean diameter of about 2–3 nm was observed. Interestingly, after 1 week, many TiO2

Features of metal oxide colloidal nanocrystal characterization

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Fig. 6.2 TEM images of colloidal iron oxide nanoparticles (CION) [12].

nanoparticles with a bigger size could be seen. Thus, the new TiO2 colloid suspensions were preferred for the preparation of the next experiment to maintain its small size. Gavila´n et al. compared four different synthesis strategies and coatings to synthesize colloidal flower-shaped iron oxide nanoparticles [14]. In their research, the iron oxide nanoparticles were synthesized based on the partial oxidation of Fe(OH)2, polyolmediated synthesis, or the reduction of iron acetylacetonate. Besides, the nanoparticles are functionalized either with dextran or citric acid or embedded in polystyrene to investigate their stability. All the colloidal NF (flower-shaped nanoparticles) were characterized by using TEM, STEM, and HRTEM. The sample preparation for TEM analysis was performed by putting a droplet of the diluted suspension in the water on holey carbon film coated TEM Cu grid and then letting it dry in air at room temperature.

6.2.3 Atomic force microscopy (AFM) To analyze the surface of a rigid material, atomic force microscopy (AFM) is an excellent technique. It also allows for 3D characterization of nanoparticles with subnanometer resolution. The AFM utilizes a mechanical probe to magnify surface features up to 10 million times, and it shows 3D images of the surface. The AFM consists of a cantilever with a sharp tip (probe) at its end, which is used for scanning purposes. Basically, the cantilever is made up of silicon or silicon nitride with a tip radius of curvature on the order of nanometers. When the tip is brought into proximity with a sample surface, the forces between the tip and the sample lead to a deflection of the cantilever. There are three significant abilities of AFM: force measurement, imaging, and manipulation. AFM can be used to measure the forces between the probe and the sample as a function of their mutual separation. This can be applied to perform force spectroscopy and to measure the mechanical properties of the sample. For imaging, the reaction of the probe to the forces that the sample imposes on it can be used to generate 3D images (topography) of a sample surface at a high resolution.

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In manipulation, the forces between the tip and sample can also be used to manipulate the properties of the sample in a controlled way. Generally, AFM is similar to electron microscope techniques, SEM and TEM, where proper sample preparation is the main point to obtain high-quality data. In a preparation sample of AFM, the samples do not have to be conducive, which makes sample preparation much easier for the user. AFM particle imaging requires that the particles rigidly adhere to a substrate; the particles need to be dispersed on a substrate and the substrate roughness is less than the size of the nanoparticles. Usually, an adhesive such as poly-Llysine, PEI (poly-ethyleneimide), or APTES (aminopropyltriethoxy silane) is used to facilitate chemical bonding between the particle and substrate. Meanwhile, spincoating of polymers or HPOG is used to create hydrophobic substrates. However, if the nanoparticles are not dispersed on the substrate, it is not possible to characterize them. The difficulty of dispersing nanoparticles on the substrate brings challenges to the researcher because it often requires experimentation. One of the significant factors that needs to be considered is the interfacial free energy and electrostatic energy associated with the nanoparticles. This is due to the tendency of the nanoparticles to clump together or remain far apart. Besides hydrophilic-hydrophobic forces interacting between particles, the substrate and solution can cause agglomeration and coalescence. In many cases, additives and surfactants present in the particle suspension may cause various effects on dispersing of the particles, especially during and after evaporation. Basically, for AFM particle analysis, the size of the particles should be greater than the topographical features of the substrate. The most commonly used substrates that work very well for fine sizes such as colloids include glass, mica, and silicon work [15]. In general, there are many reports on the synthesis of colloidal metal oxide nanoparticles. However, the reports available on the characterization and preparation samples of AFM are limited. Ferna´ndez et al. [16] investigated the kinetic growth of RuO2 colloidal nanoparticles over solid support by using atomic force microscopy (AFM) analysis. They prepared the AFM sample by using the deposition method and utilized a mica sheet as support. In order to have a clean surface, a few surface layers of mica were removed. The single-coated RuO2-mica sheets were then prepared by spin coating one drop of the colloidal suspension onto a freshly cleaved mica sheet at 2000 rpm for 1 min, which allows a uniform spreading of RuO2 nanoparticles on the surface. The RuO2-mica sample was stuck on a magnetic stainless-steel disc using double-sided adhesive tape and placed in the J-Type Piezo Scanner. Fig. 6.3A displays the AFM image of a noncalcined sample prepared by single deposition of the RuO2 colloidal suspension (RuM(fresh)), whereas Fig. 6.3B shows the image of the RuO2 colloidal after undergoing calcination at 450°C (RuM(calcined)). Based on the images, they claimed that the RuM(fresh) changed from amorphous clusters of 15–25 nm height (mean height: 20.4 nm) to two different forms that are agglomerations with small crystallites. They formed nanorod-like structures of sizes in the ranges of 13–15 nm in height, 15–27 nm in width, and up to 70–110 nm in length after calcination (RuM(calcined)) [16]. Meanwhile, Tahmasebi Garavand et al. [17] investigated the coloration process of colloidal tungsten oxide nanoparticles in the presence of hydrogen gas. In their research, AFM analysis was used to estimate the size distribution of the nanoparticles.

Features of metal oxide colloidal nanocrystal characterization 89

Fig. 6.3 AFM topographic images of single-coated RuO2-mica samples: (A) RuM(fresh) and (B) RuM(calcined) [15].

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Fig. 6.4 (A) Two- and (B) three-dimensional AFM images of tungsten oxide nanoparticles on Si surface synthesized by pulsed laser ablation [17].

They performed the sample preparation by using the deposition method. The dried colloidal tungsten oxide nanoparticle sample was deposited on Si substrates before analyzing with AFM measurement by tapping mode. The resulting image of tungsten oxide nanoparticle colloids is depicted in Fig. 6.4, and it shows that the size of the nanoparticles ranges from 40 to 130 nm.

6.3

Spectral characterization of colloidal metal oxides

In this section, the fundamental principle of several characterizations on spectroscopy techniques such as Fourier transform infrared (FTIR), Raman spectroscopy, UV–vis spectroscopy, photoluminescence spectroscopy (PL), X-ray photoelectron spectroscopy (XPS), and nuclear magnetic resonance (NMR) spectroscopy are explained. The use of these spectral techniques in characterizing the colloidal metal oxides is also briefly discussed.

6.3.1 Fourier transform infrared spectroscopy FTIR is the term used to describe a Fourier transform (mathematical process) that responds to convert a large quantity of raw spectrometric data from a molecule or chemical structure into an infrared absorption spectrum. In principle, the spectrum represents a unique pattern or fingerprint of specific functional groups or chemical bonding by their characteristic absorption of infrared radiation in vibrational modes such as stretching, bending, twisting, rocking, wagging, and out-of-plane deformation occurring at different wavenumbers (or frequencies) in the IR region of the light spectrum [18]. It is also well known for its applicability for a wide range of materials and conditions for which it can be fully utilized to provide more information on qualitative and quantitative analysis. Technically, the wavelength range of interest is between 2.5

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and 25 μm (4000 and 400 cm
1) where the region is referred to as medium infrared [19, 20] The process involves emitting a beam of IR radiation from a glowing blackbody source before it reaches into the interferometer compartment and is subsequently split in two by the beam splitter. The split beam is then reflected by mirrors and recombined to create a constructive and destructive interference known as an interferogram. The resultant beam now reaches the sample that is placed in a sample compartment to produce a unique IR spectrum that is further displayed on the interferogram. The interferogram spectrum is the actual product of specific frequencies of energy absorbance by the individual samples through the vibration of the bonds within a molecule, and the results are collected together with wavelength information [21]. The desirable spectrum was acquired after being subtracted with the spectrum of the background by the FTIR interface software to nullify the background of the instrument operation. Identifying a suitable and effective method for sample handling in FTIR is crucial so that one can obtain the best quality data possible to avoid any disputes and improve confidence in the presentation of results. Generally, there are four well-known methods to analyze the samples: transmission, diffuse reflectance (DRIFTS), true specular reflectance/reflection absorption, and attenuated total reflection (ATR). Different methods require different operating principles. For example, a transmission method can be used alone without any attachment to other instrumentation accessories such as a microscope or liquid/gas cell [21]. The user can directly place the sample in the IR beam pathway. As the IR beam passes through the sample, the transmitted energy is measured and a spectrum is produced. However, this method is time consuming because the user must often prepare the sample into a mull, film, pellet, etc., before the transmission analysis can be carried out. Diffuse reflectance (DRIFT) works when samples are penetrated with an IR beam. Two types of reflected energy will be produced known as specular and diffuse reflectance. Specular reflectance occurs at the surface of the sample experiencing one or multiple reflections on the surface without any interaction while diffuse reflectance is produced from the interaction of the sample particle with the penetrated beam and subsequently scatter from the sample matrix. The diffuse reflectance consists of several pieces of spectral information on IR absorption. Furthermore, the DRIFTS accessory improves the collection of the diffuse reflectance energy while minimizing the specular reflectance energy. The sample preparation for this method still requires mixing/grinding the organic or inorganic samples with potassium bromide (KBr) into a fine powder (<10 μm), without the need for pelleting with a hydraulic press, to obtain accurate DRIFTS spectra in the IR middle region. Also, this method increased the spectra resolution while reducing the interference [22]. True specular reflectance is a method that works based on reflective efficiencies of a sample surface (flat, reflective, and large surfaces). Principally, each sample has its refractive index that differs with the light frequency to which it is exposed. In this case, the process involves measuring the energy that is directly reflected on the surface of the sample. By analyzing the frequency bands in which the change of the refractive index rate is high, the absorbance of the respective sample can be retained. The reflection-absorption works on the same basis; however, different sample properties

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lead to different circumstances. For instance, when the energy passes through the surface layer, it is possible that the energy that is being absorbed into the sample matrix would be subsequently reflected below the surface layer. Therefore, a combination of true specular reflectance and reflection-absorption can happen when the requirement for both approaches is matched to which outstanding qualitative data is desired. Attenuated total reflectance (ATR) is a method that provides a preliminary step to characterize samples with several advantages such as minimum preparation procedure (less labor-intensive), quick processing, and reduced error on results due to KBr grinding. This method is used to measure the changes that occur in an internally reflected IR beam that meets the sample through an optically dense and high refractive index crystal (e.g., zinc selenide, diamond). The energy is being absorbed by the sample when the sample is placed in contact with the ATR crystal, which subsequently produces an attenuated evanescent wave in the regions of the IR spectrum. Despite mixing the sample with KBr as in transmission FTIR, the sample is positioned directly on the sampling holder of the instrument over the optical window with the crystal. It is then held in place by a micrometer controlled compression clamp to warrant good contact between the sample and the crystal [22]. The FTIR spectroscopy analysis has become a robust method to obtain significant assessments and information about chemical composition characterizations, especially on colloidal metal oxide nanoparticles (NPs), due to the sensitivity of molecular vibrations to bond strengths and configurations. In this context, several studies have been carried out to effectively differentiate and quantify the spectra formed by the metal oxide. In 2008, Namduri and Nasrazadani prepared binary mixtures of iron oxides containing pure commercial magnetite (Fe3O4), maghemite (γ-Fe2O3), and hematite (α-Fe2O3) [23]. All these samples were mixed with KBr pellets before being compressed by hydraulic pressure with constant compression magnitude to avoid variance in absorbance intensity. The FTIR spectra collection was done for 32 scans with 2 cm
1 resolutions, and CaO (3640 cm
1) was used as the calibration curve to quantify the number of iron oxides present in the real samples collected from the secondary side of the Comanche peak steam electric station (CPSES). It was observed that the high absorption bands at high wavenumbers are due to OH stretching while at lower wavenumbers it is because of FedO lattice vibration. The FTIR spectra of magnetite, maghemite, and hematite exhibit strong IR absorption bands at specific reference wavenumbers of 570, 630, and 540 cm
1, respectively. The correlation factors of 0.822 (magnetite added to maghemite), 0.8584 (maghemite added to hematite), and 0.8708 (magnetite added to hematite) were also obtained. A further study was carried out by Kalam and coworkers, who prepared NiO nanoparticles via the formation of nickel linoleate before thermal decomposition at 400°C for 2 h [24]. The functional groups of the NiO NPs were analyzed by a JASCO 460 plus at room temperature in the range from 400 to 4000 cm
1 by using the KBr pellet method. The samples were spurred by the BOC Edwards gold-coating machine. Based on the FTIR spectra shown in Fig. 6.5, the main absorption bands of the OdH, CdH, symmetry, and asymmetry C]O stretching vibrations of the as-synthesized nickel linoleate were identified at 3423, 2930, 2847, 1725, 1579, and 1453 cm
1, respectively. The intensity of the peak at 3423 cm
1 is significantly decreased due to the

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elimination of the CdH and CdO bonds. A new band appears at 455 cm
1, which indicates that nickel linoleate is completely decomposed at 400°C and the band is the characteristic of the NidO stretching vibrational mode. The gradual decomposition of the precursor to produce NiO with high purity was confirmed by FTIR. Interestingly, further research has been carried out to study the effectiveness of FTIR in determining functionalized metal oxide nanoparticles. For instance, Shah et al. [25] prepared iron oxide in situ functionalized with gallic acid (GA) via the coprecipitation method. GA was used as various water-soluble antioxidants for

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therapeutic applications. The FTIR spectra of iron oxide NPs, in situ functionalized (GA1 and GA2), and postfunctionalized (GA3) were obtained (Fig. 6.6). The peaks at 550, 551, 554, and 554 cm
1 represent a characteristic FedO stretching for iron oxide NPs, GA1, GA2, and GA3, respectively. The broad peak at 3100–3200 cm
1 refers to –OH stretching of phenol. The peaks at 1079, 1089, and 1078 cm
1 correspond to Fe-O-C for sample GA1, GA2, and GA3, respectively. The peaks at 1633, 1611, and 1630 cm
1 confirm the presence of a carbonyl group in GA1, GA2, and GA3, respectively. Further study on the surface reactivity of iron oxide NPs was attained after the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay. In this case, functionalized iron oxide samples were mixed with excess DPPH. The mixture was kept in the dark for 30 min and then washed thrice with ethanol. NdO stretching gave two peaks at 1530, 1310, 1513, 1335, 1530, and 1329 cm
1 for GA3, GA1, and GA2, respectively. This confirms the attachment of the DPPH radical to the surface of functionalized iron oxide and not a single peak for DPPH radicals appeared in the FTIR spectra. To summarize, the FTIR analysis confirmed that functionalized iron oxide is scavenged the DPPH radicals and yields a functionalized iron oxide-DPPH composite. It was suggested that the free radicals can be easily removed from the system by a magnet and can then be further reused.

6.3.2 Raman spectroscopy Raman spectroscopy is a vibrational spectroscopic technique used to provide information on molecular vibrations and crystal structures that can be further used for sample identification and quantification. This technique uses a shining monochromatic light source (i.e., laser) to irradiate a sample. It generates an infinitesimal amount of Raman scattered light, which is detected as a Raman spectrum using a CCD (charge coupled device) camera. Most of the scattered light is of the same frequency as the excitation source; this phenomenon is known as Rayleigh or elastic scattering, and there is no change in energy. However, a tiny percentage of scattering is an inelastic process. Thus, a scattered light has a different energy from incident light, which is why this inelastic scattering is called Raman scattering (Raman effect). In other words, a very small amount of the scattered light (ca. 10
5% of the incident light intensity) is shifted in energy from the laser frequency due to interactions between the incident electromagnetic waves and the vibrational energy levels of the molecules in the sample. Plotting the intensity of this “shifted” light versus frequency would produce a Raman spectrum. Commonly, Raman spectra are plotted concerning the laser frequency such that the Rayleigh band lies at 0 cm
1. On this scale, the band positions will lie at frequencies that correspond to the energy levels of different individual functional group vibrations. Thus, the Raman spectrum can be interpreted similarly to the infrared absorption spectrum. Furthermore, the fingerprinting pattern in a Raman spectrum makes it possible to identify substances, including polymorphs, and evaluate local crystallinity, orientation, and stress. By studying the spectra, one can identify the rotational level and thus the particular molecule. Similarly, the intensities of a specific Raman line help to determine the concentration of a molecule in the sample. By these means, Raman spectroscopy can be used to perform both qualitative and quantitative analysis. The advantage of using

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Raman analysis is that the Raman effect can be manifested itself in accordance to the light scattered off the sample as opposed to the light absorbed by the sample. Subsequently, it requires little or no sample preparation and is insensitive to aqueous absorption bands. This process further facilitates the measurement of solids, gases, and liquids indirectly or through transparent containers such as glass, quartz, and plastic [26, 27]. Raman scattering can be classified into two categories: Stokes Raman and antiStokes Raman. Stokes Raman scattering is a process in which an electron is excited from the ground state and falls to a vibrational state. It involves energy absorption by the molecule. Thus, Stokes Raman scattered light has less energy (longer wavelength) than the incident light. In contrast, anti-Stokes Raman scattering is a process in which an electron is excited from the vibrational state to the ground state. It involves an energy transfer to the scattered photon. Thus anti-Stokes Raman scattered light has more energy (shorter wavelength) than the incident light. Nevertheless, the dominant process is Rayleigh scattering, and Raman scattering is an extremely weak process because only one in every 106–108 photons scatters. The ratio of Stokes Raman and anti-Stokes Raman scattering depends on the population of the various states of the molecule. At room temperature, the number of molecules in an excited vibrational state is smaller than that of the ground state. Thus the intensity of Stokes Raman light is higher than anti-Stokes Raman light. The intensity of anti-Stokes Raman light increases when the temperature increases and hence the intensity ratio of anti-Stokes and Stokes light can be used to measure the temperature of the sample. In the standard measurement, Rayleigh scattered light is rejected utilizing a notch filter, and only the Stokes Raman scattering is recorded [28]. Colloidal metal oxide NPs have been of continuous research interest because their intrinsic properties could help to improve their specific catalytic performance. This can be seen from a study done by Singhal and coworkers [29], where they prepared colloidal Fe-doped indium oxide NPs via simple one-pot thermal decomposition at 220°C for 2 h. In this context, Raman was used to study the doping effects in which the shifts in lattice Raman vibrational energies can occur with increasing dopant concentration. From the data obtained (Fig. 6.7A), the observed Raman spectra have identified several bands around 306, 365, 494, and 628 cm
1 that can be associated with phonons and structural properties of indium oxide. All the dominant peaks of In2O3 are also observed in the Fe-doped In2O3 spectra. However, the spectra exhibited broad, less intense, and relatively shifted toward lower frequencies as the iron content in the (In1
xFex)2O3 NPs increases from 0 to 0.1. These results reveal that the local symmetry in the NPs is different from that of bulk, but the crystal structure is the same in both. The Raman band at 306 cm
1 for (In0.9Fe0.1)2O3 NPs exhibits a downward shift of  15 cm
1. This can be associated with the decrease in binding energy of the IndO bond as a result of the substitution of In3+ by Fe3+. Furthermore, no additional Raman bands are observed for (In1
xFex)2O3 NPs as x changes from 0 to 0.1, indicating the absence of any impurity phase. Magnetic properties of the NPs showed a weak ferromagnetic behavior at room temperature, which results from the low dopant concentration. Therefore, fewer donor electrons are available in the sample to form shifted defect bands, which would align the 3D magnetic spins in large domains.

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1.0

2LO mode, 1321 cm–1 G=66 cm–1

Bulk (l=532 nm) Si(111) (l=515 nm) TERS/Ag tip (l=532 nm) SERS/Au tip (l=633 nm) Spin-wave Two Magnon

0.5

1584 cm–1 G=75 cm–1

0.0

Bulk In2O3

1200

(A)

200

300

400 500 600 Raman shift (cm–1)

700

(B)

1400 1600 Raman shift (cm–1)

Fig. 6.7 (A) Room-temperature Raman spectra of bulk and (In1
xFex)2O3 NPS, where x ¼ 0.0, 0.05, 0.1 [29]. (B) Second-order 2LO mode and magnon mode are visible in the Raman spectra. The spectrum of the bulk material measured at λ ¼ 532 nm was adapted from the RRUFF database. The spectra of NPs on silicon using 514.5 nm excitation and on a gold tip were measured using 632.8 nm excitation. The TERS spectrum of nanoparticles with a silver tip was measured under 532 nm excitation [30].

Further study on the colloidal iron oxide (hematite) NPs has been carried out by Rodriguez et al. [30]. They have prepared the NPs via forced hydrolysis of an acidic ferric chloride solution (pH 2.0) at 95°C for ferric nitrate solution. In this study, the prepared samples were analyzed by tip-enhanced Raman spectroscopy (TERS) using atomic force microscopy (AFM) mounted on an inverted microscope with a confocal spectrometer and a CCD camera. The enhanced spectra were obtained after briefly placing a microdrop (5 μL) hematite colloid in contact with a freshly etched gold or silver tip followed by sucking off the drop. Then, the samples were drop-coated on a thin glass microscope slide and dried. The incident laser power used was 1 mW at 532 nm. For laser focusing an oil immersion, a long-distance objective (40 , N.A. 1.35, Olympus) was used. Spectra were recorded with an acquisition time of 5 s. In the spectral region of 1200–1700 cm
1 (Fig. 6.7B), two dominant bands can be observed in the enhanced spectra collected from NPs on metallic tips. Precisely, the band centered around 1318 cm
1 is a second-order 2LO phonon mode while the one centered around 1584 cm
1 is ascribed to a spin-wave or two-magnon mode. This band is practically absent in conventional Raman spectra of those NPs directly deposited on silicon (111) or a glass substrate. It was also observed that there is no significant difference in the results obtained under different excitation wavelengths (green laser, λ ¼ 514.5 nm) and using a silver tip. Thus, the findings showed that the coupling of localized optical fields and spin-waves could provide a way to excite and control spin-waves with potential implications in spintronics and magnonics applications. Meanwhile, the combination of a colloidal iron oxide with carbon-based materials such as graphite and graphene has been investigated by Champi et al. [31]. In their study, the spherical iron oxide NPs were obtained using the laser ablation technique,

98

Colloidal Metal Oxide Nanoparticles

which is formed primarily by α-hematite (α- Fe2O3), γ-hematite (γ-Fe2O3), and goethite (Fe-OOH) phases. These three oxides were superficially incorporated on graphite microflakes (MFG) and a few layers of graphene microflakes (FLG) via a thermal process to investigate their influence on the electrooptical properties after the combination process. The analysis showed that Raman analysis at λ ¼ 422 nm and 534 nm before (MFG-422 and MFG-534) and after graphite microflake doping (MFG-422/ FexOy and MFG-534/FexOy) has an intensity in the band D, much more pronounced after the incident green laser beam (Fig. 6.8). Also, this band is overlapped by other energy vibrational modes in case of the incident blue laser beam. Meanwhile, a few layers of graphene microflakes at 422 nm, mainly 5 and 10 layers before (5-FLG and 10-FLG) and after doping (5-FLG/FexOy and 10-FLG/FexOy), displayed that the appearance of the band at D + D00 is related to the scattering of phonons at the two edges of the CdC chains, forming the FLG by the presence or formation of surface defects, resulting from interaction with the FexOy NPs after insertion. The variations in Raman shift can be associated with the alteration of the vibrational modes of the CdC for an effect of weak interaction with nanostructures for 10-FLG, MFG-422, and MFG-534. However, the shift is detected in the 2D band at 5-FLG. This phenomenon can be attributed to the increase in charge carriers caused by strong interaction doping.

G

G

l = 534 nm

l = 422 nm 2D

2D

D+D″

MFG/FexOy

10-FLG/FexOy

D

l = 422 nm

l = 534 nm

G

G 2D

2D

D+D″ 10-FLG

D

l = 422 nm

G

Intensity (a.u.)

Intensity (a.u.)

MFG

l = 422 nm

G

2D

2D D+D″

MFG/FexOy

5-FLG/FexOy

l = 422 nm

l = 422 nm

G

G 2D

D+D″

2D

MFG 5-FLG

1200

(A)

1400

1600

2200 2400 2600 2800 3000

Raman shift (cm–1)

1200

(B)

1400

1600

2200 2400 2600 2800 3000

Raman shift (cm–1)

Fig. 6.8 (A) Raman spectroscopy at 422 nm and 534 nm of graphite flakes before (Gr-422 y Gr-534) and after doping (Gr-422/FexOy y Gr-534/FexOy). (B) Also, we show the Raman spectra at 422 nm from GPC of 5 and 10 layers before (5-FLG and 10-FLG) and after doping (5-FLG/ FexOy and 10-FLG/FexOy) [31].

Features of metal oxide colloidal nanocrystal characterization

99

In addition, the G band shows invariability before and after doping. This analysis was used to calculate the maximum width of the dimension (FWHM) of the 2D and G bands, which had a more significant magnitude after doping as the number of graphene layers increased (5 to 10 cm
1). This process further confirmed that the relaxation process followed by doping involved the back donation process. This was generated by a strong interaction effect in the case of the 5-FLG samples, which decreased with increasing the number of graphene layers.

6.3.3 UV–vis spectroscopy UV-DR spectroscopy has often been considered as a useful tool for the optical characterization of metal oxide NPs. Reflectance spectroscopy is a standard technique in the determination of the absorption properties of materials whereby it is very closely related to UV–vis spectroscopy, and both of these techniques use visible light to excite valence electrons to empty orbitals. The difference in these techniques is that UV–vis spectroscopy measures the relative change of transmittance of light as it passes through a solution, whereas diffuse reflectance is used to measure the relative change in the amount of reflected light off a solid surface. A solution that is entirely transparent and colorless has 100% transmission of all visible light, which means that it does not contain any dissolved components that could affect the electronic transitions over that energy range. Of the same means, a white powder would effectively reflect 100% of all visible light with which it comes into contact. However, if the material has electronic energy levels that are separated by energy in the visible region, then it might absorb some of the light energy to move electrons from the filled energy level (valence band) into this empty level (conduction band). This causes a relative decrease in the amount of light at that energy in accordance to the reference source. In other words, the percentage of transmission or reflectance would subsequently decrease [32–35]. In the case of colloidal metal oxide NPs, the properties that can potentially be estimated from the diffuse reflectance are the band-gap energy (also referred to as the band gap) and the absorption coefficient. The determination of the band gap using diffuse reflectance measurement is considered a standard technique. In principle, the solid sample must be sufficiently thick (between 1 and 3 mm) so that all the incident light is scattered or absorbed before reaching the back surface of the sample. The light reflection works in the ultraviolet (10–420 nm), visible (420–700 nm), and nearinfrared (700–2500 nm) regions by the solid samples. The same procedure may apply to the sample with coatings [36]. However, for nonopaque substrates and coatings with optically smooth surfaces, a combination of reflectance and transmittance measurements is needed to endow the sample with specific optical properties. This can be achieved by plotting the data using standard optical equations, which take reflection and the transmission interface into consideration. In addition, these conventional methods allow the determination of the absorption coefficient of the sample as a function of wavelength, or at least a variable proportional to the absorption coefficient; it can then be used to find that specific band gap. The absorption coefficient also allows the depth distribution of light absorption in the metal oxide NPs to be determined.

100

Colloidal Metal Oxide Nanoparticles

Due to the low scattering effect in solid samples, it is easy to extract the band-gap (Eg) values from their absorption spectra provided that their thickness is known. However, in colloidal samples, the scattering effect is enhanced because the more superficial area is exposed to the light beam. In normal incidence mode, dispersed light is considered as absorbed light, and the technique (optical absorption) does not distinguish between the two phenomena. Unlike transmission UV–Vis, which follows Beer-Lambert’s Law, the Kubelka-Munk signal intensity function (K-M) is used in UV-DR to linearize the diffuse reflectance signal against chromophore concentration [37, 38]. The band-gap energy can be determine using the equation of [F(R)  hv]2 ¼ A(hv
Eg). The values for direct band-gap energy were plotted against excitation energy (hυ) where the absorption coefficient F(R) is calculated according to the K-M equation [38–40] FðRÞ ¼

ð1
RÞ2 2R

where R is the reflectance value of the thick samples layers, and A is a proportionality constant. Later, the band-gap energy was then estimated based on the extrapolated linear line according to Tauc’s plot. This direct relationship can be used for quantitative studies on solid or powder samples of infinite layer thickness containing uniformly distributed metal ions in low concentration [41, 42]. Colloidal metal oxide NPs offer a unique combination of intrinsic and tunable optical properties, which makes them an ideal class of materials for efficient charge separation. For instance, Goharshadi et al. [43] studied the preparation of cerium oxide NPs via the microwave method assisted by a set of ionic liquids on the bis (trifluoromethylsulfonyl)imide anion and different cations of 1-alkyl-3methyl-imidazolium. The UV-DR spectra of the samples were recorded using a photodiode array equipped with a glass of 1 cm path length within the range of 300–550 nm in the air (Fig. 6.9I). From the study, the prepared samples exhibit a strong absorption band (λ < 400 nm) at the UV region due to the charge-transfer transitions from O 2p to Ce 4f, which overwhelms the well-known f–f spin-orbit splitting of the Ce 4f state. Based on the spectra, most of the UV light is blocked, allowing the CeO2 NPs to become a UV blocker. The results reveal that the band gap energy increases when the particle size is decreased, indicating a blue shift regarding the absorption edge of the NPs. This phenomenon is attributed to the quantum size effect. Because the size-related band-gap shift of semiconductor nanocrystals can be quantified, it is also possible to calculate an optical particle size with the band-gap shift measured from the absorption spectra. It was observed that the particle size of the samples is in the range of 6.33–8.00 nm with almost a similar band-gap energy (3.48–3.54 eV). Interestingly, tuning the size, shape, and optical properties of the colloidal CeO2 NPs could endow the materials with desirable features and functions by incorporating other metal oxides or appropriate elements into the host lattices. This can be seen from work done by Magdalane et al. [44], who prepared CeO2–CdO NPs via simple chemical precipitation and the hydrothermal method. The analysis on UV-DR is carried out in the wavelength range of 200–800 nm and the band gap is calculated based on the

Absorbance (a.u.)

4 3

(D) (C)

2

(B) 1

(A)

0 300

200

400

(I) Direct Bandgap

(A)

600

700

800

80 60 40 3.19 eV 20

(B)

Indirect Bandgap

4

Intensity (arb. units)

100

Intensity (arb. units)

500

Wavelength (nm)

3 3.09 eV 2

1

0

0 1

2

3

4 hv (eV)

5

6

7

1

2

3

4 hv(eV)

5

6

7

3.5

80 60 40

(D)

3.0 Intensity (arb. units)

Intensity (arb. units)

Indirect Bandgap

(C)

Direct Bandgap

100

3.15 eV

20 0

2.5 2.0 2.90 eV

1.5 1.0 0.5 0.0

1

2

3

4 hv (eV)

5

6

7

1

2

3

4 hv (eV)

5

6

7

(II) Fig. 6.9 (I) UV-DR spectra for CeO2 NPs prepared using different ionic liquids (ILs) (A) No ILs was used, (B) 1-ethyl-3-methyl-imidazolium bis (trifluoromethylsulfonyl) imide ([C2mim] [NTf2]), (C) 1-butyl-3-methyl-imidazolium bis (trifluoromethylsulfonyl) imide ([C4mim] [NTf2]), and (D) 1-hexyl-3-methyl-imidazolium bis (trifluoromethylsulfonyl) imide ([C6mim] [NTf2]) [43]. (II) UV-DR spectra of CeO2–CdO nanocomposite. (A) Direct band gap, (B) indirect band gap via precipitation method, (C) direct band gap, and (D) indirect band gap via hydrothermal method [44].

102

Colloidal Metal Oxide Nanoparticles

Kubelka-Munk function by plotting [F(R)  hv]1/2 versus photon energy for the indirect band gap and [F(R)  hv]2 versus photon energy for direct band-gap transition. The results obtained showed that both direct and indirect band-gap energies were found to decrease in parallel with the decrease in particle size of the NPs when compared to the individual metal oxides (Fig. 6.9I). A hydrothermally synthesized CeO2– CdO sample displayed band-gap values of Ed ¼ 3.15 eV (393 nm) and Ei ¼ 2.90 eV (427 nm), whereas a CeO2–CdO sample prepared by the precipitation method exhibited slightly higher band-gap values of Ed ¼ 3.19 eV (388 nm) and Ei ¼ 3.09 eV (401 nm). It was observed that the changes in the band-gap energy are due to the different preparation methods, average grain size, shape, and structural disorder in the lattice. The optical property of the absorbance of cerium oxide-cadmium oxide in the UV region suggests that it can be used as a good candidate for UV light-active materials. The combination of CeO2 and CdO could reduce the band gap of CeO2 by increasing the amount of Ce4+ states, resulting in the formation of localized energy states that are closer to the conduction band. Furthermore, the peak at 400 nm is associated with the fluorite cubic structure of nanocomposites due to the quantum size effect of the blue shift in the UV–visible spectra, which confirm the charge between the O 2p and Ce 4f states in O2– and Ce4+. The band-gap engineering through lattice substitution of other colloidal metal oxides has been further studied by Gionco et al. [45]. In their study, they prepared zirconium dioxide doped with cerium and erbium through the hydrothermal process. The UV-DR spectrometer coupled with an integration sphere was used to analyze the band-gap energies (Eg) of the prepared samples. From the spectra (Fig. 6.10), pure ZrO2 showed some band-gap transition occurring at about 250 nm (5 eV), which is due to the photoexcitation of the electron from the valence band (vb) to the conduction band (cb). A very weak absorption between 250 and 350 nm is also observed, and it was due to the traces of point defects that always present in the pure materials with no absorption happening in the visible region (λ > 400 nm). The use of different types and amounts of the dopant dramatically affects the optical properties of the materials. In the case of Ce-doped ZrO2, the presence of the dopant strongly influences the transition of an electron from vb to cb of zirconia by increasing the absorption edge (redshift) of the oxide with increasing cerium content. It was also observed that the samples change their color from the pure white of the pure zirconia to a primrose yellow for 5% Ce-doped ZrO2. The optical properties of the nanocomposite were evaluated using Tauc’s plot and linearization of the plot using (αhν)2 versus hν for typical direct band-gap energy. As can be seen, the addition of Ce gradually narrows the Eg value down to 3.55 eV, which corresponds to a 1.6 eV narrowing. In the case of Er-doped ZrO2, there are two distinct effects. The first one is an absorption band centered at about 290 nm, which is similar, though far less intense, to that observed in the same region for Ce–ZrO2. This constitutes a maximum Eg value for the 0.5% Ce–ZrO2 sample, then decreases in intensity for the 1.0% Ce–ZrO2 sample and finally increases again for the 5% Ce–ZrO2 sample. The second effect is the presence of a multitude of absorption bands related to the states of Er3+. The intensity of these bands increases when increasing the Er content and their presence indicates that Er ions are well diluted in the matrix and preserve their optical properties. The band-gap energy in the case of Er doping is almost unmodified, maintaining its value of around

Features of metal oxide colloidal nanocrystal characterization

103

Fig. 6.10 UV-DR spectra of (A) Ce-doped ZrO2 of (1) pure ZrO2, (2) 0.5% Ce-doped ZrO2, (3) 1.0% Ce-doped ZrO2, (4) 5% Ce-doped ZrO2, and (B) Er-doped ZrO2. Inset of (A): Tauc plot of 5% Ce-doped ZrO2. Inset of (B): magnification of the 200–800 nm region [45].

5.1 eV. It was believed that the intraband gap states formed by the rare Earth orbitals are responsible for the “double jump” absorption leading to excitation of the electrons in the cb (in particular for Ce–ZrO2).

6.3.4 Photoluminescence spectroscopy Photoluminescence spectroscopy is a conventional technique used to characterize colloidal metal oxide, where the information from its luminescence spectra can be extracted to observe the material imperfections, impurities, band gap, and recombination mechanisms. This technique is a nondestructive and noncontact method in analyzing the electronic structure of materials. In principle, the method uses a laser

104

Colloidal Metal Oxide Nanoparticles

beam that is directed onto a sample where the light is being absorbed or captured by the sample, inducing a photoexcitation process. This process causes the material to experience excitation of electrons from a ground state to a higher electronic state, and then releases energy (photons) as it relaxes and returns to its original lower energy level. When these electrons return to their initial or equilibrium states, the excess energy released may include the emission of light (photoluminescence). In other words, the energy of the emitted light relates to the difference in energy levels (band gap) between the two electronic states involved in the transition process. In addition, the quantity of the emitted light is related to the relative contribution of the radiative process. Moreover, this instrument uses an excitation wavelength that is selected by one monochromator, and luminescence is observed through a second monochromator, usually positioned at 90°C to the incident light to minimize the intensity of scattered light reaching the detector. If the excitation wavelength is set and the emitted radiation is scanned, an emission spectrum is produced [46–48]. The spectrum is recorded by measuring the intensity of emitted radiation as a function of either the excitation wavelength or the emission wavelength. An excitation spectrum is obtained by monitoring the emission at a fixed wavelength while changing the excitation wavelength. When corrected for variations in the source’s intensity and the detector’s response, a sample’s excitation spectrum is nearly identical to its absorbance spectrum. The excitation spectrum offers a convenient means for selecting the best excitation wavelength for quantitative or qualitative analysis. In an emission spectrum, a fixed wavelength is used to excite the sample, and the intensity of emitted radiation is monitored as a function of wavelength. Although a molecule has only a single excitation spectrum, it has two emission spectra, one for fluorescence and one for phosphorescence. When the sample absorbs an ultraviolet or visible photon, one of its valence electrons moves from the ground state to an excited state with conservation of the electron’s spin. Emission of a photon from the singlet excited state to the singlet ground state or between any two energy levels with the same spin is called fluorescence (Fig. 6.11). The probability of fluorescence is very high and the average lifetime of an electron in the excited state is only 0.1–10 ns. Thus, fluorescence decays rapidly once the source of excitation is removed. In some cases, an electron in a singlet excited

(A)

Singlet ground state

Singlet

(B) excited state

Triplet

(C) excited state

Fig. 6.11 Electron configurations for (A) a singlet ground state, (B) a singlet excited state, and (C) a triplet excited state.

Features of metal oxide colloidal nanocrystal characterization

105

state is transformed to a triplet excited state in which its spin is no longer paired with the ground state. Emission between a triplet excited state and a singlet ground state or between any two energy levels that differ in their respective spin states is called phosphorescence. Because the average lifetime for phosphorescence ranges from 1 ms to 10 s, phosphorescence may continue for some time after removing the excitation source [49]. In a fluorimeter, the excitation and emission wavelengths are chosen based on absorption or interference filters. A low-pressure mercury vapor lamp is typically used as the excitation source for the fluorimeter due to intense emission lines distributed throughout the ultraviolet and visible region. Meanwhile, in a spectrofluorimeter, a high-pressure xenon arc lamp is usually used as the excitation source when equipped with a monochromator due to the continuous emission spectrum. The sample cells used for molecular fluorescence are similar to molecular absorption. In phosphorescence, two out-of-phase choppers can be used to block the emission from reaching the detector when the sample is being excited and to prevent source radiation from reaching the sample while measuring the phosphorescence emission. Recently, considerable research has been focused on the exploration of the unique properties of the NPs, especially the photoluminescence (PL) properties. This is because PL may reveal the presence of crystalline defects resulting from the preparation process. Concerning this, the oxygen vacancies have been assumed to be the most likely candidates for the recombination centers in luminescence processes [50]. This can be seen from a study conducted by Taunk et al. [51], who prepared zinc oxide NPs through the chemical precipitation method. The excitation spectra were recorded under 500 nm wavelength with a broad peak at 235 nm. Meanwhile, the emission spectra were recorded under a UV light of 235 nm wavelength, and the peaks were observed in the blue region around 407 nm with a broad peak at around 484 nm. The peak at 407 nm appeared from the recombination of free excitons through an exciton-exciton collision process or due to the intrinsic defects such as oxygen and zinc interstitials. The broad blue emission band at around 484 nm is the result from the radiative recombination of a photogenerated hole with an electron occupying the oxygen vacancy. Nevertheless, surface states have also been recognized as the cause of the visible emission in the ZnO NPs. Moreover, the PL intensity is highest indicating the highest recombination of electrons and holes [52]. It is believed that there are some defects in the ZnO nanostructures at the surface and subsurface due to their fast reaction formation process and sizeable surface-to-volume ratio. There are also some studies that have been done concerning the interfaces change in ZnO NPs. Koscis and coworkers [53] studied the preparation of ZnO NPs via the vacuum (vapor phase) transfer technique to avoid the uncontrolled influence of oxygen and other contaminants from the air. From their study, they have established the relationship between PL emission properties and the composition of the solid-gas interface (Fig. 6.12I). Apparently, the room temperature UV excitation light of hν ¼ 4.6 eV (λ ¼ 270 nm) produces a strong and broad PL emission band at hν ¼ 2.1 eV (λ ¼ 590 nm) on native ZnO (ZnOnat), which was attributed to oxygen interstitials in the surface of the NPs. Thermal annealing of activated ZnO (ZnOact) leads to changes in the PL emission spectra by shifting 0.2 eV to lower energies at

106

Colloidal Metal Oxide Nanoparticles

(I) 1.5´105

ZnOact PL intensity / counts

PL intensity / counts

ZnOnat p < 10–6 mbar p (O2) = 10 mbar

1.0´105

5.0´104

(A)

0.0 300

400

500

600

700

800

Wavelength / nm

1.5´105

p < 10–6 mbar p (O2) = 10 mbar

1.0´105

5.0´104

(B)

0.0 300

400

500

600

700

800

Wavelength / nm 0.0 mol%

Intensity (a.u.)

Intensity (a.u.)

(II) 0.0 mol% 0.1 mol% 0.5 mol% 1.0 mol%

676 606

392

400

(A)

500

600

700

Wavelength (nm)

800

400

(B)

500

600

700

800

Wavelength (nm)

Fig. 6.12 (I) Photoluminescence emission spectra (A) ZnOnat and (B) ZnOact NPs in vacuum (black) and in O2 gas atmosphere at a pressure of 10 mbar (gray) [53]. (II) (A) PL emission of ZnO:Ag nanoparticles with different Ag concentration and (B) deconvoluted PL curve of pure ZnO [54].

hv ¼ 1.9 eV (λ ¼ 650 nm). Both types of emissions have been related to excess oxygen in ZnO NPs. The activation-induced changes in the PL emission properties can be due to a variety of reasons that include changes in the level of nonstoichiometry of the oxide, the concentration of luminescent-related defects, particle size and shape, and, ultimately, the composition of the particle surfaces. Further research had been carried out regarding the properties and characteristics of ZnO NPs doped with other elements to facilitate the course of their practical applications. For instance, Kumar et al. [54] investigated the role of Ag doping on the surface characteristic of ZnO via a simple and easy solution-combustion method. This study demonstrated that a different doping concentration of Ag would subsequently affect its PL behavior. The main features of the PL spectra of ZnO can be classified into two groups: near band edge emission (BEE) and deep level emission (DLE) (Fig. 6.12II). For the pure ZnO, the emission band consists of a weak UV band (near band edge) at around 378 nm and a combination of an orange band at 614 nm and a red band at approximately 753 nm. It was reported that the visible emission from ZnO consists of violet-blue, green, and orange-red emission, and they attributed these to Zni, Vo, and Oi intrinsic defect levels, respectively. The increase in UV intensity was due to

Features of metal oxide colloidal nanocrystal characterization

107

the enhancement of crystallinity. In addition, the intensity of DLE decreased with an increase in the Ag concentration from 0 to 1 mol%, and thus, the related defect emission of ZnO NPs was also reduced. The reduction of DLE with Ag doping indicated a decline in the defects and improved the crystallization of ZnO. In the DLE region, two peaks were observed at 606 and 676 nm while BEE was observed at 392 nm. It was believed that the shifting in the peak position in the orange-red emission is due to the different kinds of transitions. Furthermore, the origin of the visible emission peaks identified at  600–760 nm is generally attributed to DLE such as Vo and Oi, which were observed in the oxygen-rich sample.

6.3.5 X-ray photoelectron spectroscopy X-ray photoelectron spectroscopy (XPS,) also known as electron spectroscopy for chemical analysis (ESCA), is the most widely used method for the surface chemistry of a material that covers the measurement of the elemental composition, empirical formula, chemical state, and electronic state of the elements within a material. In general, the XPS spectra are obtained by irradiating a solid surface with a beam of X-rays that originally came from electron emission guns, followed by the generation of an X-ray photon by a monochromator. As the sample absorbs an X-ray photon, the photoelectron will be emitted from the surface of the sample. The kinetic and binding energy of the electron depends on the photon energy irradiated on the surface of the sample. A photoelectron spectrum is recorded by counting ejected electrons over a range of electron kinetic energies. The elemental identity, chemical state, and quantity of a detected element can be determined and measured from the binding energy and intensity of a photoelectron peak in an XPS spectrum. XPS analysis does not involve complicated sample preparation that can directly use the as-synthesized sample for analysis. Generally, the data analysis is conducted using specific software such as CASAXPS, Igor Pro, Unifit software, etc. Several researchers have employed Origin software to fit their XPS spectra, which is also helpful in obtaining the fitted highresolution XPS spectra. Illustration of a typical experimental configuration for X-ray photoelectron spectroscopy experiments, together with the various types of measurements possible, is shown in Fig. 6.13. In the case of the metal oxide colloidal, the XPS analysis was usually conducted to further comprehend the chemical and bonding environment of the prepared metal oxides [56, 57]. Based on XPS analysis, the success of metal oxide synthesis and formation can be validated. For instance, the creation of hydrogenated ZnO@MnO core-shell nanocables prepared by a wet chemical process can be observed in the high-resolution XPS spectra of Mn 2p and Zn 2p (Fig. 6.14I) [58]. Other than that, the impurities of the metal oxide lattice structure also can be analyzed by the XPS technique. The element of doping in the metal oxides can reduce its band gap where this band gap gives a significant impact on optical properties for photocatalysis application. It has been reported that the incorporation of metal and nonmetal dopants in the metal oxide lattice could enhance visible light harvesting ranging from 460 to 698 nm, which potentially utilizes 13%–49% of the solar energy irradiation [60]. For example, the reduction of the TiO2 band gap from 3.2 eV to

108

Colloidal Metal Oxide Nanoparticles

Fig. 6.13 Illustration of a typical experimental configuration for X-ray photoelectron spectroscopy experiments, together with the various types of measurements possible, including (A) simple spectra or energy distribution curves, (B) core-level photoelectron diffraction, (C) valence-band mapping or binding energy vs k plots, (D) spin-resolved spectra, (E) exciting with incident X-rays such that there is total reflection and/or a standing wave in the sample, (F) using much higher photon energies than has been typical in the past, (G) taking advantage of space and/or time resolution, and (H) surrounding the sample with high ambient sample pressures of several torrs [55].

(2.80–2.95 eV) can be attained by controlling the concentration of carbon and nitrogen doping in the prepared samples [52, 61–64]. The carbon and nitrogen doping can be observed in C 1s and N 1s high-resolution XPS spectra, as shown in Fig. 6.14II. Based on Fig. 6.14IIA, the nitrogen atom successfully substituted with an oxygen atom in TiO2 can prove by the presence of a pair of N 1s features around 396.0 and 399.9 eV [59], while the carbon atom does not substitute oxygen atom in the lattice of TiO2 because a peak around 281 eV resulting from TidC bond [61] does not presence in Fig. 6.14IIB. The interaction of metal oxides with another chemical environment can be estimated by the shifting of the binding energy of the XPS spectra [65]. Besides, it was reported that the colloidal suspensions of hematite (α-Fe2O3) in contact with aqueous solutions of 50 mM alkali metal chloride electrolytes (NaCl, KCl, RbCl, CsCl) were investigated by X-ray photoelectron spectroscopy (XPS) [66]. XPS detected Na+, K+, Rb+, Cs+, and Cl
at the hematite/water interface during adsorption/desorption of the electrolytes. A significant shift in the binding energies of surface-bound species was induced by the electric potential of the hematite/water interface.

Features of metal oxide colloidal nanocrystal characterization

Mn 2p data Mn 2p3/2

Intensity (a.u.)

642.2 eV

Mn 2p1/2

653.8 eV

635

(A)

640

645

650

655

660

Zn 2p1/2

1044.4 eV

1020

1030

(B)

Binding energy (eV)

Zn 2p data Zn 2p3/2

1021.3 eV

Intensity (a.u.)

(I)

109

(II) Ti-N

A

Intensity

Intensity

1050

C-H C-H

a

N-H

1040

Binding energy (eV)

N-H

Ti-N

B

C-H

b c

C=O

C-C

C-O C-H

d

C-C C-O

C=O

(A)

408

404

400

396

Binding energy (eV)

392

(B)

290

288

286

284

282

280

278

Binding energy (eV)

Fig. 6.14 (I) XPS spectra of (A) Mn 2p and (B) Zn 2p collected from the HZM core/shell nanocable. Mn 2p3/2 and Mn 2p1/2 peaks were located at ca. 642.2 and 653.8 eV, suggesting Mn4+ ions. The Zn 2p3/2 and Zn 2p1/2 lines were found at the binding energies of about 1021.3 and 1044.4 eV, which were consistent with the values reported for ZnO [58]. (II) (A) N 1s highresolution XPS spectra of (a) N3-TiO2 and (b) C3-N3-TiO2 samples calcined at 500°C. (B) C 1s high-resolution XPS spectra of (a) undoped TiO2, (b) N3-TiO2, (c) C3-TiO2, and (d) C3-N3-TiO2 samples calcined at 500°C [59].

6.3.6 NMR spectroscopy NMR spectroscopy is an analytical chemistry technique used in quality control and research for determining the content and purity of a sample as well as its molecular structure. NMR spectroscopy, which is sensitive to the short-range order of all the resonant nuclei in the sample investigated, should be ideal to study nanomaterials, where the long-range order is usually interrupted by the surface and other defect sites [67]. In principle, this spectroscopy technique relies on the interaction between material and electromagnetic radiation. This technique is employed to observe the local magnetic fields around the atomic nuclei of the individual material. The NMR signal is obtained when sensitive radio receivers detect the excitation of the material nuclei with radio waves into the nuclear magnetic resonance. This gives access to details of the electronic structure of a molecule and its individual functional groups. However, not all nuclei are suitable for NMR. In fact, 1H and 13C are the essential NMR active nuclei in organic chemistry.

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Co3O4@ heparin heparin

Selective broadening of HI of I2S residues

heparin Co3O4 @heparin

H1 of I2S residues

6

(A)

5

4

3

2

ppm

6

5

4

3

2

ppm

(B)

Fig. 6.15 (A) 1H HR-MAS NMR comparison of the heparin spectrum with that of Co3O4@heparin nanoparticles. (B) 1H NMR comparison of the heparin solution spectrum with that of the Co3O4@heparin supernatant [70].

The NMR technique has a significant role in characterizing the colloidal metal oxides. For example, the stabilization of a colloidal metal oxide nanocrystal by the amino acid-based ligand exchange method has been investigated by solution 1H NMR techniques [68]. The amino acids are tightly bound to the surface, and their 1 H NMR resonances are broadened beyond detection. On the other hand, the colloidal solutions of long-alkyl-chain-amine stabilized ZnO nanoparticles have been characterized by NMR spectroscopy [69]. In a separate study, Vismara and coworkers employed NMR spectroscopy to confirm the formation of three types of metal oxide@heparin adducts (Co3O4@heparin, NiO@heparin, and Fe3O4@heparin) [70]. They have combined the typical advantages of solid- and liquid-state NMR techniques to understand the formation of metal oxide@heparin adducts in both phases. Their finding indicated that only Co3O4@heparin was successfully detected by this technique. It was postulated that the drastic reduction of its mobility due to a powerful connection to the metal oxide surface results in lack of heparin detection for Fe3O4@heparin and NiO@heparin. The 1H HR-MAS NMR of heparin was compared with Co3O4@heparin nanoparticles, as shown in Fig. 6.15. The interaction of both parties was confirmed by the selective disappearance of the anomeric signal (H1) of 2-O-sulphate iduronic acid (I2S) residues. Overall, the previous works paved the way for the study of more complex systems, such as metal oxide nanoparticles that are stabilized by several types of ligands and bioactive material, for a better understanding of the surface chemistry of metal oxide nanoparticles.

6.4

Probing of nano colloids of metal oxides by diffraction techniques

Colloidal metal oxides are versatile compounds, depending on the physical and chemical properties of the inorganic core and the ligand-capped surface. Colloidal stability is a primary challenge in synthesizing nanoparticle colloidal suspension, as it has a tendency to aggregate to minimize surface tension. One of the critical techniques

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111

to determine the immediate structure and compositional characteristic of a metal oxide colloidal is the diffraction method. Diffraction techniques are the most significant approach to the analysis of crystalline solids, providing both phase and structural information. Crystals with defects and amorphous materials information can be obtained by a diffraction method, also. Diffraction is defined as a coherent scattering of waves or radiation from an object as a result of the size, which is comparable with the wavelength. In general, there are three types of diffraction methods: X-ray, electron, and thermally neuron.

6.4.1 X-ray diffraction Often, X-ray diffraction (XRD) is considered a subset of X-ray scattering, where X-rays are scattered by the electrons in atoms, and diffraction can occur for a periodic array of scattering centres, and finally analyzed by X-ray crystallography. Generally, wide-angle X-ray diffraction (WAXD), or typically established as X-ray diffraction (XRD), is elegantly exploited by researchers to determine the structure of the molecule, particularly for bulk polycrystalline particles with a diameter of >10 nm. In depth, XRD provides information about the arrangement of atoms within a crystalline material as well as lattice dimensions, nonbulk, and bulk material structures. X-rays ˚ , the same order of magnitude as the interhave a wavelength λ in the range of 1–100 A ˚ ) between planes in the crystal. A concept of the XRD planar spacing d (around 2–6 A technique is the constructive interference occurs when the intensities of the waves add to each other while the waves cancel each other in most directions through destructive interference, determined by Bragg’s law [71]. 2d sin θ ¼ nλ where d is the spacing between diffracting planes, θ is the incident angle, n is an integer, and λ is the wavelength of the beam. Diffraction patterns obtained can offer information about the size and symmetry of the unit cell, the crystalline phase present, the location of the atoms, and other crystal defects. XRD experiments are routinely carried out with either single-crystal or powdered samples. For the sample preparation, both powder and single crystal have similar instrumentation setups. In principle, XRD requires very little material, but a complete structure determination can be made with a crystal of 0.01 mg or less without necessarily destroying the sample. Both a polycrystalline sample (fine powder) and a crystal are mounted at first, followed by irradiation with X-rays. Typically, for metals, Cu Kα or Mo Kα are used as X-ray sources, relying on molecule size and d spacing [72, 73]. In a metal oxide colloidal, powder XRD is a useful technique to identify the phase identification as well as unit cell dimensions, as colloidals are always formed as the bulk material of a crystalline solid at the atomic scale. Often, all possible Bragg diffractions could be observed in the powder pattern. The different Bragg peaks are labelled as indexed diffraction using the numbers (hkl) under powder XRD. This technique is to identify unknown crystals in the synthesized material by matching the positions and intensities of the peaks observed in the diffraction pattern to a standard

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diffraction pattern or from calculation. Generally, the experimentally determined diffraction pattern can be compared to a collection of known diffraction patterns of materials in the International Center for Diffraction Data (ICDD). This database provides the data field of inorganic and organic materials, including interplanar spacings, relative intensities, and hkl indexing. Also, there are several other databases available to match actual crystalline species, including the Cambridge Crystallographic Data Center (CCDC) and the US National Institute of Standards and Technology (NIST). On the other hand, to determine the crystallite size of the polycrystalline samples, the Scherrer formula is used by calculating broadening X-ray peaks or known as full width at half maximum (FWHM) of each crystallite. Generally, the Scherrer formula applies to crystallite size in the range of 5–100 nm [74, 75]. The colloidal metal oxide is an innovative material that is investigated by powder XRD. For example, Tubio et al. fabricated 3D CuO/Al2O3 composites with complex geometries via a 3D printing technique to control the stability of the complex composite structures [76]. The samples were analyzed using Cu Kα radiation at a wave˚ . A step time of 1 s and a step size of 0.05 degree were used, and length λ of 1.5418 A the diffraction pattern was collected between 10 and 80 degree of d spacing, 2θ. Using copper nitrate and Al2O3 powder as the main gradients, the present phases in ink sintered at 1400°C were rich with CuO tenorite (JCPDS 01-1117) and α-Al2O3 (JCPDS 02-1227), attached with copper aluminate spinel, CuAl2O4 (JCPDS 01-1153) as the secondary phase reflecting from the XRD diffractogram. A comparative study was done by Elbasunay on colloidal manganese oxide nanoparticles and nanorods for direct integration into the energetic matrix [77]. The colloidal nanoparticles and nanorods were initially centrifuged and freeze-dried before analyzing the crystalline phase of manganese oxides. Within an XRD angle range of 20–70 degree, nine peaks of manganese oxide nanoparticles depicted manganese (IV) oxide, the MnO2 crystalline structure as matched to the Joint Committee on Powder Diffraction Standards (JCPDS) from the International Center for Diffraction Data (ICDD) card number 01-073-153. Mn2O3 nanorods (JCPDS 00-024-035) were noticed in sharp crystalline structures without any interfering substances. Ziashahabi et al., who studied the phase transitions of fresh and 1 week after synthesis Zn-ZnO hybrid nanostructures, reported that strong wurtzite zinc oxide (JCPDS 01-079-0207) was observed at diffraction peaks of 2θ ¼ 36.96 degree (100), 40.11 degree (002), 42.29 degree (101), 55.83 degree (102), 66.72 degree (110), and 74.47 degree (103), and minor hexagonal zinc peaks at 42.36 degree, 45.59 degree, 50.65 degree, and 63.97 degree, which correspond to (0 0 2), (1 0 0), (1 0 1), and (1 0 2) planes of fresh samples [78]. However, after a week of sample production, the hexagonal zinc crystals formed as a major species. Using an X-ray source of ˚ , the percentage of the oxidation phase was deterCo Kα radiation at λ ¼ 1.78897 A mined using the relative peak surface area of the Zn and ZnO phases. Consequently, the incomplete oxidation process observed was due to a larger zinc cluster that formed in the initial stage of synthesis. On the other hand, stacking or crystal faults also can be manifested in diffraction peaks as both hkl-dependent peak broadening accompanied by shifts in the peak position. Typically, crystal faults occur in metallic nanoparticles, as the regular stacking of atomic planes in a crystallite is interrupted or reversed due to

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surface tension. A study was done by Fazio et al. that showed an XRD pattern of as-synthesized materials indexed as (104) and (006), about Rh2O3 for nanosized colloidal rhodium oxides prepared by pulsed laser ablation in water (Fig. 6.16) [79]. After annealing, the XRD peaks had a more uniform peak width. The XRD spectrum was then changed after the thermal treatment at 200°C in air, an abundance of new peaks ascribe to RhO2 phase, was observed, attributed to the removal of stacking fault coming from the thermal treatment. A comparison between XRD patterns of multicore iron oxide magnetic nanoparticles (MNC) and doped Gd and Eu MNC, prepared by a one-step synthesis procedure using a solvothermal method, was investigated by Petran et al., using Cr Kα radiation with 2θ between 30 and 150 degree [80]. Overall, they found that all the investigated samples possessed Eu/Gd-doped Fe3O4 magnetic nanoclusters (JCPDS 19-0629), with an abundance of Fe3O4 crystal phase with no distinct impurity phases. Also, it was clearly observed that the widths of XRD peaks increased as the Gd concentration increased in the samples. The presence of doped Gd decreased the crystallite size and increased the lattice stress in the crystal lattice of magnetite. However, no Gd compound was found, although the Gd concentration increased to 15%. It was worth noting that the nature of the rare Earth was not affected the crystallite size and strains but depend on rare earth concentration. Different X-ray sources for scattering purposes rely on the crystalline materials. Basically, a metal oxide colloidal has no issue on these XRD sources, as their particle

Fig. 6.16 XRD spectra of as-prepared and annealed nanosized colloidal rhodium oxides (right) [79].

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Norm. Intensity

1

As grown Sn

0 1

Exchanged Ag-Sn

0 2

(A)

(B)

3

4

5

6

7

Momentum transfer (Å–1)

Fig. 6.17 (A) In situ synchrotron XRD setup used to monitor the galvanic exchange reaction in the nanocrystal. (B) XRD patterns from SN nanocrystals after synthesis and Ag-SN nanocrystals after galvanic exchange reaction with silver for 33 min at 90°C [81].

size broadening is significantly larger than the instrument one. Synchrotron radiation is an alternative X-ray source for impractical samples with the laboratory X-ray sources. The unique properties offered by the synchrotron source are high flux and collimation, energy tenability, and shortened measurement times, which is helpful for in situ real-time studies. In situ XRD studies are mostly used to construct specialized environmental cells or kinetic studies on changes of crystalline materials. An example of the use of an in situ synchrotron source is work performed by Kiegner et al. to monitor the galvanic exchange in colloidal Sn toward AgdSn nanocrystals [81]. A thermocouple mounted close to the Sn nanoparticles was set up to monitor the temperature changes during the heating process while Fig. 6.17A showed a photograph of the diffraction setup. Meanwhile, a 2D powder XRD was applied to monitor the galvanic exchange colloidal reaction. The results (Fig. 6.17B) showed that peaks corresponding to the metallic α-Sn cores conquered the XRD pattern for as-synthesized Sn nanocrystals. The spherically shaped nanocrystals of 13 nm of Sn were also in agreement with the Rietveld refinements. Interestingly, after the treatment with Argentum (Ag), both Ag and Sn peaks were undetected, but the diffraction peaks appeared representing an intermetallic AgxSn consisting of the hexagonal ζ-phase and the orthorhombic ε-phase. In fact, the interaction of this material with any colloidal metal oxides also could be explored by this technique.

6.4.2 Small-angle scattering techniques (SAXS/SANS) In principle, a difference between wide and small angle X-ray scattering is the angle of 2θ. Small angle X-ray scattering (SAXS) is a technique to measure the scattering intensity at a small angle or large distances. Basically, SAXS probes the structure in the nanometer to micrometer range by measuring the scattering intensity at scatter˚ . Like XRD, ing angles 2θ close to 0 degree for X-ray wavelengths of the order of 1 A we can consider SAXS as a function to characterize the final synthesis product or determine the structure of the particle as well as the structure of ordered systems such as lamellae and fractal-like materials. Besides, the SAXS technique is also known as

Features of metal oxide colloidal nanocrystal characterization

115

log (I)

log (I)

an excellent technique to study colloids of all types, metals, cement, oil, etc. [15]. SAXS experiments can be illustrated in transmission geometry; either the samples are suspended in capillaries, deposited onto thin wafers, or in powders or gels formed. SAXS has been used to compare the colloidal nanoparticle characterization with other techniques, such as transmission electron microscopy (TEM) and XRD. Unlike TEM, where the tendency to spot a biased sample image and uncovered the entire sample, SAXS provides structural data averaged over macroscopic sample volumes as well as structural changing during kinetic processes. Pavlopoulou et al. used SAXS to characterize Pt nanoparticle fractal networks during a three-step synthesis process [82]. The scattering data were collected both before and after reduction for two synthesis steps to observe the spatial distribution of the platinic anions and Pt nanoparticles in a microgel network. Biswas et al. investigated the formation of ZnO nanorods and the growth kinetics in the presence/absence of capping molecules, under the observation of TEM and SAXS [83]. In their case, the ZnO samples were taken at different reaction times and measured ex situ. To summarize, the polyvinyl pyrrolidone (PVP)-capped ZnO nanorods grew longer at a higher rate with a smaller diameter than uncapped ZnO nanorods; the same results appeared from TEM and SAXS (Fig. 6.18). For the growth mechanism of ZnO nanorods, the diffusion-limited Ostwald ripening process could be considered in the case of the uncapped nanorods, but it has to fit a new model involving both diffusion and surface reactions to reveal the growth mechanism of PVPcapped ZnO nanorods. Gutsche et al. [75] performed the time-resolved characterization of silica-coated magnetite nanoparticles during the synthesis process, under observation of TEM and SAXS. In their case, Fe3O4 nanoparticles were initially synthesized via coprecipitation of FeCl3 and FeCl2 in alkaline media, before coating with silica to be used as magnetite cores for a basis of second shell coater. Later, the shell growth of the nanostructured particles was monitored by SAXS. To summarize, the scattering curves of core-shell magnetite particles kept changing with reaction time. The SAXS curve exhibited a specific side maximum after 30 min of the progressing growth of shell

Reaction time (h)

Reaction time (h)

1 2 3 6 12 18 24

–2.0

(A)

1 2 3 6 12 18 24

–1.5

–1.0

log (q)

–0.5 –2.0

(B)

–1.5

–1.0

–0.5

log (q)

Fig. 6.18 SAXS data of (A) uncapped and (B) PVP-capped ZnO nanorods obtained after different times of reaction. Solid lines are the model fits the experimental data [83].

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thickness. Besides, SAXS curves also described a core-shell sphere model in which providing information of the final shell thickness with different TWOS concentration; the same results appeared from TEM analysis.

6.4.3 Electron diffraction On the other hand, electron diffraction (ED) is primarily used for gas phase identification and also unit cell determination on small crystallites in the electron microscope. The advantages of electron diffraction are that electrons are much less penetrating and scatter much more intensely than X-ray. As a result, electrons are sensitive, even on a very thin layer sample, thus giving a strong diffraction pattern in a short time. Nevertheless, ED analysis is usually performed in a transmission electron microscope (TEM) or a scanning electron microscope (SEM) as electron backscatter diffraction, also known as selected-area electron diffraction (SAED). In these instruments, electrons are accelerated by an electrostatic potential to gain the desired energy and determine their wavelength before they interact with the sample to be studied. Even though SAED may deduce the structure of the crystal, this technique is preferable for relatively simple molecules (small crystal materials) and requires a much higher level of user input or high energy electrons. As electrons are interacting actively with the matter, this technique needs a very thin sample to observe a diffraction pattern in transmission. Ever more intense SAED experiments in TEM can be performed on a single crystal of the smallest nanometer size, combined with direct imaging of the sample to collect the actual information. Some metal oxide colloidals have been studied by selected-area electron diffraction (SAED). As an example, Bian et al. modified the conventional metal oxide mesocrystals into new nanocomposite materials containing two different metals, Zn and Cu, for effective charge separation [84]. For the obvious observation of ZnO and CuO mesocrystal structure at a calcination temperature of 500°C, the selected-area electron diffraction (SAED) was used in line with TEM instead XRD. The SAED pattern recorded for an individual metal oxide revealed that the ZnO rod has a single crystalline structure [inset of Fig. 6.19A] while CuO mesocrystals appeared as sphere-like with a diameter size of around 500 nm. These results proved the capability of the electron diffraction technique to support HRTEM in recognition of the crystallographically oriented morphology of the samples. SAED was performed by Nguyen and Do to identify the presence of rare Earth oxide nanocrystals (NCs) in a monodisperse colloidal [85]. Initially, Sm2O3 and CeO2 NCs were prepared at a high metal monomer concentration of a nitrate salt solution. Spotted the single samaria and ceria particles of by SAED showing that both particles have the distinct diffraction rings of cubic structure, as supported by powder XRD in which both metal oxides possessed bodycentered cubic (bcc) structures. On the other hand, SAED was performed by Bajpai et al. to observe the dispersion of ferrite particles in the polyvinylidene fluoride (PVDF) and the relationship to the piezoelectric-polymer matrix [85]. Different Fe3O4 concentrations (MNP) with respect to PVDF nanocomposites were prepared using a solution casting method in the film formed. Overall, SAED patterns of pure PVDF provided a crystal formed in film cast. Interestingly, after the addition of 1%

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Fig. 6.19 Pure metal oxide mesocrystals. (A) TEM image of ZnO, Scale bar, 500 nm. (B) TEM image of CuO. Scale bar, 500 nm. SAED patterns (insets of TEM images) showed the singlecrystal diffraction [84].

MNP on PVDF, the ferrite particles showed good dispersion in the PVDF matrix, and the average size of Fe3O4 nanoparticles was below 30 nm. Varying the Fe3O4 concentration into 0.5% and 2% MNP created a poor distribution of ferrite particles because of the agglomeration morphology.

6.5

Conclusion

There are several promising characterization techniques that can be employed to study the physicochemical characterization of the prepared colloidal metal oxides. The data obtained from the analysis might differ from others that depend on the parameter used during the examination and sample preparation. On the other hand, the type of preparation methods and conditions might be influential to the data obtained from the specific characterization techniques. Thus, to characterize the colloidal metal oxide sample adequately, the combination of several characterizations will be advantageous because it strengthens the explanation and justification of the results and data. The most important aspect is that the fundamental principle of the characterization techniques should be a proper understanding to give the interpretation of the obtained data correctly.

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