The properties of the nanoparticles, such as chemical, electronic, optical, and mechanical properties can differ significantly from particles with a macro scale, due to the greater reactivity at the molecular level in function to the high surface-volume ratio. Therefore, to obtain more information about the properties and potential applications of these nanostructures, their characterization is essential. The nanoparticles can be characterized in terms of morphology, size, surface area, porosity, elemental composition, crystalline structure, adsorption potential, surface charge, and various other physical properties (Mourdikoudis et al. 2018).
Several techniques are applied to characterize nanoparticles (Fig. 3), among them the most used are: scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy (EDS, EDX or XEDS), Fourier transform infrared spectroscopy (FTIR), dynamic light scattering (DLS), Zeta potential, Brunauer-Emmett-Teller method (BET), Barret-Joyner-Halenda method (BJH), thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) (Campos et al. 2015).
The most important parameters in the characterization of nanoparticles are the size and morphology. SEM and TEM are the most used techniques to evaluate these parameters. The principle of electron microscopy is the use of accelerated electron beams and electrostatic or electromagnetic lenses to generate images with high resolution, based on the electron wavelengths (Crucho and Barros 2017). The images of TEM, compared to SEM, provide more precise information about the size, shape, and crystallography of the nanoparticles due to the greater magnification and resolution obtained in this technique.
Techniques based on electron microscopy require careful sample preparation, which involves chemical fixation, staining, chemical dehydration, incorporation, critical point drying, cutting in thin sections, cryofixation or incorporation, and coating. However, the sample preparation for SEM is less demanding than for TEM. In the SEM, the samples are fixed on metallic support with double carbon adhesive tape and spray-coated with gold or carbon to make the sample conductive and increase the contrast of the image (De la Calle et al. 2016). The sample preparation for TEM is more complex and time-consuming because it usually requires cuts in ultrafine sections to allow the transmission of electrons. The thin films containing the samples are prepared on copper grids coated with carbon. For this, the solution sample is deposited on the grid, and the excess is removed with absorbent paper.
EDS (or EDX or XEDS) is used for the elemental analysis or chemical characterization of the nanomaterial. This technique is applied together with SEM or TEM and it is based on the interaction of some source of X-ray excitation and a sample because each chemical element has a unique atomic structure which allows a unique set of peaks on its electromagnetic emission spectrum (Crucho and Barros 2017). FTIR is a chemical analysis technique used to identify surface the functional groups present in the nanoparticles. FTIR measures the absorption intensity of the infrared light as a function of the wavelength of the light (Campos et al. 2015).
DLS and zeta potential determine the size distribution and surface charge of nanoparticles, respectively. In the DLS, the colloidal suspension of spherical particles is illuminated by a beam of monochromatic light (laser) directed to the photon detector. The light intensity disperses over time due to the Brownian motion of that is related to the equivalent hydrodynamic diameter of particles. This diameter is determined from an autocorrelation function. The DLS provides information about all the particles quickly, being one of the advantages of this technique (Crucho and Barros 2017).
The Zeta potential is an important indicator of the surface charge of the nanoparticles. This technique can be used to predict and control the stability of colloidal suspensions or emulsions, and it is essential for the understanding of dispersion and aggregation processes (Parhi and Suresh 2012). In addition, the surface hydrophobicity can be estimated by this technique. The value of ± 30 mV of the zeta potential is generally used to infer the stability of the particles. The absolute value above 30 mV indicates a stable condition, while below 30 mV indicates characteristics of instability, such as aggregation, coagulation, or flocculation (Sapsford et al. 2011).
The textural properties of the nanoparticles are generally determined by physical adsorption techniques, which are extremely important to evaluate the adsorption capacity of the nanoparticles. In these methods is used a surface analyzer that uses nitrogen (N2) gas as an adsorbent and liquid N2 (77 K) as a refrigerant medium, being the surface area obtained in the relative pressure range P/ P0 of 0.05 to 0.35 (Campos et al. 2015). To obtain the adsorption/desorption isotherms and the specific surface area is used the BET mathematical method. Size, shape, and distribution of the pores can be calculated from the isotherms by BJH mathematical model (Campos et al. 2015).
TGA and DSC can measure the thermal stability. TGA determines the thermal degradation according to the sample mass variation as a function of the temperature, and it allows evaluating if there is a residual solvent in the nanoparticles. DSC evaluates the physical-chemical state of the nanoparticles, determining the phase transitions, such as temperatures of glass transition (Tg), crystallization, and melting. Tg is the reversible transition that occurs in amorphous materials (including amorphous regions within semicrystalline polymers), where the material changes from a hard and relatively brittle state into a molten or rubber-like state (Crucho and Barros 2017).
For evaluation of hydrophobicity of the nanoparticles, the contact angle that the liquid (water drop) forms when deposited on the surface is measured. With a digital microscope, the interface between the water drop and the solid is photographed, and the angle is automatically determined (Dwivedi et al. 2017). To choose the most appropriate technique must know the strengths and limitations of all to know if the use of only one is sufficient to obtain reliable information about a specific parameter, or if a combination of techniques for characterizing of the nanoparticles is necessary (Mourdikoudis et al. 2018).