**1.6 Cs2SnI6 formation processes**

Deposition of perovskite films by spin coating process with anti-solvent is a highly common method employed in perovskite photovoltaics research [25]. This method is a good way on a laboratory scale, but it is not suitable for large-area or mass production process. Here, we introduce a new two-step process (a CsI deposition in Step 1 by espraying process and vaporization of SnX2 or SnX4 in Step 2) method of Cs2SnX6 (X = halide) compounds film formation. In earlier research, a series of experiments describe how we have optimized our two-step solution processes for synthesizing iodosalt Cs2SnI6-xBrx thin films to achieve suitable properties as solar photon absorbers for light to charge conversion [10]. This paper is well explained what the importance of Step 1 is and how to apply this. As another approach for making better thin films, we adopted the method suggested by Saparov et al. [26] that Vapor SnI4 treatment is a thermally activated chemical reaction and the reaction temperature is independent of the SnI4 temperature needed to establish the vapor concentration. The schematic representation of the experimental vaporized step was illustrated in **Figure 2(a)**. The as-made CsI film prepared by e-spraying and excess SnI4 powder was placed in a sealed glass container with the different positions (the center: CsI

**Figure 2.**

*Vaporized technique as a step 2 process: (a) illustration showing vaporizing procedure; (b) XRD analysis and cross-sectional image for the different film thickness; (c) vaporized condition for SnI4 powder; and (d) morphological study from SEM and TEM analysis for 200°C and 300°C for 1 hour.*

film, the edge: excess SnI4 powder) and rapidly heated to the reaction temperature (25–200°C or 300°C) for 1 hour in a box furnace at a rate of 10°C/min. In our first observation, even if the films show very smooth surfaces, SnI4 vaporization condition at 200°C for 60 min is not enough to fully convert the Cs2SnI6 crystal because of the existence of the main peaks of CsI film at all the thickness appears at 2θ = 27.6o (see **Figure 2(b)**). Therefore, we choose a different condition based on the ground of the work of Fuchizak [27, 28]. In more detail, at the initial stage of the experimental research into the melting behavior, Simon's equation is used:

$$\frac{p}{p\_0} = \left(\frac{T\_m}{T\_0}\right) \mathbf{C}\_s \mathbf{-1} \tag{1}$$

where T0 and p0 are the values at the reference state,*T*m is the melting temperature at pressure p, and cS is a constant. This substitution is believed not to cause any significant issues. Second, the Kechin melting curve equation is discussed. This equation was derived from

$$\frac{d\ln T\_m}{dp} = \frac{\Delta V}{\Delta H} = \frac{\Gamma\_m}{K\_m} \tag{2}$$

Here, ΔV and ΔH denote the changes in volume and enthalpy upon melting, and hence the first equality merely states the Clapeyron-Clausius relationship. K represents the isothermal bulk modulus [27]. The subscript "m" denotes that the quantities are calculated from a melting curve, or more precisely, along a solidus. Thus, Γm and Km are considered as the asymptotic quantities of Γ and K evaluated in *Lead-Free Perovskite and Improved Processes and Techniques for Creating Future… DOI: http://dx.doi.org/10.5772/intechopen.106256*

the solid state. Because only a solid state is involved in the assessment of the second equality, it was referred to as a "one-phase" approach in contrast to the first equality, called a "two-phase" approach. Γ is defined by:

$$
\Gamma = \frac{-dlnT}{dp} = 2\left(Y - \frac{1}{3}\right) \tag{3}
$$

where γ is Grüneisen's parameter, and the latter equality is evolved from Lindemann's melting law. The quite intriguing point in Kechin's treatment for Eq. (2) is to employ the Padé approximation to express the RHS and to obtain the solution:

$$\frac{T\_m}{T\_0} = \left(\mathbf{1} + \frac{p}{a}\right)^b e^{-cp} \tag{4}$$

when L = M = 1 was chosen in the Padé approximant. The constants, a, b, and c, are expressible in terms of the original thermodynamic quantities contained in Eq. (2) as follows:

$$a = \frac{\Delta H\_0}{\Delta H\_0'} = \frac{K\_{mo}}{K\_{m0}'}$$

$$b = \frac{\Delta V\_0}{\Delta H\_0'} + ac = \frac{\Gamma\_{mo}}{K\_{m0}'} + a \quad \text{and} \quad c = \frac{\Delta V\_0'}{\Delta H\_0'} = -\frac{\Gamma\_{m0}'}{K\_{m0}'}$$

where a prime denotes a pressure derivative, and the subscript "0" means that the quantity is estimated at p = p0(≃0). When c = 0, Eq. (3) can be simplified to Eq. (1). Eq. (3) is "almighty" in that it can capture an unusual melting curve with a maximum at pmax = b/c � a.

However, Eq. (3) was used only as a fitting guide, and no examination was attempted to demonstrate the fitted parameters on the basis of Eq. (4). Here, we are simply fitted to Eq. (3), treating a, b, and c as fitting parameters with "best-fit" value. The overall aspect of the fit is not bad, but the actual melting curve seems to break more abruptly near 1.5 GPa, beyond which it becomes almost flat, with a slight maximum at about 3 GPa (**Figure 2(c)**). Based on this information, we test a different sets of condition Cs2SnI6 film produced by vaporized SnI4 treatment with the different thicknesses. XRD analysis and morphology study for the different thickness can be seen in **Figure 2(b)**. All of the diffraction peaks are indexed as Cs2SnI6 with the space group, Fm-3 m(225) (JCPDS #04–016-3227). This experimental study shows that the complete reacted 500-nm-thick Cs2SnI6 film can be obtained after SnI4 vapor exposure at 300°C for 1 hour. However, when the thickness is over 500 nm, a CsI impurity peak started to appear. Thus, to remove unreacted CsI, a different treatment condition is needed (e.g. we can also confirm the completely converted Cs2SnI6 film at 300°C for 2 hour). Furthermore, we obtain the large Cs2SnI6 crystal for the 300°C cases. From SEM top-view images in **Figure 2(d)**, the 300°C treated sample has shown an increased grain size with diameters of 453 � 35 nm, while the diameters of 200°C treated sample are in the range of 240 � 58 nm. The TEM images are used to further examine the crystal size. The sizes for 200°C and 300°C treated Cs2SnI6 films are estimated to be 269 � 24 nm and 450 � 16 nm, respectively, which are consistent with the SEM observations. The grain size (D) of two samples is also independently calculated from XRD data using Scherrer formula [29]. The (222) peak at 2 θ = 26.5o is fitted to estimate the grain size of Cs2SnI6.. The 222 peak gives an estimate of the average

crystallite size only in the *ab*-plane direction. As expected, the average grain size increases only slightly after 1 h of annealing at 300°C (*D* = 58.80 0.2 nm) compared with the 200°C treated samples (D = 52.21 0.6 nm). The increased grain size correlates with an improved film conductivity. This improvement is mainly provided by the carrier mobility being enhanced from 1.94 cm2 /(Vs) for the 200°C treated film to 11.24cm2 /(Vs) for the 300°C treated Cs2SnI6 film, and to a lesser extent by the carrier concentration that increases slightly from 1.57 1015 cm3 to 4.89 1015 cm3 at a film thickness of 1.5 μm. This experimental research indicates that bulk electrical conductivity reduces with the decreasing grain size. The electrical property change can be attributed to fewer boundaries impeding electron mobility in the 300°C treated films [30].

The optical properties of Cs2SnI6 film prepared by the vaporized technique can be also seen in **Figure 3(a)**. The film formed vaporized condition followed the same optical (1.6 eV) and electrical properties are quite similar to the literature results [26]. This reason can be understood by the following experiment: X-ray photoemission spectroscopy (XPS) and ultraviolet photoelectron spectroscopy (UPS) measurements of the Cs2SnI6 film produced by the different methods were performed for compositional and chemical states analysis. The presence of Cs, Sn, and I elements is clearly discernible (**Figure 3(b)**). The binding energies of 619.7 eV and 631.2 eV are indicative of I3d bonded to Cs3d at binding energies (BEs) of 725.1 and 739 eV, in good agreement of result for CsI peak [31]. In the case of the Sn compound, the main binding energies of Sn3d5/2 and Snd3/2 obtained from solution method are about 488 eV and 496 eV, respectively, attributed to Sn4+ state (see **Figure 3(b)** middle column). Interestingly, in the case of the vaporization method, the main binding energy at 487.3 eV can be assigned to Sn2+, leading to intrinsic defects and instable form, with a nominal formula Cs+ 2Sn2+(I6) 4 [26, 32–34]. The vaporization of a system of tetrahedral MX4 groups linked through vertices (silica-like structure) is accompanied by a reduction in the coordination number of the metal, in some instances to polymeric species which dissociate to monomers at higher temperature [35]. Thus, the formation of the Sn2+ oxidation states can be explained by halogen transfer during the high-temperature process [36–38]. The position of energy levels for occupied states can be also determined by UPS analysis. (**Figure 3(b)** right column) The BE of the HOMO onset of Cs2SnI6 film prepared from the different method is determined by the intersect of the linear extrapolation of the leading edge of the HOMO peak and the straight background line. The Fermi level in most of the presented spectra is fixed at zero binding energy, and all the measured positions are

#### **Figure 3.**

*(a) The optical absorption and PL analysis at 1000 nm thickness prepared by the vaporized technique at 300°C for 1 hour, and (b) XPS and UPS analysis for Cs2SnI6 prepared from the different technique.*

#### *Lead-Free Perovskite and Improved Processes and Techniques for Creating Future… DOI: http://dx.doi.org/10.5772/intechopen.106256*

referred with respect to the Fermi level. The HOMO onset of Cs2SnI6 powder and film from solution method are observed to be 5.52 1.2 eV, while for the vapor method they are measured to be 5.58 0.9 eV. The downshift of HOMO level with increasing bandgap can be considered by the distortion of crystal from the Sn2+ state. The different oxidation state can affect not only crystal structure account of the different ionic radius of Sn2+ (102 pm) and Sn4+ (0.69 pm) but also has a profound influence on a number of physical properties [39, 40]. The Sn2+compounds are expected to have distortions of their bonded configurations because of the influence of their nonbonded pair of electrons, while the 5s0 p0 configuration of the Sn4+ ion should give regular octahedral coordination for tin in ionic lattices. The bond length of Cs2SnI6 can be seen in **Figure 1(b)** [17, 41]. The missed half of Sn atom brought the Sn-I length (2.89 Å) closer to the actual value (2.85 Å), while estimated Sn-I length of Sn2+ was about 3.22 Å. The incongruous Sn-I length leads to the distortion of Cs2SnI6. From Goldschmidt tolerance factor (*t*), we can simply understand the stability and distortion of Cs2SnI6 crystal with Sn2+ and Sn4+ oxidation state [42]. The tolerance factor is calculated from the ionic radius of the atoms [43]. A tolerance factor of 0.71–0.9 originates from a distorted perovskite structure with tilted octahedra. In the case of the tolerance factor is higher (>1) or lower (<0.71), perovskite phase cannot be formed. This rule made for oxide perovskite, but the trend is still valid for pero-halide perovskite materials structure. The calculated tolerance factor of Sn2+ oxidation state can be estimated by 0.9012 (from SPuDS software program), while the maximum *t* achievable of Sn4+ oxidation state is 0.998. The decreased t value of the Sn2+ oxidized state indicates that the network of corner-shared SnI6 octahedral will tilt in order to fill space, causing a less stable structure.

**Figure 4** illustrated the electronic structure of Sn2+ state Cs+ 2Sn2+I6 4 and Sn4+ state Cs+ 2Sn4+I 6 presented by Xiao et al. [33, 41]. The chemical bonding nature and the origin of the bandgap in Cs2SnI6 can be understood by DFT calculations for some hypothetic structure. The qualitatively arranged group of electronic structure on the energy scale can be seen in **Figure 4(a)**. The electron structure on an isolated [36] octahedron (i.e. {I6} 0 cluster) is firstly displayed. The 18 I 5p orbitals of the {I6} octahedron are split to seven groups, following by the energy eigenvalues at the Г point and the group theory. The six radial I 5p orbitals split into three groups of a1g (I-I bonding) and eg & t1u (I-I antibonding). The 12 tangential I 5p orbitals form 4 triply

#### **Figure 4.**

*(a) Total and projected DOSs of qualitative interaction diagram for the {I6} 0 cluster, the {SnI6} cluster, and the {SnI6} sublattice models. The orbital are qualitatively arranged on the energy scale. A schematic illustration of {I6} a1u orbital: (b) schematic electronic structure for the different state Cs2SnI6. Reprinted form [41].*

degenerated groups of 1t1u & t2g (I-I bonding) and t2u & t1g (I-I antibonding). By adding a Sn atom and two electrons (transferred from the tow Cs atoms, which is ionized to Cs+ in Cs2SnI6) into the {I6} octahedron, the electronic structure of a {SnI6} 2 octahedron cluster is obtained. Therefore, the main difference between the +2 and + 4 oxidation state is the Sn 5 s orbital position. The unoccupied Sn 5 s orbital at the Cs+ 2Sn4+I 6 state is contributed to the conduction band maximum (CBM). However, the calculated Cs+ 2Sn2+I6 4 state had the fully occupied Sn 5 s orbital and I 5p-Cs 6 s antibonding CBM state. The +2 oxidation state of Sn has deeper VBM, and it can be explained by its wide bandgap. Using the one-micron-thick Cs2SnI6 film produced by solution and vapor as a photosensitizer, we fabricated three different series of solar cells structure: (a) nanoporous TiO2 /Cs2SnI6/Au; (b) nanoporous TiO2 / Cs2SnI6/Spiro-OMeTAD/Au; and (c) nanoporous TiO2/Cs2SnI6/LPAH/Au. As shown in the SEM cross section, a nanoporous TiO2 layer with interpenetrating layer of Cs2SnI6 is placed as the next layer. A selected HTM layer is next deposited followed by the evaporation of a thin Au contact layer. Three different series of HTM layers prepared from solution and vapor processes are shown in **Figure 5(a)**. The bottom of SEM images is also displayed in their band diagrams. The *J-V* curves for each of the device structure are plotted in **Figure 5(b)**, along with a table showing their characteristics. For configuration a. and d., we observed a substantial short circuit in the device of both solution- and vapor-processed samples. For configuration e., the vaporized samples show the best performance in typed cells (*η* = 0.505%), while the solution-processed solar cell shows the best performance (*η* = 0.177%) in the configuration c.. The overall improved PCE at the vaporized process is attributed to their

#### **Figure 5.**

*(a) {, #558} and cross-sectional images of a Cs2SnI6 film device (bottom: band alignment diagram) (b) J-V curves for different structures and device performance as described in the table above.*

*Lead-Free Perovskite and Improved Processes and Techniques for Creating Future… DOI: http://dx.doi.org/10.5772/intechopen.106256*

smooth surface, but still a low efficiency at 0.5%. However, it should be noted that large-effective-surface-area polyaromatic hydrocarbon (LPAH) can be dispersed well in alcoholic solvent (such as ethanol and isopropanol) without any polymer binder or surfactants [44]. Interestingly, the LPAH suspension with isopropanol also shows long-term dispersion stability. We believe that our findings make it possible to use this unique carbon nanostructural material as HTM material. In order to prove the effectiveness of LPAH, we tested that the case of a methylammonium lead iodide (MAPbI3) thin film can lead to high-efficiency device. (This book will not cover it).

Operating mechanisms of the Cs2SnI6-based solar cells have raised a number of questions. The optimization and further improvement of a new material require a deep knowledge of the working principles of this photovoltaic device. In order to understand the effectiveness for photosensitizer, the charge transfer process is studied by two different tools such as electrochemical impedance spectroscopy (EIS) and femtosecond transient optical spectroscopy (i.e. TAS and time-resolved PL (TRPL) spectroscopy) for measuring accumulation of a photogenerated charge and the diffusion length (*L*D) [45–47].

#### *1.6.1 Impedance analysis*

In earlier reports, dye-sensitized solar cells (DSSCs) have been successfully modeled by equivalent circuit elements, which have helped to elucidate the roles of internal interfaces as well as device components [48, 49]. From simulated model, average charge carrier lifetime, electronic densities of states, and charge carrier concentrations can be calculated. However, in the single-electrode system like BHJ organic photovoltaic devices or perovskite solar cell, the different impedance model is applied due to their geometrical difference [50–52]. Herein, we consider the properties of the impedance associated with diffusion coupled with recombination [45, 46, 51]. As seen in **Figure 6(a)**, electron energy diagram of an electron-transporting materials (specially, nanostructured metal oxide, TiO2, SnO) in contact with a holeconducting material (or redox medium), displaying the electrochemical potential of electrons *E*Fn (Fermi level), when a voltage *V* is applied to the substrate, and assuming that conduction band energy (*E*c), is stationary with respect to the redox level, *E*redox. The equivalent circuit (transmission line model, TL) for a small periodic ac perturbation contains the resistance for electron transport throughout the metal oxide nanoparticles, *rtr*; the resistance in the hole-transporting medium (hole or ion conduction) *rHTM*; the recombination resistance at the metal oxide/HTM interface, *rrec*; and the chemical capacitance for charge accumulation in the metal oxide particles, *Cμ*. The TL pattern related to the carrier transport at lower frequency which is due to a coupling of capacitance with recombination is demonstrated by a straight line. (The extension of the straight line cuts the semicircle at low frequencies).

The model corresponding to the reflecting boundary condition is shown in **Figure 6(a)** and contains three main elements. The first is the chemical capacitance (*C*μ), which makes *C*μ dominate the total capacitance at sufficient forward bias. The *C*μ is related to the variation of the electron Fermi level in the TiO2 caused by the variation of the electron density as a function of the voltage. The fitting of TL allows to separate the two resistive parameters, for an active film of area *A* and layer thickness *L*. The second is the recombination resistance, *R*rec, and the third is the transport resistance *R*tr, that is reciprocal to the carrier conductivity, *σ* and the conductivity relates to the free electrons diffusion coefficient, as:

#### **Figure 6.**

*(a) Electron energy diagram and general TL (b) concentration at the left boundary with concentration in the diffusion-recombination model. Curve represents the case (1)* Ln *> >* L,*(2)* Ln *< <* L *(3) long diffusion length with strong recombination at the back contact (c) the equivalent circuit used to fit the experimental data and impedance spectroscopy characterization. Reprinted from [46, 51].*

$$R\_{rc} = \frac{\tau\_n}{C\_\mu},\ R\_{tr} = \frac{L}{A\sigma},\ \sigma = \frac{C\_\mu D\_n}{L}$$

It is important to remark the following property:

$$R\_{tr} = \left(\frac{L}{L\_d}\right)^2 R\_{rc} \text{ and } L\_d = \left(\frac{R\_{rc}}{R\_{tr}}\right)^{1/2} L$$

The diffusion length (*L*d) is also obtained from electron diffusion coefficient, *D*n, and electron lifetime *τ*n, as *Ld* ¼ ffiffiffiffiffiffiffiffiffiffi *Dnτn* p and indicates the average distance that generated or injected electrons travel before recombining. Influence of *L*d of the carrier distribution in forward bias under dark conditions is illustrated in **Figure 6(b)**. For reflecting boundary (1) of long diffusion length, the carrier profile is nearly homogeneous. For short diffusion length (2), a gradient of carriers for the size of diffusion length is built from the injection point, and the rate of recombination at the back surface becomes another important factor. Finally, if the rate is large (3), excess carriers cannot remain at this boundary, and a gradient for the size of the semiconductor layer is built. **Figure 6(c)** shows a set of the characteristic impedance spectra pattern obtained for the Cs2SnI6/LPAH/Au at different applied voltages in the working conditions under 0.1 sun illumination. For all the spectra, an arc is observed at high frequencies related to the transport in Cs2SnI6/LPAH. At low frequencies, for samples, the classical feature of a transmission line, TL, discussed earlier is clearly visible. The TL pattern is defined by a straight line, associated with the carrier

*Lead-Free Perovskite and Improved Processes and Techniques for Creating Future… DOI: http://dx.doi.org/10.5772/intechopen.106256*

#### **Figure 7.**

*Transport and recombination parameters vs. voltage: (a) recombination resistance,* R*rec,; (b) conductivity of active layer considering the geometric cell area; (c) diffusion length; and (d) cross-sectional SEM images of solutionprocessed film (inserted in (top) vapor processed film (bottom) photo image) for 500 nm thick Cs2SnI6 film.*

transport, followed by an arc at lower frequency, which is due to a coupling of capacitance with recombination. The fitting results are presented in **Figure 7**.

Important information about the recombination in the solar cell is contained in the recombination resistance, *R*rec, and the transport rate is related to conductivity, *σ*. In the case of thin film (500 nm), a Cs2SnI6 film produced by vaporized process exhibits two orders of higher conductivity, while it displays lower *R*rec at comparable potentials (higher recombination rate) compared with Cs2SnI6 film from solution process. Therefore, diffusion length (*Ld*) of vapor-processed Cs2SnI6 film (0.76 μm at low voltage) is increased by as much as 65.2%, compared with solution-processed film (0.46 μm at low voltage). This reason can be considered as improved Cs2SnI6 film quality. For example, solution-processed Cs2SnI6 film shows the rough film with pinhole surface because of the loss during converting crystal formation such as being washed away by dropping SnI4 alcoholic solvent (**Figure 7(d)**). The light absorption properties of Cs2SnI6 film can be determined by absorption coefficient. Materials with strong absorption coefficients more readily absorb photons, which excite electrons into CB. Thus, knowing the absorption coefficients of materials aids engineers in determining which material to use in their solar cell designs. The calculated coefficient (*α*) of 7.11 102 cm1 at 550 nm measured for Cs2SnI6 film (at 500 nm) is about two order lower than that of 1.32 104 cm1 at 550 nm for MAPbI3 film (at 400 nm) [53]. Although a wider absorption spectrum of Cs2SnI6 film is benefit from light absorption, a low *α* must be improved to be the efficient photosensitizer. The higher *α* can be obtained by increasing film thickness developed. For example, *α* is estimated to be 1.7 103 cm1 and 8.5 103 cm1 at 550 nm for 1000 nm and 1500 nm Cs2SnI6 film, respectively, which indicates that *α* of thicker film is an order of magnitude higher than that of thinner film. However, from calculated diffusion length and the

experimental limitation for a completely reacted Cs2SnI6 film, we conclude that about 1.0 μm thick is the best condition for the efficient solar cell. Unlike aforementioned results, the oppose behavior, i.e. increased transport rate and decreased recombination rate at thicker film, can be observed due to the existence of CsI impurity at vapor process. Consequentially, in the case of about 1.0 μm thick, solution-processed Cs2SnI6 film shows longer diffusion length (1.5 μm) than that of vapor process (0.78 μm). This result indicates solution process is more favorable technique for thicker layer film. However, vapor-processed Cs2SnI6 film shows a high photocurrent and increased performance regardless of CsI impurity (leading to decrease *L*d) compared with solution method. Therefore, our group believes that a completely converted or singlecrystalline Cs2SnI6 film over 1.5 μm thick under well-controlled vapor process leads to the outstanding solar performance.

#### *1.6.2 Femtosecond time-resolved transient absorption spectroscopy*

The further photo-induced charge transfer processes can be confirmed by the excited-state dynamics measured from femtosecond transient absorption (fs-TA) spectroscopy [54]. In the case of over 800 nm, the totally black colored Cs2SnI6 film has a problem to transmit light through the samples. Therefore, >500 nm of Cs2SnI6 film is used for this study. **Figure 8** presents the normalized ground-state fs-TA spectra of solution and vapor-processed Cs2SnI6 film on Al2O3 (<100 nm, Aldrich). Samples are excited with 600 nm, and 10 nJ laser pulses are used with the same

#### **Figure 8.**

*Femtosecond transient absorbance spectra with white light continuum probe and pulsed fs laser excitation at 600 nm and 10 nJ laser pulses are used with the same spectrum spanning from 500 to 800 nm. Dynamics extracted at 650 nm (black) and 725 nm (blue) for (a) solution and (b) vapor process for a two-step Cs2SnI6 film.*

*Lead-Free Perovskite and Improved Processes and Techniques for Creating Future… DOI: http://dx.doi.org/10.5772/intechopen.106256*

spectrum spanning from 500 to 800 nm. Both samples show two main features: a positive band in the range of 600–680 nm and broad negative band peaked at 680– 800 nm. The broad positive band is resulted in the superposition of a ground-state bleaching (GSB) and simulated emission (SE) due to the close resemblance to the spectra of steady absorption and photoluminescence; the negative spectral feature is assigned to photo-induced absorption of excited state (PIA) as bleaching transitions from valence band to a conduction band [55]. The peak at 590 nm in case of solution is considered a noise peak caused by the uncovered Cs2SnI6 layer film defect. In the global analysis procedure, the decay-associated spectra with time constant probing at 630 nm and 725 nm are plotted in **Figure 8(c)** and **(d)**.

The completely reacted and covered Cs2SnI6 film shows three time constants of 1.9 ps (74%), 42.4 ps (21%), and 6835 (5%) at 650 nm as well as 0.73 ps (73%), 40.5 ps (21%), and 5152 ps (6%) at 725 nm, while a solution-processed Cs2SnI6 film reveals three time constants of 2.02 ps (75%), 40.9 ps (22%), and 6344 ps (3%) at 650 nm and 1.31 ps (67%), 38.4 ps (29%), and 5862 ps (5%) at 725 nm. The fast component for these samples is accounted for charge carrier trapping at grain boundaries of perovskite. We assign the longer time component (τ2) to electron injection into glass. This long-lifetime component, not resolved in this work, is most likely electron-hole recombination [56–59]. For 650 and 725 nm, the small differences observed between solution (*τ*2,650*nm* = 40.9 nm and *τ*2,725*nm* = 38.4 nm at solution process, while for vapor process, *τ*2,650*nm* = 42.4 nm and *τ*2,725*nm* = 40.5 nm). The small differences observed for both samples are not significative enough to draw any conclusion regarding the electron injection process. The further experiment for this measure did not progress by the difficulty in the sampling. For example, in electric field deposition system, a conductive substrate is prerequisite for making a continuous and homogeneous thin film. However, for fs-TA spectroscopy analysis, nonconductive substrate is favorable to clarify the electron transfer dynamics of material itself. Therefore, in this thesis, fs-TA is no longer used. In spite of possible charge dynamic properties charge injection and the similar diffusion length (*Ld* ≈ 0.8 μm at 500 nm) of Cs2SnI6 film compared with MAPbI3-based solar cell (*Ld* ≈ 1 μm), our initial finding showed very low device efficiencies. Nevertheless, we were encouraged because the device operated as a photosensitizer even when the conduction band energy level between TiO2 and Cs2SnI6 layer is nearly the same. A possible solution to this problem can be sought in bandgap tuning, and this can be achieved i) through the modification of the electrontransporting layer and ii) using an appropriate Cs2SnI6-xBrx absorption layer. These two approaches are discussed in the next paper.


**About the Editor**

**Sergei Petrovski** is an applied mathematician with thirty years of research experience in mathematical ecology and ecological modelling. His research spans across a broad variety of problems in ecology and population dynamics, with a particular emphasis on modelling complex multiscale ecological, agro-ecological and socio-ecological systems. Some of his older results on ecological pattern formation and biological invasion modelling have become textbook material. His recent research on the effect of global warming on atmospheric oxygen, where he discovered a new type of ecological catastrophe, was highlighted by the media around the world. He published four books and more than 130 papers in peer-reviewed journals. He currently holds the position of Chair in Applied Mathematics at the University of Leicester (UK). He is the Editor-in-Chief of *Ecological Complexity* (Elsevier) and the Section Editor-in-Chief for the "Theoretical and Mathematical Ecology" section of *Mathematics* (MDPI). He is also the founder and the scientific coordinator of the Models in Population Dynamics and Ecology (MPDE) conference series.


*3.3. Origin of Infection*

Out of the 398 patients, 250 (63%) were infected in Sweden, while 138 (35%) had acquired infection while traveling abroad to 55 different countries, representing all continents except Oceania and Antarctica, over the two weeks preceding disease onset. Ten cases had missing or uncertain data concerning origin of infection (Table 2). *Cryptosporidium parvum* was the most common species in cases of contracting infection in Sweden (84%; 211/250) and abroad (57%; 78/138); meanwhile, *C. hominis* was identified in 3% (8/250) of domestic cases and in 30% (41/138) of the cases infected abroad.

*Cryptosporidium* chipmunk genotype I (*n* = 5), *C. ubiquitum* (*n* = 2), and *C. ditrichi* (*n* = 1) were found only in cases infected in Sweden, while *C. meleagridis* (*n* = 8), as well as *C. suis*, *C. viatorum*, and *Cryptosporidium* horse genotype (*n* = 1 each), were exclusively found in travel-related cases. *Cryptosporidium felis*, *C. erinacei*, and *C. cuniculus* were diagnosed both in domestic and travel-related cases (Table 2).

#### *3.4. Molecular Characterization of Cryptosporidium parvum*

Subtyping using the *gp60* protocol was successful for 99% (296/300) of the *C. parvum*positive samples, including the sample with mixed *C. hominis* and *C. parvum* (Table 3). In total, nine subtype families (IIa, IIc, IId, IIe, IIl, IIn, IIr, IIs, and IIt) and 42 subtypes were identified (Table 3). The most common subtype family was IIa, which was observed in 164 patients. It was represented by 22 different subtypes, of which IIaA16G1R1 (*n* = 42), IIaA15G2R1 (*n* = 31), and IIaA17G1R1 (*n* = 20) were the most common. The remaining 19 IIa subtypes were found in 1–13 patients each. Subtype family IId (*n* = 118 patients) was the second-most common subtype family, represented by 11 different subtypes, of which IIdA22G1 (*n* = 37) and IIdA20G1 (*n* = 24) were the most frequent. The remaining nine IId subtypes were found in 1–16 patients each. Three patients were co-infected with two *C. parvum* subtypes: one with IIaA14G2R1 and IIaA15G2R1, and two with IIaA15G2R1 and IIdA19G1 (Table 3). Subtypes from subtype families IIc, IIe, IIl, IIn, IIr, IIs, and IIt were found in one or two patients each (Table 3).

**Table 3.** *Cryptosporidium parvum gp60* sequences generated in this study.

**Table 3.** *Cont.*

**Table 3.** *Cont.*

1 Sequences submitted to GenBank during this study are indicated in boldface type. Accession numbers in non-boldface type refer to reference sequences from GenBank. 2 Four samples from an outbreak [27]; 3 two samples from an outbreak [27].

> Among the IIa and IId subtypes identified in the present study, several sequence variations were observed, either in the conserved non-repetitive part or in the repetitive area. In Tables 3 and 4, all subtypes and subtype variants are referred to via a corresponding Gen-Bank acc. no. with 100% identity. For instance, in subtype IIaA16G1R1, the most common variant is IIaA16G1R1b (EU647727), which was found in 39 patients, and was the most common subtype in patients infected in Sweden (*n* = 30). Subtype IIaA16G1R1b\_variant (KT895368), wherein the TCG repeat is located at a different position in the repeat region compared to IIaA16G1R1b, was found in two patients. This type of sequence variation has been described by Alsmark et al. [14], and it was found in four IIa subtypes, but not in any other subtype family (Table 3). Subtype variations were also seen in IId subtypes, exemplified by IIdA22G1, where three variants were identified, differing by one single nucleotide polymorphism (SNP) in the conserved part, AY166806 (*n* = 16), FJ917374 (IIdA22G1c; *n* = 19), and KR349103 (*n* = 2). Another type of sequence variation was found in IIaA14G1R1r1, which has an interruption of the TCA repeats by an ACA. This subtype, which was found in six patients, was named according to the proposed nomenclature by Amer et al. [28], who described a similar sequence variation, IIaA14G1R1r1b, in a sample from a calf.

> Three new *C. parvum gp60* subtype families, IIr, IIs and IIt, were identified in one patient each. The sequences showed 100% identity with *C. parvum* at the SSU rRNA gene: IIr and IIt to AF164102 (gene copy A), and IIs to LC270281 (gene copy B). At the *gp60* locus, subtype IItA13R1 (KU852718) was identified in a patient (Swec402) who had visited Tanzania prior to infection. The closest matches in GenBank were 93% to *C. parvum* subtype family IIb (AY166805) and 90% to IIp (MK956000). The other two patients (Swec447 and Swec434) were both infected in Sweden, the first with *gp60* subtype IIsA14G1 (KU852720), where the closest match was 95% identity to subtype family IIe (KU852716), and the second

with subtype IIrA5G1 (KU852719), which showed 92% similarity to the *C. hominis* subtype family Ie (AY738184). This observation prompted us to investigate two additional genes, actin and *hsp70*. As regards the actin locus, the isolate was 100% identical to *C. parvum* sequence MH542350, and at the *hsp70* locus, where 1911 bp were successfully sequenced, it differed by eight SNPs compared with the IOWA *C. parvum* strain (XM625373) in the conserved part. These SNPs, however, did not display any changes in the amino acid sequence.

**Table 4.** *Cryptosporidium hominis gp60* sequences generated in this study.

1 Sequences submitted to GenBank during this study are indicated in boldface type. Accession numbers in non-boldface type refer to reference sequences from GenBank. 2 Cases described in Lebbad et al., 2018 [29].

#### *3.5. Molecular Characterization of Cryptosporidium hominis*

*Gp60* subtyping was successful for 49 out of 50 *C. hominis* isolates (including the sample with mixed species) (Table 4). Seven subtype families, Ia, Ib, Id, Ie, If, Ii, and Ik, and 17 subtypes were identified. The most common subtype was IbA10G2 (*n* = 15), wherein 13 cases had contracted infection while abroad; the remaining 2 reflected domestic infections. The second-most common subtype was IbA9G3 (*n* = 9), detected in patients who were infected in nine different countries, mainly in Africa (Table 4). In addition to the two cases with IbA10G2, another three subtypes were found in patients infected with *C. hominis*

in Sweden: IaA18R3 (*n* = 2), IfA12G1R5 (*n* = 1), and IkA18G1 (*n* = 2). The cases with the uncommon subtype families Ii and Ik have been described in a separate article [29].

#### *3.6. Molecular Characterization of C. hominis/C. parvum Mixed Infection*

One patient, a 4-year-old girl from Syria, had a mixed *C. hominis* and *C. parvum* infection with subtypes IaA18R3 and IIaA16R1.

#### *3.7. Outbreaks and Family Clusters*

Four outbreaks, all caused by *C. parvum*, were identified during the study period (Table 5). The first outbreak occurred among veterinary students in 2013, and two different subtypes were found, IIaA16G1R1 and IIdA24G1 [27]. Outbreaks 2, 3 and 4 were all foodborne and involved subtypes IIaA16G2R1, IIaA17R1, and IIdA17R1, respectively. Three small family clusters were also detected; two related to traveling, and one where a contaminated water well was the suspected vehicle (Table 5).

**Table 5.** Outbreaks and family clusters involving *C. parvum* and *C. hominis* identified in the study period.

1 Outbreak described in Kinross et al., 2015 [27]; 2 described in Lebbad et al., 2018 [29].

*3.8. Molecular Characterization of Additional Species*

Of 30 isolates from additional species, 28 were successfully sequenced at the SSU rRNA locus. Subtyping with the *gp60* protocol was successful for 29 isolates; the only exception was *C. ditrichi*, wherein no suitable primers were available (Table 6).

**Table 6.** *Cryptosporidium gp60* sequences from non-*hominis* and non-*parvum Cryptosporidium* species generated in this study.

1 Sequences submitted to GenBank during this study are indicated in boldface type. Accession numbers in non-boldface type refer to reference sequences from GenBank. 2 isolates included in Stensvold et al., 2014 [23]; 3 isolate included in Stensvold et al., 2015 [22]; 4 isolates included in Rojas et al., 2020 [21]; **5** case described in Beser et al., 2015 [30]; 6 case described in Beser et al., 2020 [31].

> A recently adopted child from Lithuania was infected with *C. suis*. A *gp60* sequence was achieved using the *Cryptosporidium* chipmunk primers [19], and by means of additional sequencing primers (data not shown) subtype XXVaR37 was obtained. This case and method will be described in a separate article.

> Cases with *Cryptosporidium* chipmunk genotype I subtype XIVaA20G2T1 and *C. ubiquitum* subtype XIIa-1 were found in five and two patients, respectively, all infected in Sweden.

> Two patients were infected with *C. erinacei*. The SSU rDNA sequences from their samples were not identical; the sequence from patient Swec627 (KU892565) infected in Sweden differed by two SNPs from the closest *C. erinacei* match in GenBank (KC3056047), while

the sequence from patient Swec653 infected in Greece was 100% identical to KC3056047 (Figure 2). The actin DNA sequence obtained from isolate Swec627 was 100% identical to a *C. erinacei* isolate (MN237648) from a European badger in Poland (unpublished). Based on *gp60* analysis, a new *C. erinacei* subtype, XIIIaA23R12, was identified in the first patient (Swec627), while subtype XIIIaA24R9 was found in the second patient (Swec653).

**Figure 2.** Phylogenetic relationships between partial SSU rDNA *Cryptosporidium* sequences obtained in the present study and sequences retrieved from the NCBI database. Trees were constructed using the neighbor-joining method based on genetic distance calculated by the Kimura's 2-parameter model as implemented in MEGA X. The final dataset included 749 positions. Bootstrap values ≥50% from 1000 replicates are indicated at each node. Isolates from this study are indicated in boldface.

Four patients were diagnosed with *C. felis*; three in Sweden, and one in Indonesia. The recently described *gp60* assay for *C. felis* [21] yielded four different sequence types.

One patient infected in Kenya with *C. viatorum* subtype XVaA3b was identified during the study period. Material from this case was used to develop a *C. viatorum gp60* subtyping assay [22].

The eight patients diagnosed with *C. meleagridis* were all infected in Asia. Six of the samples were identified as genotype 1 at the SSU rRNA locus (AF112574), while sequencing of this gene failed for the remaining two isolates. Investigation of the *gp60* gene was successful for all eight isolates and revealed three subtype families, IIIb, IIIe and IIIg, and six different subtypes (Table 6). Subtype IIIbA23G1R1c (KU852727) differed by eight SNPs in the post-repetitive part of the sequence from IIIbA23G1R1b (KJ210609), and was named IIIbA23G1R1c according to the proposed nomenclature [23].

Two subtype families of *C. cuniculus*, Va and Vb, and five different *gp60* subtypes were observed. It was noted that the *C. cuniculus* Vb sequences published in GenBank carried 2–5 ACA repeats just after the TCA repeats (data not shown); thus, we followed the recommendation by Nolan et al. from 2010 [32] and included an R in the subtype designation, as in VbA29R4 for isolate Swe658, with 29 TCA repeats followed by 4 ACA repeats (KU852734). One patient infected in Greece carried a new subtype, VbA31R4. The sequence from patient Swec678 had the same numbers of TCA and ACA repeats as a VbA20R2 strain from the UK (GU971649), but differed by six SNPs and a 3 bp deletion in the post-repetitive part of the sequence, resulting in five amino acid changes. The subtype variant was designated VbA20R2b (KU852735), according to the proposed *gp60* nomenclature [33].

A third subtype family of *Cryptosporidium* horse genotype, VIc, was identified in a patient (Swe490) who had visited Kenya. This subtype, referred to as VIcA16 (KU852738), showed 88% and 87% identity to subtype families VIa and VIb, respectively. Four ACA repeats followed just after the TCA repeats, a feature also observed in *C. cuniculus* subtype family Vb. An extended molecular investigation including the SSU rRNA, actin, and *hsp70* genes was performed. The SSU rDNA sequence (KU892564) differed by one SNP from *Cryptosporidium* horse genotype sequences deposited in GenBank (FJ435962, MK775041). The closest match for the actin sequence (KU892571) was a sequence from *Cryptosporidium tyzzeri* (AF382343), from which it differed by eight SNPs. No actin sequences from the horse genotype were available in GenBank for comparison. The *hsp70* sequence KU892577 (1895 bp) showed 100% identity with the four *Cryptosporidium* horse genotype sequences available in GenBank. However, none of these sequences (298–403 bp) were long enough to cover the area with the 12 bp segment repeats towards the 3 end of the *hsp70* gene. The horse genotype sequence from our study exhibited 10 repeats of a 12 bp segment with SNPs at the third and sixth bases—GG(C/T)GG(A/T)ATGCCA.

## *3.9. Phylogenetic Analyses*

A phylogenetic tree, which contained representative SSU rDNA sequences from all 12 species and genotypes detected in the present study and published sequences from most *Cryptosporidium* species/genotypes hitherto detected in humans, was constructed (Figure 2). In the *gp60* tree, one representative sequence from each subtype family detected in this study, except *C. felis* and *C. suis*, was included (*n* = 26). Sequences from established subtype families are clustered with sequences from this study. The new *C. parvum* subtype family IIt clustered with IIb, subtype family IIr with Ie, and subtype family IIs with IIe, while the new *Cryptosporidium* horse genotype subtype family VIc clustered with VIa and VIb (Figure 3).

**Figure 3.** Phylogenetic relationships between partial *gp60 Cryptosporidium* sequences obtained in the present study and sequences retrieved from the NCBI database. Trees were constructed using the neighbor-joining method based on genetic distance calculated by the Kimura's 2-parameter model as implemented in MEGA X. The final dataset included 840 positions. Bootstrap values ≥50% from 1000 replicates are indicated at each node. New subtype families observed in this study are indicated by filled circles. All isolates from this study are indicated in boldface.


**7. Conclusion**

In this chapter, we discussed the use of medical image processing and analysis in detecting and quantification of GCA. We discussed a semi-automated segmentation of temporal arteries from 2D temporal artery US and MRI images using image processing and analysis algorithms. These algorithms depend on various image processing algorithms, including image enhancement, noise reduction, pixel densities histogram analysis, and statistical analysis tools. First, the Gaussian filters and noise reduction algorithms are applied to enhance the temporal artery structures, which effectively enhances the temporal artery contrast, because the shape information of the blood flow is considered. Afterward, seed points are detected automatically through threshold pre-processing operation. Based on the set of seed points and threshold analysis, region growing is applied, which grows in the target region. Then, the temporal artery region is extracted by connected threshold and region growing approaches, which are capable of segmenting the artery due to the pixel intensity thresholds and the seed point approach. Three regions of interest were extracted, the temporal artery wall, the blood flow, and the GCA region. Then the statistical and measurement tools are used to quantify the diameters, area, and volume of the GCA regions, and to detect and identify the size and location of the GCA region. The semi-automatic interaction is involved in the entire segmentation process for finding the segmentation parameters. Hence, the proposed algorithm is efficient to perform complete, and accurate extraction of temporal arteries. The proposed semi-automatic segmentation method can be used for studies focusing on three-dimensional visualization and volumetric quantification of Giant Cell Arteritis.

*Medical Image Processing and Analysis Techniques for Detecting Giant Cell Arteritis DOI: http://dx.doi.org/10.5772/intechopen.97161*


**Author details**

Aida Doroudian1 , Mahdieh Emadi1 , Reza Hosseinzadeh2 and Parvaneh Maghami1 \*

1 Department of Biology, Science and Research Branch, Islamic Azad University, Tehran, Iran

2 Department of Chromatography Research Group, Iranian Academic Center for Education, Culture, and Research(ACECR), Urmia, Iran

\*Address all correspondence to<EMAIL_ADDRESS>
© 2022 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


*1.6.1 Materials balances of electrostatic desalter*

The establishment of a material balance is necessary for modeling [7, 25, 29]. The material balance material allows us to have an idea of the results we need to get and correct some errors during the project in order to have a satisfactory performance of our facilities. To calculate the material balance of electrostatic desalter, it is necessary to know the data:

status "Expense" is similar to the desalting- dewatering process. 140 t of emulsion � 1.4 t of water in emulsion = 138.6 t of oil. The status "Expense" is similar to the

dewatered oil or desalted oil will be 138.6 t – 0.4158 t = 138.0897 t. According to this task and Russian GOST R 51828-2002, the water content in the desalted oil shall not exceed 0.5% of the mass. Thus, the water contained in the desalted oil will be:

The amount of water X is 0.0691 t.

The water content-X is 0.0691 t in the desalted oil. The total water content phase

Based on the previous results and by the possibility that we can really have more

The exercise of modeling is a variant very often useful and used in the modeling of units and devices [7, 14, 19]. This task is interesting in case we do not have a simulator or simulation and modeling program like Hysys Aspen to solve this operation. In the framework of modeling the desalination unit, we use the ASTM D 341-2003 standard is based on Walter's equation and proposes the dependence of

*lg* � *lg*ð Þ¼ *ν* þ 0, 8 *a* þ *b* � *lgT*, (6)

*a* ¼ *lg* � *lg*ð Þ� *ν*1 þ 0, 8 *b* � *lgT*1 (7)

0.4191 t + 0.4191 t = 0.8383 t. Consequently, the summary material balance of the installation is made. The total amount of drainage water is equal to the drainage water by oil treatment stage: 0.9332 t + 14.07 t = 15.0032 t. The material balance of

losses. We arbitrarily decide to multiply our losses by 2; the total loss is:

the electrostatic desalter installation is presented in **Table 2**.

*1.6.2 Modeling of the desalting process with electrostatic desalter*

the kinematic viscosity of crude oil (hydrocarbon):

100 = 0.4191 t. The amount of

138*:*0897 t � 99*:*95% mass*:* (4) X � 0*:*05% mass*:* (5)

desalting-dewatering process. Loss is equal: ð Þ 138*:*6�0*:*3

*The descriptive diagram of the desalting process.*

*Crude Distillation Unit (CDU)*

*DOI: http://dx.doi.org/10.5772/intechopen.90394*

**Figure 8.**

**115**

in the "incoming" status is 14 t + 0.14 t = 14.14 t.

The quantity of oil emulsion chosen is 140 t/h. the water Content of the initial emulsion is 1% of the total mass. The consumption of the demulsifier (surfactant) is 30 g/t. Our work in this part is to make material balances of the pre-treatment of the oil at the refinery. Electrostatic desalter performs two procedures at the same time which are: dehydration and desalination. The descriptive diagram e of the desalting process is presented in **Figure 8**. The amount of freshwater or water processing supplied at the desalting stage is 10% of the mass. The reagent is fed only at the dehydration stage. We consider the reagent water-soluble. First, the status of "incoming" is drawn up. The

#### **Table 1.**

*The physicochemical characteristics of Bonga crude oil.*