2. Introduction on intelligence material design

### 2.1. Experimental data

production around the world. Although the research and development of CIGS are still in crucial phase due to low production yields, non-reproducibility, and non-uniformity over large area confronted during the industrialization and commercialization. Governing such issues, we published our first research paper in the year 2003 on "Steps toward industrialization of Cu-III-VI2 thin film solar cells: A novel in-line concept" [1]. After that, the concept of in-line sputtering and selenization become international standard globally. From that time, dozens of CIGS manufacturing units established worldwide but rare claim successful in production due to difficulty in controlling the local chemical composition distribution of the film. Moreover, the production efficiency of large-area photovoltaic (PV) cells and panels varies in the wide range from 6 to 13%. During the decades of fast development of Cu-III-VI2 thin film solar cells, much more research and industrial method were proposed. In this chapter, we will depict the principles and development of some essential issues for industrialization of Cu-III-VI2 thin film solar cells.

In the year 2003, we published another research "Preliminary steps toward industrialization of Cu-III-VI2 thin film solar cells: development of an intelligent design tool for non-stoichiometric photovoltaic materials" [1] pointing on the problem encountered during the commercialization. Over the years, many experimental and theoretical research works published in many journals focused on various subjects of problems and its solutions for CIGS TFSCs [2–9].

In 2013, we published one more research article "Steps toward removing some obstacles of industrialization of CIGS solar cells" [10]. This article pointing to the new concept of metal organic sputtering was used to tune and tailor the film compositions based on the programme material and device design. What shown in Figure 1 is the method of our intelligence material and device design, describing the detailed calculation of the neutral defect concentrations of non-stoichiometric CuInSe2, CuGaSe2, and ZnO in specific atomic chemical potential condi-

Figure 1. The scheme of our materials design and device design in which the electrical and device properties are

optimized, and related to the process parameters such as, chemical potential and non-stoichiometry.

tions (μx = 0, X = Cu, In/Ga, Zn).

130 Emerging Solar Energy Materials

We all know that Cu-III-VI2 typically have a wide phase stability range, which extends a few atomic percents of the chemical composition of the thin-film, contract to III-V, and II-VI compounds. Shown in Figure 2 is the chemical composition for a near-stoichiometric CuInSe2. The variations in the CuInSe2 film was detected using a transmission electron microscope (TEM) equipped with a field emission gun [10]. A similar result had also been reported for CIGS thin-film [11].

#### 2.2. Theoretical data

In 2003, we published an example of the design tool for the non-stoichiometric compound using the concept of minimization of total free energy [1, 12, 13], which includes the configurational entropy, that defined as;

Figure 2. Chemical composition of a near-stoichiometric CuInSe2 film measured consecutively by using an electron beam with a 3 nm probe size along a line marked on a TEM micrograph (left) and the plotted data (right) (corresponding to the data in Table 1).


Table 1. Chemical composition of a near-stoichiometric CuInSe2 films.

$$\text{G(T, Crystal\ size)} = \Sigma n\_i E\_{\text{ft}} - T S\_{\text{config}}, \\ \text{S}\_{\text{config}} = K \ln \frac{N\_{\text{total}}!}{\pi\_i N\_{\text{j}}!} \tag{1}$$

Figure 3. The calculated carrier concentration and electrical conductivity of CuInSe2 (left) and CuGaSe2 (right) at 300 K.

Some Essential Issues and Outlook for Industrialization of Cu-III-VI2 Thin-Film Solar Cells

http://dx.doi.org/10.5772/intechopen.77023

133

Figure 4. The measured conductivity of the CuInSe2 thin-film along the Cu2Se-In2Se3on-tie line with composition (Cu2Se)

1x(In2Se3)x(line 1) and the calculated range (between line 2 and 3) near the Cu2Se-In2Se3 tie line at 300 K.

where ni is the number of the ith defect, Efi is the formation energy, Sconfig is the configurational entropy, T is the temperature, K is the Boltzmann constant, N is the total number of lattice sites, and Ni is the total number of defect sites of the ith defect. We find the possible results for the coexistence of donors and acceptors in CuMSe2 (M = In, Ga), which includes either the new defects produced through interaction or donor-acceptor pair/cluster formation.

Table 2 shows the defect formation energies and the defect transition levels. We also find the possible phases of CuMSe2 resulted due to the compensated donor-acceptor pairs in different Cu concentration, for example, Cu1M3Se5 phase is observed by 80% Cu1M5Se8 and 20% CuMSe2.


Table 2. The defect formation energies and defect transition levels used in our calculations [14].

Some Essential Issues and Outlook for Industrialization of Cu-III-VI2 Thin-Film Solar Cells http://dx.doi.org/10.5772/intechopen.77023 133

G T; Crystal size <sup>¼</sup> <sup>Σ</sup>niEfi � TSconfig, Sconfig <sup>¼</sup> Kln Ntotal!

Maximum 28.2 28.1 57.1 1.18 Minimum 17.2 22.6 47.9 0.62 Average 20.9 25.9 53.3 0.81 Standard deviation 2.73 1.37 2.80 0.12

Cu(at%) In(at%) Se(at%) Cu/In

where ni is the number of the ith defect, Efi is the formation energy, Sconfig is the configurational entropy, T is the temperature, K is the Boltzmann constant, N is the total number of lattice sites, and Ni is the total number of defect sites of the ith defect. We find the possible results for the coexistence of donors and acceptors in CuMSe2 (M = In, Ga), which includes either the new

Table 2 shows the defect formation energies and the defect transition levels. We also find the possible phases of CuMSe2 resulted due to the compensated donor-acceptor pairs in different Cu concentration, for example, Cu1M3Se5 phase is observed by 80% Cu1M5Se8 and 20%

defects produced through interaction or donor-acceptor pair/cluster formation.

Table 2. The defect formation energies and defect transition levels used in our calculations [14].

Table 1. Chemical composition of a near-stoichiometric CuInSe2 films.

CuMSe2.

132 Emerging Solar Energy Materials

<sup>π</sup>jNj! (1)

Figure 3. The calculated carrier concentration and electrical conductivity of CuInSe2 (left) and CuGaSe2 (right) at 300 K.

Figure 4. The measured conductivity of the CuInSe2 thin-film along the Cu2Se-In2Se3on-tie line with composition (Cu2Se) 1x(In2Se3)x(line 1) and the calculated range (between line 2 and 3) near the Cu2Se-In2Se3 tie line at 300 K.

To solve the charge neutrality equation, we require several parameters, such as the carrier concentrations, Femi level at a certain temperature and ionized/neutral defect concentrations. In Figure 3, the calculated carrier concentration and electrical conductivity of CuInSe2 and CuGaSe2 at 300 K are shown. Note that in Figure 4, the conductivity will increase first and then decrease down to the film composition from stoichiometry to Cu-poor, after that the conductivity is even lower than that of the stoichiometry.

#### 3. Brief on the device design

The simulator SCADS 3.2 [15] has been widely accepted for numerical analysis of CIGS solar cell devices. In 2014, the 19% efficiency of the solar cell was simulated by Naoki Ashida et al. [16]. In this report, the 2 μm thick CIGS absorber layer was divided into two regions, such as low defect density region (front side) and high defect density region (back side).

We also developed an alternate full function (indoor, outdoor, and I-V, C-V) analytic solar cell simulator, in which the following (time-independent) device equations are considered.

a. The continuity equation

$$\mathbf{O} = -\frac{1}{\mathbf{q}} \frac{\mathbf{d}}{\mathbf{dx}} \boldsymbol{\tau}\_p + \mathbf{G}\_p - \mathbf{R}\_p,\\ \mathbf{R}\_p = \frac{\Delta p}{\mathbf{\tau}\_h},\\ \Delta p = p\_n - p\_{no} \tag{2}$$

$$\mathbf{O} = -\frac{1}{\mathbf{q}} \frac{\mathbf{d}}{\mathbf{dx}} \boldsymbol{\tau}\_n + \mathbf{G}\_n - \mathbf{R}\_n \boldsymbol{R}\_n = \frac{\Delta n}{\mathbf{\tau}\_\varepsilon}, \Delta n = n\_p - n\_{po} \tag{3}$$

b. Transport equations

$$
\tau\_p = \mathbf{p} \mathbf{q} \mu\_p \to -\mathbf{q} D\_p \frac{\mathbf{dp}}{\mathbf{dx}} \tag{4}
$$

$$
\pi\_n = \mathbf{n} \mathbf{q} \mu\_n \to + \mathbf{q} D\_n \frac{\mathbf{dn}}{\mathbf{dx}} \tag{5}
$$

In the last decades, many studies on interface and surface compositional profile have been dealt with the advanced characterizations for the high-efficiency CIGS solar cells. A few

Figure 5. The comparison of the computed efficiencies as compared with NREL's database of ZnO/CdS/CuInSe2 solar

Some Essential Issues and Outlook for Industrialization of Cu-III-VI2 Thin-Film Solar Cells

http://dx.doi.org/10.5772/intechopen.77023

135

2. Ordered defect compounds (ODC: CuInSe2, CuIn3Se5, CuIn5Se8, etc.) resulted from CuInSe2/CIGS solar cell studies, in which the X-ray photoelectron Spectroscopy (XPS) investigations depicted the depletion of Cu near the surface, and the theory as well

3. Shown in Figure 6, defect pairs (2Vcu and Incu) stabilizes the CuInSe2 surface and band alignment gives hole barrier at the interface via the investigations by low energy electron

1. Conduction band profiles are changed by the three stage selenization [17].

experiments predicted ordered defect compound structured [18].

examples are:

cells: (upper) 3D view, (lower) 2D view.

We have considered all the boundary conditions (n-QNR/SCR interface, front contact, p-QNR/ SCR interface, and back contact), in which QNR stands for the quasi-neutral region and SCR stands for space charge region for a typical n-CdS/p-CIGS device structure. In results of our simulation, we show that the higher efficiency cells are distributed along the line from Cu: Se = 0.3:0.5 to the stoichiometric point and the line from Cu:Se = 0.21:0.52 to the stoichiometric point. What is shown in Figure 5 is the comparison of the computed efficiencies with the national renewable energy laboratory (NREL) experimental data, where the device structures of these cells are ZnO/CdS/CuInSe2. As to the higher efficiency cells, the atomic compositions are especially concentrated near Cu:Se = 0.22:0.51 or along the line from Cu:Se = 0.22:0.51 to the stoichiometric point.

To solve the charge neutrality equation, we require several parameters, such as the carrier concentrations, Femi level at a certain temperature and ionized/neutral defect concentrations. In Figure 3, the calculated carrier concentration and electrical conductivity of CuInSe2 and CuGaSe2 at 300 K are shown. Note that in Figure 4, the conductivity will increase first and then decrease down to the film composition from stoichiometry to Cu-poor, after that the conduc-

The simulator SCADS 3.2 [15] has been widely accepted for numerical analysis of CIGS solar cell devices. In 2014, the 19% efficiency of the solar cell was simulated by Naoki Ashida et al. [16]. In this report, the 2 μm thick CIGS absorber layer was divided into two regions, such as low defect density region (front side) and high defect density region

We also developed an alternate full function (indoor, outdoor, and I-V, C-V) analytic solar cell

τh

τe

dp

dn

, Δp ¼ pn � pno (2)

, Δn ¼ np � npo (3)

dx (4)

dx (5)

simulator, in which the following (time-independent) device equations are considered.

dx <sup>τ</sup><sup>p</sup> <sup>þ</sup> Gp � Rp, Rp <sup>¼</sup> <sup>Δ</sup><sup>p</sup>

dx <sup>τ</sup><sup>n</sup> <sup>þ</sup> Gn � Rn, Rn <sup>¼</sup> <sup>Δ</sup><sup>n</sup>

τ<sup>p</sup> ¼ pqμ<sup>p</sup> E � qDp

τ<sup>n</sup> ¼ nqμ<sup>n</sup> E þ qDn

We have considered all the boundary conditions (n-QNR/SCR interface, front contact, p-QNR/ SCR interface, and back contact), in which QNR stands for the quasi-neutral region and SCR stands for space charge region for a typical n-CdS/p-CIGS device structure. In results of our simulation, we show that the higher efficiency cells are distributed along the line from Cu: Se = 0.3:0.5 to the stoichiometric point and the line from Cu:Se = 0.21:0.52 to the stoichiometric point. What is shown in Figure 5 is the comparison of the computed efficiencies with the national renewable energy laboratory (NREL) experimental data, where the device structures of these cells are ZnO/CdS/CuInSe2. As to the higher efficiency cells, the atomic compositions are especially concentrated near Cu:Se = 0.22:0.51 or along the line from Cu:Se = 0.22:0.51 to the stoichio-

tivity is even lower than that of the stoichiometry.

<sup>O</sup> ¼ � <sup>1</sup> q d

<sup>O</sup> ¼ � <sup>1</sup> q d

3. Brief on the device design

134 Emerging Solar Energy Materials

(back side).

a. The continuity equation

b. Transport equations

metric point.

Figure 5. The comparison of the computed efficiencies as compared with NREL's database of ZnO/CdS/CuInSe2 solar cells: (upper) 3D view, (lower) 2D view.

In the last decades, many studies on interface and surface compositional profile have been dealt with the advanced characterizations for the high-efficiency CIGS solar cells. A few examples are:


The properties of the interfaces in semiconductor devices are critically dependent on the detailed atomic structure of the contact plane. Therefore, the model of the junction in chalcopyrite thin-films was simulated by the well-defined interface to classify the influence of grain boundaries, lateral inhomogeneity and chemical variations in compositions and their distributions across and aside from the contact planes. By X-ray photoelectron spectroscopy (XPS), ultra-violet photoelectron spectroscopy (UPS), Low energy electron diffraction (LEED), scanning tunneling microscopy (STM), and X-ray photoemission electron microscope (XPEEM), we can be obtain all these information using the modern analytic tools such as in-situ band alignment, band broadening, and chemical reacted interfaces. After that by experiments and incorporated with our material analysis we could determine their crystalline structure with high resolution for better accuracy and reproducibility obtained in the device design for the

Some Essential Issues and Outlook for Industrialization of Cu-III-VI2 Thin-Film Solar Cells

http://dx.doi.org/10.5772/intechopen.77023

137

In sections above, the opto-electrical properties of the polycrystalline semiconductors are

In this section, the way of the poly-structure generation is better described through careful observation of the transfer procedures during the manufacturing process, which would be beneficial to know the deposited atoms final positions and the microstructures of the materials. The composition and the structures could be tuned based on controlling and modifying the process by adjusting the process parameters in order to obtain the desired opto-electrical properties.

We describe the better understanding of the way to generate poly-structure through careful observation of the particle transfer procedures during the manufacturing processes after knowing the final positions of the deposited atoms and the materials microstructures. On controlling and modifying the process, the composition as well structure can be tuned directly

The metallic grain structures are described by the original Thornton's zone model [21] according to the sputtering gas pressure and the substrate temperature. Since the high deposition rate, the magnetron sputtering process is most preferred for the industrial application. Also, the energy-dependent sputter yield is noted. Ellmer illustrates the inter-relationships between the process parameters (like substrate temperature and deposition rate) and the structural/optoelectrical properties in a new model [22]. However, the pressure (particles

The Berg's model is particularly utilized in the ZnO reactive sputtering. Basically, the surface coverage on the deposited film is just the composition of the film, but the composition is not easy to control since the system is unstable, where it requires the plasma diagnose sensor for feedback control. About the basic idea of the Berg's model [23, 24], the changes of the number

of absorbed oxygen atoms per unit area Nx at the surfaces of the target is:

by varying the process parameters to acquire the desired opto-electrical properties.

future industrial applications.

4. Brief on the process design

affected by structure and composition greatly.

momentum) effect is not considered in this model.

4.1. Berg's model

Figure 6. The complete band alignment includes the copper depletion at the interface.

diffraction (LEED), angular resolved ultraviolet photoelectron spectroscopy (ARUPS) and auger electron spectroscopy (AES) [14].

4. Secondary ion mass spectrometry (SIMS) depth profile of Cu, In, Ga, Se, Cd, and Na revealed the CdS/CIGS/ZnO diffusion phenomena as shown in Figure 7 [19].

Sample Figure 7(a) and (b) were obtained from the different origins, note that the difference in the Ga profile in the SIMS depth profiles are due to the different processes.

5. Defect in grains and grain boundaries [20].

Figure 7. SIMS depth profile of Cu, In, Ga, Se, Cd, and Na. (1) CdS/CIGS and ZnO diffusion. (2) Cu, In, Ga, and Se depth profile. (3) Quantitative analysis of Na in CIGS.

The properties of the interfaces in semiconductor devices are critically dependent on the detailed atomic structure of the contact plane. Therefore, the model of the junction in chalcopyrite thin-films was simulated by the well-defined interface to classify the influence of grain boundaries, lateral inhomogeneity and chemical variations in compositions and their distributions across and aside from the contact planes. By X-ray photoelectron spectroscopy (XPS), ultra-violet photoelectron spectroscopy (UPS), Low energy electron diffraction (LEED), scanning tunneling microscopy (STM), and X-ray photoemission electron microscope (XPEEM), we can be obtain all these information using the modern analytic tools such as in-situ band alignment, band broadening, and chemical reacted interfaces. After that by experiments and incorporated with our material analysis we could determine their crystalline structure with high resolution for better accuracy and reproducibility obtained in the device design for the future industrial applications.
