The manufacturing of perovskites is a complex process; therefore, the scientific community mainly relies on simulation tools for material optimization. For this purpose, various simulation tools such as wx-AMPS, SCAPS-1D, Silvaco-TCAD, etc. are available online for research and design, but we have used SCAPS-1D in this work.

CsPbI₃ was selected because of its thermal stability due to its band gap of 1.73 eV, it has a wide absorption range of sunlight, which allows it to capture a large part of the solar spectrum and this property is essential for efficient conversion of solar energy into electricity. However, it is well known that CsPbI₃ suffers from phase instability at room temperature, often transforming from the black perovskite (α) phase to the yellow non-perovskite (δ) phase. This instability indeed limits its long-term operational stability. Nevertheless, our choice of CsPbI₃ is motivated by its wide band gap (1.73 eV), all-inorganic composition (free from organic cations such as MA⁺ or FA⁺), and potential for high thermal stability when stabilized via compositional or interfacial engineering, as reported in recent studies [5][6]. Therefore, our simulation focuses on its intrinsic photovoltaic potential under idealized stable conditions. Its structure is shown in Figure 1.

Figure 1. Crystal structure of CsPbI₃.

Before starting the simulation, it is essential to have prior knowledge of certain parameters of each layer of the cell. Table 1 and Table2 group together the parameters of the different materials used for the simulation. All material parameters, such as bandgap, mobility, and carrier densities, were taken from peer-reviewed literature [7]-[11] without manual fitting, ensuring that the simulated device structure reflects realistic material properties reported experimentally.

Table 1. Parameters of each cell layer used for simulation

Table 2. HTM layer parameters.

Table 1 shows the input parameters of ETM, HTM of the absorber layer. On the other hand, Table 2 groups the HTM parameters for the second part of the simulation in order to find a perfect combination. In addition, all simulations were carried out using the conditions of the AM1.5G solar spectrum, which is equivalent to a power density of 1000 Wm² at 300 K ambient temperature.

PEDOT:PSS and CuSCN are two commonly used materials in perovskite solar cells due to their specific advantages. PEDOT (poly(3,4-ethylenedioxythiophene)) and PSS (poly (styrene sulfonate)) (PEDOT:PSS). These two materials refer to a mixture of two conductive polymers, This mixture is used in many electronic and optical applications due to its high conductivity and transparency properties, which facilitates the transport of electrical charges generated by the perovskite to the electrodes of the solar cell, good transparency that allows light to reach the perovskite and generate charges and facilitates the alignment of energy levels between the perovskite and the electrode, thus improving the efficiency of charge collection.

CuSCN (copper thiocyanate) is a chemical compound consisting of copper ions (Cu²⁺) and thiocyanate ions (SCN⁻), often used as a semiconductor material in some electronic devices and as a catalyst in certain chemical reactions. It is a chemically stable material, which is important for the long-term durability of perovskite solar cells and offers simpler and potentially lower manufacturing costs.

3.1.1. Effect of the Thickness E (μm) of the PTAA Layer (HTM)

In this study, we also modulated the thickness of PTAA (hole transport layer) Poly(triarylamine) (PTAA) instead of just PTAA, in a variation range of 50 nm to 300 nm to determine the optimal thickness of the HTM material by fixing the other parameters constant. Figure 2 presents the effect of this thickness variation on the performance of the solar cell. We note that as the thickness of this layer varies, the conversion efficiency η, the short-circuit current density and the open-circuit voltage remain almost constant, and we observe a slight decrease in the form factor FF from 0.05 μm to 0.15 μm before being constant up to 0.30 μm.

Figure 2. Variation of HTM layer thickness as a function of cell characteristics.

After extensive analysis, we determined the optimal HTM thickness to be 50 nm, which was consistent with the initial setting of our study. In a solar cell structure, the p-type layer (HTM) should generally be thicker than the n-type layer (ETM). This helps reduce the probability of charge recombination by facilitating the rapid transport of an equal number of charge carriers to their respective terminals [11]. Furthermore, a larger thickness for the HTM has additional benefits, as it improves the ability of the light-collecting layer to absorb photons.

3.1.2. Effect of the Thickness W (μm) of the ETM Layer

ZnO layer thickness (ETM), changing it from 20 nm to 200 nm, while the other parameters were kept constant. Figure 3 presents the results of this variation of the ETM thickness and illustrates the effect of this variation on the performance parameters of the solar cell. From 0.02 to 0.2 μm, we observe a decrease in the short-circuit current density J_sc (mA/cm²) from 18.075 to 18.019 mA/cm² or a rate of 0.3%; as well as for the form factor of 84.00% at 83.08% or a rate of 1.1% and the conversion efficiency η (%) of 22.32 to 21.99 or a rate of 1.5%, on the other hand the open circuit voltage remains constant V_oc (V).

Figure 3.ZnO thickness depending on cell characteristics.

Increasing the ETM thickness resulted in lower values of V_oc, J_sc, FF and η, although this decrease was insignificant. This observation can be attributed to the fact that thicker ETM partially absorbs light, thus delaying charge generation and electron collection rate. As the ETM becomes thicker, the performance loss becomes more pronounced due to the decrease in light transmission [10]. ZnO was selected as the electron transport material due to its high electron mobility, suitable band alignment with CsPbI₃, and low-temperature processability. While TiO₂ is more commonly used, ZnO offers better conduction properties and can reduce interfacial recombination when properly passivated. Comparative results in Section 3.3 confirm its superior performance in this configuration.

However, it is important to emphasize that, according to our results, the thickness of the ETM had a limited impact on the photovoltaic performance of the solar cell, which is consistent with previous work [11]. Therefore, a thickness of 20 nm was identified as the best thickness for ETM in this study.

3.1.3. Effect of the Thickness E (μm) of the CsPbI₃ Absorbing Layer

For this part, we study the cell characteristics as a function of the thickness of the absorbing layer, which varies from 200 nm to 1100 nm, keeping the other parameters constant. The optimal thickness of the absorbing layer is crucial to maximizing photon absorption and generating electron-hole pairs.

Figure 4. Variation of the thickness (μm) of the perovskite depending on the characteristics of the cell.

Therefore, the overall performance of the solar cell mainly depends on the thickness of the absorber layer. The graphs shown in Figure 4 illustrate the variations of the open-circuit voltage (V_oc), the short-circuit current density (J_sc), the fill factor (FF) and the efficiency (η) as a function of the thickness of the perovskite layer, respectively.

According to the simulation results, we notice that when the thickness of the active layer increases, there is a decrease in the open circuit voltage (V_oc) from 1.49 V to 1.45 V or a rate of 2.7% and the form factor (FF) which goes from 85.51 to 80.98 or a rate of 5.3%, on the other hand we have an increase in the short-circuit current density (J_sc) from 13.10 mA/cm² to 20.65 mA/cm² or a rate of 57.6% and the conversion efficiency (η) from 16.70% to 24.24% it reaches this percentage at 1μm of the thickness, after this value it undergoes a fall.

By increasing the thickness of the active layer, the current density (J_sc), open-circuit voltage and efficiency increase because a thicker absorber layer will absorb more photons, which will create many more excitons and allow the generation of electron-hole pairs.

But with too thick an absorbing layer, the chances of recombination also increase because the generated photocharges have to travel a greater distance to be diffused [12]. This increased absorption helps increase the efficiency of the solar cell by capturing more photons for the generation of electron-hole pairs.

Figure 5. Variation of PTAA acceptor concentration (Na) as a function of cell characteristics.

In this study, the Na doping of PTAA is considered as a theoretical assumption used to explore how the modification of acceptor density in the HTM layer influences cell performance. In practice, alkali-metal incorporation in organic HTMs remains challenging; however, recent works have reported partial ionic doping or surface treatment approaches that modify energy levels or improve hole extraction. Our approach, therefore, aims to provide an initial numerical insight rather than a confirmed experimental process. Doping is a very important process used to improve the photovoltaic properties of semiconductors, it influences the electrical behavior of the layers and thus affects the cell performance. Figure 5 shows the effect of Na of PTAA on the open circuit voltage V_oc, short circuit current J_sc, form factor FF and conversion efficiency η of the PSC when varied from 10¹² cm⁻³ to 10¹⁶ cm⁻³, and we notice an increase in all the parameters.

This increase in electrical potential creates a separation of excitons with a lower recombination rate, which increases the performance of the cell. It promotes conductivity, thus facilitating the transport of holes to the anode, while reducing the defect and impurity density in the layer.

This part aims to find a HTM material that performs better than the organic PTAA material that allowed us to obtain 24.24% efficiency. So, we will fix the other parameters of the perovskite and keep ZnO as the ETM because it has the best performance compared to other ETMs, and it is therefore the best ETM for the CsPbI₃ absorbing layer [13]. We will use two other HTM materials, PEDOT:PSS and CuSCN (see Figure 6).

For PEDOT:PSS

Figure 6. Variation of the perovskite layer thickness with PEDOT:PSS as HTM as a function of the cell characteristics.

For CuSCN

We summarize (Table 3) the performance obtained after the use of different hole transport material, both fixing the active layer (CsPbI₃) and the layer of electron transport material (ZnO) (see Figure 7).

Figure 7. Variation of the thickness of the perovskite layer with CuSCN as HTM.

Table 3. Simulation results of the performance of each HTM.

Figure 8. The performance of each HTM layer.

After the simulation of the two materials, we notice that the results of the materials are almost similar, but CuSCN has better performance than PEDOT:PSS, but we retain that PTAA remains the best HTM material for a CsPbI₃ absorbing layer (see Figure 8).

Table 4 shows the comparative analysis of recent experimental and theoretical work on CsPbI₃-based perovskites with our results. The SCAPS-1D model used here does not include explicit interface defect layers or surface recombination velocities. While this simplification allows for a clearer evaluation of bulk-layer effects, it may slightly overestimate the simulated efficiency compared to experimental data.

Table 4.The comparison of PV parameters of different solar cells based on CsPbI₃.

We note that the efficiency reached 19.1% in 2022 theoretically and 18.4% experimentally in 2019. As the results were not up to expectations in most theoretical studies, we tried to optimize the performance of this perovskite, and our results were the best, with an efficiency of 24.2%. It should be noted that the present simulation does not explicitly account for defect states at interfaces, ion migration phenomena, or long-term phase degradation, which are known to affect the real-world stability of perovskite devices. These aspects will be considered in future work using defect-layer and time-dependent modeling to enhance the physical accuracy of the simulation.