The triumphant development of non-lead perovskites such as MAGeI₃ (CH₃NH₃GeI₃) and CsSnI₃ has paved the way for high-throughput thin-film solar cells (Hemalatha et al., 2023; Panjikaran et al., 2024). These materials exhibit compelling electrical, optical, and processing properties that rival or surpass those of their lead-based counterparts. Specifically, they offer advantages such as bandgap tunability, large carrier mobility, strong visible–infrared range absorption coefficients, and improved stability compared to MAPbI₃.

The Solar Cell Capacitance Simulator (SCAPS) is a widely recognized and utilized software environment for solar modeling research, developed by the Electronic and Information Systems Department at Ghent University in Belgium (Burgelman et al., 2025; Al-Hattab et al., 2022). This simulation tool employs fundamental equations, including electron and hole Poisson equations, continuity equations, and transport equations, to model the capture of sunlight and the subsequent generation, movement, and extraction of electron-hole pairs in solar devices.

One of SCAPS’s key strengths is its flexibility, allowing researchers to design and simulate specific solar devices by manipulating a broad range of material properties. The simulation outputs are invaluable for assessing the impact of various factors on device performance and for gaining insights into crucial solar cell characteristics. These include material defect density, defect placement, recombination rates, and band gap alignment across different layers of the device (Burgelman et al., 2004; Burgelman et al., 2025).

The versatility of SCAPS makes it an essential tool in addressing a wide spectrum of fundamental questions in both materials science and device physics related to solar cell technology. By enabling detailed simulations and analyses, SCAPS contributes significantly to the advancement of solar cell research and development.

The behavior and characteristics of charge carriers within solar devices are fundamentally described by three key equations:

a) The Poisson equation

These three equations collectively form the mathematical foundation for understanding and modeling the movement, distribution, and interactions of electrons and holes in solar cell structures. They provide a comprehensive framework for analyzing the electrostatic potential, charge carrier dynamics, and current flow within photovoltaic devices.

Fundamental equations used in the SCAPS-1D simulation software for modelling solar cell devices include

a) Carrier Continuity Equation: This equation describes the change in hole and electron concentrations over time, considering current densities, recombination, and generation processes (Islam et al., 2021).

In Equations 1, 2, J_p and J_n are hole and electron current densities, respectively.

R(x) and G(x) are recombination and generation processes, respectively.

b) Diffusion–Drift Equations: These equations describe the current densities for holes and electrons in terms of carrier concentrations, mobilities, and diffusion constants.

In the above Equations 3, 4, μ n   a n d   μ p are electron and hole mobilities and D_p and D_n are hole and electron diffusion constants, respectively.

c) Poisson Equation: This equation relates the electrostatic potential to charge carrier concentrations and doping densities in the semiconductor.

Poisson equation is given in the Equation 5, where V(x) is the electrostatic potential, ε is the absorber permittivity, q is the electronic charge, N D + and N A − are the donor and acceptor densities, respectively, and finally, p(x) and n(x) are the position-dependent hole and electron concentrations.

The working mechanism of the proposed device is shown in Figure 3. When photons with energy greater than or equal to the band gap of the absorber layers (MAGeI₃ and CsSnI₃) fall on the solar cell, they excite electrons from the valence band to the conduction band, creating electron–hole pairs. In the MAGeI₃ layer, photons with energy greater than 1.78 eV excite electrons from the valence band (−5.7 eV) to the conduction band (−3.92 eV). These excited electrons then move through the MAGeI₃ layer to the ZnO layer. Similarly, in the CsSnI₃ layer, photons with energy greater than 1.4 eV excite electrons from the valence band (−5.0 eV) to the conduction band (−3.6 eV). The electrons in the conduction band of CsSnI₃ move toward the ZnO layer, while the holes left in the valence band of CsSnI₃ move toward the P3HT layer.

The electrons that reach the ZnO layer are collected by the FTO layer and then move toward the Al electrode, while the holes that reach the P3HT layer are collected by the Ag electrode. This movement of electrons and holes ensures efficient charge separation and collection, converting light into electrical energy. The energy band diagram helps visualize this process by showing the energy levels and the direction of electron and hole movement, with curved arrows indicating the pathways for electrons and holes. This mechanism utilizes the different band gaps of the absorber layers to capture a broader spectrum of sunlight, enhancing the efficiency of the solar cell.

The thicknesses of the absorber layers of CsSnI₃ and MAGeI₃ were varied and plotted, and the effects of changing the thicknesses were investigated. The opto-electronic characteristics were studied under the AM1.5 illumination. The plots presented in Figures 4A–D illustrate the behavioral patterns of open-circuit voltage (V_OC), short-circuit current density (J_SC), fill factor, and efficiency as the thickness of the CsSnI₃ layer is varied from 200 nm to 1,000 nm. It is observed that with an increase in the thickness of the CsSnI₃ layer, both V_OC and fill factor exhibit a slight decreasing trend, while the current and efficiency curves show an upward trend. This might be because of the band alignment mismatch, due to which interfacial recombination can occur. The optimal results are achieved with a CsSnI₃ thickness of 1,000 nm, yielding values of V_OC = 1.23 V, J_SC = 34.79 A, a fill factor of 84.35%, and an efficiency of 36.37%, which represent the highest values recorded to date. On the other hand, no significant changes were seen when we varied the thickness of the MAGeI₃ layer.

In this proposed model, the hole transport layer P3HT thickness is varied from 0.01 µm to 0.1 µm, and the results are given in Table 2. It is observed that the optimum performance of the device is achieved at the P3HT layer thickness of 0.01 µm. In the experimental aspect, acquiring a thickness of 10 nm is impractical, so the HTL thickness is fixed at 50 nm.

Figure 5 shows the difference in the device performance with and without the defects. We investigated the incorporation of defect levels in CsSnI₃ and MAGeI₃ layers, ranging from 1 × 10¹⁰ to 1 × 10¹⁴, and analyzed their impact on open-circuit voltage (V_OC), short-circuit current density (J_SC), fill factor, and overall device efficiency. The resulting graphs are shown in Figures 6A–D. The observed trend indicates that both V_OC and J_SC remain relatively stable up to a defect concentration of 1 × 10¹², after which a decline is noted. Conversely, the fill factor exhibits a decreasing trend with increasing defect levels up to 1 × 10¹², followed by a slight improvement. When we also consider the MAGeI₃ layer, the device efficiency also decreases, as anticipated in the presence of defects. Consequently, we determine the optimal defect level to be 1 × 10¹².

The density of states in the conduction and valence bands varies with temperature, as follows in the Equations 6–8, where T₀ represents the default temperature, set at 300 K, where the parameter value should be defined in SCAPS-1D. Similarly, the thermal velocity (V_th) is also influenced by temperature, as shown in the following equations. All other parameters are considered to be independent of temperature. The diffusion coefficient used in the calculations, given by D = μ K T , is temperature-dependent, which contradicts the information provided in the initial SCAPS manual. N C T = N C T 0   T T 0 1.5 (6) N V T = N V T 0   T T 0 1.5 (7) V th T = V th T 0   T T 0 0.5 (8)

Figure 7 shows J–V (current density vs. voltage) curves for different temperatures, each represented by a distinct color and symbol. As temperature increases, we observe a slight shift in the curves, indicating changes in the device’s electrical characteristics. The open-circuit voltage (V_OC) appears to decrease slightly with increasing temperature, which is typical for solar cells due to increased carrier recombination at higher temperatures. However, the short-circuit current density (J_sc) seems to increase with temperature, likely due to enhanced carrier generation. The overall shape of the curves suggests that the fill factor may also be affected by temperature changes, potentially improving slightly at higher temperatures. These temperature-dependent variations in V_OC, J_SC, and fill factor collectively influence the device’s efficiency, with the optimal operating temperature likely falling within the measured range. Table 3 shows the values of the parameters.

We also investigated the effects of temperature variation on the device, systematically varying the temperature from 260 K to 380 K. Figure 7 illustrates the impact of temperature changes on open-circuit voltage (V_OC), short-circuit current density (J_SC), fill factor, and device efficiency. It is observed that V_OC exhibits a slight decrease, while J_SC increases with rising temperature. This behavior can be attributed to changes in carrier mobility as the temperature increases. The fill factor decreases until approximately 320 K, after which it begins to rise. In contrast, device efficiency decreases linearly with increasing temperature. This pattern is evident in Figures 8A–D.

In the proposed device, when the dopant concentration of the CsSnI₃ absorber layer was varied from 1 × 10 14 to 1 × 10 17 , it was observed, from Table 4, that solar parameters values increased, especially Voc, device efficiency and fill factor, giving the maximum efficiency of 28.63%, with a fill factor of 70.61% and a V_OC of 1.1655 V. J_SC, on the other hand, was seen declining, possibly because of the chance of recombination rate due to the increase in the carriers. No particular changes were seen in the parameters when we changed the dopant concentration in the layer of MAGeI₃.

Series and shunt resistances are critical parameters in solar cells affecting their efficiency. The former is due to the current movement through the cell’s emitter and base as well as contact resistances. High series resistance reduces the fill factor and J_SC, impacting the overall performance of the device.

On the other hand, shunt resistance arises due to manufacturing defects. If the shunt resistance is low, it can create alternate current paths, reducing voltage and current flow, particularly under low light conditions, resulting in significant power losses. Ideally, it is desired that the series resistance should be minimum, and the shunt resistance should be maximum.

Quantum efficiency in solar cells measures how efficiently incident photons are converted into electric current. It is typically expressed as a combination of external quantum efficiency (EQE) and internal quantum efficiency (IQE). The former is attributed to optical losses, and the latter reflects the efficiency of charge carrier collection from absorbed photons. Different absorber layers significantly impact quantum efficiency (QE). The choice of materials affects absorption characteristics and recombination rates, influencing overall efficiency.

Replacing a single layer of MAGeI₃ with double layers of MAGeI₃ and CsSnI₃ can enhance the quantum efficiency of solar devices. This configuration benefits from the complementary bandgaps, improving light absorption and charge carrier dynamics.

CsSnI₃, with its smaller bandgap, allows for better harvesting of lower-energy photons, potentially increasing overall efficiency beyond that of MAGeI₃ alone. The combination can also reduce recombination losses, further boosting performance. Figure 9 shows the comparison of the two devices, one with a single junction of MAGeI₃ and one device with dual-absorber layers of MAGeI₃ and CsSnI₃. The latter shows a better result, promising good practical output.