Simulation and Optimization of Lead-Free Perovskite Solar Cells Based on FASnI3

In recent years, perovskite solar cells have garnered significant attention due to their high power conversion efficiencies, ease of fabrication, and excellent optoelectronic properties. However, the presence of toxic lead in conventional perovskite materials like MAPbI3 poses environmental and health risks, limiting their widespread adoption. To address this issue, we focus on lead-free alternatives, specifically tin-based perovskites such as FASnI3, which offer comparable performance with reduced toxicity. This study employs numerical simulations using the Solar Cell Capacitance Simulator (SCAPS) to design and optimize a novel perovskite solar cell structure with the configuration FTO/Zn(O_0.3,S_0.7)/FASnI3/NiO/Au. By investigating key parameters like layer thicknesses, defect densities, and electronic properties, we aim to enhance the device’s efficiency and stability while minimizing environmental impact. The simulations provide insights into carrier transport, recombination mechanisms, and interface effects, guiding the development of high-performance, eco-friendly perovskite solar cells.

The numerical modeling in this work is based on solving fundamental semiconductor equations within the SCAPS environment. The Poisson equation describes the electrostatic potential distribution in the device:

$$ \frac{d}{dx} \left( \epsilon(x) \frac{d\psi}{dx} \right) = q \left[ p(x) – n(x) + N_D^+(x) – N_A^-(x) + p_t(x) – n_t(x) \right] $$

where $ \epsilon $ is the dielectric constant, $ \psi $ is the electrostatic potential, $ q $ is the electron charge, $ p $ and $ n $ are hole and electron concentrations, $ N_D^+ $ and $ N_A^- $ are ionized donor and acceptor densities, and $ p_t $ and $ n_t $ are trapped hole and electron densities. The continuity equations for electrons and holes account for carrier generation and recombination:

$$ -\frac{1}{q} \frac{dJ_n}{dx} + R_n(x) – G(x) = 0 $$
$$ \frac{1}{q} \frac{dJ_p}{dx} + R_p(x) – G(x) = 0 $$

Here, $ J_n $ and $ J_p $ are electron and hole current densities, $ R_n $ and $ R_p $ are recombination rates, and $ G $ is the carrier generation rate. The drift-diffusion model defines the current densities:

$$ J_n = qn\mu_n E + qD_n \frac{dn}{dx} $$
$$ J_p = qp\mu_p E – qD_p \frac{dp}{dx} $$

where $ \mu_n $ and $ \mu_p $ are electron and hole mobilities, $ D_n $ and $ D_p $ are diffusion coefficients, and $ E $ is the electric field. These equations are solved under standard test conditions: AM1.5G illumination with 100 mW/cm² intensity and a temperature of 300 K. The model assumes uniform material properties and uses the control variable method to optimize parameters for maximum power conversion efficiency (PCE), open-circuit voltage ($ V_{oc} $), short-circuit current density ($ J_{sc} $), and fill factor (FF).

The perovskite solar cell structure simulated in this study consists of multiple layers, each with specific roles in carrier transport and photon absorption. The front contact is fluorine-doped tin oxide (FTO), which serves as a transparent electrode with a work function of 4.4 eV. The electron transport layer (ETL) is Zn(O_0.3,S_0.7), selected for its suitable band alignment and high electron mobility. The light-absorbing layer is FASnI3, a lead-free perovskite with a narrow bandgap that facilitates efficient photon harvesting. The hole transport layer (HTL) is NiO, known for its stability and good hole extraction properties. Finally, the back contact is gold (Au) with a work function of 5.1 eV. The energy band diagram illustrates the alignment of conduction and valence bands, promoting efficient charge separation and collection. Key material parameters for each layer are summarized in Table 1, which includes thickness, bandgap, electron affinity, dielectric constant, and carrier concentrations. These parameters are derived from literature and optimized through iterative simulations to achieve high performance in the perovskite solar cell.

Table 1: Material Parameters for the Perovskite Solar Cell Layers
Parameter	FTO	Zn(O_0.3,S_0.7)	FASnI3	NiO
Thickness (nm)	500	10–100	100–1200	40
Bandgap (eV)	3.50	2.83	1.41	3.80
Electron Affinity (eV)	4.00	3.50–3.65	3.52	1.46
Relative Dielectric Constant	9.0	9.0	8.2	11.7
Effective DOS in CB (cm⁻³)	2.2×10¹⁸	2.2×10¹⁸	1.0×10¹⁸	2.5×10²⁰
Effective DOS in VB (cm⁻³)	1.8×10¹⁹	1.8×10¹⁹	1.0×10¹⁸	2.5×10²⁰
Electron Mobility (cm²/V·s)	20.0	100.0	22.0	2.8
Hole Mobility (cm²/V·s)	10.0	25.0	22.0	2.8
Donor Doping (cm⁻³)	1×10¹⁵	1×10¹⁸	0	0
Acceptor Doping (cm⁻³)	0	0	7.0×10¹⁶	1.0×10¹⁸
Defect Density (cm⁻³)	1×10¹⁵	1×10¹⁵	1×10¹²–1×10¹⁸	1×10¹⁵

Interface properties play a critical role in the performance of perovskite solar cells, as they influence carrier recombination and extraction. The defects at the interfaces between Zn(O_0.3,S_0.7)/FASnI3 and FASnI3/NiO are modeled as neutral traps with specific capture cross-sections and energy distributions. Table 2 summarizes the defect parameters used in the simulations, including defect type, capture cross-sections for electrons and holes, energy distribution, reference energy level, characteristic energy, and total defect density. These parameters are essential for accurately simulating non-radiative recombination processes, such as Shockley-Read-Hall (SRH) recombination, which can limit the efficiency of the perovskite solar cell. By optimizing these interface properties, we can minimize carrier losses and enhance the overall device performance.

Table 2: Defect Parameters at Interfaces and in the Active Layer
Parameter	Zn(O_0.3,S_0.7)/FASnI3	FASnI3	FASnI3/NiO
Defect Type	Neutral	Neutral	Neutral
Electron Capture Cross-section (cm²)	1×10⁻¹⁹	2×10⁻¹⁴	1×10⁻¹⁹
Hole Capture Cross-section (cm²)	1×10⁻¹⁹	2×10⁻¹⁴	1×10⁻¹⁹
Energy Distribution	Single	Gaussian	Single
Reference Energy Level (eV)	0.60	0.65	0.60
Characteristic Energy (eV)	—	0.1	—
Total Defect Density (cm⁻³)	1×10¹²–1×10¹⁸	2×10¹⁵	1×10¹⁵

The thickness of the FASnI3 active layer is a crucial parameter that affects both light absorption and carrier recombination in the perovskite solar cell. We varied the thickness from 100 nm to 1200 nm and observed the changes in $ V_{oc} $, $ J_{sc} $, FF, and PCE. As the thickness increases, the absorption of photons improves, leading to a higher generation of electron-hole pairs. However, beyond a certain point, the increased path length for carriers enhances recombination losses. The open-circuit voltage $ V_{oc} $ can be expressed as:

$$ V_{oc} = \frac{kT}{q} \ln \left( \frac{J_l}{J_0} + 1 \right) $$

where $ k $ is Boltzmann’s constant, $ T $ is temperature, $ J_l $ is the light-generated current density, and $ J_0 $ is the reverse saturation current density. Initially, $ V_{oc} $ increases with thickness due to improved light absorption and higher $ J_l $, but it saturates as recombination dominates. Similarly, $ J_{sc} $ rises with thickness because of enhanced photon capture, but it plateaus when the thickness exceeds the carrier diffusion length, leading to increased recombination. The fill factor FF decreases gradually due to higher series resistance and recombination in thicker layers. The power conversion efficiency PCE reaches a maximum at an optimal thickness of 500 nm, where the trade-off between absorption and recombination is balanced. This result underscores the importance of optimizing the active layer thickness in perovskite solar cells to achieve high efficiency.

Defect density in the FASnI3 active layer significantly influences carrier recombination and overall performance of the perovskite solar cell. We simulated defect densities ranging from 10¹² cm⁻³ to 10¹⁸ cm⁻³ and analyzed the impact on device parameters. The SRH recombination rate $ R_{SRH} $ is given by:

$$ R_{SRH} = \frac{np – n_i^2}{\tau_p (n + n_i) + \tau_n (p + p_i)} $$

where $ n_i $ is the intrinsic carrier concentration, and $ \tau_n $ and $ \tau_p $ are electron and hole lifetimes. The carrier lifetime $ \tau $ is related to defect density $ N_t $ by:

$$ \tau = \frac{1}{\sigma V_{th} N_t} $$

Here, $ \sigma $ is the capture cross-section, and $ V_{th} $ is the thermal velocity. The diffusion length $ L $ is a key parameter affected by defect density:

$$ L = \sqrt{D\tau} = \sqrt{\frac{kT \mu}{q \sigma V_{th} N_t}} $$

where $ D $ is the diffusion coefficient and $ \mu $ is the carrier mobility. As $ N_t $ increases, $ L $ decreases, leading to higher recombination rates and reduced $ V_{oc} $ and PCE. Our simulations show that for defect densities below 10¹⁴ cm⁻³, the performance remains relatively stable, but beyond this threshold, $ V_{oc} $, $ J_{sc} $, and PCE degrade rapidly. This highlights the need for high-quality, low-defect FASnI3 films in perovskite solar cells to minimize recombination losses and achieve high efficiency.

The electron transport layer thickness is another critical factor in optimizing perovskite solar cell performance. We varied the Zn(O_0.3,S_0.7) ETL thickness from 10 nm to 100 nm and evaluated the device output. A thinner ETL may lead to insufficient electron extraction and increased shunt paths, while a thicker ETL can cause higher series resistance and reduced photon absorption in the active layer. The electron current density $ J_n $ depends on the electric field and diffusion within the ETL:

$$ J_n = qn\mu_n E + qD_n \frac{dn}{dx} $$

At an ETL thickness of 30 nm, we observed the highest PCE of 19.05%, with balanced carrier extraction and minimal resistance. Thinner layers below 30 nm resulted in lower $ J_{sc} $ and FF due to poor charge collection, whereas thicker layers above 30 nm showed saturation in performance metrics. This optimization ensures efficient electron transport without compromising light absorption in the perovskite solar cell, emphasizing the role of ETL thickness in device design.

The electron affinity of the Zn(O_0.3,S_0.7) ETL affects the band alignment at the interface with FASnI3, influencing carrier injection and recombination. We varied the electron affinity $ \chi $ from 3.50 eV to 3.65 eV and monitored the device parameters. The conduction band offset $ \Delta E_c $ between the ETL and perovskite layer is given by:

$$ \Delta E_c = \chi_{ETL} – \chi_{Perovskite} $$

where $ \chi_{Perovskite} $ is 3.52 eV for FASnI3. A positive $ \Delta E_c $ (e.g., $ \chi_{ETL} = 3.50 $ eV) creates a small energy barrier that facilitates electron extraction while reducing interface recombination. In contrast, a negative $ \Delta E_c $ (e.g., $ \chi_{ETL} > 3.52 $ eV) leads to a larger barrier, increasing recombination and lowering $ V_{oc} $. Our simulations confirm that at $ \chi = 3.50 $ eV, the perovskite solar cell achieves the highest PCE, as the optimal band alignment promotes efficient carrier transport and minimizes losses. This finding underscores the importance of tuning electronic properties in the ETL for high-performance perovskite solar cells.

Interface defect density between the Zn(O_0.3,S_0.7) ETL and FASnI3 active layer plays a vital role in carrier recombination and device performance. We simulated interface defect densities from 10¹² cm⁻³ to 10¹⁸ cm⁻³ and analyzed the effects on $ V_{oc} $, $ J_{sc} $, FF, and PCE. Interface defects act as recombination centers, capturing photogenerated carriers and reducing the collection efficiency. The recombination rate at the interface can be modeled using the SRH formula, with the defect density directly influencing the carrier lifetime. For defect densities below 10¹³ cm⁻³, the performance remains stable, but as the density increases, $ V_{oc} $ and PCE decline due to enhanced recombination. This behavior is consistent with the relationship between defect density and diffusion length, as higher defect densities shorten the effective carrier diffusion length, increasing recombination losses. Therefore, controlling interface defect density is essential for maximizing the efficiency of perovskite solar cells, and values below 10¹³ cm⁻³ are recommended for optimal performance.

After optimizing all parameters, the perovskite solar cell exhibits significantly improved performance. The final optimized parameters include a FASnI3 thickness of 500 nm, a defect density of 10¹⁴ cm⁻³ in the active layer, a Zn(O_0.3,S_0.7) ETL thickness of 30 nm with an electron affinity of 3.50 eV, and an interface defect density of 10¹³ cm⁻³ between ETL and FASnI3. The current-density-voltage (J-V) characteristics under AM1.5G illumination show a $ V_{oc} $ of 1.16 V, a $ J_{sc} $ of 28.08 mA/cm², an FF of 88.22%, and a PCE of 28.65%. This represents a substantial improvement over the initial simulation results, demonstrating the effectiveness of parameter optimization in enhancing the performance of lead-free perovskite solar cells. The high PCE achieved in this study competitive with traditional lead-based devices, highlighting the potential of FASnI3-based perovskite solar cells for sustainable photovoltaics.

In conclusion, this numerical study using SCAPS simulations provides a comprehensive analysis of a lead-free perovskite solar cell based on FASnI3. By systematically optimizing layer thicknesses, defect densities, and electronic properties, we have demonstrated a path to high efficiency and reduced environmental impact. The results show that an active layer thickness of 500 nm balances light absorption and recombination, while low defect densities in the bulk and interfaces minimize carrier losses. The ETL properties, including thickness and electron affinity, are critical for efficient charge transport. The optimized perovskite solar cell achieves a PCE of 28.65%, making it a promising candidate for next-generation photovoltaic applications. Future work could focus on experimental validation and further refinement of material parameters to advance the development of eco-friendly perovskite solar cells.