Comprehensive Analysis for Low-Cost and Highly Efficient Perovskite Solar Cells Using SCAPS-1D with an Inexpensive Hole Transport Material, Electron Transport Material, and Back Contact Considering the Toxicity

Abstract

Perovskite solar cells (PSCs) are rapidly advancing due to their high power conversion efficiencies (PCEs) and low fabrication costs. However, their commercialization is hindered by lead toxicity and the use of expensive materials, such as Spiro-OMeTAD and gold electrodes. This study presents a comprehensive SCAPS-1D simulation-based analysis of 14 perovskite absorber materials, spanning both Pb-based and lead-free compounds, under a unified device architecture using low-cost, nontoxic components: ZnO as the electron transport material (ETM), PEDOT:PSS + WO₃ as a dual hole transport material, and nickel as the back contact. Key device parameters, including absorber thickness, defect density, electron affinity, series resistance, and temperature, were systematically optimized. Among the materials evaluated, MASnI₃ exhibited the highest PCE of 27.98%, surpassing even MAPbI₃ (27.10%), and demonstrating its viability as a sustainable, nontoxic absorber. The proposed cell architecture achieves high efficiency at a total material cost below 4 euro/g, significantly reducing the economic barrier compared to conventional designs. This work establishes a scalable, eco-friendly PSC architecture and provides a simulation-driven framework to accelerate experimental development and industrial application.

1. Introduction

Photovoltaics has long played a pivotal role in global energy harvesting, with solar energy emerging as a reliable, abundant, and renewable solution to meet growing energy demand. Among emerging photovoltaic technologies, perovskite solar cells (PSCs) have garnered significant attention due to their exceptional power conversion efficiencies (PCEs), low-temperature fabrication, and tunable optoelectronic properties. Since the first report of a perovskite-based device with a 3.81% efficiency by Kojima et al., continuous research and material innovation have propelled PSCs to a certified efficiency of 25.8%,, making them one of the fastest-advancing solar technologies to date.

The fundamental way of representation for the crystal structure of perovskite is AMX₃, where A denotes organic cation, whereas metal cations like Co²⁺, Cu²⁺, Cr²⁺, Fe²⁺, Ge²⁺, Cd²⁺, Mn²⁺, Sn²⁺, or Pb²⁺ are represented through M and X is used to illustrate halide anions like Br^–, Cl^–, or I^–. Nowadays, HC­(NH₂)₂ (FA), Cs⁺, or CH₃NH₃ ⁺ (MA) is being used as organic cation A, and Sn²⁺or Pb²⁺ is getting more preference as metal cation M to the researchers. Perovskite has several advantages over other absorber materials; for example, a minimal amount of excitation is required to dislodge the ions, which means that it has low excitation binding energy, and the absorption coefficient is relatively higher. Moreover, tunability is another crucial feature of perovskite materials. Additionally, the carrier (electron and hole) mobility is sublime, and the diffusion length is longer compared to other organic materials. Perovskite has very high absorption in the visible-light wavelength range, and no ellipsometric effect is available in this region. These properties have established perovskites as highly attractive absorber materials for thin-film solar applications.

Despite these promising attributes, two critical bottlenecks hinder the commercialization of PSCs: (i) the reliance on toxic lead-based compounds and (ii) the use of costly materials such as Spiro-OMeTAD and gold for charge transport and electrode layers. Studies have shown that these components can account for more than one-third (33.9%) of total device cost, making the search for low-cost, sustainable alternatives a pressing need. While some prior research has investigated nontoxic or inexpensive components individually, few have addressed all three dimensions such as efficiency, cost, and environmental safety, in an integrated optimization framework.

Recent advancements in both Pb-based and Pb-free perovskite solar cells have demonstrated significant progress in optimizing the efficiency, stability, and device architecture. For example, MAPbI₃-based devices with polymer dual passivation have reached efficiencies above 20%, while thermally stable FAPbI₃ and interface-engineered CsPbI₃ cells have achieved up to 26%. , On the Pb-free front, MASnI₃ and FASnI₃ devices have been optimized using novel HTL/ETL combinations and plasmonic structures, reporting PCEs close to 27%. − These findings provide strong evidence of performance enhancement across absorber types, highlighting the need for a unified, simulation-based comparisonan area that this study directly addresses.

In this work, we introduce a comprehensive simulation-based methodology to design perovskite solar cells (PSCs) that simultaneously optimizes power conversion efficiency (PCE), environmental compatibility, and economic feasibility. Using the SCAPS-1D simulation platform, we systematically evaluate 14 perovskite absorber materials, comprising both Pb-based and Pb-free classes, under a fixed, low-cost, and scalable device architecture. This architecture features a novel material combination: ZnO as a stable and inexpensive electron transport material (ETM), PEDOT:PSS + WO₃ as a dual-function hole transport layer (HTL), and nickel (Ni) as a cost-effective and earth-abundant back contact. Unlike conventional simulation studies that vary transport layers across absorber types, our work ensures direct and fair comparison by fixing all nonabsorber layers and maintaining identical simulation parameters, thus isolating absorber-specific effects.

While the environmental concerns surrounding Pb-based perovskites are well-established, we intentionally include MAPbI₃, MAPbI_3(1–x)Br_3x , and MAPbI_3–x Cl _x in our analysis to serve as high-performance reference benchmarks. These lead-containing absorbers represent the current state of the art in PSC efficiency and allow us to critically assess whether Pb-free candidates, such as MASnI₃, CsSnI₃, and FASnI₃, can match or exceed their performance under consistent architectural and operational constraints. The comparative scope of 14 absorbers simulated under uniform interfacial conditions is a key novelty of this work and provides a level of material-to-material comparability that is often missing in the literature.

Beyond the absorber comparison, this study introduces several innovations that distinguish it from previous simulation efforts. First, we demonstrate, for the first time in the context of MASnI₃ and MAPbI₃ devices, the synergistic effects of combining PEDOT:PSS + WO₃ as a cost-effective dual HTL, which improves hole extraction and band alignment while maintaining low toxicity and high scalability. Second, we integrate material pricing from commercial suppliers (e.g., Sigma-Aldrich) directly into our design process to guide the selection toward low-cost architectures. The total material cost of our optimized cells remains below 4 euro/g, in stark contrast to conventional structures that often exceed 500 euro/g due to the use of gold and Spiro-OMeTAD.

Finally, we perform a multidimensional optimization across key physical parametersabsorber thickness, defect density, electron affinity, series resistance, and temperaturewhile analyzing conduction/valence band offsets (CBO/VBO), generation–recombination profiles, quantum efficiency spectra, and the impact of back contact metal work function. The MASnI₃-based architecture achieves a record-level simulated efficiency of 27.98%, outperforming the Pb-based MAPbI₃ (27.10%) under identical conditions. Notably, these high efficiencies are achieved using only earth-abundant and non-noble materials, making the design viable for industrial-scale production.

In summary, this study establishes a new simulation benchmark for eco-friendly and economically viable PSCs. It provides not only a novel device structure but also a robust comparative platform for evaluating the true potential of lead-free perovskites. The findings offer a practical roadmap toward the commercialization of PSCs that are highly performing, scalable, and sustainable.

2. Material Selection

Determining the highly efficient cell structure is a significant focus of this study. The efficiency of the cell structure is mainly dependent on the absorber materials. Although a bunch of perovskite absorber materials are available, all of them cannot exhibit a higher efficiency. Hence, we have chosen highly efficient absorber materials from previous studies. Different research groups have introduced several new perovskite materials and cell structures. Each cell structure shows different power conversion efficiencies (η (%)). The following is a list of common absorbers; their relative efficiency and references are given in Table .

1. PCE of Some Perovskite Materials and the Relevant References.

absorber material	η (%)	reference
MASnI3	23.36%
FASnI3	14.03%
MAPbI3(1–x)Br3 x	17.9%
Cs2AgBiBr6	5.44%
Cs2TiX6	6.75%
MAGeI3	13.5%
CsPbI3	21.06%
MAPbI3	∼24%	,

Table indicates that each perovskite absorber material has different η values (%) from others. Additionally, a perovskite absorber material can exhibit different η (%) under different conditions with different HTM and ETM. It is also clear from the table that there are mainly two types of absorber materials available. They are Pb-based absorber materials and other cation-based absorber materials. However, Pb induces toxicity that harms the human body and the environment, obstructing its commercialization. −

Determining highly efficient cell structures with inexpensive material is another key aspect of the study. The importance of a cost-effective cell structure can be realized by the cell structure and their relative cost represented in Table .

2. Common Cell Structure, Efficiency, and Cost of HTM, ETM, and Back Contact Materials .

cell structure	ETM cost (euro/g)	HTM cost (euro/g)	back contact cost (euro/g)	total cost (euro)	η (%)
FTO/TiO2/CsGeI3/Spiro-OMeTAD/Ag	27.2	528	9.01	564.21	18.30%
ZnO(nr)/CH3NH3SnI3/Cu2O/Au	13.6	15.76	264	293.36	20.23%
ZnO(nr)/CH3NH3SnI3/Spiro-OMeTAD/Au	13.6	528	264	805.6	20.21%
ITO/NiO/MASnI3/PCBM/Ag	19.7	1130	9.01	1158.71	29.19%
FTO/Perovskite/Spiro-OMeTAD/Au	0	528	264	792	19.16%
ITO/PEDOT:PSS/MAGeI3/PCBM/Ag	1.324	1130	9.01	1140.334	11.16%
ITO/PEDOT:PSS/MAGeI3/C60/Ag	1.324	677	9.01	687.334	13.5%
FTO/TiO2/MAPbI3/Spiro-OMeTAD/Au	27.2	528	264	819.2	23.18%
FTO/TiO2/MAPbI3/NPB/Au	27.2	725	264	1016.2	22.56%
FTO/TiO2/MAPbI3/P3HT/Au	27.2	749	264	1040.2	19.38%
FTO/TiO2/MAPbI3/ MEH-PPV/Au	27.2	798	264	1089.2	21.23%
ITO/NiO/CH3NH3PbI3–x Cl x /PCBM/Ag	19.7	1130	9.01	1158.71	22%
FTO/TiO2/CH3NH3PbI3–x Cl x /Spiro-OMeTAD/Ag	27.2	528	9.01	564.21	29.56%
FTO/ZnO/MASnI3/PEDOT:PSS/Au	0.172	1.324	264	265.496	21.22%

^aThe price of each material is taken from Sigma-Aldrich.

Table indicates that the cells are either expensive or not optimized. The cells are costly, for either the high cost of HTM and ETM or the high cost of back contact materials. Hence, it is necessary to choose low-cost HTM, ETM, and back contact materials initially to simulate cost-effective and efficient perovskite solar cells. As simulation can reveal the output characteristics of the cell and is effective for designing and fabricating perovskite solar cells, it is necessary to choose low-cost HTM, ETM, and back contact to develop low-cost and highly efficient perovskite solar cells.

First, we collected common HTM and ETM for highly efficient cell structures from previous studies and their relative price to determine low-cost HTM and ETM. The following is a list of some common HTM and ETM and their relative cost. We have calculated the per gram price to make the comparison easier.

Table indicates that PEDOT:PSS and WO₃ are the least expensive HTM, and ZnO is the least expensive ETM. Hence, we have chosen PEDOT:PSS + WO₃ as the HTM and ZnO as the ETM for the study. Second, we have taken 14 common perovskite absorber materials for our research. We have divided those materials according to toxicity. Three of them are Pb-based absorber materials, while 11 of them do not contain Pb. We have taken more absorber materials as different absorber materials exhibit other output characteristics for different HTM and ETM. Hence, all common absorber materials are considered to determine the highly efficient cell structure. The cost of back contact material is also crucial for determining low-cost cells. However, we did not choose the back contact materials initially. Instead, we have simulated the best two cells from two categories with all possible back contact materials to reduce the risk of efficiency drop due to the impact of back contact. We have chosen the least expensive back contact materials from best performing back contact materials. In this process, the cell can retain efficiency with minimal expense.

3. Common HTM and ETM for Highly Efficient Perovskite Solar Cells and Their Cost .

material name	material type	price (euro/g)
Spiro-OMETAD	HTM	528
CuI	HTM	21.6
NiO	HTM	19.7
PCBM	HTM	1130
PEDOT:PSS	HTM	1.324
WO3	HTM	1.26
graphene	HTM	1070
P3HT	HTM	749
CdS	ETM	10.35
ZnO	ETM	0.172
SnO2	ETM	38.4
WS2	ETM	23.8

^aThe price of each material is taken from Sigma-Aldrich.

3. Device Physics and Simulation

Perovskite solar cells generally consist of HTM, ETM, an absorber, and contacts. However, several researchers have also introduced HTM-free and ETM-free perovskite solar cells. In this study, we chose a common cell structure with an ETM, absorber, HTM, and contacts. The light is illuminated from the ETM side of the cell. The following is the cell structure used in the study.

Simulations are performed by the SCAPS-1D simulator, a single-dimensional solar cell capacitance simulator developed by Burgelman and his co-workers at the University of Gent, Belgium. This prime solar cell simulator has several advantages, including the possibility of simulating the environmental and cell parameters and representing data graphically and numerically. Furthermore, the cell can be simulated by changing each parameter; the data can be saved and used later. Due to all of these advantages and user-friendly interfaces, we have chosen SCAPS-1D to model and simulate the cell structure in this study.

We have chosen PEDOT:PSS + WO₃ as the HTM, and ZnO is used as the ETM for the current study. The general perovskite solar cell structure is shown as Figure . These materials are considered due to outstanding characteristics and the cost of these materials. Table lists the fundamental specifications of these materials.

1.

Device structure for a perovskite solar cell.

4. Basic Parameters of PEDOT:PSS + WO₃ and ZnO.

material	thickness (μm)	E g (eV)	χ (eV)	ε r	N c (cm –3 )	N v (cm –3 )	μ n (cm2/(V s))	μ p (cm2/(V s))	N D (cm –3 )	N A (cm –3 )	N t (cm –3 )
PEDOT:PSS + WO3	0.1	1.8	3.4	18	2.2 × 1018	1.8 × 1019	4.5 × 10–2	4.5 × 10–2	0	1 × 1018	1 × 1014
ZnO	0.05	3.3	4.1	9	4 × 1018	1 × 1019	1 × 102	2.5 × 101	1 × 1018	1 × 105	1 × 1014

In Table , E _g, χ, ε_r, N _c, N _v, μ_n, μ_p, N _D, N _A, and N _t represent bandgap energy, electron affinity, relative permittivity, effective conduction band density, effective valence band density, electron mobility, hole mobility, donor concentration, acceptor concentration, and defect density, respectively.

During simulation, the interface layer between the HTM/perovskite absorber material and perovskite absorber material/ETM is also considered to significantly impact the cell’s performance. The interface layer can introduce defects in the interface between the HTM/absorber material and absorber material/ETM, reducing the cell’s performance. The temperature is 300 K, while the solar radiation spectrum is AM 1.5G. AM 1.5G provides an illumination power of 1000 W m^–2. The hole and electron thermal velocities are 1 × 10⁷ cm/s, while band-to-band recombination is 2.3 × 10^–9 cm³/s.

This study uses two types of perovskite materials to design and simulate low-cost, highly efficient perovskite solar cells. First, Pb-based toxic materials such as MAPbI₃, MAPbI_3–x Cl _x , and MAPbI_3(1–x)Br_{3 x} are analyzed. The simulation parameters for these Pb-based toxic materials are listed in Table .

5. Simulation Parameters of the Pb-Based Perovskite Absorber Materials.

material	thickness (μm)	E g (eV)	χ (eV)	εr	N c (cm–3)	N v (cm–3)	μn (cm2/(V s))	μp (cm2/(V s))	N D (cm–3)	N A (cm–3)	N t (cm–3)
MAPbI3	0.5	1.5	3.9	10	2.75 × 1018	3.9 × 1018	1 × 101	1 × 101	0	1 × 1015	1 × 1014
MAPbI3–x Cl x	0.5	1.55	3.93	6.5	2.5 × 1020	2.5 × 1020	2 × 100	2 × 100	0	1 × 1015	1 × 1014
MAPbI3(1–x)Br3 x	0.5	1.7	3.79	6.5	2.2 × 1018	1.8 × 1019	2 × 100	2 × 100	0	1 × 1015	1 × 1014

In contrast, the other category of perovskite absorber materials consists of nontoxic perovskite materials, such as MASnI₃, CsSnI₃, FASnI₃, MAGeI₃, Cs₃Bi₂I₉, Cs₂AgBiBr₆, Cs₂TiI₆, Cs₂TiBr₆, Cs₂TiCl₆, MASnBr₃, and Cs₂TiF₆. Table provides the simulation parameters and values for the nontoxic perovskite absorber material.

6. Simulation Parameters of Lead-Free Nontoxic Perovskite Absorber Materials.

material	thickness (μm)	E g (eV)	χ (eV)	εr	N c (cm–3)	N v (cm–3)	μn (cm2/(V s))	μp (cm2/(V s))	N D (cm–3)	N A (cm–3)	N t (cm–3)
MASnI3	0.5	1.3	4.2	10	1 × 1018	1 × 1018	1.6 × 100	1.6 × 100	0	1 × 1015	1 × 1014
CsSnI3	0.5	1.27	4.47	18	1.8 × 1019	2.2 × 1018	4.37 × 100	4.37 × 100	0	1 × 1015	1 × 1014
FASnI3	0.5	1.41	3.52	8.2	1 × 1018	1 × 1018	2.2 × 101	2.2 × 101	0	1 × 1015	1 × 1014
MAGeI3	0.5	1.9	3.98	10	1 × 1016	1 × 1015	1.62 × 101	1.01 × 101	1 × 1015	0	1 × 1014
Cs3Bi2I9	0.5	2.03	3.4	9.68	4.98 × 1019	2.11 × 1019	4.3 × 100	1.7 × 100	0	1 × 1015	1 × 1014
Cs2AgBiBr6	0.5	2.05	4.19	5.8	1 × 1016	1 × 1016	1.181 × 101	4.9 × 10–1	0	1 × 1015	1 × 1014
Cs2TiI6	0.5	1.8	4.2	18	1 × 1019	1 × 1019	4.4 × 100	2.5 × 100	1 × 1015	0	1 × 1014
Cs2TiBr6	0.5	1.6	4.47	10	1 × 1019	1 × 1019	4.4 × 100	2.5 × 100	1 × 1015	0	1 × 1014
Cs2TiCl6	0.5	2.23	4	19	1 × 1019	1 × 1019	4.4 × 100	2.5 × 100	1 × 1015	0	1 × 1014
MASnBr3	0.5	2.15	4.17	10	2.5 × 1019	2.5 × 1019	1.6 × 100	1.6 × 100	1 × 1015	0	1 × 1014
Cs2TiF6	0.5	1.9	4.3	18	1 × 1019	1 × 1019	4.4 × 100	2.5 × 100	1 × 1015	0	1 × 1014

The selection of PEDOT:PSS + WO₃ as the hole transport layer (HTL) and ZnO as the electron transport layer (ETL) in this study is grounded in both economic and scientific rationale. While their affordability significantly reduces total device cost, these materials were primarily chosen for their favorable energy level alignment (Figure ) with a broad range of perovskite absorber materialsboth toxic (Pb-based) and nontoxic. Band alignment is a critical criterion for efficient charge extraction and reduced interface recombination, and both PEDOT:PSS + WO₃ and ZnO offer conduction and valence band positions that are well-matched to the energy levels of the 14 absorber materials considered in this work. This compatibility ensures efficient hole and electron transport across the absorber interfaces, as supported by the simulated band alignment diagrams included in the study. Finding HTM/ETM combinations that are simultaneously low-cost and capable of maintaining optimal energy band offsets (minimal VBO and CBO) across diverse absorber types is highly nontrivial. PEDOT:PSS + WO₃ and ZnO provide this rare combination of energetic compatibility, material stability, and economic feasibility, justifying their consistent use in all simulated architectures. This strategic constraint also ensures that absorber performance comparisons are fair, isolating the effects of the absorber material itself without variations introduced by transport layers.

2.

Band alignment diagram of materials used in this study.

4. Results and Discussion

In this study, optimal values were used for the simulation, making the process of identifying a highly efficient absorber layer more reliable. The output parameters, including open-circuit voltage (V _oc), short-circuit current density (J _sc), fill factor (FF), and efficiency (η) for different absorber-based perovskite solar cells (PSCs), are presented in Tables and . These parameters are crucial, as the efficiency is directly dependent on them, and they share an interdependent relationship, as expressed in eq . The equation includes P _in as the input power:

$$\eta =\frac{\mathrm{FF}\times V_{\mathrm{oc}}\times J_{\mathrm{sc}}}{P_{\mathrm{in}}}$$ 1

7. Output Parameters of Perovskite Absorber Materials Containing Pb.

absorber	V oc (V)	J sc (mA/cm2)	FF (%)	η (%)
MAPbI3	1.05	28.54	84.99	25.49
MAPbI3(1–x)Br3 x	1.11	22.38	84.48	20.97
MAPbI3–x Cl x	0.91	26.28	82.58	19.78

The results of this study were evaluated by considering the presence of lead (Pb). It is widely recognized that Pb is a toxic heavy metal that poses severe health risks to humans and is detrimental to all living organisms, including plants and animals. , The output parameters such as open-circuit voltage (V _oc), short-circuit current density (J _sc), fill factor (FF), and eta (η) obtained from the simulation for different Pb-based absorber PSC are shown in Table .

Table shows that among the lead-based perovskites, MAPbI_3(1–x)Br_{3 x} achieves the highest open-circuit voltage (V _oc) of 1.11 V, while MAPbI_3–x Cl _x exhibits the lowest V _oc at 0.91 V. The higher V _oc observed in MAPbI_3(1–x)Br_{3 x} is attributed to bandgap widening resulting from the substitution of iodide with bromide ions, which raises the conduction band and lowers the valence band. This increased bandgap enhances the built-in potential and reduces recombination, thus elevating V _oc. However, the same bandgap increase leads to reduced absorption in the longer-wavelength region of the solar spectrum, causing a significant drop in short-circuit current density (J _sc), as seen in the lower J _sc of 22.38 mA/cm² for MAPbI_3(1–x)Br_{3 x} compared to 28.54 mA/cm² for MAPbI₃. This reflects the classic V _oc–J _sc trade-off governed by the Shockley–Queisser limit. Although fill factor (FF) values are comparable across compositions, MAPbI₃ records the highest FF at 84.99%, likely due to optimal band alignment and minimal series resistance in the device configuration. In contrast, MAPbI_3–x Cl _x has a slightly lower FF (82.58%), potentially due to greater energy mismatch and increased interface recombination. Based on its balanced performance, with high J _sc, V _oc, and FF values, MAPbI₃ is selected for further optimization and simulation.

The performance of lead-free perovskite solar cells (PSCs), summarized in Table , reveals a broad range of photovoltaic characteristics. V _oc values span from 0.579 V (Cs₂TiBr₆) to 1.24 V in MAGeI₃, primarily influenced by differences in the bandgap energy and energy level alignment. While MAGeI₃’s wide bandgap accounts for its high V _oc, it limits light absorption in the lower-energy spectrum, resulting in a reduced J _sc. In contrast, CsSnI₃ achieves the highest J _sc (33.90 mA/cm²) owing to its narrower bandgap (∼1.3 eV), which facilitates broad-spectrum absorption and efficient photogeneration. However, despite its high current density, CsSnI₃ exhibits a significantly lower fill factor (65.51%). This is primarily attributed to its poor carrier transport properties and higher recombination rates as simulated in the SCAPS-1D environment. Specifically, CsSnI₃ has a relatively high intrinsic carrier concentration and shallow energy levels, which can enhance carrier recombination under operating conditions. Additionally, the simulated defect density and low built-in potential can lead to an increased ideality factor, causing early voltage saturation and limiting the maximum power point. These factors collectively degrade the FF, despite a high photocurrent. In contrast, Cs₃Bi₂I₉ shows a higher FF (85.50%) due to better band alignment and simulated interface properties, though with a lower J _sc. Among all candidates, MASnI₃ provides the most balanced performance, with high J _sc, moderate V _oc, and stable FF, resulting in the highest simulated efficiency (24.08%). It is therefore selected for further optimization.

8. Output Parameters of a Perovskite Absorber that Does Not Contain Toxic Pb.

absorber	V oc (V)	J sc (mA/cm2)	FF (%)	eta (%)
MASnI3	0.93	35.14	73.54	24.08
MAGeI3	1.24	17.81	73.06	16.13
FASnI3	0.63	31.42	78.39	15.60
Cs3Bi2I9	1.04	16.40	85.50	14.54
CsSnI3	0.62	35.90	65.51	14.52
Cs2AgBiBr6	1.04	15.35	76.25	12.18
Cs2TiCl6	1.07	14.20	74.41	11.31
Cs2TiI6	0.87	18.78	69.05	11.30
Cs2TiBr6	0.61	24.82	63.44	9.59
MASnBr3	0.87	14.80	72.57	9.36
Cs2TiF6	0.77	17.88	67.27	9.27

Figures and present the initial quantum efficiency (QE) and J–V characteristics of the MAPbI₃ and MASnI₃-based cells, respectively. In Figure , the MAPbI₃ cell achieves a peak QE of approximately 99% at a wavelength near 570 nm, with QE remaining above 85% initially. The QE declines sharply beyond 820 nm, limiting the carrier collection from longer-wavelength photons. Similarly, Figure shows the MASnI₃-based cell starting at ∼85% QE, peaking at around 99% near 550–600 nm, and then dropping to nearly zero beyond 950 nm, consistent with its narrower bandgap. These trends indicate that both cells are optimized for midvisible spectrum absorption but suffer from low edge-of-spectrum QE due to recombination losses, weaker internal electric field, and incomplete absorption near the band edges. The relatively low initial QE at the spectral extremes can also be linked to nonoptimized layer thickness and interface mismatch, which reduce photon-to-electron conversion efficiency. These observations reinforce the need for parameter tuning in absorber and transport layers to improve the overall spectral response.

3.

(a) Initial J–V curve and (b) QE curve of the MAPbI₃-based cell.

4.

(a) Initial J–V curve and (b) QE curve of the MASnI₃-based cell.

In this phase of the study, the P+PIN+ structure was implemented. A thin P+ layer was utilized as a back surface field (BSF) to create near-ohmic contact and enhance the cell performance by reducing the surface recombination velocity (SRV). Additionally, a thin intrinsic layer of the absorber material was employed to form an interface between the absorber and the N+ layer, effectively minimizing recombination losses. The P+P layer was engineered by grading the materials based on doping density, whereas the N+ region was achieved by increasing the doping concentration.

These modifications are expected to enhance the overall performance of the PSCs, leading to higher efficiencies and improved stability, thus making lead-free PSCs a viable alternative to their lead-based counterparts.

4.1. Effect of Thickness

The absorber layer is a key factor for achieving high efficiency in perovskite solar cells (PSCs). There is a crucial relationship between the output parameters of the cell and the thickness of the absorber layer. As the thickness increases, more light is absorbed, leading to the generation of a greater number of electron–hole pairs. This enhances the short-circuit current density (J _sc) due to increased photogeneration. However, an increase in thickness also introduces competing effects: it can reduce recombination at the back contact due to a stronger back surface field, but it simultaneously increases the bulk recombination probability due to longer carrier diffusion paths, which may ultimately reduce efficiency. In this part of the study, both MAPbI₃ and MASnI₃-based cells were simulated with thickness values ranging from 0.1 to 1 μm.

According to Figure , for the MAPbI₃-based cell, the efficiency increases with a thickness up to 0.325 μm, where it peaks and then decreases beyond this point. J _sc shows a steady increase with thickness, achieving a maximum of 28.6 mA/cm² at 1 μm due to more complete absorption of incident photons. On the other hand, V _oc decreases from 1.125 V at 0.1 μm to 1.07 V at 1 μm because thicker absorbers increase the likelihood of bulk recombination, which lowers the quasi-Fermi level splitting and suppresses V _oc. The fill factor (FF) initially decreases due to increased resistance and carrier transport inefficiency but shows a mild recovery at higher thicknesses as the electric field strength improves. The FF peaks at 86.5% at 0.1 μm and dips to a minimum of 85.07% at 0.55 μm. The optimal balance of these parameters is achieved at 0.325 μm, where V _oc = 1.10 V, J _sc = 28.47 mA/cm², FF = 85.42%, and efficiency = 26.71%.

5.

Open-circuit voltage V _oc (V), short-circuit current J _sc (mA/cm²), fill factor FF (%), and efficiency η (%) curves for the MAPbI₃-based cell according to thickness.

From the simulation results presented in Figure , it is evident that at a thickness of 0.1 μm, the fill factor and open-circuit voltage are maximized, with values of 0.99 V and 82.88%, respectively. However, the efficiency and J _sc are minimized at this thickness, with values of 31.32 mA/cm² and 25.74%, respectively. The short-circuit current density increases with thickness, while the open-circuit voltage decreases. Efficiency initially increases with thickness and then decreases beyond a certain point, following the observed variation in the thickness. The fill factor initially decreases with increasing thickness but increases again after a specific threshold. The optimal thickness for the MASnI₃-based cell is found to be 0.25 μm, yielding maximum efficiency. The output parameters for this optimized thickness are a V _oc of 0.97 V, a J _sc of 34.81 mA/cm², an FF of 80.91%, and an efficiency of 27.95%.

6.

Open-circuit voltage V _oc (V), short-circuit current J _sc (mA/cm²), fill factor FF (%), and efficiency η (%) curves for the MASnI₃-based cell according to thickness.

These observations underline that optimizing absorber thickness is essential to achieving the best trade-off between light absorption and recombination loss. Thin absorbers suffer from insufficient generation, while overly thick absorbers introduce resistive and recombination penalties. Therefore, the identified optimal thicknesses0.325 μm for MAPbI₃ and 0.25 μm for MASnI₃maximize carrier collection while minimizing performance losses from recombination and transport resistance, aligning well with previous theoretical findings. ,

4.2. Effect of Temperature

Previous simulations were conducted at a fixed temperature of 300 K. However, in real-world conditions, the operating temperature of perovskite solar cells (PSCs) varies due to environmental and thermal loads. Therefore, in this study, temperature-dependent simulations were performed over a range of 260–400 K to investigate the thermal behavior of both MAPbI₃ and MASnI₃-based devices.

As illustrated in Figure , MAPbI₃-based cells exhibit linear performance degradation with increasing temperature. Specifically, the V _oc, fill factor (FF), and efficiency decrease consistently, while J _sc initially drops slightly and then stabilizes. This behavior is attributed to enhanced carrier recombination, thermal activation of traps, and ion migration at elevated temperatures, which reduce the built-in potential and quasi-Fermi level splitting. ,

7.

Open-circuit voltage V _oc (V), short-circuit current J _sc (mA/cm²), fill factor FF (%), and efficiency η (%) curves for the MAPbI₃-based cell according to temperature.

The increased lattice vibration also raises series resistance and impedes charge extraction, further reducing the FF. These trends are typical for hybrid perovskites and validate the need for temperature-tolerant cell architectures.

In contrast, the MASnI₃-based cell exhibits nonlinear temperature dependence, as shown in Figure . Meanwhile, V _oc and efficiency also decline steadily with temperature, consistent with thermal recombination dynamics. , The trends in FF and J _sc are distinctly nonlinear. At a lower temperature (260 K), FF is relatively low, likely due to insufficient thermal energy for effective charge extraction and activation of shallow defect states. As the temperature increases, FF improves, reaching a peak at an intermediate temperature (∼320–330 K), before declining again due to thermally induced recombination and resistive losses. This rise and fall in FF suggest a temperature-activated transport regime, where moderate thermal energy enhances carrier mobility and reduces interface resistance but excessive heat reverses these gains.

8.

Open-circuit voltage V _oc (V), short-circuit current J _sc (mA/cm²), fill factor FF (%), and efficiency η (%) curves for the MASnI₃-based cell according to temperature.

Similarly, the short-circuit current density (J _sc) follows an inverted parabolic trend: it starts high at 260 K, decreases to a local minimum at intermediate temperature, and then increases again at higher temperatures, peaking near 400 K. This is due to two competing effects: at lower temperatures, the carrier lifetime is sufficient to support high J _sc, but poor mobility limits extraction. At intermediate temperatures, increased recombination and interface barriers reduce the level of J _sc. At higher temperatures, thermally assisted transport enhances carrier collection again, despite increased recombination.

These nonlinear behaviors in MASnI₃ arise from its higher sensitivity to defect activation, self-doping effects, and narrower bandgap, which make it more responsive to thermal changes compared to MAPbI₃. The complex temperature dependence of J _sc and FF underscores the importance of designing MASnI₃-based PSCs with careful thermal management and defect passivation to ensure a stable performance under operational fluctuations.

In summary, while both cell types degrade in efficiency as temperature increases, the nonmonotonic behavior of FF and J _sc in MASnI₃ reveals a more complex interplay of thermal activation, recombination, and transport phenomena. These insights emphasize the necessity for thermal optimization in device engineering, especially for Sn-based, lead-free perovskites, to enhance the long-term stability and performance reliability under real-world conditions.

4.3. Effect of Absorber Layer Electron Affinity

Electron affinity (χ) is a critical parameter in device modeling as it directly influences the energy band alignment between various layers in a device. Specifically, it plays a pivotal role in determining the valence band offset (VBO) and conduction band offset (CBO), which are key factors for optimizing charge carrier transport and minimizing recombination losses. These parameters are mathematically expressed as

$$\mathrm{VBO}={\chi }^{\mathrm{HTL}}-{\chi }^{\mathrm{PER}}+{E_{\mathrm{g}}}^{\mathrm{HTL}}-{E_{\mathrm{g}}}^{\mathrm{PER}}$$ 2

$$\mathrm{CBO}={\chi }^{\mathrm{PER}}-{\chi }^{\mathrm{ETL}}$$ 3

Here, χ^PER is the electron affinity of the absorber material; χ^HTL and χ^ETL are the electron affinities of the hole transport layer (HTL) and electron transport layer (ETL), respectively. E _g ^HTL is the bandgap of the HTL, and E _g ^PER denotes the bandgap of the absorber layer.

The electron affinity of absorber materials significantly impacts the overall device performance by aligning the energy levels of adjacent layers, thus optimizing charge transport and reducing potential energy barriers. These observations align with the findings Wang et al., who demonstrated the correlation between energy level alignment and device efficiency.

Simulation results in Figure show that by varying the electron affinity (χ) of the absorber material between 3.0 and 4.5 eV, the performance of perovskite-based solar cells can be substantially tuned. For the MAPbI₃-based cell, the efficiency increases with electron affinity and reaches a maximum of 27.10% at 3.75 eV. Similarly, the MASnI₃-based cell peaks at 27.98% efficiency at 4.00 eV. These optimized points confirm that proper alignment of energy levels between the absorber and transport layers is essential for maximizing charge extraction and minimizing recombination losses, in agreement with a previous study.

9.

Efficiency (%) curves of MAPbI₃ and MASnI₃-based cells according to electron affinity (eV).

The electron affinity of the absorber directly influences the conduction band offset (CBO) at the interface with the electron transport material (ETM), here ZnO. This band offset determines whether the device exhibits a “spike-type” or “cliff-type” alignment. A spike-type alignment occurs when the ETM conduction band is lower than that of the absorber, creating a small energy barrier that can block minority carrier injection and suppress recombinationbeneficial if the spike is moderate (<0.3 eV). A cliff-type alignment, where the ETM conduction band lies above that of the absorber and promotes majority carrier flow but increases the risk of interface recombination due to a lack of an energy barrier.

In this study, both MAPbI₃ and MASnI₃ exhibit changes in performance, consistent with transitions between these two alignment types. For MAPbI₃, the optimal electron affinity of 3.75 eV yields a near-zero or slightly positive CBO with ZnO, suggesting a mild spike-type alignment, which favors efficient electron extraction, while preventing recombination. At lower electron affinities (<3.5 eV), the alignment shifts toward a cliff, increasing recombination and reducing performance. However, MAPbI₃ maintains a stable output due to its relatively robust interfacial electronic structure and defect tolerance.

In contrast, MASnI₃ is far more sensitive to the electron affinity shift. As the electron affinity increases beyond 4.00 eV, the conduction band of MASnI₃ sinks below that of ZnO, creating a larger spike that begins to obstruct electron transport and reduce performance. Below this value, the system trends toward a cliff-type alignment, which again promotes recombination. This explains the sharper performance peak in MASnI₃ and its nonlinear response: small deviations in χ can quickly move the CBO into an unfavorable range, either by introducing a too-steep spike or a recombination-prone cliff. Therefore, the optimal point (χ = 4.00 eV) likely corresponds to a minimal positive CBO, ensuring a balanced band alignment that maximizes extraction, while limiting interfacial losses.

These findings highlight the importance of band alignment engineering. For MAPbI₃, performance is relatively resilient across a range of CBOs, but for MASnI₃, precise electron affinity tuning is critical to avoid spike/cliff extremes and to ensure device stability and efficiency.

4.4. Effect of Back Contact

Back contact plays a vital role in the device performance of PSCs. The efficiency of the cell increases with the increment of the metal work function of back contact. In this section, two cells are simulated by 10 different back contact materials. The metal work function of different back contact materials is given in Table .

9. Different Back Contact Materials and Their Metal Work Function.

back contact material ,	Cu	Ag	Fe	C	Au	W	Ni	Pt	Pd	Se
metal work function, Φm (eV)	4.65	4.74	4.81	5	5.1	5.22	5.5	5.6	5.7	5.9

By investigation of Figure , it can be said that the efficiency is increasing with the metal work function (eV) of back contact, and after a particular value of the metal work function (eV), the efficiency is almost constant.

10.

Efficiency Curve of MAPbI₃ and MASnI₃-based cells according to back contact metal work function (eV).

Here, six back contacts can retain maximum efficiency for both optimized cells. As we aim to determine a low-cost and highly efficient cell structure, we choose the back contact material according to the price of the materials from these six back contact materials.

Table clearly identifies the least expensive back contact materials. Although all six back contacts can provide maximum efficiency, Ni is the least costly back contact among them. Hence, we chose Ni as the back contact for our study to improve the cost-effectiveness of the cells. Contact parameters after optimization are given in Table .

10. Back Contact Materials that Provide Maximum Efficiency and Their Price .

metal name	metal work function (eV)	price (euro/g)
Au	5.1	264
W	5.22	13.5
Ni	5.5	2.232
Pd	5.6	635.714
Pt	5.7	230
Se	5.9	11.32

^aThe price of each material is taken from Sigma-Aldrich.

11. Back Contact and Front Contact Parameters.

parameters	back contact	front contact
surface recombination velocity of electrons (cm/s)	1.000 × 105	1.000 × 107
surface recombination velocity of holes (cm/s)	1.000 × 107	1.000 × 105
metal work function (eV)	5.5	4.3
majority carrier barrier height relative to E f (eV)
MAPbI3	–0.3000	0.2000
MASnI3	–0.3000	0.2000
majority carrier barrier height relative to E v (eV)
MAPbI3	–0.3749	0.1641
MASnI3	–0.3749	0.1641

4.5. Effect of the Absorber Layer Defect Density

Defect density optimization is an optimization technique to increase cell performance. There is a direct effect of the defect density on device output parameters. The recombination rate is increased with an increment of defect density, which reduces the carrier lifetime and diffusion length of the carrier. Hence, the efficiency is also deduced. In this section, both cells are simulated with a defect density of 1.00 × 10¹⁰ (1/cm³) to 1.00 × 10¹⁸ (1/cm³).

In the simulated MAPbI₃-based perovskite solar cell (where L _p = L _n and τ_p = τ_n), both the diffusion length and carrier lifetime decreased with an increase in defect density. The highest power conversion efficiency was observed when the diffusion length ranged from 510.0 to 16.0 μm and the carrier lifetime ranged from 1.00 × 10⁷ to 1.00 × 10⁴ s. The optimal performance was achieved at a defect density of 1.00 × 10¹³ cm^–3, corresponding to an efficiency of 27.1% (Figure ).

11.

(a) Impact of the defect density on the diffusion length, (b) impact of the defect density on the carrier lifetime, and (c) impact of defect density on the power conversion efficiency of the MAPbI₃-based cell.

Figure shows that at a low defect density of 1.00 × 10¹⁰ cm^–3, the values of L _p, L _n, τ_p, and τ_n were 64.0 μm, 640.0 μm, 1.00 × 10⁶ s, and 1.00 × 10⁸ s, respectively, with a maximum efficiency of 27.99%. As the defect density increased, all these parameters declined consistently, confirming that higher defect densities negatively impact device performance in the MASnI₃-based perovskite system.

12.

(a) Impact of defect density on the diffusion length, (b) impact of the defect density on the carrier lifetime, and (c) impact of the defect density on the power conversion efficiency of the MASnI₃-based cell.

The efficiency is the lowest (9.56%) for the MASnI₃-based cell when N _t is at maximum. We have chosen the defect density value as 1.00 × 10¹³ (1/cm³), where the efficiency is 27.99%.

4.6. Effect of Series Resistance

Series resistance (R _s) is a fundamental parameter that significantly impacts the performance of photovoltaic devices. It primarily affects the short-circuit current density (J _sc) and fill factor (FF), which collectively determine the power conversion efficiency (PCE). An increase in R _s introduces resistive losses that hinder charge carrier transport, reduce the fill factor, and limit the overall charge extraction efficiency. These effects ultimately lead to a noticeable decline in device efficiency, as supported by previous studies. ,

Simulation results, as illustrated in Figure , reveal that the efficiency (η) of the device consistently decreases with increasing R _s. Under ideal conditions (R _s = 0 Ω), a maximum efficiency of 27.87% is achieved. As R _s increases to 6 Ω, the efficiency declines to 23.31%. Notably, the open-circuit voltage (V _oc) appears to show a slight increase, which may seem counterintuitive. In practical devices, V _oc is predominantly determined by the separation of quasi-Fermi levels and is typically not influenced by R _s, especially under open-circuit conditions where the current is zero and series resistance has no direct electrical effect.

13.

Efficiency and open-circuit voltage curves of the MAPbI₃-based cell according to series resistance.

The minor increase in simulated V _oc with increasing R _s is likely a numerical artifact or a consequence of changes in internal recombination dynamics captured by the SCAPS-1D simulation environment rather than a physically meaningful behavior. It may result from slight shifts in internal carrier distributions or reduced recombination current under zero current conditions. However, in real photovoltaic devices, V _oc either remains constant or slightly decreases with increasing R _s due to indirect effects, such as elevated recombination caused by higher internal resistive heating. Therefore, the observed trend in V _oc should not be interpreted as a performance benefit.

As shown in Figure , both J _sc and FF decrease steadily with increasing the value of R _s. At R _s = 6 Ω, J _sc drops to 28.47 mA/cm², and FF falls to 73.34%, clearly demonstrating the impact of resistive losses on current extraction and voltage efficiency.

14.

Short-circuit current and fill factor curves of a MAPbI₃-based cell according to series resistance.

Recognizing that eliminating R _s entirely is not feasible in real devices, a practical value of R _s = 1 Ω was selected for further simulation and optimization. Under this condition, MAPbI₃-based cells yield optimized values of V _oc = 1.10 V, J _sc = 28.47 mA/cm², FF = 86.42%, and η = 27.10%. For MASnI₃-based cells, the corresponding values are V _oc = 0.97 V, J _sc = 34.89 mA/cm², FF = 82.51%, and η = 27.98%.

Figure further provides the outcome of impact of series resistance on the performance of the MASnI₃ based cell. When R _s = 0 Ω, the device achieves a maximum efficiency of 29.1%, while with R _s = 6 Ω, the efficiency sharply drops to 22.45%, primarily due to reductions in FF and J _sc. V _oc remains mostly unchanged across the R _s range, as expected.

15.

Efficiency and open-circuit voltage curve of a MASnI₃-based cell according to series resistance.

These findings underscore the necessity of minimizing series resistance in PSCs to maintain high FF and efficiency, in agreement with established experimental and theoretical research. ,

The simulation results presented in Figure indicate that both short-circuit current density (J _sc) and fill factor (FF) decline consistently as the series resistance (R _s) increases from 1 to 6 Ω. This trend reflects the growing impact of resistive losses, which hinder charge carrier extraction and reduce the device’s power output. Given that real-world photovoltaic devices always exhibit some finite resistance, a practical value of R _s = 1 Ω is selected for optimization, representing a realistic balance between ideal behavior and manufacturability. Under these conditions, the MASnI₃-based cell achieves optimal output parameters: V _oc = 0.97 V, J _sc = 34.89 mA/cm², FF = 82.51%, and power conversion efficiency (PCE) = 27.98%. These values confirm that while zero-resistance conditions are useful for theoretical benchmarking, low but realistic R _s values must be targeted to ensure both high performance and practical feasibility in perovskite solar cell deployment.

16.

Short-circuit current and fill factor curve of a MASnI₃-based cell according to series resistance.

From the above discussion, it can be said that both cells show optimized efficiency, which is also practically achievable. According to the Shockley–Queisser limit, the maximum efficiency achievable for a single-junction solar cell is 33.14%, and the efficiency of both MAPbI₃ and MASnI₃-based cells does not exceed the limit. The previous study also confirmed the achievability of these efficiencies as MAPbI₃-based achieved a power conversion efficiency of 26.74%, and MASnI₃-based cells achieved a 27.43% power conversion efficiency in the previous study.

Here, both cells are optimized and can provide optimal efficiency. The quantum efficiency of both cells in Figure clearly identifies that both cells are optimized. Here, both cells show a nearly 87% quantum efficiency. However, the quantum efficiency of both cells reaches almost 100% at the midrange of the wavelength and drops significantly at the final range of wavelength.

17.

Quantum efficiency of the optimized cells.

Therefore, the simulation result and price of the materials confirm that the proposed cell can provide a higher efficiency with the least expensive ETM, HTM, and back contact materials.

4.7. Performance Analysis

This section of the study discusses performance improvement and the reasons behind the improvement. Here, the reason behind the overall improvement is shown and analyzed through initial and optimized cell properties such as generation current, recombination current, generation profile, recombination profile, and band diagram of the cell.

For MAPbI₃-based cells, according to Figure , the initial and optimized generation and recombination curve shows that the overall performance of the optimized cell is increased compared to the initial cell. Although the recombination current did not drop significantly, generation current has grown considerably on the optimized cell. Hence, the overall cell performance of the optimized cell performance has also increased.

18.

Generation and recombination current of the MAPbI₃-based cell.

The reason for overall performance, generation current, and recombination current ratio improvement can be described in Figure . In Figure , the X (μm) indicates the depth within the cell structure, starting from the front contact and extending through the absorber to the back contact. Figure reveals the electron–hole pair generation and recombination on the initial and optimized cells. It can be observed that, although the generation rates did not rise significantly, the ratio between generation and recombination improved significantly. A broader picture in Figure , described by Figure , defines that.

19.

Generation–recombination profile of the MAPbI₃-based cell.

20.

(a) Generation–recombination profile of the initial MAPbI₃-based cell and (b) generation–recombination profile of the optimized MAPbI₃-based cell.

The reason for the improvement in the ratio between generation and recombination ratio can be described in Figure . In Figure , X (μm) indicates the depth within the cell structure, starting from the front contact and extending through the absorber to the back contact. On point A, the back surface field is generated between the back contact and HTM due to the optimized back contact of the cell. This back surface field reduces the recombination between the HTM and back contact. On points B and C, VBO and CBO are induced due to the introduction of a thin (30 nm) intrinsic absorber layer and optimization of the electron affinity of the absorber layer. These VBO and CBO reduce the recombination on the interface between the absorber and ETM. Additionally, the interface between the HTM and absorber is also improved. Hence, the performance of the optimized cell is improved compared with the initial cell.

21.

Energy band diagram of the MAPbI₃-based cell.

The MASnI₃-based cell also has similar impacts as the MAPbI₃-based cell for optimizing parameters. Initial cells have comparatively lower generation currents. However, the generation current improved significantly after optimizing material and cell parameters (Figure ). Hence, the overall cell performance has also improved considerably. The reason behind the generation’s current improvement can be described by the generation–recombination profile of the cell. The generation–recombination profile of the cell is shown in Figure . In Figure , X (μm) indicates the depth within the cell structure, starting from the front contact and extending through the absorber to the back contact. It can be seen from Figure that overall carrier recombination has dropped significantly compared with carrier generation. A broader picture of the generation recombination profile in Figure identifies the numerical comparison between the initial and optimized cell generation recombination profiles. The reason for the generation recombination profile can be described by the initial and optimized cell band diagram. In Figure , X (μm) indicates the depth within the cell structure, starting from the front contact and extending through the absorber to the back contact. Figure shows that the initial cell has no optimized VBO and CBO, which results in higher recombination after optimizing the cell by varying cell parameters and materials parameters and introducing intrinsic absorber materials between absorber materials. The interface recombination points B, C, D, and E can be reduced significantly. While the probability of recombination on point A is reduced by optimizing back contact materials.

22.

Generation and recombination current of the MASnI₃-based cell.

23.

Generation–recombination profile of the MASnI₃-based cell.

24.

(a) Generation–recombination profile of the initial MASnI₃-based cell and (b) generation–recombination profile of the optimized MASnI₃-based cell.

25.

Energy band diagram of the MASnI₃-based cell.

After continuous simulation and optimization, the following cell structure of Figure is finalized for the study.

26.

Optimized cell structures for the study.

Table clearly indicates that cell structures of the current study clearly outplay previous cell structures as these two cells can provide high efficiency while the materials cost is lowest for these cells. Hence, these cells are noble cell structures for further study and fabrication.

12. Cost of Materials and Efficiency Comparison of Cell Structures (Current and Previous Studies) .

cell structure	ETM cost (euro/g)	HTM cost (euro/g)	back contact cost (euro/g)	total cost (euro)	η (%)
FTO/TiO2/CsGeI3/Spiro-OMeTAD/Ag	27.2	528	9.01	564.21	18.30%
ZnO(nr)/CH3NH3SnI3/Cu2O/Au	13.6	15.76	264	293.36	20.23%
ZnO(nr)/CH3NH3SnI3/Spiro-OMeTAD/Au	13.6	528	264	805.6	20.21%
ITO/NiO/MASnI3/PCBM/Ag	19.7	1130	9.01	1158.71	29.19%
FTO/Perovskite/Spiro-OMeTAD/Au	0	528	264	792	19.16%
ITO/PEDOT:PSS/MAGeI3/PCBM/Ag	1.324	1130	9.01	1140.334	11.16%
ITO/PEDOT:PSS/MAGeI3/C60/ Ag	1.324	677	9.01	687.334	13.5%
FTO/TiO2/MAPbI3/Spiro-OMeTAD/Au	27.2	528	264	819.2	23.18%
FTO/TiO2/MAPbI3/NPB/Au	27.2	725	264	1016.2	22.56%
FTO/TiO2/MAPbI3/P3HT/Au	27.2	749	264	1040.2	19.38%
FTO/TiO2/MAPbI3/MEH-PPV/Au	27.2	798	264	1089.2	21.23%
ITO/NiO/CH3NH3PbI3–x Cl x /PCBM/Ag	19.7	1130	9.01	1158.71	22%
FTO/TiO2/CH3NH3PbI3–x Cl x /Spiro-OMeTAD/Ag	27.2	528	9.01	564.21	29.56%
FTO/ZnO/MASnI3/PEDOT:PSS/Au	0.172	1.324	264	265.496	21.22%
ZnO/MAPbI3/PEDOT:PSS + WO3/Ni	0.172	1.292	2.232	3.696	27.10 (this study)
ZnO/MASnI3/PEDOT:PSS + WO3/Ni	0.172	1.292	2.232	3.696	27.98 (this study)

^aThe price of each material is taken from Sigma-Aldrich.

5. Conclusions

This study presents a comprehensive, simulation-guided framework for designing high-efficiency, low-cost, and environmentally sustainable perovskite solar cells (PSCs). Using SCAPS-1D, we evaluated 14 absorber materials that are both Pb-based and lead-free within a fixed, low-cost device architecture featuring ZnO (ETM), PEDOT:PSS + WO₃, and nickel (Ni) as the back contact. The optimized configurations yielded power conversion efficiencies of 27.10% for MAPbI₃ and 27.98% for MASnI₃, confirming that nontoxic MASnI₃ can rival conventional lead-based absorbers in performance.

A key contribution of this work is the simultaneous optimization of efficiency, affordability, and environmental safetythree factors typically explored in isolation. By tuning the absorber thickness, electron affinity, defect density, and series resistance, we achieved enhanced carrier generation, reduced recombination, and favorable energy level alignment across a wide spectral range.

These results establish a practical blueprint for building scalable PSCs using abundant and low-cost materials. The simulation-driven approach also reduces experimental trial and error, accelerating the discovery and validation of efficient perovskite architectures.

Looking ahead, future research should focus on experimental validation, long-term operational stability, and scalable manufacturing. By addressing performance, cost, and toxicity in a unified design, this study offers a crucial step toward next-generation solar technologies that are both commercially viable and environmentally responsible.

The parameter data used to support the findings of this study are included in the article.

The authors did not receive any external funding for the study.

The authors declare no competing financial interest.