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Scientific Reports volume 16, Article number: 4270 (2026) Cite this article
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Recent research has put the spotlight on PSCs (perovskite solar cells) where leads are not present, because they’re better for the environment and have impressive photovoltaic features. Though, the lead-based options like MAPbI₃ are high performers, but their toxicity is a big drawback. In this study, we’re introducing Ba₃PCl₃ as a new, non-toxic absorber material to tackle those environmental worries while keeping strong optoelectronic properties. To boost efficiency, we checked out different electron transport layers (ETLs), and it turns out cerium oxide (CeO₂) performed best for improving carrier extraction and reducing recombination. We modelled and optimized the device architecture using SCAPS-1D, focusing on things like absorber thickness and defect density. A comprehensive parametric sweep showed that fine-tuning these factors really makes a difference in device performance. The top configuration achieved a J_SC (short circuit current density) equal to 43.35 mA/cm², a V_OC (open circuit voltage) equal to 0.7059 V, a FF (fill factor) equal to 82.92%, and a PCE (power conversion efficiency) equal to 25.38%.
PSCs (perovskite solar cells) are rapidly advanced in the area of photovoltaics, achieving a increase in efficiency from 3.8% to over 26.1% within a decade¹. As of 2023, certified single-junction PSCs have achieved over 25.2% efficiency, while tandem perovskite–silicon cells have surpassed 29% in laboratory settings^2,3,4,5. The commercialization of high-efficiency, stable, and environmentally friendly PSC modules is increasingly viable, marking a significant step toward their integration into the global solar energy market^6,7,8. This impressive growth stems from the different features of perovskite materials, like their adjustable bandgap, high light absorption, and simpler manufacturing processes^9,10,11. Yet, there are still hurdles to tackle when it comes to their reliability and scaling for industrial use¹². Recent research has been zeroing in on fresh approaches to boost the performance and consistency of PSCs’ supply chains. These approaches involve tweaking interfaces and grain boundaries to reduce current–voltage hysteresis and enhance charge transfer¹³. Numerical methods are crucial for modeling and simulating the various factors affecting solar cell efficiency. With these techniques, researchers can fine-tune device designs, grain structures, and material compositions, leading to better power conversion efficiencies (PCEs) and stability during use. Here, we introduce a new combined approach using various numerical methods to accordingly enhance the working of perovskite solar cells, aiming for peak efficiency. This strategy tackles the inherent challenges of perovskite materials and sets the groundwork for creating more stable and efficient solar cells. We aim to provide insights that will contribute to the next generation of PSCs with high performance by employing computational models and experimental data, ultimately facilitating the transition of these PSCs from laboratory settings to real-world applications. When it comes to electron transport layers (ETLs) in PSCs, titanium dioxide (TiO₂) and zinc oxide (ZnO) have been the go-tos due to their flexible structures and good band alignments. However, the performance of ZnO is highly dependent on how it’s synthesized—especially in managing oxygen vacancies—while TiO₂ faces issues with low electron mobility and instability when exposed to UV light¹⁴, leading to more recombination and less durability over time. These drawbacks push us to look for alternative ETL materials.
Perovskite solar cell (PSCs) generally achieves high efficiencies largely thanks to carefully engineered ETLs (electron transport layers) and HTLs (hole transport layers) that optimize reduce recombination and charge extraction. Early ETLs like TiO₂ were valued for their stability and suitable energy alignment, but their low electron mobility and requirement for high-temperature processing limited performance.
More recently, SnO₂ has emerged as a superior alternative because of its higher electron mobility, low-temperature processability, and deep conduction band, contributing to enhanced V_OC, reduced hysteresis, and better device stability¹⁵. Bilayer ETLs such as TiO₂/WO₃ have demonstrated improved electron extraction and recombination suppression, enabling power conversion efficiencies (PCEs) exceeding 20%¹⁶. Similarly, ZnO-based ETLs enhanced with dopants or surface passivation have achieved PCEs over 20% while improving environmental stability¹⁷. On the HTL side, inorganic materials like NiOₓ and VOₓ offer better energy level alignment, enhanced hole mobility, and improved chemical robustness. VOₓ-based HTLs, in particular, have delivered devices with PCEs approaching 19.7% and improved reproductibility¹⁸.
In this study, we’re using cerium oxide (CeO₂) as the ETL. It has a wider bandgap of 3.5 eV, a decent dielectric constant (ε = 9), and low recombination rates. CeO₂ improves band alignment with the absorber and boosts electron extraction while minimizing recombination losses thanks to its deep defect levels and long carrier lifetimes^11,19,20,21.
For the absorber, we’re investigating Ba₃PCl₃, an up-and-coming lead-free material with a slim bandgap of 0.997 eV, an electron affinity of 4.5 eV, and high dielectric permittivity²². These traits make Ba₃PCl₃ well-suited for capturing a wide solar spectrum while showing good tolerance to defects and reasonable carrier mobility.
We selected PEDOT:PSS for the HTL (hole transport layer) in our simulations because it effectively extracts holes due to its energy alignment (with a bandgap equal to 1.6 eV and an electron affinity equal to 3.55 eV and high acceptor density, which helps with efficient hole transport and reduces interfacial recombination^23,24.
Additionally, the study finds the significance of front and back contact material work functions, temperature of operation, and quantum efficiency, and conducts thorough J-V analysis²⁵.
For modeling, we’re using Solar Cell Capacitance Simulator in 1 Dimension (SCAPS-1D), (version 3.3.07: URL- https://scaps.elis.ugent.be/) to analyze how the thickness of the ETL as well as the absorber layer, defect densities, capture cross-sections, and doping concentrations affect device performance. We’re also looking at JV curves, capacitance and voltage characteristics, quantum efficiency and analysis of impedance to understand the electronic quality and how performance metrics, for example J_SC,V_OC; are impacted by defects.
In the work, we have a low bandgap material of Ba₃PCl₃. The novelty factor is concurrently;
Multiple ETLs with one HTL, the front and back contact optimization. Along with this the overall impact of different optimizing factors are also studied. Our goal is to optimize the configurations and material properties to boost overall efficiency, all while staying environmentally friendly by using non-toxic materials like Ba₃PCl₃ and CeO₂ respectively.
Here, in the study, we use the SCAPS-1D software for simulation as well as to optimize all main parameters of the solar cell. This includes things like how thick the absorber is, doping levels, electron properties and transport layers (HTL and ETL), and the front and back contact’s work functions. We also take a look at quantum efficiency, the operating temperature, and the current voltage (JV) characteristics. SCAPS tackles a set of core semiconductor equations which include Poisson’s equation along with continuity equations for electrons as well as holes. These equations dictate how the electrostatic potential and carrier movement function throughout the device. For testing, we illuminate the solar cell structure with the AM 1.5G spectrum, having power density of 1000 mW/m² to see how it performs in real-world conditions. Using the AM 1.5 standard solar spectrum, a widely used benchmark for evaluating solar cell performance, with the SCAPS modelling program is known as “SCAPS AM 1.5.” While AM 1.5, a conventional irradiance spectrum that depicts sunlight flowing through 1.5 times the thickness of the atmosphere, is frequently used to evaluate solar cells under typical terrestrial circumstances, SCAPS is a one-dimensional tool for simulating solar cells²⁶.
Our simulated device is set up as ITO/CeO₂/Ba₃PCl₃/PEDOT:PSS/Au. Here, CeO₂ is working as the electron transport layer, Ba₃PCl₃ acting as the absorber, PEDOT:PSS is working as hole transport layer, ITO functions as the front oxide with transparency and conductivity, and Au is used as the rear metal contact.
The Ba₃PCl₃ layer is 1.375 µm thick and has a bandgap equal to 0.997 eV, which allows it to absorb light effectively in the infrared range. We keep the thickness of the HTL as well as the ETL at 0.1 µm. With a wider bandgap of 3.5 eV and good energy alignment, CeO₂ facilitates efficient electron extraction while reducing issues with recombination at the interfaces. Likewise, PEDOT:PSS efficiently transports holes because of its high work function and as it is more compatible with the absorber layer.
The solar cell works in three key steps: first, absorption of light by the Ba₃PCl₃ layer, creating electron and hole pairs; second, the present electric field helps separate these charge carriers; and third, electrons travel through CeO₂ to the FTO front contact, while holes move through PEDOT:PSS to the Au rear contact. This design minimizes energy loss and boosts how efficiently the carriers can be collected.
Unlike the commonly used multi-layered perovskite stacks, this configuration simplifies the design yet still lead to effective absorption of light as well as transport of charge. We can directly improve the short J_SC and the PCE, by optimizing the physical parameters of the absorber material, defect densities, and interfacial qualities of the layers. Figure 1 describes the structural representation and the schematic of energy levels depicting carrier transportation of the device.
(a) Structural representation of PSC under AM1.5G illuminance (b) Schematic of energy levels depicting carrier transport in ETL and HTL.
Table 1 describes a summary of the physical parameters for each layer in the simulation; while Table 2 shows the interface defect levels for the simulation.
It is feasible to get the maximum possible efficiency of solar cells by applying a computational modelling approach. Particularly noteworthy is the prices and development durations connected with constructing a solar cell become unsustainable without numerical modelling^32,33. Through the utilization of this approach, the requirement of conducting potentially dangerous examinations of component layer qualities is eliminated. Instead, a summarized study is provided to maximize cell performance. In addition, it is a helpful instrument for analysing the relative value of various material properties by using examples from the solar cell industry as a basis for reference. In addition, simulation has grown significantly, particularly in materials research. It is significant to note that the model that Burgelman and colleagues created³⁴. It allows for the opportunity to address the productivity of the PSC device and consider the critical parameters. The equation governs the conditions of the semiconductors in their steady state in one dimension. It is possible to present the relationship between the ρ (charge density) and the E (electric fields) for the p–n junction in the given manner^35,36:
The symbol (varphi) is electrostatic potential, the symbol q represents charge, the symbol ({varepsilon }_{s}), represents the static relative permittivity, n and p symbols refers the electrons and the hole, respectively. The symbols ({N}_{A}^{+}) and ({N}_{D}^{+}) are referred to as the acceptor and donor density, respectively, while the symbol N_def (x) represents the defect density of both.
Despite this, the carrier continuity equation of the PSC is structured as follows³⁷: In this context, the terms ({j}_{p}) and ({j}_{n}) refer to the hole’s and electron’s current density, while G is the rate at which carriers are obtained. Additionally, ({U}_{p}left(n,pright)) represent the recombination of respective carriers.
While the carrier current density is also obtained from the equation given below,
where (q) is charge,({mu }_{p}) and ({mu }_{n}) is the carrier mobility, ({D}_{p}) and ({D}_{n}) is the carriers’ diffusion coefficient.
Typical architecture involves solving solar cell problems using SCAPS 1D, as described in the flow chart below. It shows the steps from taking user input for the identified problem to getting output, which involves multiple steps. Figure 2 describes the Graphical representation of the working of SCAPS 1D.
Graphical representation of the working of SCAPS 1D.
The SCAPS-1D software usually includes the fundamental formulas for solar cell properties, such as the generation-recombination rates and the current density.
The present section describes and analyses the outcomes derived from estimating the performance characteristics of PSC configurations based on Ba₃PCl₃ based PSCs.
Adjusting the bandgap and energy level alignment of materials within a perovskite solar cell (PSC) is crucial for enhancing dynamics of charge carrier and boosting how well the device performs. To get the electrons to move efficiently from the absorber layer to the electron transport layer (ETL), the conduction band (CB) of the absorber needs to sit a bit higher than that of the ETL. On the flip side, for effective hole transport, the valence band (VB) of the hole transport layer (HTL) should be positioned slightly lower than the absorber’s VB to help the holes move over.
Figure 3 shows the simulated energy band diagram for the proposed PSC structure: ITO/CeO₂/ Ba₃PCl₃/PEDOT:PSS/Au, at a thermal equilibrium of 300 K. The Ba₃PCl₃ absorber has a bandgap of 0.997 eV, with its CBM (conduction band minimum) about − 4.5 eV and VBM (valence band maximum) at − 5.497 eV. The CeO₂ ETL has a bandgap of 3.5 eV and an electron affinity equal to 4.6 eV, resulting in a conduction band minimum equal to –4.6 eV, which creates a small offset of 0.1 eV compared to Ba₃PCl₃. This small potential difference allows for easy electron injection from the absorberlayer into the ETL, which minimizes the recombination losses.
Representation of single ETL and Double HTL PSC under AM1.5G illuminance.
When it comes to hole transport, PEDOT:PSS has a valence band placement of –5.15 eV, which is higher than that of Ba₃PCl₃. This VB offset of around 0.35 eV makes it easier for holes to shift to the HTL from the absorber layer. The energy levels between Ba₃PCl₃, CeO₂, and PEDOT:PSS are well aligned, creating low energy barriers for charge movement and reducing recombination losses along the interfaces.
Additionally, the choice of front (ITO) and rear (Au) metal contacts is intentional; they aim to create a built in electric field throughout the device. This natural electric field helps separate charge carriers and effectively drives the electron–hole pairs toward their designated contacts, which supports better PCE. The thoughtful band alignment and material choices lead to smooth charge transport and minimal energy loss at the interfaces, which enhances the overall working of the simulated lead-free PSC. Furthermore, the selection of suitable contact materials for the front and rear electrodes establishes an internal electric field across the device, promoting smooth and effective charge carrier transport throughout the entire structure³⁸.
Here for lead-based PSC, a study was conducted to check the device’s performance in response to variations in the absorber layer thickness³⁹. The researchers discovered that the PCE first grew in proportion to the increase in the abs layer thickness. The amount of abs layer thickness at which the PCE is at its highest point is referred to as abs_ideal When the absorber thickness is less than the abs_ideal thickness, the cell performance is reduced. This is because the insufficient absorption of incident light leads to inadequate charge carrier formation and poor cell performance. Due to the inability of thinner absorber layers to successfully absorb photons with longer wavelengths, the creation of charge carriers is thus constrained. Figure 4 shows the impact of Absorber thickness and defectivity and reaches a maximum value at thickness level of 2 µm and a defectivity level of 1 × 10¹³ cm^-3, respectively. 
The following figures (Fig. 5– Fig. 9) shows how the parameters of the carrier transport layer like thickness and defect density impact the working of the Ba₃PCl₃-based device we’re proposing. For finding out the optimized ETL; We investigated that, when the thickness of the CeO₂ electron transport layer (ETL) changes from 0.1 µm to 0.5 µm, and the PEDOT:PSS HTL (hole transport layer) changes from 0.1 µm to 0.5 µm affected things, as you can see in the Fig. 5. The findings indicated that thinner ETL and HTL layers (specifically at 0.1 µm) resulted in a pretty impressive PCE of up to 25.38%. But as we increased the thickness of these layers, we noticed a steady drop in performance. This drop in efficiency likely happens because of increased recombination losses and limited charge transport, which stem from higher resistance and longer paths for the carriers to travel in thicker layers⁴⁰. Plus, thicker transport layers might hinder effective light absorption in the Ba₃PCl₃ absorber layer, which ultimately cuts down on the overall energy conversion efficiency.
(a–d) Variation in PV parameters of the PSC under AM1.5G illumination, influenced by the thickness and defect density of the Ba₃PCl₃ absorber layer.
The detail outputs is shown in Fig. 4.
The HTL variation contour plot is depicted showing all four PV parameters in Fig. 5.
(a–d) Variation in PV parameters of the PSC under AM1.5G illumination, influenced by the thickness and defect density of the HTL Layer (PEDOT-PSS).
The ETL variation contour plot is depicted showing all four PV parameters in Fig. 6.
(a–d) Variation in PV parameters of the PSC under AM1.5G illumination, influenced by the thickness and defect density of the ETL Layer (Mg Doped ZnO).
The contour plot is depicted showing all four PV parameters in Fig. 7.
(a–d) Variation in PV parameters of the PSC under AM1.5G illumination, influenced by the thickness and defect density of the ETL Layer (C₆₀).
The contour plot is depicted showing all four PV parameters in Fig. 8.
(a–d) Variation in PV parameters of the PSC under AM1.5G illumination, influenced by the thickness and defect density of the ETL Layer (CeO₂).
The contour plot is depicted showing all four PV parameters in Fig. 9.
(a–d) Variation in PV parameters of the PSC under AM1.5G illumination, influenced by the thickness and defect density of the ETL Layer (CeO₂).
The obtained contour plots shown in Fig. 10a–d illustrate the combined impact of series resistance (R_s) and shunt resistance (R_sh) on the key photovoltaic (PV) parameters of the Ba₃PCl₃ based solar cell. It is evident that low R_s and high R_sh values are essential to achieve optimal device performance. As R_s increases, there is a significant reduction in the J_SC and FF, due to higher resistive losses and limited charge extraction. Lower R_sh results in decreased V_OC and PCE, because of enhanced leakage currents and increased recombination. The highest PCE is observed when R_s is minimal and R_sh is maximized, emphasizing the need for careful optimization of these resistances to minimize parasitic losses. PSCs perform in an optimal way when we minimize the value of R_S and when we maximize the value of R_Sh because this ensures that we extract charge in an efficient way plus internal loss is at a minimum. To manage these resistive losses as well as increase device output, engineering strategies are commonly used. These strategies do include an improved electrode design plus high-quality material deposition along with interface passivation^41,42,43. Overall, these results confirm that controlling both series and shunt resistances is crucial for increasing the efficiency as well as stability of perovskite solar cells.
(a–d) The PV parameters on the output of the PSC with respect to series and shunt resistances.
In Fig. 11a–d, we have shown a detailed study about the significant impact of different front and back metals on the PV parameters of the PSC device. Front contacts used are FTO,ITO, Al doped ZnO, back metals used are Ni,Cu,Ti & the combinations of these tends to give more efficiency, J_SC, V_OC, FF. The best result is obtained which gives PCE = 25.38%, J_SC = 43.35 mA/cm², V_OC = 0.7060 V, FF = 82.95%. In PSCs (perovskite solar cells), the front and back contacts play a crucial role in obtaining efficiency, stability, and overall performance. Selecting the optimal combination of front and back contacts is essential because they Enable Efficient Charge Collection, Determine Energy Band Alignment, Affect Transparency and Light Absorption, Impact Stability and Lifetime, etc.⁴⁴. The numerical value for PCE is shown in Table 3, J_SC in in Table 4, V_OC in in Table 5 and FF is depicted in in Table 6; respectively.
(a–d) The PV parameters on the output of the PSC with respect to Impact of Front and Back Contact Materials on Photovoltaic Parameters.
The variations in device efficiency with different contact materials mainly stem from differences in work function alignment between the contacts and the absorber layers, which directly affect charge extraction. Poor alignment can create energy barriers, leading to charge accumulation and enhanced interface recombination. Additionally, the presence of trap states and interfacial defects at poorly matched contacts further contributes to carrier loss. Optical reflection at certain metal interfaces may also reduce light absorption slightly. Overall, optimal contact selection ensures efficient carrier transport and minimizes recombination losses^45,46,47.
Figure 12 depicts the comprehensive examination of the temperature effect on solar cell performance, which includes the sensitive parameters like J_SC, V_OC, FF, and PCE. It is clear that J_SC is temperature dependent. Equations (1) and (2) show how states density (DoS) in the CB or VB [N_C(T)/N_V(T)] varies with varying temperature. The thermal velocity V_th(T) varies with the varying temperature, as shown by Eq. (3). Temperature variations are thought to have no impact on other variables. In these calculations, a temperature-dependent quantity termed the diffusion coefficient (D = kT/q) is used. In SCAPS-1D, the default temperature (T₀) is set to 300 K, which serves as the reference point for the parameters defined in Eqs. (1)–(3).
The J-V parameter on the output of the PSC with respect to different temperatures.
As the temperature increases, the parameters like N_C(T), N_V(T), and V_th(T) also increases, impacting overall device performance. The rise in the effective states density provides more available states for electrons and holes, affecting carrier concentrations. Higher temperatures increase the thermal velocity of carriers, which shorten the carrier lifetimes and enhance the rates of recombination (Eq. 8). While the impact of temperature on V_OC is shown in Eq. 9⁴⁸. As shown in Fig. 3, the J-V characteristics at varying temperatures clearly show a decline in V_OC and FF, while the J_SC remains nearly constant. The drop in V_OC as temperature rises is mainly due to a higher reverse saturation current and increased recombination losses and Thermal Agitation occurs⁴⁹. Higher temperature gradients further reduce the PCE, showing the importance of thermal stability for high-performance solar cells. The highest outputs at optimal states are summarized in Table 6. This temperature-dependent behavior aligns with earlier studies on perovskite solar cells, which is reported by Sobayel et al.⁵⁰.
The J–V curve visually shows how a solar cell’s J (current density) changes with the V (applied voltage). From Fig. 12, the J–V curve is presented for various temperatures varying from 300 to 400 K. The current density for every temperature remains more or less same but the voltage varies for every values of temperature.
The improved Ba₃PCl₃ perovskite solar cell shows really impressive quantum efficiency (QE) covering a wide spectrum of light wavelengths, as illustrated in Fig. 13a. It’s clear that choosing the right front and back contacts, along with optimizing the absorber layer (Ba₃PCl₃), makes a big difference in boosting the overall QE. This device really excels at capturing light and collecting carriers, leading to an impressive average QE of around 80% based on our simulation. Apart from that, the capacitance–voltage (C–V) details in Fig. 13b, you’ll get a look at the built-in potential and how charge is distributed in the device. The sharp increase in capacitance at lower voltages suggests that we’ve got effective depletion width modulation and solid interface quality⁵¹. With increment in abs thickness generally leads to improved quantum efficiency (QE), as a thicker absorber can capture more photons⁵². Moreover, Ravishankar et al. In the current study, found out a significant impact of frequency over over QE characteristics. The QE dropped by as much as 10%, especially at lower frequencies (50 Hz or below), suggesting that slower processes may be hindering charge extraction⁵³.
(a,b) The optimized QE and C-V parameters of the PSC device.
In Fig. 13b, C-V graph shows a noticeable rising curve, which tells us quite a bit about what’s happening inside the PSC device. At low voltages (up to around 0.6 V), the capacitance stays low and stable, this is typical and indicates the device is in its depletion region, where very few charges are actively contributing. But as the voltage increases, especially near 0.7–0.8 V, the capacitance rises sharply. This usually means that a large number of charges are starting to accumulate, likely at the interfaces or within the active layer. The peak around 0.8 V suggests that the cell is reaching a point where it can’t store much more charge, possibly due to interface saturation or the holes and electrons movement in the perovskite layer.
Figure 14 clearly shows the current density vs voltage (J vs V) characteristics for the Ba₃PCl₃-based PSC device. This double absorber design really well balances J_SC and V_OC, enhancing overall efficiency. When we optimized factors like absorber thickness, defect density (both bulk and interface), resistivity, and temperature, we got a V_OC of 0.7059 V and a J_SC of 43.35 mA/cm². Plus, the Ba₃PCl₃-based PSC has a FF of 82.92%, which matches what we’ve seen in previous studies, as highlighted in Table 7. The significant improvement in J_SC is primarily attributed to the broader absorption spectrum and enhanced light harvesting ability of Ba₃PCl₃, as previously reported by Karna et al.²⁸. Furthermore, keeping the defect densities low in both the absorber bulk and at the interfaces helps minimize non-radiative recombination losses, just as Abbas et al. have also shown⁵⁴. By carefully tuning all these key factors together, the device achieves a combined improvement across all performance metrics, which matches well with the results seen in recent SCAPS-1D simulation studies⁵⁵. As the Ba₃PCl₃ has a small bandgap of 0.997 eV, which allows it to absorb a broad range of the solar spectrum, including infrared light. This wide absorption increases the number of photons converted into charge carriers (electrons and holes). As a result, more charge carriers contribute to the photocurrent. Therefore, the short-circuit current density (J_SC) is high due to enhanced light absorption and carrier generation.
The optimized J-V parameters on the PSC under the single and double ETL-based PSC device.
In conclusion, the transition to lead free perovskite solar cells, enabled by novel material combinations and advanced optimization strategies, demonstrates tremendous potential for the evolution of sustainable and high efficiency photovoltaic systems. In particular, the use of Ba₃PCl₃ with its wider bandgap, in combination with a suitable complementary lower bandgap material, enables more comprehensive solar spectrum absorption and, consequently, higher overall efficiencies. The optimized device configuration demonstrated excellent photovoltaic parameters, including a J_SC (short-circuit current) of 43.35 mA/cm², a V_OC of 0.71 V, a FF of approximately 82.92%, and a PCE equal to 25.38%. These outputs underscore the strong possibility of lead-free perovskite materials as a feasible alternative option to traditional MA based perovskite solar cells. Although provocation related to long-term stability and large-scale implementation persist, the findings presented here provide a better foundation for the future evolution of stable, more efficient, and environmentally benign solar energy solutions.
The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.
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The authors would like to thank University of Ghent, for providing SCAPS software.
Open access funding provided by Manipal University Jaipur. The authors declare that no funds, grants, or other financial support were received during the preparation of this manuscript.
Technology Innovation and Development Foundation, Indian Institute of Technology Guwahati, Guwahati, Assam, 781039, India
Sagar Bhattarai
Centre for Research Impact Outcome, Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, Punjab, 140401, India
Sagar Bhattarai
Department of ECE, Gauhati University, Guwahati, Assam, 781014, India
Roshni Banthia
Department of Nuclear and Renewable Energy, Ural Federal University Named After the First President of Russia Boris Yeltsin, Ekaterinburg, Russia, 620002
Abhinav Kumar
Department of Mechanical Engineering and Renewable Energy, Technical Engineering College, The Islamic University, Najaf, Iraq
Abhinav Kumar
Department of Physics, Yıldız Technical University, 34349, Istanbul, Turkey
Ahmet Sait Alali
Department of Physics and Material Science, Madan Mohan Malaviya University of Technology, Gorakhpur, 273010, India
D. K. Dwivedi
Department of Botany, Gauhati University, Guwahati, Assam, 781014, India
Bhaben Tanti
Department of Electronics and Communication Engineering, C. V. Raman Global University, Bhubaneswar, Odisha, 752054, India
Madhusudan Maiti
Department of Electronics and Communication Engineering, Manipal University Jaipur, Jaipur, Rajasthan, 303007, India
Suddhendu DasMahapatra
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S. Bhattarai and R. Banthia conducted the investigation and wrote the original draft. A. Kumar and A. S. Alali contributed to conceptualization, methodology, and writing – review & editing. D. K. Dwivedi performed formal analysis, software development, and project administration. M. Maiti contributed to investigation, analysis, and writing – review & editing. B. Tanti contributed by addressing reviewer comments, refining the analysis, and improving the overall quality of the manuscript. S. DasMahapatra supervised the work and contributed to conceptualization and writing – review & editing. All authors reviewed and approved the final manuscript.
Correspondence to Suddhendu DasMahapatra.
The authors declare no competing interests.
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Bhattarai, S., Banthia, R., Kumar, A. et al. Tailoring Ba₃PCl₃-based perovskite solar cells via multi-parameter optimization for high power conversion efficiency. Sci Rep 16, 4270 (2026). https://doi.org/10.1038/s41598-025-34494-2
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Received: 01 September 2025
Accepted: 29 December 2025
Published: 27 January 2026
Version of record: 30 January 2026
DOI: https://doi.org/10.1038/s41598-025-34494-2
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