Solar Cell Parameters Research Articles

Study of the Photovoltaic Parameters of Inorganic Solar Cells Based on Cu<i>2</i>O and CuO

A theoretical study of the photovoltaic parameters of inorganic solar cells based on ZnO/Cu2O and ZnO/CuO heterojunctions was carried out to improve the energy conversion efficiency. The influence of the thickness, charge carrier concentration and band gap of Cu2O and CuO films, as well as ZnO, on the photovoltaic parameters of solar cells has been studied. The simulation results showed that the efficiency of solar cells is significantly affected by the contact potential difference, the diffusion length of minority charge carriers, the amount of generated photocurrent and the recombination rate. The maximum efficiency of a solar cell based on ZnO/Cu2O was obtained equal to 10,63%, which is achieved with a band gap, thickness and charge carrier concentration in Cu2O equal to 1.9 eV, 5 μm and 1015 cm–3 and band gap, thickness and the concentration of charge carriers in ZnO is equal to 3,4 eV, 20 nm and 1019 cm–3, as well as the displacement of the edges of the conduction bands is 0.8 eV. For a solar cell based on ZnO/CuO, a maximum efficiency of 18.27% was obtained with a band gap, thickness and charge carrier concentration in CuO equal to 1.4 eV, 3 μm and 1017 cm–3, as well as a displacement of the conduction band edges of 0.03 eV. The obtained results of modeling solar cells can be used in the design and manufacture of inexpensive and efficient photovoltaic structures.

A Comprehensive Approach to Optimization of Silicon-Based Solar Cells

In this work, we report a detailed scheme of computational optimization of solar cell structures and parameters using PC1D and AFORS-HET codes. Each parameter’s influence on the properties of the components of heterojunction silicon-based solar cells (HIT) has been thoroughly examined. The proposed approach follows a stringent sequence of steps to optimize various parameters of the studied HITs. Furthermore, we have revealed the effects of the metal-semiconductor contact, and a model of a photocell with an ohmic contact and a Schottky contact has been simulated. The optimal model of HIT for available materials has been proposed and fabricated based on the results of these simulations. A comparison of predicted and measured performance unequivocally demonstrates the efficiency of the proposed scheme in developing silicon-based HITs, providing reassurance about its practical application.

Performance optimization of MA0.5FA0.5PbI3/CsPbI3 based hybrid perovskite solar cell emphasizing on double absorber layer

Abstract The utilization of cesium-based lead halide (CsPbI3) PSC has considerable potential in the photovoltaic industry due to their high efficiency, underpinned by features such as a high absorption coefficient, thermal stability, and commendable efficiency. Nevertheless, the bandgap of CsPbI3, standing at 1.7 eV, poses a challenge as it is relatively high for a single-junction device. To overcome this limitation, we introduced a dual absorber layer structure by interleaving CsPbI3 with a lead-based hybrid perovskite material, denoted as MA0.5FA0.5PbI3. This investigation focused on the MA0.5FA0.5PbI3/CsPbI3 hetero-junction structure to ascertain the maximum possible efficiency. Therefore, this study proposed a PSC with the configuration of Ag/MoO3/MA0.5FA0.5PbI3/CsPbI3/IGZO/Au. In this setup, MoO3 (Molybdenum Trioxide) is used as the HTL and IGZO (Indium Gallium Zinc Oxide) as the ETL. Silver (Ag) serves as the back contact and gold (Au) is the front contact. This device demonstrated remarkable characteristics with Voc = 1.307 V, Jsc = 22.71 mA cm−2, FF = 86.58%, and η = 26.21%, showcasing a substantial improvement compared to previously reported CsPbI3-based homojunction PSCs. Furthermore, this study delved into the effects of absorber doping, absorber material thickness, bulk defect, and interfacial defects on solar cell parameters to obtain high-performance solar cells.

Application of improved Jellyfish search algorithm for 9-parameters cell extraction and GMPPT in PV systems

Optimization algorithms are essential tools used to address real-world problems through minimization or maximization processes. In the context of photovoltaic (PV) systems, various optimization algorithms have been employed to extract solar cell parameters using minimization techniques, and to identify the maximum power point (MPP) using maximization approaches. However, under partial shading conditions or during rapidly changing irradiance, many of these algorithms tend to get trapped in local minima, failing to locate the global maximum power point (GMPPT). This shortcoming leads to significant energy losses from PV cells. Similarly, the extraction of solar cell parameters is often compromised by the random search behavior and inadequate exploration and exploitation capabilities of many existing algorithms. The Jellyfish Search Optimization (JSO) algorithm is a recent, parameter-free method developed to tackle a wide range of optimization problems. Despite its innovative design, JSO is prone to premature convergence and exhibits a longer convergence time. To address these limitations, this paper proposes a modified version of the JSO algorithm, which integrates the state-of-the-art features of JSO with the Lévy flight characteristic from the cuckoo search algorithm. This combination aims to achieve a better balance between exploration and exploitation. To validate the effectiveness of the proposed Improved Jellyfish Search Optimization (IJSO) algorithm in PV systems, extensive experiments were conducted. These experiments included benchmarking with complex test functions, extracting cell parameters using various solar cell models, and maximizing energy output from PV systems under different environmental conditions. The results demonstrate that the proposed IJSO algorithm effectively enhances parameter extraction and global maximum power point tracking, making it a promising solution for optimizing energy extraction from PV cells in dynamic conditions.

Performance optimization of FASnI3 based perovskite solar cell through SCAPS-1D simulation

The article provides a detailed look at the fabrication of a high-performance structure for FASnI3-based perovskite solar cells (PSCs). The FTO/CeO2/FASnI3/CuI/Au structure is designed using the Solar Cell Capacitance Simulator in One Dimension (SCAPS-1D) to investigate the fabricated PSC's performance. This investigation's main objective is to improve PSCs performance by using non-traditional Hole transport layer (HTL) and Electron transport layer (ETL) materials, such as CeO2 and CuI, which have both been the subject of limited research. Moreover, the investigation seeks to determine the impact of several perovskite layer characteristics, including bandgap (Eg), electron affinity (χ), acceptor density (NA), thickness (t), and defect density (Nt). Additionally, this study also investigates the effect of various back contact work functions. Significant improvements in solar cell parameters, such as power conversion efficiency (PCE) from 22.06% to 24.87% and current density (Jsc) from 26.0274 to 30.675 mA/cm2, were observed by optimizing the device's parameters. In contrast, the fill factor (FF) and open circuit voltage (Voc) decreased their values from 86.13% to 87.10% and 0.9843 to 0.9308 V, respectively. These findings show that our designed solar cell structure performs better than those with conventionally used HTLs and ETLs. Consequently, this study highlights the potential benefits of lead-free PSCs and presents fresh opportunities for their development and use in various solar applications.

A more accurate Co-Content function calculation, using alternative integration methods, for Current–Voltage curves measured in the zero volt to open-circuit voltage range

AbstractIn this article, the application of the Newton–Cotes quadrature formula, the 3/8 rule, the Boole’s rule, and order 5 and 6 integration techniques, are explored to more accurately calculate the Co-Content function, of Current–Voltage (IV) measurements done between 0 V and the open circuit voltage, which include a percentage noise of the short circuit current. Their impact on the extraction of the five photovoltaic devices’ parameters (within the one-diode model) is investigated and reported. The shunt resistance, series resistance, ideality factor, and photocurrent can be obtained with less than 10% error, using these integration techniques and 101 measured points per volt, when the percentage noise is 0.05% or less, of the short circuit current. It is not possible to obtain the saturation current with less than 10% error. These integration techniques are implemented in photovoltaic devices, such as solar cells and single-crystalline silicon, CdTe, CIGS, and heterojunction with intrinsic thin-layer solar panels IV curves, to extract the five solar cell parameters.

Machine learning-assisted SCAPS device simulation for photovoltaic parameters prediction of [formula omitted] perovskite solar cells

Perovskite solar cells (PSCs) have garnered significant research attention because of their remarkable surge in power conversion efficiency (PCE) surpassing 26% within a short timeframe. However, the widespread adoption of these highly efficient PSCs is hampered by the inherent toxicity associated with lead (Pb)-based perovskites, which currently dominate the field. Researchers have explored alternative cations like Ge2+ and Sn2+ Owing to their identical oxidation states to Pb2+, paving the way for lead-free PSC development. By examining the critical factors influencing CsSnI3 thin film solar cells’ performance as well as their interdependencies, this work seeks to improve the efficiency of these devices. To do so, machine learning algorithms (ML) are employed to figure out the critical factors influencing the completion of CsSnI3 solar cells. A new dataset of 7870 data points is generated through simulations with SCAPS-1D to effectively depict the perovskite solar cell. Five ML regression algorithms are thereafter utilized to predict the photovoltaic parameters of solar cells, such as the fill factor (FF), open circuit voltage (VOC), short circuit current (JSC), and PCE. The study shows that random forest (RF) and decision tree (DT) are the best performing algorithms, among which DT produces high accuracy and low error for predicting the PCE with a coefficient of determination R2 of 0.99, Pearson’s coefficient (Rvalue) of 0.99, Spearman’s correlation coefficient (ρ) of 0.99 and root mean square error of 0.08 on the testing set. Finally, this study offers valuable guidance for further experiment optimization by shedding light on the optimal device dimensions and essential components.

Simultaneously Optimizing Molecular Stacking and Phase Separation via Solvent‐Solid Hybrid Additives Enables Organic Solar Cells with over 19% Efficiency†

Comprehensive SummaryGiven the crucial role of film morphology in determining the photovoltaic parameters of organic solar cells (OSCs), solvent or solid additives have been widely used to realize fine‐tuned film morphological features to further improve the performance of OSCs. However, most high‐performance OSCs are processed only using single component additive, either solvent additive or solid additive. Herein, a simple molecular building block, namely thieno[3,4‐b]thiophene (TT), was utilized as the solid additive to coordinate with the widely used solvent additive, 1‐chloronaphthalene (CN), to modulate the film morphology. Systematical investigations revealed that the addition of TT could prevent the excessive aggregation to form a delicate nanoscale phase separation, leading to enhanced charge transport and suppressed charge recombination, as well as superior photovoltaic performance. Consequently, the PM6:Y6 based OSCs with the addition of hybrid additive of CN + TT demonstrated the optimal PCE of 18.52%, with a notable FF of 79.6%. More impressively, the PM6:Y6:PC71BM based ternary OSCs treated with the hybrid additives delivered a remarkable efficiency of 19.05%, which ranks among the best values of Y6‐based OSCs reported so far. This work highlights the importance of the hybrid additive strategy in regulating the active layer morphology towards significantly improved performance.

A combined DFT and finite difference simulation study on hybrid halide perovskite-based solar cells

This work reports the modelling and numerical estimation of the photovoltaic parameters of perovskite solar cells (PSCs) containing formamidinium lead iodide (FAPbI3) and formamidinium tin iodide (FASnI3) in the form of light active materials using SCAPS 1D software. The analysis is done by introducing diverse hole and electron transport materials and back metal contacts to identify the most appropriate device configuration that can deliver optimum photovoltaic output. The optoelectronic properties and the absorption spectra of the two compounds are estimated by DFT calculation using WIEN2k, which incorporates density functional theory (DFT) principles and are provided as input to SCAPS 1D to improve the accuracy of modelling study. For FAPbI3 as absorber material, the configuration FTO/IGZO/FAPbI3/NiO/Au shows the highest photovoltaic parameter exhibiting a power conversion efficiency (PCE) and fill factor (FF) of 19.75 % and 74.29 % respectively. With FASnI3 as the absorber material, FTO/PCBM/FASnI3/P3HT/Au gives a PCE and FF of 21.6 % and 67.74 % respectively. The work also includes the analysis of influence of defect density at the interface layers and series and shunt resistance on performance of above-mentioned device architectures to identify their limitations under real experimental conditions. The influence of various attributes of perovskite on the performance of the device is examined to determine their optimum values.

Fabrication of cost-effective lead-free silver bismuth iodide based mesoscopic Rudorffite solar cells

Lead-free Ag–Bi–I Rudorffite materials, specifically AgBiI4, Ag2BiI5, Ag3BiI6 and AgBi2I7, have garnered substantial attention as prospective alternatives to lead halide perovskites in solar cell technology. Rudorffite-based solar cells have conventionally employed a mesoporous structure, integrating unstable and costly hole-transport layers (HTLs) in conjunction with noble metal electrodes. This study presents carbon-based, all-inorganic AgBiI4, Ag2BiI5, Ag3BiI6 and AgBi2I7 Rudorffite solar cells that circumvent the need for HTLs and noble metal electrodes. The absorber layers composed of AgBiI4, Ag2BiI5, Ag3BiI6 and AgBi2I7 materials were synthesized via melt-solidification. Notably, Ag2BiI5 based solar cell achieved PCE of 0.93 % among all the Silver Bismuth Iodide (SBI) devices which is the highest efficiency reported for Ag2BiI5 solar cell to date. The corresponding solar cell parameters include an open-circuit voltage (Voc) of 0.634 V and a short-circuit current (Jsc) of 3.63 mA/cm2. Consequently, our work presents a pathway toward developing Rudorffite solar cells with simplified fabrication methods and reduced cost.

Characterization of rear-side potential-induced degradation in bifacial p-PERC solar modules

Bifacial solar modules are increasingly preferred over monofacial modules to maximize the solar power output within a limited space. Owing to their high efficiency and compatibility with existing production lines, bifacial p-type passivated emitter and rear contact (p-PERC) solar modules have dominated the market since their commercialization. This study analyzes the influence of Al2O3, a passivation layer of p-PERC solar cells, on the PID and its underlying mechanism. Experiments were conducted on bifacial p-PERC module samples to analyze their electrical properties. Additionally, cell-like samples were fabricated to measure characteristics, for example, carrier lifetime, that are difficult to assess in full modules. To accelerate module degradation, experiments were conducted at 85 °C and 85 % humidity, while a voltage of −1000 V was applied to investigate the PID phenomenon. The results reveal degradation at the rear of the module caused by polarization effects, which were confirmed through changes in solar cell parameters and recombination current. The proposed mechanism indicates that the degradation in bifacial p-PERC solar modules is caused by the field-effect deterioration of the Al₂O₃ layer caused by alkali ions diffusing from the glass. This is observed through changes in the carrier concentration within Si and the detection of alkali ions within Al2O3. Our analysis considers both module and cell structure samples to delineate the influence of Al2O3 on the PID, which has not been previously reported. This study enhances the understanding of the polarization effect in bifacial p-PERC solar cells, thus contributing to the advancement of solar cell passivation strategies.

Current matching and filtered spectrum analysis of wide-bandgap/narrow-bandgap perovskite/CIGS tandem solar cells: A numerical study of 34.52 % efficiency potential

Perovskite (PVK) materials with wide-bandgap (WBG) play a crucial role in achieving high-performance tandem devices but phase segregation and open-circuit voltage (VOC) loss hinders in surpassing the efficiency of single-junction solar cells. Present work discloses a numerical simulation which has been carried out using a WBG material CH3NH3PbI3-xClx of bandgap (Eg) 1.65eV as an absorber layer of the top cell (TCELL) and a Cu(In,Ga)Se2-based cell having narrow-bandgap (NBG) of Eg (1.27eV) has been used as bottom cell (BCELL). The TCELL utilizes polyethyleneimine ethoxylated (PEIE) interfacial layer to promote charge-collection and charge-tunneling. The TCELL and BCELL have been optimized by various optimization processes such as simultaneous thickness variation of active-region with defect density (DD), variation of interface defect density (IDD) with solar-cell parameters a commendable power conversion efficiency (PCE) of 27.06 %, and 26.77 % has been achieved for respective solar-devices. Variations of numerous electron transport layer (ETL) and hole transport layer (HTL) have also been performed to acquire highly optimized TCELL. Thus, a perovskite/CIGS tandem solar cell (PVK/CIGS-TSC) device has been obtained using filtered-spectra analysis and current-matching (method which display a promising photovoltaic (PV) parameter with a high VOC of 2.29 V, short-circuit current density (JSC) of 17.41 mA/cm2, fill factor (FF) of 86.45 % and PCE of 34.47 %. These discoveries hold significant promise for the future development of TSCs.

Voltage root mean square error calculation for solar cell parameter estimation: A novel g-function approach

The existing research on estimating solar cell parameters mainly focuses on minimizing the Root-Mean-Square Error (RMSE) between the estimated and measured current values of solar cells (referred to as the RMSEI). This involves using an analytical expression for current - I as a function of voltage - U (I = f1(U)) expressed through the Lambert W function. This paper introduces a new analytical solution for calculating the RMSE between measured and estimated solar cell voltages (referred to as the RMSEU). The formula is derived using the g-function or LogWright function, which provides a numerically applicable method for representing the analytical relation between solar cell voltage and current (U = f2(I)). Moreover, the paper presents the original formulas for calculating Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) for solar cell voltages expressed through the g-function. The paper also compares various published approaches and examines two well-known solar cells/modules, namely the RTC France solar cell and the SOLAREX MSX–60 PV solar module, in terms of the RMSEU and single-diode solar cell models. Additionally, a novel metaheuristic algorithm, known as the Chaotic Walrus Optimization Algorithm (Chaotic-WaOA), is proposed for solar cell parameter estimation. This algorithm is applied to both mentioned solar cells to determine their parameters in terms of minimal RMSEU. In order to verify the proposed research, experimental observations were conducted on a 60Wp monocrystalline solar module installed at the Faculty of Sciences and Mathematics in Niš, Serbia. This was done using a specialized PV-KLA apparatus under different outdoor conditions. The research was also verified with a Cadmium telluride solar module (CdTe75638) and a multi-crystalline silicon solar module (mSi0188). The investigation results demonstrate the accuracy, applicability, and numerical feasibility of the proposed RMSE expression and algorithm. Additionally, the study confirms the applicability of the g-function in invertible solar cell modeling.

Energy Yield Modeling of Perovskite–Silicon Tandem Photovoltaics: Degradation and Total Lifetime Energy Yield

This study investigates the impact of degradation in perovskite‐silicon tandem solar cells by means of energy yield (EY) modelling over the entire lifetime. First, we assess the impact on EY of degradation in the individual solar cell parameters of the perovskite top cell. Our analysis reveals that degradation in fill factor, due to a decline in perovskite top cell shunt resistance (RSh), has the most severe impact on the EY, emphasizing the imperative to rectify perovskite imperfections in thin film processing causing RSh decline. Second, we investigate implications of degradation in the perovskite top cell on the EY of current mismatched tandem solar cells. Third, we examine critical thresholds for the “acceptable degradation levels” in the perovskite top cell with regard to degradation in each solar cell parameter, assuming that the total loss in EY must be comparable to the degradation in state‐of‐the‐art silicon. Overall, our study highlights that degradation of the perovskite top cell needs to be assessed with care when extrapolating the impact on the lifetime EY of perovskite‐silicon tandem solar cells. The severity of degradation for different degradation mechanisms in a single junction perovskite solar cell cannot be translated one‐to‐one to tandem devices.

Optimization of critical input parameters for dye-sensitized solar cells (DSSCs) to achieve high efficiency

Optimization of critical input parameters for dye-sensitized solar cells (DSSCs) to achieve high efficiency

SILAR deposition and characterization of ZnO films for numerical investigation as electron transport layer in solar cells

The SILAR method of thin film deposition has attracted the scientific community over the years due to its easiness, low cost, availability of room temperature deposition, and more over due to the variation in properties of thin films available by varying deposition parameters.This work is carried out in a way to comprehensively compare two ZnO thin film samples prepared from precursor media with Zinc Acetate (S1) and Zinc Chloride(S2) salts deposited by SILAR method in Perovskite Solar cell applications. The XRD, FTIR, Raman, FESEM, and UV-Visible analysis were carried out for identifying the structural, morphological, and optical quality of these samples. The role of these samples as Electron Transport Layer (ETL) in Perovskite Solar cell were identified using General purpose PhotoVoltaic Device model (GPVDM) simulation software which is well adapted for studying Solar cell architecture. It provided the output Solar cell parameters like Jsc, Voc, FF, PCE, etc and by varying the active layer and Hole Transport Layer (HTL) thicknesses, the optimized efficiency of devices with samples S1 and S2 were obtained as 21.88% and 21.96%.The results showed that SILAR-synthesized ZnO thin films could be potential candidates for ETL applications in Perovskite Solar cells.

Crystalline silicon solar cell with an efficiency of 20.05 % remanufactured using 30 % silicon scraps recycled from a waste photovoltaic module

Several studies have aimed to develop methods for recycling and recovering valuable materials from waste photovoltaic (PV) modules to keep up with the increasingly stringent waste disposal guidelines. However, silicon (Si) recovered from disposed PV modules is rarely used as a raw material in the solar industry. In this study, 30 % Si recovered from waste PV modules was added to a feedstock to grow a 6inch single-crystalline Si ingot using the Czochralski method. The single-crystalline Si ingot was re-melted and manufactured to produce a higher quality single-crystalline Si ingot with a minority carrier lifetime of 274–1527 μs and purity of 7N7. Thereafter, a Si wafer was manufactured via cropping, squaring, and wafering. Finally, the Si wafer was used to fabricate a solar cell via a conventional process. Solar cell parameters, such as open circuit voltage, short circuit current density, fill factor, and efficiency, were analyzed using a solar simulator. The manufactured solar cell had an efficiency of 20.05 %, which is approximately 0.97 % lower than that of commercial wafer-based solar cells. Moreover, the factors influencing the solar cell efficiency were evaluated.

(Invited) Parameter Prediction in Colloidal Quantum Dot Solar Cells Using Residual Neural Networks Trained on Experimental Data

Colloidal quantum dots (CQDs) are an attractive third-generation material for photovoltaics, especially as infrared materials for multi-junction solar cells. Characterization and materials parameter prediction both play a critical role in the rising efficiencies in this field. However, there are numerous materials properties that need to be measured in order to fully characterize a device, leading to high research costs and slow development times. Here, we leverage recent advancements in machine learning (ML), along with a recently-demonstrated multimodal spectral characterization method [1], to predict complex materials parameters in CQD solar cells from simple current density-voltage (JV) curves, using an algorithm trained on experimental data.[2]Past work ML prediction of materials properties has focused on using simulated data due to the difficulty in collecting enough experimental data to fully train an algorithm. While it is not feasible to fabricate thousands of devices in a typical research lab, it is possible to measure several thousand points on a single device. We used a micrometer-resolution 2D characterization method with millimeter-scale field of view to acquire enough training data using only a handful of devices, while learning the spatial relationships between materials parameters. Photoluminescence, trap state density, transient photovoltage, transient photocurrent, and carrier mobility were predicted (Figure 1) by five different residual neural networks, each using a ResNet block and containing over 300k learnable parameters. The design of the networks were based on the ResNet50 architecture [3]. We also implemented a novel neighborhood approach to reduce errors and account for spatial correlations in device behavior, leading to insights into transport mechanisms and correlation lengths in CQD thin films. This method could be used to study a wide range of material systems and devices, ultimately leading to a universal prediction model that greatly simplifies the characterization process for optoelectronic devices and accelerates development times.

Study of the Photovoltaic Parameters of Inorganic Solar Cells Based on Cu2O and CuO

Study of the Photovoltaic Parameters of Inorganic Solar Cells Based on Cu2O and CuO

NiOx Passivation in Perovskite Solar Cells: From Surface Reactivity to Device Performance.

Nonstoichiometric nickel oxide (NiOx) is one of the very few metal oxides successfully used as hole extraction layer in p-i-n type perovskite solar cells (PSCs). Its favorable optoelectronic properties and facile large-scale preparation methods are potentially relevant for future commercialization of PSCs, though currently low operational stability of PSCs is reported when a NiOx hole extraction layer is used in direct contact with the perovskite absorber. Poorly understood degradation reactions at this interface are seen as cause for the inferior stability, and a variety of interface passivation approaches have been shown to be effective in improving the overall solar cell performance. To gain a better understanding of the processes happening at this interface, we systematically passivated specific defects on NiOx with three different categories of organic/inorganic compounds. The effects on NiOx and the perovskite (MAPbI3) deposited on top were investigated using X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), and scanning electron microscopy (SEM). Here, we find that the perovskite's structural stability and film formation can be significantly affected by the passivation treatment of the NiOx surface. In combination with density functional theory (DFT) calculations, a likely origin of NiOx-perovskite degradation interactions is proposed. The surface passivated NiOx layers were incorporated into MAPbI3-based PSCs, and the influence on device performance and operational stability was investigated by current-voltage (J-V) characterization, impedance spectroscopy (IS), and open circuit voltage decay (OCVD) measurements. Interestingly, we find that a superior structural stability due to interface passivation must not relate to high operational stability. The discrepancy comes from the formation of excess ions at the interface, which negatively impacts all solar cell parameters.