Search Results (627)

Bifacial photovoltaic technology is made up of solar cells with the ability to generate electrical power on both sides of the cell (front and rear), consequently, they generate more energy in the same area compared to conventional or monofacial solar cells. The present work deals with the calculation of the energy yield using bifacial solar cells under the specific environmental conditions of Tampico, Tamaulipas, Mexico. Two configurations were compared: (1) tilted, optimized in height and angle, oriented to the south, and (2) vertically optimized in height, oriented east–west. The results were also compared with a standard monofacial solar cell optimally tilted and oriented south. The experimental data were acquired using a current–voltage (I-V) curve tracer designed for this purpose. This study shows that the vertically optimized bifacial solar cell produces similar electrical power to the conventional monofacial solar cell, with the benefit of maximum production in peak hours (8:30 and 16:30). In contrast, in the case of the inclined bifacial solar cell, about 26% more in the production of electrical power was reached. These results guide similar studies in other places of the Mexican Republic and regions with similar latitudes and climate. Full article

With a low surface recombination velocity, it is possible to increase the efficiency of solar cells as the thickness is decreased. A maximum appearing in the efficiency versus thickness curve is mostly due to the same trend in the short-circuit current versus thickness curve. The trend of the short-circuit current versus thickness curve will be clearly discussed based on the view of competition between generation and recombination rates near the rear surface. If surface passivation can be well introduced, the win-win situation for the material cost and efficiency can be achieved based on our results. Full article

In the world of solar technology, precisely extracting photovoltaic cell and panel parameters is key to efficient energy production. This paper presents a new metaheuristic algorithm for extracting parameters from photovoltaic cells using the functionality of the PID-based search algorithm (PSA). The research includes single-diode (SDM) and double-diode (DDM) models applied to RTC France, amorphous silicon (aSi), monocrystalline silicon (mSi), PVM 752 GaAs, and STM6-40 panels. Datasets from multijunction solar cells at three temperatures (41.5 °C, 51.3 °C, and 61.6 °C) were used. PSA performance was assessed using root mean square error (RMSE), mean bias error (MBE), and absolute error (AE). A strategy was introduced by refining PID parameters and relocating error calculations outside the main loop to enhance exploration and exploitation. A Lévy flight-based zero-output mechanism was integrated, enabling shorter extraction times and requiring a smaller population, while enhancing search diversity and mitigating local optima entrapment. PSA was compared against 26 top-performing algorithms. RTC France showed RMSE improvements of 0.67–2.10% in 3.35 s, while for the mSi model, PSA achieved up to 40.9% improvement in 5.57 s and 22.18% for PVM 752 in 8.52 s. PSA’s accuracy and efficiency make it a valuable tool for advancing renewable energy technologies. Full article

In the purpose of enhancing solar cell efficiency and sustainability, zinc selenide (ZnSe) and silicon (Si) play indispensable roles, offering a compelling combination of stability and transparency while also highlighting their abundant availability. This study utilizes the SCAPS_1D tool to explore diverse heterojunction setups, aiming to solve the nuanced correlation between key parameters and photovoltaic performance, therefore contributing significantly to the advancement of sustainable energy solutions. Exploring the performance analysis of heterojunction solar cell configurations employing ZnSe and Si elements, various configurations including SnO₂/ZnSe/p_Si/p⁺_Si, SnO₂/CdS/p_Si/p⁺_Si, TiO₂/ZnSe/p_Si/p⁺_Si, and TiO₂/CdS/p_Si/p⁺_Si are investigated, delving into parameters such as back surface field thickness (BSF), doping concentration, operating temperature, absorber layer properties, electron transport layer properties, interface defects, series and shunt resistance. Among these configurations, the SnO₂/ZnSe/p_Si/p⁺_Si configuration with a doping concentration of 10¹⁹ cm⁻³ and a BSF thickness of 2 μm, illustrates a remarkable conversion efficiency of 22.82%, a short circuit current density (J_sc) of 40.33 mA/cm², an open circuit voltage (V_oc) of 0.73 V, and a fill factor (FF) of 77.05%. Its environmentally friendly attributes position it as a promising contender for advanced photovoltaic applications. This work emphasizes the critical role of parameter optimization in propelling solar cell technologies toward heightened efficiency and sustainability. Full article

Organic photovoltaic (OPV) technology, namely, organic solar cells (OSCs), have garnered attention as a sustainable and adaptable substitute for traditional silicon-based solar panels. Their lightweight construction, adaptability with various substrates, and capacity for low-energy production techniques make them formidable contenders for sustainable energy applications. Nonetheless, due to the swift advancement of OPV technology, there is increasing apprehension that existing life cycle assessment (LCA) studies may inadequately reflect their environmental consequences. This review aggregates and assesses LCA research to ascertain the extent to which existing studies accurately represent the genuine sustainability of OPVs. This paper conducts a comprehensive analysis of materials, manufacturing processes, device architecture, and end-of-life pathways, identifying methodological deficiencies, emphasizing critical environmental performance metrics, and examining how conceptual product design can improve environmental results. The results highlight the necessity for standardized, transparent LCA frameworks adapted to the changing OPV landscape. Full article

We investigated monocrystalline passivated emitter rear contact cells for light- and elevated-temperature-induced degradation. Among the cell performance factors, a short current density results in a significant decrease in the short term. The quantum efficiency is also affected by carrier recombination-active defects, especially in the case of the reference cell, which has a decreased quantum efficiency across the wavelength, unlike the commercial cell. The front side of the cell has a diffuse hydrogen distribution, and it is related to LeTID. We observe how the hydrogen changes during each process and the changes in the profile during the degradation. The hydrogen appears to redistribute within the silicon wafer and saturate at a certain equilibrium state. The hydrogen distribution is correlated with the changes in the lifetime and, finally, short current density. Regeneration occurs depending on the hydrogen concentration within the emitter, and the closer the concentration is to saturation, the less degradation occurs. Full article

Perovskite solar cells (PSCs) are emerging as leading candidates for sustainable energy generation due to their high power conversion efficiencies and low fabrication costs. However, their performance remains constrained by non-radiative recombination losses primarily at grain boundaries, interfaces, and within the perovskite bulk that are difficult to characterize under realistic operating conditions. Traditional methods such as photoluminescence offer valuable insights but are complex, time-consuming, and often lack scalability. In this study, we present a novel Long Short-Term Memory (LSTM)-based deep learning framework for dynamically predicting dominant recombination losses in PSCs. Trained on light intensity-dependent current–voltage (J–V) characteristics, the proposed model captures temporal behavior in device performance and accurately distinguishes between grain boundary, interfacial, and band-to-band recombination mechanisms. Unlike static ML approaches, our model leverages sequential data to provide deeper diagnostic capability and improved generalization across varying conditions. This enables faster, more accurate identification of efficiency limiting factors, guiding both material selection and device optimization. While silicon technologies have long dominated the photovoltaic landscape, their high-temperature processing and rigidity pose limitations. In contrast, PSCs—especially when combined with intelligent diagnostic tools like our framework—offer enhanced flexibility, tunability, and scalability. By automating recombination analysis and enhancing predictive accuracy, our framework contributes to the accelerated development of high-efficiency PSCs, supporting the global transition to clean, affordable, and sustainable energy solutions. Full article

As photovoltaic (PV) installations expand globally, effective recycling of end-of-life crystalline silicon solar cells has become increasingly important, including the recovery of valuable metals such as silver (Ag) and aluminium (Al). Traditional nitric acid-based chemical leaching methods, although effective, present environmental challenges due to the generation of hazardous nitrogen oxide (NO_x) emissions. To address these concerns, this study investigated alternative hydrometallurgical leaching strategies. Two selective treatments (NaOH for Al, and NH₃ + H₂O₂ for Ag) and one simultaneous treatment (HNO₃ + H₂O₂) were evaluated for metal recovery efficiency. All methods demonstrated high recovery efficiencies, achieving at least 99% for both metals within 60 min. The investigated methods effectively suppressed NO_x emissions without compromising leaching efficiency. These findings confirm that hydrometallurgical leaching techniques incorporating hydrogen peroxide can achieve efficient and environmentally safer recovery of silver and aluminium from solar cells, providing valuable insights into the development of more sustainable recycling practices for photovoltaic waste management. Full article

Recently, research and development in the field of dye-sensitized solar cells has been actively advanced, as the technology constitutes a potential alternative to silicon-based photovoltaic devices. Modification of the molecular structure of the dye can enhance the adsorption on the TiO₂ surface, improve the light absorption capacity, suppress the charge recombination, increase the electron injection rate, and thereby improve the overall performance of the solar cell. Carbazole and phenothiazine are rigid heterocyclic compounds containing nitrogen as a heteroatom with large π-conjugated skeletons. Phenothiazine differs from carbazole by the presence of sulfur as an additional electron-rich heteroatom. The inclusion of this heteroatom in the structure of the compounds can indeed improve the electron-donating properties, affect the conjugation, and thus affect the optical, electronic, and electrochemical properties of the chromophores as a whole. The difference in planarity when comparing carbazole with phenothiazine can be useful from several points of view. The planar structure of carbazole increases the degree of conjugation and the electron transfer capacity, which can increase the photocurrent of the cell. The nonplanar structure of phenothiazine helps to prevent π-stacking aggregation. This review comprehensively summarizes the progress in the field of synthesis of organic dyes for solar cells with an emphasis on the comparative analysis of two electron-donating moieties, carbazole and phenothiazine. In addition, the review describes in detail the relationship between the structure of the compounds (dyes), their properties, and the performance of solar cells. Full article

The rising demand for sustainable energy solutions has spurred the development of advanced materials for photovoltaic devices. Among these, transparent conductive oxides (TCOs) play a pivotal role in enhancing device efficiency, particularly in silicon-based solar cells. However, the reliance on indium-based TCOs like ITO raises concerns over cost and material scarcity, prompting the search for more abundant and scalable alternatives. This study focuses on the fabrication and characterization of aluminum-doped zinc oxide (ZnO:Al, AZO) thin films deposited via Atomic Layer Deposition (ALD), targeting their application as transparent conductive oxides in silicon solar cells. The ZnO:Al thin films were synthesized by alternating supercycles of ZnO and Al₂O₃ depositions at 225 °C, allowing precise control of composition and thickness. Structural, optical, and electrical properties were assessed using Scanning Electron Microscopy (SEM), Energy-Dispersive X-ray Spectroscopy (EDS), Transmission Electron Microscopy (TEM), Raman spectroscopy, spectroscopic ellipsometry, and four-point probe measurements. The results confirmed the formation of uniform, crack-free ZnO:Al thin films with a spinel-type ZnAl₂O₄ crystalline structure. Optical analyses revealed high transparency (more than 80%) and tunable refractive indices (1.64 ÷ 1.74); the energy band gap was 2.6 ÷ 3.07 eV, while electrical measurements demonstrated low sheet resistance values, reaching 85 Ω/□ for thicker films. This combination of optical and electrical properties underscores the potential of ALD-grown AZO thin films to meet the stringent demands of next-generation photovoltaics. Integration of Zn:Al thin films into silicon solar cells led to an optimized photovoltaic performance, with the best cell achieving a short-circuit current density of 36.0 mA/cm² and a power conversion efficiency of 15.3%. Overall, this work highlights the technological relevance of ZnO:Al thin films as a sustainable and cost-effective alternative to conventional TCOs, offering pathways toward more accessible and efficient solar energy solutions. Full article

This study explored advancements in photovoltaic technologies by enhancing the electronic quality of multicrystalline silicon (mc-Si) through silicon nitride (SiN_x) and hydrogen (H₂) plasma deposition via plasma-enhanced chemical vapor deposition (PECVD). This innovative approach replaced toxic chemical wet processes with H₂ plasma and SiN_x. The key parameters of silicon solar cells, including the effective lifetime (τ_eff), diffusion length (L_diff), and iron concentration ([Fe]), were analyzed before and after this sustainable solution. The results show significant improvements, particularly in the edge region, which initially exhibited a low τ_eff and a high iron concentration. After the treatment, the τ_eff and L_diff increased to 7 μs and 210 μm, respectively, compared to 2 μs and 70 μm for the untreated mc-Si. Additionally, the [Fe] decreased significantly after the process, dropping from 60 ppt to 10 ppt in most regions. Furthermore, the treatment led to a significant decrease in reflectivity, from 25% to 8% at a wavelength of 500 nm. These findings highlight the effectiveness of the PECVD-SiN_x and H₂ plasma treatments for improving the optoelectronic performance of mc-Si, making them promising options for high-efficiency photovoltaic devices. Full article

Perovskite, as a promising candidate for the next generation of photovoltaic materials, has attracted extensive attention. To date, the power conversion efficiency (PCE) of perovskite solar cells (PSCs) has reached 26.7%, which is competitive with that of commercial silicon cells. However, high PCE is usually achieved in devices with a small surface area fabricated by the spin-coating method. Perovskite thin films, as the most important layer, suffer from poor uniformity and crystallization caused by the large-area fabrication process, which leads to a dramatic drop in efficiency and exhibits poor reproducibility. Here, we summarize common architectures of PSC and perovskite solar modules (PSMs), as well as analyzing the reasons for efficiency loss on the modules. Subsequently, the review describes the mechanism of perovskite growth in detail, and then sums up recent research on small-to-large-area perovskite devices. Large-area fabrication methods mainly include blade coating, slot-die coating, spray-coating, inkjet printing, and screen printing. Moreover, we compare the advantages and disadvantages of each method and their corresponding mechanisms and research progress. The review aims to provide potential logical conclusions and directions for the commercial large-area perovskite fabrication process. Full article

Solar photovoltaic (PV) technology has emerged as the most preferred source of clean energy generation and has been deployed at a large scale. However, end-of-life management of the PV modules is a critical issue that has garnered the recent attention of lawmakers and researchers alike. Consequently, several researchers are actively developing technology to recycle the end-of-life PV modules. Since silicon PV modules account for more than 90% of the modules deployed globally, most of these efforts are focused on recycling crystalline silicon PV modules. Researchers have primarily focused on recovering pure silver from the contacts and pure Si from the solar cells. However, to ensure complete recyclability of such panels, the different polymers used in these modules must also be recycled. This review addresses the issue of recycling the polymers from end-of-life c-Si modules. Scopus and Google Scholar were used to search for the relevant literature. This review presents the current state-of-the-art technology related to polymer recycling found in the PV modules, the challenges encountered in their recycling, and the outlook. While research on the recycling of polymers has progressed in the last few decades, the instances of their applications in the recycling of polymers from PV panels are rarely reported in the literature. In this work, certain technical pathways, which can be employed to recycled polymers obtained from end-of-life PV panels, are presented. Recycling the polymers from the end-of-life silicon PV modules is crucial for improving the sustainability of solar PV technology. Full article

The growing imperative for sustainable building retrofits has spurred significant interest in advanced photovoltaic (PV) solutions. This study evaluates the feasibility and competitiveness of incorporating CIGS thin-film photovoltaic (PV) modules into retrofit projects for aging buildings. By combining qualitative analyses of market and environmental factors with a quantitative multi-criteria index model, this research assesses CIGS performance across five critical dimensions: aesthetic, economic, safety, energy saving, and innovation. The weights assigned to each criterion were determined through expert evaluations derived from structured focus group discussions. The results demonstrate that CIGS exhibits substantial strengths in aesthetic, economic, safety, energy saving, and innovation while maintaining reasonable economic feasibility. The quantitative assessment demonstrated that CIGS thin-film solar cells received the highest overall score (88.92), surpassing silicon-based photovoltaics (86.03), window retrofitting (88.83), and facade cladding (82.21) in all five key metrics of aesthetics, economic feasibility, safety, energy efficiency, and innovation. The findings indicate that CIGS technology exhibits not only exceptional visual adaptability but also attains balanced performance with regard to environmental and structural metrics. This renders it a highly competitive and comprehensive solution for sustainable building retrofits. Full article

Optoelectronic devices, which combine optics and electronics, are vital for converting light energy into electrical energy. Various solar cell technologies, such as dye-sensitized solar cells (DSSCs), silicon solar cells, and perovskite solar cells, among others, belong to this category. DSSCs have gained significant attention due to their affordability, flexibility, and ability to function under low light conditions. The current research incorporates machine learning (ML) models to predict the performance of a modified Eu³⁺-doped Y₂WO₆/TiO₂ photo-electrode DSSC. Experimental data were collected from the “Dryad Repository Database” to feed into the models, and a detailed data visualization analysis was performed to study the trends in the datasets. The support vector regression (SVR) and Random Forest regression (RFR) models were applied to predict the short-circuit current density (J_sc) and maximum power (P_max) output of the device. Both models achieved reasonably accurate predictions, and the RFR model attained a better prediction response, with the percentage difference between the experimental data and model prediction being 0.73% and 1.01% for the J_sc and P_max respectively, while the SVR attained a percentage difference of 1.22% and 3.54% for the J_sc and P_max respectively. Full article