Search Results (635)

This work investigates the effect of interface traps on the impedance spectra of dopant-free silicon solar cells. The studied device consists of a crystalline silicon absorber with an a-Si:H/MoOx/ITO stack as the front passivating hole-collecting contact and an a-Si:H/LiF/Al stack as the rear passivating electron-collecting contact. Experimental measurements, including illuminated current–voltage (I–V) characteristics and impedance spectroscopy, were performed on the fabricated devices and after a soft annealing treatment. The annealed cells exhibit an increased open-circuit voltage and a larger Nyquist plot radius. To interpret these results, a numerical model was developed in a TCAD environment. Simulations reveal that traps located at the p/i interface (MoOx/i-a-Si:H) significantly affect the impedance spectra, with higher trap concentrations leading to smaller Nyquist plot circumferences. The numerical impedance curves were aligned to the experimental data, enabling extraction of the interfacial traps concentration. The results highlight the sensitivity of impedance spectroscopy to interfacial quality and confirm that the performance improvement after soft annealing is primarily due to reduced defect density at the MoOx/i-a-Si:H interface. Full article

The current–voltage (I-V) characteristic provides essential performance parameters of a solar cell, influenced by temperature and solar radiation. The efficiency of a solar cell is sensitive to variations in these conditions. This study electrically characterized a polycrystalline silicon solar cell in a solar simulator chamber at temperatures of 25–55 °C and irradiance levels of 600–1000 W/m². The acquired data were used to train and evaluate neural network models to predict the I-V characteristics of a polycrystalline silicon solar cell. Two recurrent neural network architectures were tested: LSTM and the GRU model. The performance of the model was assessed using MAE, RMSE, and R². The GRU model achieved the results, with MAE = $2.813\times {10}^{-3}$, RMSE = $5.790\times {10}^{-3}$, and R² = 0.9844, similar to LSTM (MAE = $2.6613\times {10}^{-3}$, RMSE = $5.858\times {10}^{-3}$, R² = 0.9840). These findings highlight the GRU network as the most efficient approach for modeling solar cell behavior under varying environmental conditions. Full article

In the last decades, small satellites such as CubeSats and PocketQubes have become popular platforms for scientific and applied missions in low Earth orbit (LEO). However, prolonged exposure to atomic oxygen, ultraviolet radiation, and thermal cycling in LEO leads to gradual degradation of onboard solar panels, reducing mission lifetime and performance. This study addresses the need to quantify and compare the degradation behavior of different solar cell technologies and protective coatings used in nanosatellites and pico-satellites. The aim is to evaluate the in-orbit performance of monocrystalline silicon (Si), gallium arsenide (GaAs), triple-junction (TJ) structures, and copper indium gallium selenide (CIGS) cells under varying orbital and satellite parameters. Telemetry data from recent small satellite missions launched after 2020, combined with numerical modeling in GNU Octave, were used to assess degradation trends. The models were validated using empirical mission data, and statistical goodness-of-fit metrics (RMSE, R²) were applied to evaluate linear and exponential degradation patterns. Results show that TJ cells exhibit the highest resistance to LEO-induced degradation, while Si-based panels experience more pronounced power loss, especially in orbits below 500 km. Furthermore, smaller satellites (<10 kg) display higher degradation rates due to lower thermal inertia and limited shielding. These findings provide practical guidance for the selection of solar cell technologies, anti-degradation coatings, and protective strategies for long-duration CubeSat missions in diverse LEO environments. Full article

Recent advances in prefabricated construction have enabled modular systems offering structural performance, rapid assembly, and design flexibility. Textile Ceramic Technology (TCT) integrates ceramic elements within a stainless-steel mesh, creating versatile architectural envelopes for façades, roofs, and pavements. This study investigates the integration of silicon photovoltaic (PV) modules into TCT to develop an industrialized Building-Integrated Photovoltaics (BIPV) system that maintains energy efficiency and visual coherence. Three full-scale solar brick prototypes are presented, detailing design objectives, experimental results, and conclusions. The first prototype demonstrated the feasibility of scaling small silicon PV units with good efficiency but limited aesthetic integration. The second embedded PV cells within ceramic bricks, improving aesthetics while maintaining electrical performance. Durability tests—including humidity, temperature cycling, wind, and hail impact—confirmed system stability, though structural reinforcement is needed for impact resistance. The third prototype outlines future work focusing on modularity and industrial scalability. Results confirm the technical viability of silicon PV integration in TCT, enabling active façades that generate renewable energy without compromising architectural freedom or aesthetics. This research advances industrialized, sustainable building envelopes that reduce environmental impact through distributed energy generation. Full article

Perovskite/Si tandem solar cells (PSTSCs) have emerged as a leading candidate for surpassing the Shockley–Queisser (SQ) efficiency limit inherent to single-junction silicon solar cells. Following their inaugural demonstration in 2015, perovskite/Si tandem solar cells have experienced remarkable technological progression, reaching a certified power conversion efficiency of 34.9% by 2025. To elucidate pathways for realizing the full potential of perovskite/Si tandem solar cells, this review commences with an examination of fundamental operational mechanisms in multi-junction photovoltaic architectures. Subsequent sections systematically analyze technological breakthroughs across three critical PSTSC components organized by an optical path sequence: (1) innovations in perovskite photoactive layers through component engineering, additive optimization, and interfacial modification strategies; (2) developments in charge transport and recombination management via advanced interconnecting layers; and (3) silicon subcell architectures. The review concludes with a critical analysis of persistent challenges in device stability, scalability, structural optimization and fabrication method, proposing strategic research directions to accelerate the transition from laboratory-scale achievements to commercially viable photovoltaic solutions. Full article

The damage characteristics of monocrystalline silicon solar cells irradiated by a nanosecond pulsed laser were investigated in a vacuum environment. An 8 ns pulsed laser was used with a 1064 nm wavelength, a 2.0 J maximum pulse energy, and a millimeter-scale ablation spot diameter. The cells were irradiated by a laser with varying fluences, irradiation positions, and pulse numbers. The damage mechanism was discussed in combination with the degradation of electrical properties, the morphology of surface damage, and electroluminescence images. A single pulse mainly caused surface heating and deformation, while multi-pulse irradiation led to the formation of melting ablation craters. More severe performance degradation was caused by irradiation at the grid line site due to fracture of the grid line electrodes. Moreover, monocrystalline silicon cells showed excellent damage resistance to fixed-position irradiations at non-gridded line areas. This work reveals, for the first time in vacuum, that grid-line fracture dominates performance degradation—enabling targeted hardening for space solar cells. Full article

Transparent conductive aluminum-doped zinc oxide (AZO) films were investigated as potential recombination layers for perovskite/silicon tandem solar cells, comparing the results of atomic layer deposition (ALD) and magnetron sputtering (MS) on vertically aligned silicon nanowire (SiNW) scaffolds. Conformality and thickness control were examined by cross-sectional SEM/TEM and profilometry, revealing fully conformal ALD coatings with tunable thicknesses (40–120 nm) versus tip-capped, semi-uniform MS films (100–120 nm). Optical transmission measurements on glass substrates showed that both 120 nm ALD and MS layers exhibit interference maxima near 450–500 nm and 72–89% transmission across 800–1200 nm; the thinnest ALD films reached up to 86% near-IR transparency. Four-point probe analysis demonstrated that ALD reduces surface resistance from 1150 Ω/□ at 40 nm to 245 Ω/□ at 120 nm, while MS layers achieved 317 Ω/□ at 120 nm. These results delineate the balance between conformality, transparency, and conductivity, providing design guidelines for AZO recombination interfaces in next-generation tandem photovoltaics. Full article

The present study investigates dye-sensitized solar cells (DSSCs) incorporating natural extracts from the microalgae Spirulina and Chlorella as photosensitizers. TiO₂-based electrodes were prepared and immersed in methanolic algae extracts for 24 and 48 h. UV–Vis spectroscopy revealed absorption peaks near 400 nm and 650 nm, characteristic of chlorophyll. Electrochemical analyses, including photochronoamperometry and open-circuit potential, confirmed the photosensitivity and charge transfer capabilities of all systems. The cell sensitized with Chlorella after 48 h of immersion exhibited the highest energy conversion efficiency (0.0184% ± 0.0015), while Spirulina achieved 0.0105% ± 0.0349 after 24 h. Chlorella’s superior performance is attributed to its higher chlorophyll content and enhanced light absorption, facilitating more efficient electron injection and interaction with the TiO₂ surface. Although the efficiency remains lower than that of conventional silicon-based solar cells, the results highlight the potential of natural colorants as sustainable and low-cost alternatives for photovoltaic applications. Nonetheless, further, improvements are required, particularly in dye stability and anchorage, to improve device performance. This research reinforces the viability of natural photosensitizers in DSSC technology and supports continued efforts to optimize their application. Full article

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