Solar RRL最新文献

The pursuit of efficient and environmentally sustainable photovoltaic technologies has intensified interest in lead-free perovskite solar cells (PSCs). This study presents a comprehensive theoretical study on a novel heterojunction device architecture integrating two active, nontoxic absorber layers: methylammonium tin iodide (MASnI₃) and antimony trisulfide (Sb₂S₃). Using the SCAPS-1D simulator under AM1.5G illumination, we systematically investigate the impact of critical device parameters, including layer thickness, doping concentrations, defect densities, and series resistance, on the device's optoelectronic performance. The optimized architecture, FTO/TiO₂/MASnI₃/Sb₂S₃/Spiro-OMeTAD/back-electrode, achieves a remarkable power conversion efficiency (PCE) of 30.84%, with a photocurrent density (J_SC) of 29.08 mA/cm², an open-circuit voltage (V_OC) of 1.22 V, and a fill factor (FF) of 87.15%. The inclusion of a 200 nm Sb₂S₃ layer not only broadens the absorption spectrum, especially in the longer wavelength region, but also enhances charge extraction through favorable band alignment. Additionally, the role of different low-cost hole transport layers was assessed (MoS₂, Cu₂O_x, NiO_x, and MoO_x), outperforming the conventional materials like Spiro-OMeTAD in terms of PCE and FF. Our results demonstrate that precise control of absorber's thickness, suppression of interfacial defects, and reduction of series resistance are key elements to achieving high-efficiency lead-free PSCs. Further analysis reveals that reducing interfacial defects and series resistance is crucial for maximizing efficiency while maintaining low defect density in the absorber layer is vital for device reliability.

The Copernicus Atmosphere Monitoring Service (CAMS) provides historical time series of global horizontal, beam normal, and diffuse horizontal irradiance in Europe, Africa, South America, and the Asia-Oceania region trough the CAMS Radiation Service (CRS). The CRS was widely validated and is routinely monitored on the basis of a large number of ground observation stations. Nevertheless, existing studies all derive average validation metrics, which can only be seen as typical, aggregated results. Users get no information about the uncertainty of the estimate at individual data points. This study systematically scans through a large database of deviations between the CRS irradiance estimates and ground-based irradiance observations. A look-up-table that describes the uncertainty of the CRS deviations is obtained by conditioning the cumulative distribution function of the deviations to the CRS model inputs. Parametric and nonparametric probabilistic representations of this uncertainty model are investigated. This model provides a probabilistic deviation for each value of the CRS estimate time series and at each geographical location. The uncertainty model shows very good calibration and sharpness metrics in all sky conditions as well as an average Continuous Ranked Probability Score of 50 W/m$��{}^2�$. Additionally, its very strong robustness against the selection of training stations is shown.

The increasing use of plug and play photovoltaic systems has raised concerns about their safety, especially with nonprofessional installations, which existing standards only partially address. This study proposes a black box testing approach to assess the personal safety of plug and play inverters. A total of 25 microinverters are assessed using three tests: (1) analyzing the residual voltage at the mains plug after disconnection, (2) the feed-in current increase under low grid voltage conditions, and (3) the maximum touch temperature during operation. Residual voltage testing reveals that 56% of the inverters comply with the limit of the latest official German plug and play system standard draft and behave similarly to other tested electrical devices. Further investigation is required to determine if exceeding this limit presents a direct safety risk. However, adding a relay was identified as an effective measure to ensure compliance. Under low voltage conditions, current increases up to 26.3% were measured, potentially stressing nondedicated circuits. In the temperature test, a positive correlation between the inverters power density and the touch temperature was found. The findings of this analysis provide insights for future standardization efforts and offer guidance to manufacturers in improving the safety of these PV systems.

Organic-thin film and perovskite solar cells are extremely promising because of their rapid progress in photovoltaic conversion efficiency (PCE). Beyond developing new materials and fabrication techniques, accurate performance characterization is essential for research and application. This study reports a round-robin interlaboratory comparison of current density–voltage (J–V) characteristics under standard test conditions (STC) and external quantum efficiency (EQE) spectra for large-area (>1 cm²) organic thin-film, perovskite, as well as reference solar cells with distinct spectral responses. Among 20 participating laboratories, the relative deviation in PCE of the samples reaches an unprecedented 111%. A comprehensive analysis identifies critical obstacles to measurement accuracy, including total incident irradiance for the samples, EQE spectrum measurements for spectral mismatch factors (SMM), temperature control, and methodologies for obtaining the J–V curves. Based on these findings, corresponding recommendations are presented to enhance the accuracy of performance characterization for emerging solar cells.

In this article, the long-term outdoor performance of inverted perovskite solar cells (PSCs) with glass–glass encapsulation is investigated over a 3-year period. Despite achieving initial power conversion efficiencies of >20%, the devices show significant degradation during summer months, particularly when surface temperatures exceed 50°C, with their internal cell temperatures increasing to ~90°C. Optical and scanning electron microscopy imaging reveal the formation of a high-resistance phase within the perovskite layer, particularly near the NiO_x interface, as the major degradation pathway. Indoor accelerated tests, conducted under heat and light conditions, replicate these effects, indicating the occurrence of thermally induced phase transitions. The measurement methodology also influences the degradation; devices measured with maximum power point tracking show slightly less deterioration than do those assessed via current–voltage curve tracing. Additionally, UV-cut filters show minimal benefits, likely owing to the inherent UV blocking feature of NiO_x. These findings underscore the critical role of thermal management and operational conditions in ensuring the stability of PSCs. Further improving the material design, encapsulation, and measurement protocols is essential for enhancing the outdoor reliability and commercial viability of PSCs.

The next-generation silicon photovoltaics will be based on passivating electron- and hole-selective contacts with both very low interface recombination and contact resistivities. While the emerging mainstream TOPCon technology has developed excellent electron-selective poly-Si/tunneling SiO_x contacts, hole-selective contacts, especially on textured surfaces, have remained a significant challenge. This contribution introduces novel high-performance hole selective poly-Si contacts on pyramid-textured Si, enabled by electrochemically produced hole transport nanopinholes in a 10 nm oxynitride passivating dielectric stack capped by p⁺ poly-Si. The highly passivating oxynitride layer is produced via atomic intermixing of O and N atoms in the initial SiO_x/SiN_y layer stack upon thermal annealing. Carrier transport is governed by nanopinhole density and size are tuned by Ag nanoparticle electrodeposition and surface attachment chemistries. This results in passivating hole contact resistivities in the mΩ-cm² range, while preserving interface recombination current prefactor around 5 fA/cm².

This work presents a novel framework for photovoltaic (PV) tracking optimization called dynamic tracking. Its core is a method of irradiance prediction using a machine learning surrogate model trained on ray tracer simulations. This approach outperforms ray tracing models in terms of computational speed while upholding accuracy for diffuse and direct irradiance. It is therefore able to predict irradiance distributions with a resolution of 11 × 11 cm² for all possible tilting configurations over a given weather time series in real time. Spatial and temporal validation under overcast and sunny conditions show that the network accurately reproduces direct and diffuse shading patterns under arbitrary weather conditions. The proposed framework simulates all possible tilt sequences for any single-axis tracking system over daily periods with a 10 min resolution in only 2 min. Using discrete dynamic programming, it then calculates the truly optimal tilting sequence with respect to average irradiation. This method predicts and avoids inter-row shading, thereby increasing yield and outperforming established strategies like backtracking or diffuse tracking methods for any weather condition.

Perovskite solar cells (PSCs) are regarded as the next-generation photovoltaic technology due to exceptional power conversion efficiency (PCE) and low fabrication costs. However, their multi-scale physical and chemical structures render empirically driven research paradigms inefficient, especially like trial-and-error approach. In recent years, classical machine learning methods based on big data have been widely applied in PSCs research, yet their effectiveness remains constrained by issues such as limited data quality, single modality of data, and insufficient generative capabilities. With the rapid advancement of artificial intelligence, particularly the rise of deep learning, reinforcement learning, and large language models, PSCs' research progressively transforms from a local data-driven to a global intelligence-driven paradigm. This review systematically summarizes recent progress in intelligence-driven methods for PSCs research, encompassing material design, process optimization, exploration of stability mechanisms, knowledge discovery, and self-driving experimentation. We further outline key points and current challenges of AI technologies in enhancing PCE, stability, and scalability of PSCs, aiming to accelerate the development from laboratory innovation to industrial application.

Tin perovskite solar cells (TPSCs) have attracted considerable research attentions as promising lead-free perovskite photovoltaics due to their ideal bandgap structure and excellent optical properties. However, the fast crystallization process, chemical instability, and high concentration of defective centers induce severe carrier recombination and affects the device performance. Therefore, effective passivation of this high concentration of defects is particularly critical to enhance their photovoltaic performance and stability. In this study, a π-conjugated molecule, 4-aminobenzonitrile (AZ) was introduced into the tin perovskite precursor. The interaction between AZ and Sn²⁺ can delay the crystal growth and achieve secondary crystallization. In addition, the introduction of para-amino group in AZ exhibited symmetrical electron cloud characteristics, which effectively reduces the recombination of defects in perovskite. A series of photophysical characterizations have proved that the defect concentration in the AZ film was significantly reduced, and the carrier separation and extraction were greatly improved. Finally, the device showed a power conversion efficiency enhancement from 9.77% to 11.09%, together with notably improved device stability.

In this work we present an optimized process for the photolithographic fabrication of inverted pyramid photonic crystals (PC) with 3.1 µm periodicity on Si(001)-substrates to improve the light trapping in single junction solar cells. Anisotropic alkaline etch was used to form the pyramids with (111)-sidewalls using partial surface masking with lithographically structured SiO₂. Ridge widths between the pyramids down to (150 ± 50) nm were achieved, while ensuring a yield of multiple (2 × 2) cm² areas per wafer sample. After deposition of an antireflection stack consisting of AlO_x, SiN_y, and SiO_z with different thickness optimizations a weighted reflection approaching that of a random pyramid reference sample could be shown. We demonstrate a path length enhancement of 25 at a wavelength of 1200 nm for our cell with PCs. This is en par with but not superior to the respective value for the reference sample with random pyramids, and still below the Lambertian limit. Furthermore, we present the first POLO²-IBC (interdigitated back contact) solar cells with such photonic crystals on the front sides. These solar cells feature a power conversion efficiency of 22.9%.