Search Results (234)

Perovskite solar cells (PSCs) leverage the exceptional photoelectric properties of perovskite materials, yet interfacial energy level mismatches limit carrier extraction efficiency. In this work, energy level alignment was exploited to reduce the charge transport barrier, which can be conducive to the transmission of photo-generated carriers and reduce the probability of electron–hole recombination. We designed a dual-transition perovskite solar cell (PSC) with the structure of FTO/TiO₂/Nb₂O₅/CH₃NH₃PbI₃/MoO₃/Spiro-OMeTAD/Au by finite element analysis methods. Compared with the pristine device (FTO/TiO₂/CH₃NH₃PbI₃/Spiro-OMeTAD/Au), the open-circuit voltage of the optimized cell increases from 0.98 V to 1.06 V. Furthermore, the design of a circular platform light-trapping structure makes up for the light loss caused by the transition at the interface. The short-circuit current density of the optimized device increases from 19.81 mA/cm² to 20.36 mA/cm², and the champion device’s power conversion efficiency (PCE) reaches 17.83%, which is an 18.47% improvement over the planar device. This model provides new insight for the optimization of perovskite devices. Full article

Fully printable carbon-based multiporous layered electrode perovskite solar cells (MPLE−PSCs) are close to being commercialized due to their excellent stability, their ability to easily be scaled up, and their amenability to mass production via non-vacuum fabrication processes. To improve their efficiency, it is important that detailed studies of the morphologies of mesoporous electrodes be carried out. In this study, we prepared five types of ZrO₂ spacer layers for MPLE−PSCs, and the morphology of ZrO₂ and device performance were evaluated using a scanning electron microscope, nitrogen adsorption/desorption measurements, electrode resistance measurements, UV-visible light reflectance measurements, and current density–voltage measurements. The results reveal that the adequate specific surface area and pore size distribution of mesoporous ZrO₂ provided high insulation ability when used as spacers between electrodes and light absorbance, resulting in a 10.92% photoelectric conversion efficiency with a 23.22 mA cm⁻² short-circuit current density. This information can serve as a guideline for designing morphologies useful for producing high-efficiency devices. Full article

Lead halide perovskite quantum dots, also known as perovskite nanocrystals, are considered one of the most promising photovoltaic materials for solar cells due to their outstanding optoelectronic properties and simple preparation techniques. The key factors restricting the photoelectric conversion efficiency of solar cell systems are the separation and transmission performances of charge carriers. Here, femtosecond time-resolved ultrafast spectroscopy was used to measure the interfacial charge transfer dynamics of different sizes of CsPbBr₃ assembled with TiO₂. The effect of perovskite size on the charge transfer is discussed. According to our experimental data analysis, the time constants of the interfacial electron transfer and charge recombination of the assembled systems of CsPbBr₃ and titanium dioxide become larger when the size of the CsPbBr₃ nanocrystals increases. We discuss the physical mechanism by which the size of perovskites affects the rate of charge transfer in detail. We expect that our experimental results provide experimental support for the application of novel quantum dots for solar cell materials. Full article

Nitrogen oxides (NO_X) are important precursors of ozone and secondary aerosols. Accurate and timely NO_X emission estimates are essential for formulating measures to mitigate haze and ozone pollution. Bottom–up and satellite–constrained top–down methods are commonly used for emission inventory compilation; however, they have limitations of time lag and high computational demands. Here, we propose a machine learning model, WOA-XGBoost (Whale Optimization Algorithm–Extreme Gradient Boosting), to retrieve NO_X emissions. We constructed a dataset incorporating satellite observations and conducted model training and validation in the Shandong region with severe NO_X pollution to retrieve high spatiotemporal resolution of NO_X emission rates. The 10–fold cross–validation coefficient of determination (R²) for the NO_X emission retrieval model was 0.99, indicating that WOA-XGBoost has high accuracy. Validation of the model for the other year (2019) showed high agreement with MEIC (Multi–resolution Emission Inventory for China), confirming its strong robustness and good temporal transferability. The retrieved NO_X emissions for 2021–2022 revealed that emission rate hotspots were located in areas with heavy traffic flow. Among 16 prefecture–level cities in Shandong, Zibo exhibited the highest NO_X rate (>1 μg/m²/s), explaining its high NO₂ pollution levels. In the future, priority areas for emission reduction should focus on heavy industry clusters such as Zibo and high traffic urban centers. Full article

Titanium dioxide (TiO₂) is a wide-bandgap semiconductor material with broad application potential, known for its excellent photocatalytic performance, high chemical stability, low cost, and non-toxicity. These properties make it highly attractive for applications in photovoltaic energy, environmental remediation, and optoelectronic devices. For instance, TiO₂ is widely used as a photocatalyst for hydrogen production via water splitting and for degrading organic pollutants, thanks to its efficient photo-generated electron–hole separation. Additionally, TiO₂ exhibits remarkable performance in dye-sensitized solar cells and photodetectors, providing critical support for advancements in green energy and photoelectric conversion technologies. Boron-doped diamond (BDD) is renowned for its exceptional electrical conductivity, high hardness, wide electrochemical window, and outstanding chemical inertness. These unique characteristics enable its extensive use in fields such as electrochemical analysis, electrocatalysis, sensors, and biomedicine. For example, BDD electrodes exhibit high sensitivity and stability in detecting trace chemicals and pollutants, while also demonstrating excellent performance in electrocatalytic water splitting and industrial wastewater treatment. Its chemical stability and biocompatibility make it an ideal material for biosensors and implantable devices. Research indicates that the combination of TiO₂ nanostructures and BDD into heterostructures can exhibit unexpected optical and electrical performance and transport behavior, opening up new possibilities for photoluminescence and rectifier diode devices. However, applications based on this heterostructure still face challenges, particularly in terms of photodetector, photoelectric emitter, optical modulator, and optical fiber devices under high-temperature conditions. This article explores the potential and prospects of their combined heterostructures in the field of optoelectronic devices such as photodetector, light emitting diode (LED), memory, field effect transistor (FET) and sensing. TiO₂/BDD heterojunction can enhance photoresponsivity and extend the spectral detection range which enables stability in high-temperature and harsh environments due to BDD’s thermal conductivity. This article proposes future research directions and prospects to facilitate the development of TiO₂ nanostructured materials and BDD-based heterostructures, providing a foundation for enhancing photoresponsivity and extending the spectral detection range enables stability in high-temperature and high-frequency optoelectronic devices field. Further research and exploration of optoelectronic devices based on TiO₂-BDD heterostructures hold significant importance, offering new breakthroughs and innovations for the future development of optoelectronic technology. Full article

With the rapid development of marine renewable energy, especially offshore photovoltaic systems, the problem of biofouling of photovoltaic equipment in the marine environment has become increasingly prominent. The attachment of marine organisms such as algae will significantly affect the photoelectric conversion efficiency of photovoltaic panels, thereby reducing the stability and economy of the system. In this study, a composite siloxane coating was designed and prepared. Methyltrimethoxysilane (MTMS) was used as the organosilicon component. The negative potential of the coating was significantly enhanced by incorporating hexagonal boron nitride nanosheets (h-BNNS). This negative potential and the negative charge on the surface of marine organisms, especially algae, would produce electrostatic repulsion, which can effectively reduce the attachment of organisms. The results show that the prepared coating exhibits excellent performance in anti-biofouling, adhesion, chemical stability, transparency, and self-cleaning properties. The transparency of the coating reached 92.7%. After immersion with Chlorella for 28 days, the coverage percentage on the coating surface was only 0.98%, while the coverage percentage on the blank sample was 23.25%. The corrosion resistance and salt resistance of the coating also ensure its stability in complex marine environments, and it has broad application prospects. Full article

Enhancing solar photovoltaic (PV) power generation is fundamental to achieving energy sustainability goals. However, elevated module temperatures can diminish photoelectric conversion efficiency and output power, impacting the safe and efficient operation of PV modules. Therefore, understanding module temperature distribution is crucial for predicting power generation performance and optimizing cleaning schedules in PV power plants. To investigate the combined effects of multiple factors on the temperature distribution and output power of dusty PV modules, a heat transfer model was developed. Validation against experimental data and comparisons with the NOCT model demonstrated the validity and advantages of the proposed model in accurately predicting PV module behavior. This validated model was then employed to simulate and analyze the influence of various parameters on the temperature of dusty modules and to evaluate the module output power, providing insights into sustainable PV energy generation. Results indicate that the attenuation of PV glass transmittance due to dust accumulation constitutes the primary determinant of the lower temperature observed in dusty modules compared to clean modules. This highlights a significant factor impacting long-term performance and resource utilization efficiency. Dusty module temperature exhibits a positive correlation with irradiance and ambient temperature, while displaying a negative correlation with wind speed and dust accumulation. Notably, alignment of wind direction and module orientation enhances module heat dissipation, representing a passive cooling strategy that promotes efficient and sustainable operation. At an ambient temperature of 25 °C and a wind speed of 3 m/s, the dusty module exhibits a temperature reduction of approximately 11.0% compared to the clean module. Furthermore, increasing the irradiance from 200 W/m² to 800 W/m² results in an increase in output power attenuation from 51.4 W to 192.6 W (approximately 30.4% attenuation rate) for a PV module with a dust accumulation of 25 g/m². This underscores the imperative for effective dust mitigation strategies to ensure long-term viability, economic sustainability, and optimized energy yields from solar energy investments. Full article

This study presents the first comprehensive theoretical investigation utilizing SCAPS-1D simulation to systematically evaluate eight hole transport materials for CsPbI₂Br perovskite solar cells under authentic indoor LED conditions (560 lux, 5700 K color temperature). Unlike previous studies employing simplified illumination assumptions, our work establishes fundamental design principles for indoor photovoltaics through rigorous material property correlations. The investigation explores the influence of layer thickness and defect concentration on performance to identify optimal parameters. Through detailed energy band alignment analysis, we demonstrate that CuI achieves superior performance (PCE: 23.66%) over materials with significantly higher mobility, revealing that optimal band alignment supersedes carrier mobility under low-light conditions. Analysis of HTL and absorber layer thickness, bulk defect concentration, interface defect density, and an HTL-free scenario showed that interface defect concentration and absorber layer parameters have greater influence than HTL thickness. Remarkably, ultra-thin HTL layers (0.04 μm) maintain >99% efficiency, offering substantial cost reduction potential for large-scale manufacturing. Under optimized conditions of a 0.87 μm absorber layer thickness, defect concentration of 10¹⁵ cm⁻³, interface defect concentration of 10⁹ cm⁻³, and CuI doping concentration of 10¹⁷ cm⁻³, PCE reached 28.57%, while the HTL-free structure achieved 17.6%. This study establishes new theoretical foundations for indoor photovoltaics, demonstrating that material selection criteria differ fundamentally from outdoor applications. Full article

As the primary electronic payload of laser interferometry system for space gravitational wave detection, the core function of the phasemeter is ultra-high precision phase measurement. According to the principle of laser heterodyne interferometry and the requirement of 1 pm ranging accuracy of the phasemeter, the phase measurement noise should reach 2π μrad/Hz^1/2@(0.1 mHz–1 Hz). The heterodyne interference signal first passes through the quadrant photoelectric detector (QPD) to achieve photoelectric conversion, then passes through the analog-to-digital converter (ADC) to achieve analog and digital conversion, and finally passes through the digital phase-locked loop (DPLL) for phase locking. The sampling timing jitter of the heterodyne interference signal caused by the ADC is the main noise affecting the phase measurement performance and must be suppressed. This paper proposes a sampling timing jitter noise suppression system (STJNSS), which can set system parameters for high-frequency signals used for inter-satellite clock noise transmission, the system clock of the phasemeter, and the pilot frequency for suppressing ADC sampling timing jitter noise, meeting the needs of the current major space gravitational wave detection plans. The experimental results after the integration of SJNSS and the phase meter show that the phase measurement noise of the heterodyne interferometer signal reaches 2π μrad/Hz^1/2@(0.1 mHz–1 Hz), which meets the requirements of space gravitational wave missions. Full article

As a critical impurity in the production of solar-grade silicon, the concentration of phosphorus (P) significantly affects photoelectric conversion efficiency. To address the challenge of P removal in solar-grade silicon production, this study proposes a combined process of Si-Fe solvent refining and SiO₂-TiO₂-CaO-CaF₂ slag treatment. Under conditions utilizing collaborative refining with an alloy composition of Si-10 wt. %Fe and a slag composition of 32 wt. %SiO₂-48 wt. %CaO-10 wt. %TiO₂-10 wt. %CaF₂, the removal rate of P in silicon can reach up to 96.8%. This paper investigates the effectiveness of combining solvent refining with slag making under fixed conditions of a Si-10 wt. %Fe alloy paired with various slag systems (no slag addition, binary slag SiO₂-TiO₂, ternary slag SiO₂-CaO-TiO₂, and quaternary slag SiO₂-TiO₂-CaO-CaF₂). Based on the experimental results, the optimal TiO₂ content in the slag system for maximizing P removal was analyzed and determined. Finally, leveraging both theoretical analysis and experimental findings, the mechanism of P removal was elucidated as a dual process: P is oxidized into Ca₃(PO₄)₂ within the slag phase, and residual P is captured by the Fe-Si-Ti ternary phase. Full article

This paper proposes a structural silicon heterojunction photosensitive element with a simple form, low manufacturing cost, and efficient performance, which has a high-intensity photoelectric effect and a high frequency range of use. It can be applied as microwave switches to active frequency selective surfaces (AFSSs) to replace PIN diodes. Meanwhile, we explore the crucial role of pentacene/silicon heterojunction in the photoelectric conversion process. It is found that due to the inherent photovoltaic effect and the built-in electric field interaction between the two materials, the insertion loss of the heterojunction formed is reduced to 4.5 dB, which is 2.5 dB lower than that of the high-resistivity silicon wafer. In order to further reduce the insertion loss, the surface of the silicon wafer is etched and then heterojunction is prepared, which can further reduce insertion loss to within 2.5 dB, and the bandwidth difference between the presence and absence of pump excitation exceeds 10 dB extends to 12 GHz, indicating that the light collecting ability of structural silicon significantly enhances its photoelectric effect. The research results demonstrate the potential of using structural silicon heterojunctions in photoelectric devices, providing new technology for high-performance microwave switches and implementing optically controlled FSSs. Full article

At present, photovoltaic power generation is becoming increasingly popular, and one of its major drawbacks is the low photoelectric conversion efficiency of photovoltaic cells. In order to improve power generation efficiency, an equivalent circuit model of photovoltaic cells and a simulation structure of photovoltaic power generation systems have been established. The working principle and MPPT (Maximum Power Point Tracking) control process of the improved Fibonacci linear search algorithm have been analyzed to achieve the goal of improving power generation efficiency. The improved Fibonacci linear search algorithm is applied in the MPPT technology of photovoltaic power generation system, and simulation experiments are conducted. Through analysis and simulation, MPPT can quickly track the maximum power point when the external lighting conditions change and has good tracking effect. Full article

This research introduces a novel hybrid machine learning framework for automated quality prediction and classification of silicon solar modules in production lines. Unlike conventional approaches that rely solely on encapsulation loss rate (ELR) for performance evaluation—a method limited to assessing encapsulation-related power loss—our framework integrates unsupervised clustering and supervised classification to achieve a comprehensive analysis. By leveraging six critical performance parameters (open circuit voltage (V_OC), short circuit current (I_SC), maximum output power (P_max), voltage at maximum power point (VPM), current at maximum power point (IPM), and fill factor (FF)), we first employ k-means clustering to dynamically categorize modules into three performance classes: excellent performance (ELR: 0–0.77%), good performance (0.77–8.39%), and poor performance (>8.39%). This multidimensional clustering approach overcomes the narrow focus of traditional ELR-based methods by incorporating photoelectric conversion efficiency and electrical characteristics. Subsequently, five machine learning classifiers—decision trees (DT), random forest (RF), k-nearest neighbors (KNN), naive Bayes classifier (NBC), and support vector machines (SVMs)—are trained to classify modules, achieving 98.90% accuracy with RF demonstrating superior robustness. Pearson correlation analysis further identifies V_OC, P_max, and VPM as the most influential quality determinants, exhibiting strong negative correlations with ELR (−0.953, −0.993, −0.959). The proposed framework not only automates module quality assessment but also enhances production line efficiency by enabling real-time anomaly detection and yield optimization. This work represents a significant advancement in solar module evaluation, bridging the gap between data-driven automation and holistic performance analysis in photovoltaic manufacturing. Full article

With the intensification of global climate change, buildings in hot climate zones face increasing challenges related to high energy consumption and thermal comfort. Building integrated photovoltaic (BIPV) façades, which combine power generation and energy saving potential, require further optimization in their climate-adaptive design. Most existing studies primarily focus on the photoelectric conversion efficiency of PV modules, yet there is a lack of systematic analysis of the coupled effects of temperature, humidity, and solar radiation intensity on PV performance. Moreover, the current literature rarely addresses the regional material degradation patterns, integrated cooling solutions, or intelligent control systems suitable for hot and humid climates. There is also a lack of practical, climate specific design guidelines that connect theoretical technologies with real world applications. This paper systematically reviews BIPV façade design strategies following a climate zoning framework, summarizing research progress from 2019 to 2025 in the areas of material innovation, thermal management, light regulation strategies, and parametric design. A climate responsive strategy is proposed to address the distinct challenges of humid hot and dry hot climates. Finally, this study discusses the barriers and challenges of BIPV system applications in hot climates and highlights future research directions. Unlike previous reviews, this paper offers a multi-dimensional synthesis that integrates climatic classification, material suitability, passive and active cooling strategies, and intelligent optimization technologies. It further provides regionally differentiated recommendations for façade design and outlines a unified framework to guide future research and practical deployment of BIPV systems in hot climates. Full article

Heterologous expression of the G231L variant of VioA into 16 strains of marine-derived Streptomyces, combined with bioactivity tracking, leads to the activation of seven antibiotic streptogramins (1–7) in Streptomyces sp. OUC20-O. Among these, compound 1, named linstreptogramin, is a new compound with an unusual linear streptogramin skeleton. The planar structure and stereochemistry of compound 1 were established based on extensive MS and NMR spectroscopic analyses, together with ECD calculations. In the antibacterial activity evaluation, compounds 1–4 showed significant growth inhibition against the multidrug-resistant Enterococcus faecium CCARM 5203 with MIC values of 0.2–1.6 µg/mL, which are comparable to the positive control vancomycin. Full article