Search Results (74)

This review paper presents a comprehensive analysis of electroluminescence (EL) imaging techniques for photovoltaic (PV) module diagnostics, focusing on advancements from conventional indoor imaging to outdoor and daylight EL imaging. It examines key challenges, including ambient light interference and environmental variability, and highlights innovations such as infrared-sensitive indium gallium arsenide (InGaAs) cameras, optical filtering, and periodic current modulation to enhance defect detection. The review also explores the role of artificial intelligence (AI)-driven methodologies, including deep learning and generative adversarial networks (GANs), in automating defect classification and performance assessment. Additionally, the emergence of drone-based EL imaging has facilitated large-scale PV inspections with improved efficiency. By synthesizing recent advancements, this paper underscores the critical role of EL imaging in ensuring PV module reliability, optimizing performance, and supporting the long-term sustainability of solar energy systems. Full article

The emergence of GaN-based micro-LEDs has revolutionized display technologies due to their superior brightness, energy efficiency, and thermal stability compared to traditional counterparts. However, the development of red-emitting micro-LEDs on silicon substrates (GaN-on-Si) faces significant challenges, among them including hydrogen-induced deactivation of p-GaN caused by hydrogen species generated from SiH₄ decomposition during SiO₂ passivation layer growth, which degrades device performance. This study systematically investigates the use of high-density metal-oxide dielectric passivation layers deposited by atomic layer deposition (ALD), specifically Al₂O₃ and HfO₂, to mitigate these effects and enhance device reliability. The passivation layers effectively suppress hydrogen diffusion and preserve p-GaN activation, ensuring improved ohmic contact formation and reduced forward voltage, which is measured by the probe station. The properties of the epitaxial layer and the cross-section morphology of the dielectric layer were characterized by photoluminescence (PL) and scanning electron microscopy (SEM), respectively. Experimental results reveal that Al₂O₃ exhibits superior thermal stability and lower current leakage under high-temperature annealing, while HfO₂ achieves higher light-output power (LOP) and efficiency under increased current densities. Electroluminescence (EL) measurements confirm that the passivation strategy maintains the intrinsic optical properties of the epitaxial wafer with minimal impact on Wp and FWHM across varying process conditions. The findings demonstrate the efficacy of metal-oxide dielectric passivation in addressing critical challenges in InGaN red micro-LED on silicon substrate fabrication, contributing to accelerating scalable and efficient next-generation display technologies. Full article

To address the challenges posed by complex backgrounds and the low occurrence in photovoltaic cell images captured by industrial sensors, we propose a novel defect detection method: MRA-YOLOv8. First, a multi-branch coordinate attention network (MBCANet) is introduced into the backbone. The coordinate attention network (CANet) is incorporated to mitigate the noise impact of background information on the detection task, and multiple branches are employed to enhance the model’s feature extraction capability. Second, we integrate a multi-path feature extraction module, ResBlock, into the neck. This module provides finer-grained multi-scale features, improving feature extraction from complex backgrounds and enhancing the model’s robustness. Finally, we implement alpha-minimum point distance-based IoU (AMPDIoU) to the head. This loss function enhances the accuracy and robustness of small object detection by integrating minimum point distance-based IoU (MPDIoU) and Alpha-IoU methods. The results demonstrate that MRA-YOLOv8 outperforms other mainstream methods in detection performance. On the photovoltaic electroluminescence anomaly detection (PVEL-AD) dataset, the proposed method achieves a mAP₅₀ of 91.7%, representing an improvement of 3.1% over YOLOv8 and 16.1% over detection transformer (DETR). On the SPDI dataset, our method achieves a mAP₅₀ of 69.3%, showing a 2.1% improvement over YOLOv8 and a 6.6% improvement over DETR. The proposed MRA-YOLOv8 also exhibits great deployment potential. It can be effectively integrated with drone-based inspection systems, allowing for efficient and accurate PV plant inspections. Moreover, to tackle the issue of data imbalance, we propose generating synthetic defect data via generative adversarial networks (GANs), which can supplement the limited defect samples and improve the model’s generalization ability. Full article

Quantum dot light-emitting diodes (QLEDs) based on high-color-purity blue quantum dots (QDs) are crucial for the development of next-generation displays. I-III-VI type QDs have been recognized as eco-friendly luminescent materials for QLED applications due to their tunable band gap and high-stable properties. However, efficient blue-emitting I-III-VI QDs remain rare owing to the high densities of the intrinsic defects and the surface defects. Herein, narrow-band blue-emissive CuAlSe₂/Ga₂S₃/ZnS QDs is synthesized via a facile strategy. The resulting QDs exhibit a sharp blue emission peak at 450 nm with a full width at half maximum (FWHM) of 35 nm, achieved by coating a double-shell structure of Ga₂S₃ and ZnS, which is associated with the near-complete passivation of Cu-related defects (e.g., Cu vacancies) that enhances the band-edge emission, accompanied by an improvment in photoluminescence quantum yield up to 69%. QLEDs based on CuAlSe₂/Ga₂S₃/ZnS QDs are fabricated, exhibiting an electroluminescence peak at 453 nm with a FWHM of 39 nm, a current efficiency of 3.16 cd A⁻¹, and an external quantum efficiency of 0.35%. This research paves the way for the development of high-efficiency eco-friendly blue QLEDs. Full article

Organic light-emitting diodes (OLEDs) based on phosphorescent materials are among the most promising technologies for displays and lightings. For red-emitting heteroleptic iridium complexes (HICs), vast and major research has been focused on the design and synthesis of cyclometalated ligands, while relatively little attention has been given to ancillary ligands which also play important roles in manipulating the optoelectronic and electroluminescent properties of HICs. Seven deep red-emitting HICs were designed and synthesized by systematically modifying the alkyl groups in β-diketone-type ancillary ligands. These HICs exhibited similar physical and optoelectronic properties, with OLED devices based on these materials achieving consistent emission peaks at 624 nm and CIE coordinates of (0.68, 0.32). Among the synthesized HICs, Ir(dmippiq)₂(dmeacac), featuring 3,7-dimethyl-4,6-nonanedione as the ancillary ligand, demonstrated the best OLED performance, achieving a champion external quantum efficiency (EQE) of 18.26%. This result highlights that engineering the alkyl groups in β-diketone ancillary ligands can significantly enhance device performance. Full article

Maintenance and monitoring of solar photovoltaic (PV) systems are essential for enhancing reliability, extending lifespan, and maintaining efficiency. Some defects in PV cells cannot be detected through output measurements due to the string configuration of interconnected cells. Inspection methods such as thermal imaging, electroluminescence, and photoluminescence are commonly used for fault detection. Among these, thermal imaging is widely adopted for diagnosing PV modules due to its rapid procedure, affordability, and reliability in identifying defects. Similarly, current–voltage (I-V) curve analysis provides valuable insights into the electrical performance of solar cells, offering critical information on potential defects and operational inconsistencies. Different data types can be effectively managed and analyzed using artificial intelligence (AI) algorithms, enabling accurate predictions and automated processing. This paper presents the development of a machine learning algorithm utilizing transfer learning, with thermal imaging and I-V curves as dual and single inputs, to validate its effectiveness in detecting faults in PV cells at King Saud University, Riyadh. Findings demonstrate that integrating thermal images with I-V curve data significantly enhances defect detection by capturing both surface-level and performance-based information, achieving an accuracy and recall of more than 98% for both dual and single inputs. The approach reduces resource requirements while improving fault detection accuracy. With further development, this hybrid method holds the potential to provide a more comprehensive diagnostic solution, improving system performance assessments and enabling the adoption of proactive maintenance strategies, with promising prospects for large-scale solar plant implementation. Full article

The organic light-emitting diode (OLED) has been regarded as the most prominent product in the current market of organic electronics, which has attracted growing attention because of their applications in full-color displays and solid-state lighting. Organic materials that exhibit strong luminescence in the solid state constitute the core position of OLED. Extensive research efforts to probe the structure of organic luminescent materials have attracted considerable attention to the conjugated fusion ring architecture. This is because it can confer molecular rigidity and helps to inhibit intermolecular interactions and non-radiative transitions, thus enhancing the performance of luminescent materials. Here, we use an efficient and simple method to construct an eight-membered ring molecular framework based on carbazole. Moreover, we have introduced groups with different electron-withdrawing abilities to develop a series of luminescent molecules. The results show that the nonplanar structure based on the eight-membered ring suppresses fluorescence quenching caused by molecular aggregation. As the doping concentration increases, the electroluminescence spectrum remains basically unchanged, indicating that the eight-membered ring structure can effectively suppress the intermolecular interaction. Notably, DCBz-pm exhibits deep blue emission with a Commission Internationale de l’Eclairage (CIE) coordinate of (0.158, 0.046), which nearly meets the BT. 2020 standards. The DCBz-CN device reaches a maximum external quantum efficiency (EQE) of 4.36%. These results offer a new design strategy for improving the performance of OLEDs. Full article

Broadband upconversion has various applications in solar photovoltaic, infrared and terahertz detection imaging, and biomedicine. The low efficiency of the light-emitting diodes (LEDs) limits the broadband upconversion performance. In this paper, we propose to use surface microstructures to enhance the electroluminescence efficiency (ELE) of LEDs. Systematical investigations on the cryogenic-temperature performances of microstructure-coupled LEDs, including electroluminescence efficiency, luminescence spectrum, and recombination rate, have been carried out by elaborating their enhancement mechanism and light emitting characteristics both experimentally and theoretically. We have revealed that the reason for the nearly 35% ELE enhancement of the optimized structure under cryogenic temperature and weak injection current is the efficient carrier injection efficiency and the high recombination rate in the active region. We also compare studies of the surface luminescence uniformity of the optimized LED with that of the unoptimized device. This work gives a precise description, and explanation of the performance of the optimized microstructure coupled LED at low temperatures, providing important guidance and inspiration for the optimization of broadband upconverter in the cryogenic temperature region. Full article

As the driving source, highly efficient silicon-based light emission is urgently needed for the realization of optoelectronic integrated chips. Here, we report that enhanced green electroluminescence (EL) can be obtained from oxygen-doped silicon nitride (SiN_x:O) films based on an ordered and tunable Ag nanocavity array with a high density by nanosphere lithography and laser irradiation. Compared with that of a pure SiN_xO device, the green electroluminescence (EL) from the SiN_x:O/Ag nanocavity array device can be increased by 7.1-fold. Moreover, the external quantum efficiency of the green electroluminescence (EL) is enhanced 3-fold for SiN_x:O/Ag nanocavity arrays with diameters of 300 nm. The analysis of absorption spectra and the FDTD calculation reveal that the localized surface plasmon (LSP) resonance of size-controllable Ag nanocavity arrays and SiN_x:O films play a key role in the strong green EL. Our discovery demonstrates that SiN_x:O films coupled with tunable Ag nanocavity arrays are promising for silicon-based light-emitting diode devices of the AI period in the future. Full article

Ambipolar organic light-emitting transistors (OLETs) are extremely appealing devices for applications from sensing to communication and display realization due to their inherent capability of coupling switching and light-emitting features. However, their limited external quantum efficiency (EQE) and brightness under ambipolar bias conditions hamper the progress of OLET technology. In this context, it was recently demonstrated in multi-stacked devices that the engineering of the interface between the topmost electron-transporting organic semiconductor (e-OS) and the emission layer (EML) is crucial in optimizing the recombination of the minority charges (i.e., electrons) and to enhance EQE and brightness. Here, we introduce a new light-emitting conjugated polar polymer (CPP) in a multi-stacked OLET to improve the electron injection from e-OS to EML and to study, simultaneously, electroluminescence-related processes such as exciton formation and quenching processes. Interestingly, we observed that the highly polar groups present in the conjugate polymer induced polarization-related relevant charge-trapping phenomena with consequent modulation of the entire electrostatic field distribution and unexpected optoelectronic features. In view of the extensive use of CPPs in OLETs, the use of multifunctional CPPs for probing photophysical processes at the functional interfaces in stacked devices may speed up the improvement of the light-emission properties in OLETs. Full article

Solar energy is an important renewable energy source, and the efficiency of solar panels is crucial. However, tiny cracks and dark spots, defects of panels, can significantly affect power generation performance. To solve the defect identification problem of solar panels, an intelligent electroluminescence (EL) image classification method based on a random network (RandomNet50) is proposed. The randomly connected network module is designed by combining dropout and feature reuse strategies. Feature reuse in random networks optimizes the network structure and improves the feature utilization efficiency. The network model uses geometric transformation and the deep convolution generative adversarial network (DCGAN) method to enhance few-shot EL images (400) with different states. The comparison experiment shows that the RandomNet50 has a good classification effect on the enhanced images. The accuracy of the CIFAR-10/EL dataset (96.15%/88.23%) is better than the residual and dense networks. The method has high classification accuracy and provides strong technical support in the field of solar cells. Full article

As a highly regarded superconducting material with a concise layered structure, MgB₂ has attracted significant scientific attention and holds vast potential for applications. However, its limited current-carrying capacity under high magnetic fields has greatly hindered its practical use. To address this issue, we have enhanced the superconducting performance of MgB₂ by incorporating inhomogeneous phase nanostructures of p-n junctions with electroluminescent properties. Through temperature-dependent measurements of magnetization, electronic specific heat, and Hall coefficient under various magnetic fields, we have confirmed the crucial role of inhomogeneous phase electroluminescent nanostructures in improving the properties of MgB₂. Experimental results demonstrate that the introduction of electroluminescent inhomogeneous phases effectively enhances the superconducting performance of MgB₂. Moreover, by controlling the size of the electroluminescent inhomogeneous phases and optimizing grain connectivity, density, and microstructural uniformity, we can further improve the critical temperature (T_C) and flux-pinning capability of MgB₂ superconducting materials. Comprehensive studies on the physical properties of MgB₂ superconducting structures added with p-n junction electroluminescent inhomogeneous phases also confirm the general effectiveness of electroluminescent inhomogeneous phases in enhancing the performance of superconducting materials. Full article

In this paper, an n-i-p-type GaN barrier for the final quantum well, which is closest to the p-type GaN cap layer, is proposed for nitride light-emitting diodes (LEDs) to enhance the confinement of electrons and to improve the efficiency of hole injection. The performances of GaN-based LEDs with a traditional GaN barrier and with our proposed n-i-p GaN barrier were simulated and analyzed in detail. It was observed that, with our newly designed n-i-p GaN barrier, the performances of the LEDs were improved, including a higher light output power, a lower threshold voltage, and a stronger electroluminescence emission intensity. The light output power can be remarkably boosted by 105% at an injection current density of 100 A/cm² in comparison with a traditional LED. These improvements originated from the proposed n-i-p GaN barrier, which induces a strong reverse electrostatic field in the n-i-p GaN barrier. This field not only enhances the confinement of electrons but also improves the efficiency of hole injection. Full article

The purpose of this paper is to review the research progress in the realization of the organic–inorganic hybrid thin-film packaging of flexible organic electroluminescent devices using the PEALD (plasma-enhanced atomic layer deposition) and MLD (molecular layer deposition) techniques. Firstly, the importance and application prospect of organic electroluminescent devices in the field of flexible electronics are introduced. Subsequently, the principles, characteristics and applications of PEALD and MLD technologies in device packaging are described in detail. Then, the methods and process optimization strategies for the preparation of organic–inorganic hybrid thin-film encapsulation layers using PEALD and MLD technologies are reviewed. Further, the research results on the encapsulation effect, stability and reliability of organic–inorganic hybrid thin-film encapsulation layers in flexible organic electroluminescent devices are discussed. Finally, the current research progress is summarized, and the future research directions and development trends are prospected. Full article

In photovoltaic power plant inspections, techniques for module assessment play a crucial role as they enhance fault detection and module characterization. One valuable technique is luminescence. The present paper introduces a novel technique termed passive luminescence. It enhances both electroluminescence and photoluminescence imaging acquisition in photovoltaic power plants under normal operation in high irradiance conditions. This technique is based on the development of an electronic board, which allows the polarity of the module to be changed, enabling the current generated by the photovoltaic string to be injected into the module and producing electroluminescence effects. Additionally, the board can bypass the module and set an open circuit, inducing photoluminescence emission using sunlight as an excitation source. The proper coordination of the board and an InGaAs camera with a bandpass filter has allowed for the integration of a lock-in technique, which has produced electroluminescence and photoluminescence pictures that can be used for fault detection. Full article