Search Results (871)

This Review examines up-to-date advancements in the integration of biomolecules and solar energy technologies, with a particular focus on biohybrid photovoltaic systems. Biomolecules have recently garnered increasing interest as functional components in a wide range of solar cell architectures, since they offer a huge variety of structural, optical, and electronic properties, useful to fulfill multiple roles within photovoltaic devices. These roles span from acting as light-harvesting sensitizers and charge transport mediators to serving as micro- and nanoscale structural scaffolds, rheological modifiers, and interfacial stabilizers. In this Review, a comprehensive overview of the state of the art about the integration of biomolecules across the various generations of photovoltaics is provided. The functional roles of pigments, DNA, proteins, and polysaccharides are critically reported improvements and limits associated with the use of biological molecules in optoelectronics. The molecular mechanisms underlying the interaction between biomolecules and semiconductors are also discussed as essential for a functional integration of biomolecules in solar cells. Finally, this Review shows the current state of the art, and the most significant results achieved in the use of biomolecules in solar cells, with the main scope of outlining some guidelines for future further developments in the field of biohybrid photovoltaics. Full article

Optical materials are widely used in large optical systems such as lithography machines and astronomical telescopes. However, optical materials inevitably produce subsurface damage (SSD) during lapping and polishing processes, degrading the laser damage threshold and impacting the service life of the optical system. The large surface roughness of the lapped optical materials further increases the difficulty of the nondestructive detection of SSD. Quantum dots (QDs) show great development potential in the nondestructive detection of SSD in lapped materials. However, existing QD-based SSD detection methods ignore the polarization sensitivity of QDs to excitation light, which affects the detection accuracy of SSD. To address this problem, this paper explores the fluorescence polarization properties of QDs in the SSD of optical materials. First, the detection principle of SSD based on the fluorescence polarization of QDs is investigated. Subsequently, a fluorescence polarization detection system is developed to analyze the fluorescence polarization properties of QDs in SSD. Finally, the SSD is detected based on the studied polarization properties. The results show that the proposed method effectively improves the detection rate of SSD by 10.8% and thus provides guidance for evaluating the quality of optical material and optimizing optical material processing technologies. The research paradigm is equally applicable to biomedicine, energy, optoelectronics, and the environment, where QDs have a wide range of applications. Full article

Ensuring the structural safety of steel trusses in escalators is critical for the reliable operation of vertical transportation systems. While manual inspection remains widely used, its dependence on human judgment leads to extended cycle times and variable defect-recognition rates, making it less reliable for identifying subtle surface imperfections. To address these limitations, a novel context-aware, multi-scale deep learning framework based on the YOLOv5 architecture is proposed, which is specifically designed for automated structural defect detection in escalator steel trusses. Firstly, a method called GIES is proposed to synthesize pseudo-multi-channel representations from single-channel grayscale images, which enhances the network’s channel-wise representation and mitigates issues arising from image noise and defocused blur. To further improve detection performance, a context enhancement pipeline is developed, consisting of a local feature module (LFM) for capturing fine-grained surface details and a global context module (GCM) for modeling large-scale structural deformations. In addition, a multi-scale feature fusion module (MSFM) is employed to effectively integrate spatial features across various resolutions, enabling the detection of defects with diverse sizes and complexities. Comprehensive testing on the NEU-DET and GC10-DET datasets reveals that the proposed method achieves 79.8% mAP on NEU-DET and 68.1% mAP on GC10-DET, outperforming the baseline YOLOv5s by 8.0% and 2.7%, respectively. Although challenges remain in identifying extremely fine defects such as crazing, the proposed approach offers improved accuracy while maintaining real-time inference speed. These results indicate the potential of the method for intelligent visual inspection in structural health monitoring and industrial safety applications. Full article

In precision cotton seeding, the toothed-disk precision seeder often experiences issues with missed seeding and multiple seeding. To promptly detect and address these abnormal seeding conditions, this study develops a modular photoelectric sensing monitoring system. Initially, the monitoring time window is divided using the capacitance sensing signal between two seed drop ports. Concurrently, a photoelectric monitoring circuit is designed to convert the time when seeds block the sensor into a level signal. Subsequently, threshold segmentation is performed on the time when seeds block the photoelectric path under different seeding states. The proposed spatiotemporal joint counting algorithm identifies, in real time, the threshold type of the photoelectric sensor’s output signal within the current monitoring time window, enabling the differentiation of seeding states and the recording of data. Additionally, an STM32 micro-controller serves as the core of the signal acquisition circuit, sending collected data to the PC terminal via serial port communication. The graphical display interface, designed with LVGL (Light and Versatile Graphics Library), updates the seeding monitoring information in real time. Compared to photoelectric monitoring algorithms that detect seed pickup at the seed metering disc, the monitoring node in this study is positioned posteriorly within the seed guide chamber. Consequently, the differentiation between single seeding and multiple seeding is achieved with greater accuracy by the spatiotemporal joint counting algorithm, thereby enhancing the monitoring precision of the system. Field test results indicate that the system’s average accuracy for single-seeding monitoring is 97.30%, for missed-seeding monitoring is 96.48%, and for multiple-seeding monitoring is 96.47%. The average probability of system misjudgment is 3.25%. These outcomes suggest that the proposed modular photoelectric sensing monitoring system can meet the monitoring requirements of precision cotton seeding at various seeding speeds. Full article

New bulk chalcogenides from the system (GeTe₆)_1−xCu_x, where x = 5, 10, 15 and 20 mol%, have been synthesized. The structure and composition of the materials were studied using X-ray powder diffraction (XRD) and energy-dispersive spectroscopy (EDS). Scanning electron microscopy (SEM) was applied to analyze the surface morphology of the samples. Some thermal characteristics such as the glass transition, crystallization and melting temperature and some physico-chemical properties such as the density, compactness and molar and free volumes were also determined. The XRD patterns show sharp diffraction peaks, indicating that the synthesized new bulk materials are crystalline. The following four crystal phases were determined: Te, Cu, CuTe and Cu₂GeTe₃. The results from the EDS confirmed the presence of Ge, Te and Cu in the bulk samples in concentrations in good correspondence with those theoretically determined. A layered thin-film material based on Ge₁₄Te₈₁Cu₅, which exhibits lower network compactness compared to the other synthesized new chalcogenides, and the azo polymer PAZO was fabricated, and the kinetics of the photoinduced birefringence at 444 nm was measured. The results indicated an increase in the maximal induced birefringence for the layered structure in comparison to the non-doped azo polymer film. Full article

The efficient depolymerization of lignin has become a key challenge in the preparation of high-value-added chemicals. Graphitic carbon nitride (g-C₃N₄)-based photocatalytic system shows potential due to its mild and green characteristics over other depolymerization methods. However, its inherent defects, such as a wide band gap and rapid carrier recombination, severely limit its catalytic performance. In this paper, a g-C₃N₄ modification strategy of K⁺ doping and surface alkalinization is proposed, which is firstly applied to the photocatalytic depolymerization of the lignin β-O-4 model compound (2-phenoxy-1-phenylethanol). K⁺ doping is achieved by introducing KCl in the precursor thermal polymerization stage to weaken the edge structure strength of g-C₃N₄, and post-treatment with KOH solution is combined to optimize the surface basic groups. The structural/compositional evolution of the materials was analyzed by XRD, FTIR, and XPS. The morphology/element distribution was visualized by SEM-EDS, and the optoelectronic properties were evaluated by UV–vis DRS, PL, EIS, and transient photocurrent (TPC). K⁺ doping and surface alkalinization synergistically regulate the layered structure of the material, significantly increase the specific surface area, introduce nitrogen vacancies and hydroxyl functional groups, effectively narrow the band gap (optimized to 2.35 eV), and inhibit the recombination of photogenerated carriers by forming electron capture centers. Photocatalytic experiments show that the alkalinized g-C₃N₄ can completely depolymerize 2-phenoxy-1-phenylethanol with tunable product selectivity. By adjusting reaction time and catalyst dosage, the dominant product can be shifted from benzaldehyde (up to 77.28% selectivity) to benzoic acid, demonstrating precise control over oxidation degree. Mechanistic analysis shows that the surface alkaline sites synergistically optimize the C_β-O bond breakage path by enhancing substrate adsorption and promoting the generation of active oxygen species (·OH, ·O₂⁻). This study provides a new idea for the efficient photocatalytic depolymerization of lignin and lays an experimental foundation for the interface engineering and band regulation strategies of g-C₃N₄-based catalysts. Full article

The non-metallic armored optoelectronic cable (NAOC) serves as a critical component in deep-sea scientific winch systems. Due to its low density and excellent corrosion resistance, it has been widely adopted in marine exploration. However, as the operational water depth increases, the NAOC is subjected to multi-layer winding on the drum, resulting in a cumulative temperature rise that can severely impair insulation performance and compromise the safety of deep-sea operations. To address this issue, this paper conducts temperature rise experiments on NAOCs using a distributed temperature sensing test rig to investigate the effects of the number of winding layers and current amplitude on their temperature rise characteristics. Based on the experimental results, an electromagnetic thermal multi-physics field coupling simulation model is established to further examine the influence of these factors on the maximum operation time of the NAOC. Finally, a multi-variable predictive model for maximum operation time is developed, incorporating current amplitude, the number of winding layers, and ambient temperature, with a fitting accuracy of 97.92%. This research provides theoretical and technical support for ensuring the safety of deep-sea scientific operations and improving the reliability of deep-sea equipment. Full article

III-Nitride semiconductors (BN, AlN, GaN, and InN) exhibit exceptional electronic and mechanical properties that render them indispensable for high-performance optoelectronic, power, and high-frequency device applications. This study implements first-principles Density Functional Theory (DFT) calculations to elucidate the influence of hydrostatic pressure on the electronic, elastic, and mechanical properties of these materials in the wurtzite crystallographic configuration. Our computational analysis demonstrates that the bandgap energy exhibits a positive pressure coefficient for GaN, AlN, and InN, while BN manifests a negative pressure coefficient consistent with its indirect-bandgap characteristics. The elastic constants and derived mechanical properties reveal material-specific responses to applied pressure, with BN maintaining superior stiffness across the pressure range investigated, while InN exhibits the highest ductility among the studied compounds. GaN and AlN demonstrate intermediate mechanical robustness, positioning them as optimal candidates for pressure-sensitive applications. Furthermore, the observed nonlinear trends in elastic moduli under pressure reveal anisotropic mechanical responses during compression, a phenomenon critical for the rational design of strain-engineered devices. The computational results provide quantitative insights into the pressure-dependent behavior of III-N semiconductors, facilitating their strategic implementation and optimization for high-performance applications in extreme environmental conditions, including high-power electronics, deep-space exploration systems, and high-pressure optoelectronic devices. Full article

This study employs density functional theory (DFT) to investigate the electronic and optical properties of molybdenum (Mo) and chalcogen (S, Se, Te) co-doped anatase TiO₂. Two co-doping configurations were examined: Model 1, where the dopants are adjacent, and Model 2, where the dopants are farther apart. The incorporation of Mo into anatase TiO₂ resulted in a significant bandgap reduction, lowering it from 3.22 eV (pure TiO₂) to range of 2.52–0.68 eV, depending on the specific doping model. The introduction of Mo-4d states below the conduction band led to a shift in the Fermi level from the top of the valence band to the bottom of the conduction band, confirming the n-type doping characteristics of Mo in TiO₂. Chalcogen doping introduced isolated electronic states from Te-5p, S-3p, and Se-4p located above the valence band maximum, further reducing the bandgap. Among the examined configurations, Mo–S co-doping in Model 1 exhibited most optimal structural stability structure with the fewer impurity states, enhancing photocatalytic efficiency by reducing charge recombination. With the exception of Mo–Te co-doping, all co-doped systems demonstrated strong oxidation power under visible light, making Mo-S and Mo-Se co-doped TiO₂ promising candidates for oxidation-driven photocatalysis. However, their limited reduction ability suggests they may be less suitable for water-splitting applications. The study also revealed that dopant positioning significantly influences charge transfer and optoelectronic properties. Model 1 favored localized electron density and weaker magnetization, while Model 2 exhibited delocalized charge density and stronger magnetization. These findings underscore the critical role of dopant arrangement in optimizing TiO₂-based photocatalysts for solar energy applications. Full article

Graphene quantum dots (GQDs) have strong potential in optoelectronics, particularly in LEDs, photodetectors, solar cells, and nanophotonics. While challenges remain in efficiency and scalability, advances in functionalization and hybrid material integration could soon make them commercially viable for next-generation optoelectronic devices. In this work, we assess the stability of various epoxy positions and their impact on the electronic and optical properties of GQDs. The oxygen binding energies and the potential barrier heights at different positions of epoxy groups at the edges and in the core of the GQD were estimated. The effect of possible transformations of epoxy groups into other edge configurations on the structural and optical properties of GQDs was evaluated. The results demonstrate that the functionalization of the GQD surface and edges with an epoxy groups at varying binding sites can result in substantial modification of the electronic structure and absorption properties of the GQDs. The prospects of low temperature annealing for controlling optical properties of epoxidized GQDs were discussed. The present computational work offers atomistic insights that can facilitate the rational design of optoelectronic systems based on GQD materials. Full article

The realization of high-precision target positioning requires the systematic suppression of nonlinear perturbations in the UAV optoelectronic system and the optimization of the cumulative deviation of coordinate transformations through error transfer modeling. This study proposes an error allocation method based on the improved raccoon optimization algorithm (KYCOA) to resolve the problem of degradation of positioning accuracy due to multi-source error coupling during UAV target positioning. Firstly, a multi-coordinate system transformation model is established to analyze the nonlinear transfer characteristics of the error, and the Taylor expansion is used to linearize the error transfer process and derive the synthetic error model under the geocentric coordinate system. Secondly, the KYCOA is proposed to optimize the error allocation by combining the good point set initialization strategy to enhance the population diversity, and the golden sine algorithm to improve the position updating mechanism in response to the defect of the traditional optimization algorithm, which easily falls into the local optimum. Simulation experiments show that the positioning error distance of the KYCOA is reduced by 66.75%, 41.89%, and 62.06% when compared with that of the original Coati Optimization Algorithm (COA), Grey Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA), respectively. In the real flight test, the target point localization error of the KYCOA is reduced by more than 40% on average when compared with that of other algorithms, which verifies the effectiveness of the proposed method in improving the target localization accuracy and robustness of UAVs. Full article

Two-dimensional (2D) hybrid organic–inorganic perovskites (HOIPs) have attracted considerable attention in optoelectronic applications, owing to their remarkable characteristics. Nevertheless, the application of 2D HOIPs encounters inherent challenges due to the presence of insulating organic spacers, which create barriers for efficient interlayer charge transport (CT). To tackle this issue, we propose a BA₂MAPb₂I₇/PEA₂MA₂Pb₃I₁₀ bilayer heterostructure, where efficient interlayer energy transfer (ET) facilitates compensation for the restricted charge transport across the organic spacer. Our findings reveal that under 532 nm light illumination, the BA₂MAPb₂I₇/PEA₂MA₂Pb₃I₁₀ heterostructure photodetector exhibits a significant photocurrent enhancement compared with that of the pure PEA₂MA₂Pb₃I₁₀ device, mainly due to the contribution of the ET process. In contrast, under 600 nm light illumination, where ET is absent, the enhancement is rather limited, emphasizing the critical role of ET in boosting device performance. The overlap of the PL emission peak of BA₂MAPb₂I₇ with the absorption spectra of PEA₂MA₂Pb₃I₁₀, alongside the PL quenching of BA₂MAPb₂I₇ and the enhanced emission of PEA₂MA₂Pb₃I₁₀ provide confirmation of the existence of ET in the BA₂MAPb₂I₇/PEA₂MA₂Pb₃I₁₀ heterostructure. Furthermore, the PL enhancement factor followed a 1/d² relationship with the thickness of the hBN layer, indicating that ET originates from 2D-to-2D dipole–dipole coupling. This study not only highlights the potential of leveraging ET mechanisms to overcome the limitations of interlayer CT, but also contributes to the fundamental understanding required for engineering advanced 2D HOIP optoelectronic systems. Full article

ZnO/SiC nanocomposite materials possess significant potential for various technological fields due to their extraordinary optical, electrical, thermal, and mechanical properties. The synthesis methods, material properties, and diverse applications of ZnO/SiC composites have been systematically explored in this study. The potential application areas of this nanocomposite include their roles in photocatalysis, optoelectronic devices, gas sensors, and photovoltaic systems. The synergetic effects of ZnO and SiC are analyzed to highlight their advantages over their individual components. Future research directions must focus on the remaining challenges to optimize these nanoscale composite materials for industrial and emerging applications. 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

This fundamental understanding of molecular structure–NLO property relationships provides critical design principles for next-generation optical limiting materials, quantum photonic devices, and ultrafast nonlinear optical switches, addressing the growing demand for high-performance organic optoelectronic materials in laser protection and photonic computing applications. In this study, it was observed that selenophene-incorporated fused D-A-D architectures exhibit a remarkable enhancement in two-photon absorption characteristics. By strategically modifying the heteroatomic composition of the Y6-derived fused-ring core, replacing thiophene (BDS) with selenophene (BDSe), the optimized system achieves unprecedented NLO performance. BDSe displays a nonlinear absorption coefficient (β) of 3.32 × 10⁻¹⁰ m/W and an effective two-photon absorption cross-section (σ_TPA) of 2428.2 GM under 532 nm with ns pulse excitation. Comprehensive characterization combining Z-scan measurements, transient absorption spectroscopy, and DFT calculations reveals that the heavy atom effect of selenium induces enhanced spin–orbit coupling, optimized intramolecular charge transfer dynamics and stabilized excited states, collectively contributing to the superior reverse saturable absorption behavior. It is believed that this molecular engineering strategy establishes critical structure–property relationships for the rational design of organic NLO materials. Full article