Search Results (587)

A quasi-continuous-wave (QCW) laser module based on a half-bridge structure is proposed for the low-voltage silicon photonics application, which forms a continuous-wave (CW) laser output when it equally distributes the heat dissipation into all lasers. Such a QCW laser module is modulated into a CW laser source for the chip-to-chip or board-to-board communication. The source current is alternatively diverted to the high-side and the low-side lasers by turning the corresponding gallium nitride high-electron-mobility transistor (GaN HEMT) on and off. The current redirection modulates multiple QCW laser outputs into a CW laser output; however, an undesirable laser downtime is produced during the transition time of the current redirection. Although for the 10 Gbps data rate transmission, a short laser downtime period may be scheduled for the time to perform either the laser steering task of the free-space optics (FSO) operation or the data pause for the fan-out delay, which is still preferred to be minimized for higher data rate transmission. The power efficiency and the laser downtime are functions of the parameters of the laser diodes, switch parasitic capacitances, input voltage, and the inductor. According to the mathematical derivation of the circuit response, the circuit design rules and the switching control strategy are provided to achieve high efficiency and low laser downtime. In the experiment, we implemented a laser module to achieve an FSO specification with a laser downtime of less than 3 ns, total harmonic distortion (THD) less than 10%, power efficiency greater than 60% and laser power higher than 1 W. Full article

Biological biogas upgrading using microalgae offers a sustainable route for simultaneous CO₂ removal and biomass production. This study sequentially evaluated liquid-to-gas ratios, L/G, of 0.6–4.0, photoperiods of 0:24–16:8 h, and light intensities of 150–400 µmol m⁻² s⁻¹ in a semi-continuous photobioreactor–absorption column (PBR-AC) with Chlorella vulgaris under moderate alkalinity conditions of 1053–1350 mg L⁻¹ CaCO₃. The system operated at D = 0.1 d⁻¹, a gas flow of 0.05 L min⁻¹, and GRT of 1.30 h. Increasing L/G from 0.6 to 4.0 improved CO₂-RE from 67.9% to 81.6% and CH₄ from 77.0% to 82.9%, showing that intensified recirculation partly compensated for the moderate carbonate-buffering capacity. Among illuminated photoperiods, 16:8 h performed best, reaching 81.4% CO₂-RE and 81.7% CH₄. At L/G = 4.0 and 16:8 h, increasing photosynthetic photon flux density (PPFD) from 200 to 300 µmol m⁻²·s⁻¹ further improved CO₂-RE from 81.4% to 82.86%, CH₄ from 81.7% to 84.4%, and biomass productivity from 0.230 to 0.250 g L⁻¹ d⁻¹. The dark control achieved 57.06% CO₂-RE, indicating substantial physicochemical CO₂ absorption, while illumination added up to 24.35 percentage points. Overall, the system showed strong upgrading potential under moderate alkalinity, although O₂ contamination, which was 1.5–2.5%, remains a key limitation. Full article

Smart manufacturing, Industry 4.0, and cyber-physical systems (CPSs) require sensing architectures capable of resolving both spatially distributed asset behavior and highly localized process states. This review examines optical fiber sensors (OFSs) and integrated photonic sensors for industrial monitoring through a deployment-oriented, multi-scale perspective. The discussion covers five major application regimes: continuous infrastructure surveillance, structural health monitoring (SHM) of load-bearing composites, dynamic condition monitoring of machinery, in situ observability in advanced manufacturing, and localized chemical or gas sensing. Extended fiber-optic networks, including distributed fiber-optic sensing (DFOS) based on Rayleigh, Raman, and Brillouin scattering, together with multiplexed fiber Bragg grating (FBG) sensors, provide passive, embeddable, and remotely interrogated monitoring for large-scale assets and harsh environments. Photonic integrated circuits (PICs) shift transduction to compact node-level devices for localized thermal, mechanical, refractive-index, absorption, vibration, and inertial measurements, while plasmonic and dielectric nanophotonic sensors extend optical monitoring toward surface-selective and chemically specific detection. Across these platforms, digital signal processing (DSP), machine learning (ML), sensor fusion, and digital-twin (DT) coupling are treated as artificial-intelligence-enabled (AI-enabled) layers for signal recovery, inverse mapping, uncertainty reduction, and predictive maintenance. The review argues that scalable industrial adoption is less limited by sensing physics than by the complete deployment chain: packaging, fiber–chip interfacing, calibration stability, interrogation robustness, and AI-enabled data interpretation. This manuscript is structured as a deployment-oriented narrative review of optical fiber and integrated photonic sensors for industrial monitoring and smart manufacturing. Full article

Emerging metallic radionuclides are expanding theranostic capabilities in nuclear medicine by improving diagnostic sensitivity, enabling dosimetry, and matched theranostic approaches. ¹⁴⁹Tb, ⁴⁴Sc, ⁵²Mn, ²⁰³Pb, and ⁵⁵Co offer distinct nuclear decay properties, including extended half-lives, variable positron emissions, and prompt γ-photons that may influence quantitative imaging performance. Cyclotron and generator routes integrating enriched targets and optimized separations support clinical-scale supply, while advances in chelation chemistry improve in vivo stability and imaging performance. Preclinical and early clinical data demonstrate that ¹⁴⁹Tb provides intrinsic α-therapy and PET imaging capability for theranostic use, ⁴⁴Sc enables extended imaging relative to ⁶⁸Ga, supporting delayed imaging and improved tumor-to-background contrast for peptide-based radiopharmaceuticals and theranostic applications. ⁵²Mn supports prolonged biological tracking for antibody- and engineered-protein-targeted studies, whereas ²⁰³Pb serves as a diagnostic surrogate for ²¹²Pb based α-therapy (via ²¹²Bi). ⁵⁵Co PET imaging supports the development and evaluation of ^58mCo Auger electron therapy. Current challenges include limited global availability of highly enriched targets, management of long-lived radioactive by-products, and the need for standardized dosimetry and regulatory pathways to ensure reproducibility and safety. Ongoing developments in automated target handling, optimized separations, next-generation chelators, and harmonized regulation may facilitate broader clinical translation. Full article

High-sensitivity detection of direct current (DC) partial discharge (PD) in HVDC gas-insulated equipment (GIE) remains challenging because conventional electrical measurements are susceptible to ambient interference and DC PD lacks a phase reference for phase-resolved analysis. Although photon counting techniques provide exceptional sensitivity and noise immunity, their diagnostic application has so far been confined to alternating current (AC) conditions. In this study, a photon-counting-based measurement platform was developed to investigate DC PD generated by three representative gas–solid insulation defects, namely conductor protrusion, surface-attached metal, and free metallic particle. Photon pulse sequences were acquired under both positive and negative voltage polarities. Successive inter-pulse time intervals were then mapped into two-dimensional kernel density estimation heatmaps to visualize defect-dependent temporal characteristics. A Random Forest classifier, integrated with SHapley Additive exPlanations (SHAP) for feature reduction, was employed for quantitative classification. The proposed method achieved classification accuracies of 97.50% and 99.17% for positive and negative polarities, respectively. Notably, the model adaptively prioritized angular-distribution features over radial-distribution features under space-charge-suppressed conditions. These results demonstrate the feasibility of photon-counting-based time-domain characterization and defect classification for DC PD, providing a quantitative, less experience-dependent framework for insulation defect identification in DC gas-insulated systems. Full article

This review presents a comprehensive and thorough evaluation of recent developments in physical vapour deposition (PVD) radiofrequency (RF)-sputtered β-Ga₂O₃ thin-film-based solar-blind ultraviolet (UV) photodetectors (SB-UVPDs), emphasizing their potential for next-generation optoelectronic applications. The review highlights different photodetector architectures, the performance characteristics of SB-UVPDs, and an overview of the attributes of β-Ga₂O₃ that make it a promising wide-bandgap semiconductor for next-generation devices. Additionally, the working principle of the PVD RF magnetron sputtering technique is discussed briefly, with a particular focus on the influence of deposition parameters, including sputtering power, gas pressure, deposition time, target-to-substrate distance, and substrate temperature, on the resulting film’s crystallinity and morphology and the optical quality of SB-UVPDs. Moreover, the impact of post-deposition treatments, such as post-annealing and elemental doping, is also discussed here for SB-UVPDs. And finally, the electrical performance characteristics of SB-UVPDs are discussed categorically based on deposition parameters. Overall, this review establishes that PVD RF magnetron sputtering is a highly versatile and controllable technique for fabricating high-quality β-Ga₂O₃ thin film-based SB-UVPDs. By carefully optimizing deposition and post-processing parameters, the optoelectronic performance of β-Ga₂O₃-based SB-UVPDs can be effectively tuned, enabling their integration into next-generation high-performance optoelectronic and photonic systems. Full article

Radiotherapy (RT) is a cornerstone of cancer treatment, traditionally recognized for its direct cytotoxic effects via DNA damage. However, emerging evidence highlights RT as a profound modulator of the tumor microenvironment (TME), acting as a “double-edged sword” that greatly influences the success of immune checkpoint inhibitors (ICIs). On the one hand, RT acts like an in situ vaccine, causing immunogenic cell death and activating the cGAS-STING pathway, which leads to dendritic cell maturation, T-cell infiltration, and reactive PD-L1 expression. This effect can turn “cold” tumors into “hot” ones, making them more responsive to immune checkpoint blockade. On the other hand, RT can lead to resistance to ICIs by promoting an immunosuppressive environment, recruiting regulatory T cells, M2 macrophages, and myeloid-derived suppressor cells. This review analyzes the mechanisms behind this immunological duality and assesses how parameters such as dose, fractionation, and particle type (e.g., carbon ion versus photon therapy) can be optimized to enhance immune activation. Lastly, we discuss future strategies that focus on innate immunity and tumor metabolism, showing how targeting nutrient depletion and ferroptosis can break down immunosuppressive barriers and position RT as an essential component of precision immuno-oncology. Full article

A ternary CdS–MoS₂–rGO photocathode was developed to enhance visible light-driven hydrogen evolution through interfacial heterostructure engineering. The composite was fabricated via a solution-based deposition method followed by thermal conversion, resulting in crystalline CdS and MoS₂ phases that were uniformly integrated within a conductive reduced graphene oxide (rGO) framework. Structural and surface analyses (XRD and XPS) confirmed the coexistence of Cd²⁺, Mo⁴⁺, and S²⁻ chemical states without detectable secondary phases. Photoelectrochemical measurements revealed that the ternary architecture significantly improves charge separation efficiency and interfacial charge-transfer kinetics compared to binary and single-component films. The CdS–MoS₂–rGO photocathode exhibited the highest photocurrent density, reduced charge-transfer resistance, and favorable Tafel slope under visible-light irradiation (0.25 sun, neutral electrolyte). Gas chromatography measurements verified that these electrochemical enhancements translate into increased hydrogen production rates, following the trend: CdS–MoS₂–rGO > CdS–rGO > MoS₂–rGO >> rGO. Applied bias photon-to-current efficiency (ABPE) analysis further confirmed improved photon utilization efficiency in the ternary system. The enhanced performance is attributed to synergistic integration of CdS (light harvesting), rGO (rapid electron transport), and MoS₂ (catalytic edge sites), which suppresses recombination and accelerates proton reduction kinetics. These findings demonstrate that rational multi-component heterostructure design is an effective strategy for improving hydrogen evolution rate under mild operating conditions. Full article

Plantago lanceolata L. is increasingly incorporated in temperate pasture systems for its agronomic resilience and potential to reduce the environmental footprint of ruminant production through its specific secondary metabolites (SMs). However, how light intensity per se regulates P. lanceolata L. physiology, nutritive value and SM accumulation remains poorly understood due to confounding factors in field studies. This controlled-environment study evaluated the effects of three light intensities (200, 300, and 400 µmol photons m⁻² s⁻¹) on morphophysiological traits, forage quality, and SM concentrations in P. lanceolata L. cv. “Ceres Tonic”. Plants were grown in controlled-environment chambers under similar temperature, humidity and nutrient conditions. Morphological traits, biomass allocation, chlorophyll fluorescence, gas exchange, chemical composition, and root architecture were measured. Additionally, the most important secondary metabolites, aucubin, catalpol and acteoside, were also evaluated. Under the different light intensity treatments plants maintained stable physiological parameters, total biomass production, leaf dimensions or root architecture. However, moderate light intensity (300 µmol photons m⁻² s⁻¹) optimized nutritive value by minimizing fiber concentrations and maximizing metabolizable energy. Acteoside concentration, as well as the iridoid glycosides aucubin and catalpol, were not affected by the different light intensities. These findings demonstrate that P. lanceolata L. maintains morphophysiological stability across the tested light intensity range studied, while selectively modulating forage quality. Full article

Detection of trace gases with high sensitivity and weak excitation power is highly desired for long-range remote sensing. Here, we report the detection of the greenhouse gas nitrous oxide (N₂O) with the power of excitation light down to picowatts, by converting the mid-infrared laser to near-infrared photons through an intra-cavity-enhanced sum-frequency upconversion system. The intra-cavity-enhanced pumping power of 1064.0 nm reaches about 200.0 W, resulting in the conversion of the 4514.6 nm mid-infrared laser to 861.1 nm with an efficiency up to 73.4% under optimal conditions. The upconverted light is then detected by a single-photon avalanche detector, followed by a time-correlated single-photon counting module, which can measure the arrival time of each upconverted photon. By performing discrete Fourier transformations of the arrival time of the detected photons, the frequency spectrum can be determined. By using frequency modulation, this method can suppress background noise significantly. Consequently, the excitation power can be brought down to about 100 pW with the concentration of N₂O being 10 ppm. As a demonstration of application, the presented system is also used for N₂O sensing in an open-path geometry, highlighting the potential for stand-off leak detection. Our proposal offers promising applications to monitor trace gases over long distances with weak excitation powers. Full article

The 795 nm wavelength corresponds to the D1 transition of rubidium atoms and is widely used in atomic optical pumping, atomic clocks, magnetometers, and precision spectroscopy. For compact free-space collimation, beam shaping, and efficient fiber coupling, edge-emitting semiconductor lasers with reduced fast-axis (vertical) divergence are highly desirable, yet low-divergence designs at 795 nm remain limited. Here, we propose and demonstrate low-divergence photonic-crystal epitaxy (LD–PC) for 795 nm edge-emitting lasers. By engineering a periodic n-side photonic-crystal stack to place the fundamental vertical mode near the photonic band edge, the vertical mode is expanded while maintaining effective modal discrimination. Narrow-ridge Fabry–Pérot lasers based on GaAsP/AlGaAs single-quantum-well epitaxy were fabricated and characterized. The optimized LD–PC device (3 μm ridge width, 1 mm cavity length) delivers 227 mW at 200 mA with a threshold current of 23 mA, a slope efficiency of 1.28 W/A, and a peak wall-plug efficiency of 55% under continuous-wave operation at 25 °C. The measured far-field divergences (FWHMs) are 7.16° and 18.83° in the lateral and vertical directions, respectively, corresponding to a reduction in the vertical divergence from >40° in the reference structure to <20° with LD–PC. These results validate photonic-crystal epitaxy as an effective route toward compact, high-performance, low-divergence 795 nm semiconductor laser sources for rubidium-based atomic systems. Full article

Glioblastoma (GBM) remains among the most treatment-refractory human malignancies. It is characterized by profound radioresistance and a highly immunosuppressive tumor microenvironment, limiting the durable efficacy of radiotherapy. Beyond direct cytotoxicity, ionizing radiation can induce immunogenic cell death and the release of damage-associated molecular patterns (DAMPs), including surface-exposed calreticulin, HMGB1, extracellular ATP/adenosine, and tumor-derived DNA. These signals engage pattern-recognition receptors and cGAS–STING–type I interferon pathways, transiently promoting antigen presentation and immune activation. In GBM, however, DAMP signaling frequently evolves toward chronic inflammation and immune suppression, characterized by myeloid cell recruitment, adenosine accumulation, and immune checkpoint upregulation, thereby contributing to tumor regrowth and radioresistance. This dual immune-regulatory role of DAMPs highlights the importance of temporal and contextual interpretation of radiation-induced immune responses. In this review, we summarize current mechanistic and translational evidence on DAMP-mediated immunomodulation in GBM radiotherapy; discuss modality-dependent considerations across photon, proton, and high-LET irradiation; and evaluate the emerging potential of DAMPs as dynamic biomarkers of treatment response. We further outline how integration of DAMP profiling with liquid biopsy, imaging, and nanotheranostic platforms may support biologically informed and adaptive radiotherapy strategies for glioblastoma. Full article

The growing demand for high-fidelity, multi-parameter, distributed sensing in critical domains such as structural health monitoring, oil and gas exploration, and secure perimeter surveillance is pushing traditional optical fiber sensors (OFS) to their performance limits. Although conventional multiplexing techniques such as time-division and wavelength-division multiplexing (TDM, WDM) have been commercially successful, they are rapidly approaching fundamental bottlenecks in sensor density, spatial resolution, and data capacity. This review argues that the synergistic convergence of space-division multiplexing (SDM) and artificial intelligence (AI) represents a paradigm shift, enabling a new generation of intelligent, high-dimensional sensing networks. We comprehensively survey the state of the art in SDM-based OFS, detailing the operating principles and applications of multi-core fibers (MCFs) for ultra-dense sensor arrays and 3D shape sensing, as well as few-mode fibers (FMFs) for mode-division multiplexing and enhanced multi-parameter discrimination. However, the unprecedented spatial parallelism provided by SDM introduces significant challenges, including inter-channel crosstalk, complex signal demultiplexing, and massive data volumes. This paper systematically explores how AI, particularly machine learning (ML) and deep learning (DL), is being leveraged not merely as a tool but as an indispensable core technology to mitigate these impairments. We critically analyze AI’s role in digital crosstalk suppression, intelligent mode demultiplexing, signal denoising, and solving complex inverse problems for parameter estimation. Furthermore, we highlight how this AI–SDM synergy enables capabilities beyond the reach of either technology alone, such as super-resolution sensing and predictive analytics. The discussion is extended to include the critical supporting pillars of this ecosystem, such as advanced interrogation techniques and the associated data management challenges. Finally, we provide a forward-looking perspective on the trajectory of the field, outlining a path toward cognitive sensing networks that are self-calibrating, adaptive, and capable of autonomous decision-making. This review is intended to serve as a foundational reference for researchers and engineers at the intersection of photonics and intelligent systems, illuminating the pathway toward tomorrow’s intelligent sensing infrastructure. Full article

The strategic choice of training system is essential for adapting viticulture to current climate change, ensuring a balance of physiological efficiency and the sustainability of productivity and oenological quality. This study evaluated the effects of vertical shoot positioning and foldable lyre systems (set at angles of 20°, 30° and 40°) on the physiological performance and yield of ‘Merlot’ grapevines. The experiment was conducted in a humid temperate region in Brazil over two consecutive seasons. The experiment followed a randomized block design. The variables evaluated included: the number of clusters per shoot, cluster weight, pruning weight, Ravaz Index, leaf area and yield; gas exchange parameters such as net CO₂ assimilation rate, stomatal conductance, transpiration rate, rubisco carboxylation efficiency, intercellular CO₂ concentration and photosynthetic photon flux density; and chemical composition of berries such as pH, Total Soluble Solids and Titratable Acidity. The data were subjected to an analysis of variance, and the means were compared using Tukey’s test at a 5% probability level. The results indicated that canopy architecture significantly influenced solar radiation interception, with the 30° and 40° foldable lyre systems achieving the highest mean daily radiation levels, exceeding the vertical positioning system by 73.7% and 76.6%, respectively. Although gas exchange at the leaf level remained comparable across all systems, agronomic performance varied considerably. The 40° foldable lyre system achieved the highest yield (22.99 t ha⁻¹), representing a 63.1% increase over the vertical positioning system (14.10 t ha⁻¹). The number of buds in the foldable lyre systems increased by around 70%, which is closely in line with the observed increase in yield. In addition, the foldable lyre systems provided about 40% more leaf area than the vertical positioning system. These findings suggest that divided canopy systems, such as foldable lyre systems, particularly at 30° and 40°, optimize bud load, fruitfulness per shoot, light interception and significantly increase yield without compromising individual physiological efficiency and berry chemical composition, with a balance between vegetation and fruit load preserved and with positive effects on the ripeness and quality of the grapes. Full article

RTD photodetectors have been widely applied in fields such as gas detection, weak signal detection, and single-photon detection. However, during further device design and optimization, it has been found that existing theoretical models cannot fully capture the diverse practical behaviors of RTD photodetectors. In this work, we analyze the influence of optical illumination on the band structure of RTDs and, based on the model proposed by Schulman et al., develop a relatively comprehensive theoretical model for RTD photodetectors. By comparing the model predictions with experimental data reported in the literature, we demonstrate that the proposed model can accurately describe the various physical effects in RTD photodetectors and faithfully reproduce the actual evolution of the I-V characteristics. This model provides a solid foundation for the design and optimization of RTD photodetector devices. Full article