Search Results (551)

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

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

Systemic sclerosis (SSc) is a complex autoimmune connective tissue disease characterized by microvascular dysfunction, immune activation, and progressive fibrosis affecting multiple organs, including the heart. Myocardial involvement represents an important but frequently underrecognized manifestation of SSc and may develop even in the absence of overt clinical symptoms. Cardiac manifestations include ventricular dysfunction, arrhythmias, conduction abnormalities, and heart failure, contributing substantially to morbidity and mortality. The underlying pathophysiology involves coronary microvascular dysfunction, immune-mediated myocardial inflammation, and progressive myocardial fibrosis, which often precede clinically apparent cardiac disease. This review aims to summarize the current understanding of myocardial involvement in SSc and to provide a comprehensive overview of contemporary multimodality cardiovascular imaging techniques for its detection, characterization, and risk stratification. A comprehensive overview of the current literature was conducted focusing on established and emerging cardiovascular imaging modalities for the evaluation of myocardial involvement in SSc. Particular attention was given to echocardiography, cardiac magnetic resonance (CMR), nuclear imaging techniques including positron emission tomography (PET) and single-photon emission computed tomography (SPECT), and cardiac computed tomography (CT). Recent advances in imaging biomarkers, parametric mapping, myocardial strain analysis, and emerging technologies such as artificial intelligence (AI), radiomics, and molecular imaging were also considered. Multimodality cardiovascular imaging plays a central role in the early detection and comprehensive assessment of myocardial involvement in SSc. Advanced imaging techniques enable improved identification of subclinical myocardial dysfunction, microvascular impairment, inflammation, and fibrosis. An integrated imaging approach combining echocardiography, CMR, nuclear imaging, and CT may facilitate earlier diagnosis, enhance risk stratification, and ultimately improve cardiovascular outcomes in patients with SSc. Full article

We investigate the potential to adopt waveguide-integrated GeSn single-photon avalanche detectors (SPADs) over a wideband wavelength range from very-near-infrared to telecommunication wavelengths based on an Si-rich SiN waveguide platform via an end-fire coupling approach. Electrical properties of GeSn SPAD heterodiodes are investigated, including their I–V characteristics, electric field distribution, charge sheet doping variation, avalanche triggering probabilities, dark count rate, and afterpulsing probability, to identify the appropriate critical parameters and to reliably benchmark against previous related simulation works. Notably, to enable a waveguide-integrated GeSn SPAD for the entire wavelength of interest, this paper finds that, among several potentially important parameters, the coupling efficiency between the input waveguide and the GeSn SPAD plays a very critical role in determining the single-photon detection efficiency (SPDE) performance, and a suitable GeSn absorber thickness should be carefully considered according to the chosen Sn content. Interestingly, although the coupling efficiency and SPDE are significantly varied between the longer wavelengths of 1310 and 1550 nm and the shorter wavelengths of 700 and 900 nm, an acceptable SPDE performance can be maintained for all wavelengths of interest for both close end-fire coupling (no gap between the amorphous Si-rich SiN waveguide and the GeSn SPAD) and a 50 nm gap assumption for simpler fabrication. Full article

Large-aperture optical synthetic aperture technology, by combining multiple aperture units, breaks through the limitations of a single reflector and has become the preferred system for extending the resolution and diffraction limit of imaging systems. In particular, segmented telescopes have accumulated extensive engineering practice experience, such as the 30 m TMT and the 39 m ELT. However, the stable maintenance of wavefront coherence between multiple sub-apertures requires strict phase synchronization and group delay matching accuracy, which hinders the further development of sparse aperture telescopes and distributed interferometric telescopes (Long-Baseline Interferometers). This review systematically summarizes the research progress on synthetic aperture systems in wavefront coherence detection and stable maintenance control, focusing on two main physical architectures (Michelson and Fizeau types) and the related control algorithms. Furthermore, based on the basic logic from “measurement” to “modulation”, it prospects the development trends driven by interdisciplinary technologies such as embodied intelligent dynamic prediction, photonic integration, and real-time sensing based on deep learning. The aim is to provide a reference for wavefront-stabilization solutions in the next-generation ultra-large-aperture optical synthetic aperture systems. Full article

Bohr’s correspondence principle acts as a link between quantum physics and classical physics theory, while squeezed light, as a special nonclassical quantum state in quantum physics, achieves precision measurements and gravitational wave detection by minimizing quantum noise in one quadrature component of the optical field. Consequently, determining whether the classical counterpart of the squeezing operator reflects classical spatial scaling transformations is of significant theoretical importance. This paper establishes a universal integral formula that transforms any operator into its Weyl ordering form using the method of integration within the ordered product of operators, combined with the coherent state representation and integration theory within Weyl ordering. By transforming both single-mode and two-mode squeezing operators into their corresponding Weyl ordering forms, their classical counterpart functions are derived. This elucidates the classical correspondence of the squeezed light field density operator and demonstrates that this correspondence fundamentally represents a classical scaling transformation. As a practical application of the classical counterpart of the single-mode squeezing operator, the photon number distribution characteristics in a single-mode squeezed light field are obtained, confirming its noise-squeezing effect. This study not only deepens the theoretical implications of Bohr’s correspondence principle from the perspective of “transformation correspondence” but also introduces novel insights into the establishment of the mathematical foundations of quantum optics and quantum statistical theory. Full article

Dark current represents a fundamental limiting factor in photodiode performance, establishing the noise floor and constraining detectivity in low-light applications. This comprehensive literature review examines publications covering the physical mechanisms underlying dark current generation and diverse techniques employed for its reduction. Covered mechanisms include diffusion current, Shockley–Read–Hall (SRH) generation–recombination, trap-assisted tunneling, band-to-band tunneling, and surface leakage, each examined with respect to its physical origin and characteristic signatures. Reduction strategies are categorized into thermal management approaches, surface passivation techniques including atomic-layer-deposited aluminum oxide (ALD Al₂O₃), guard ring architectures (attached, floating, and combined configurations), gettering and defect engineering methods, doping profile optimization, bias voltage management, and advanced device architectures such as pinned photodiodes and black silicon structures. A classification table organizes all the reviewed literature by material system, reduction technique, and key findings. Special emphasis is placed on silicon, germanium, III–V compounds, and emerging material photodiodes relevant to near-infrared detection, CMOS imaging, single-photon avalanche diodes (SPADs), and Time-of-Flight (ToF) applications. Full article

Single-event effects (SEEs) present a significant challenge to the radiation reliability of integrated circuits. Conventional SEE analysis methods for single-photon avalanche diode (SPAD) devices primarily rely on Sentaurus Technology Computer-Aided Design (TCAD) numerical simulation, which is computationally intensive and time-consuming. In this study, we propose a generalized deep learning (DL) model, using a silicon-based SPAD device with a double-junction double-buried-layer (DJDB) structure fabricated in 180 nm CMOS process as the research subject. By incorporating key parameters that influence SEEs as model inputs, the proposed approach enables rapid prediction of critical parameter metrics, including transient current peaks and dark count rates. Experimental results show that the DL model achieves a prediction accuracy of 97.32% for transient current peaks and 99.87% for dark count rates, demonstrating extremely high prediction precision. To further validate the generalization capability of the proposed network, the model is applied to predict the detection performance of the DJDB-SPAD device. The prediction accuracies for four key performance parameters all exceed 97.5%, further confirming the accuracy and robustness of the developed model. Meanwhile, compared with the conventional Sentaurus TCAD simulation method, the proposed method achieves a 336-fold improvement in computational efficiency. Overall, this method realizes the dual advantages of high precision and high efficiency, which provides an efficient and accurate technical solution for the rapid characteristic analysis and reliability evaluation of SPAD devices under single-event effects (SEEs). Full article

Glioblastoma (GBM) remains the most aggressive primary malignant brain tumor in adults, with poor survival largely driven by diffuse cellular infiltration, profound heterogeneity, and near-universal recurrence following standard therapy. Although maximizing the extent of resection is a key determinant of patient outcome, current clinical imaging modalities lack the spatial resolution necessary to detect microscopic tumor invasion and therapy-resistant cell populations. Emerging in vivo imaging technologies capable of cellular and near-single-cell resolution have therefore become a major focus in preclinical neuro-oncology research, with growing relevance for surgical guidance, treatment adaptation, and translational discovery. This review evaluates multiple optical imaging modalities, including multi-photon microscopy, near-infrared II fluorescence imaging, bioluminescence imaging, photoacoustic imaging, optical coherence tomography, confocal laser endomicroscopy, Raman spectroscopy, autofluorescence microscopy, and fluorescence macroscopy with a focus on their ability to detect residual GBM cells. Despite significant advances, these approaches remain constrained by limitations in molecular target availability, probe delivery across the blood–brain barrier, and signal variability within heterogeneous tumor regions. The biological complexity of GBM further challenges detection, as residual tumor cells are spatially dispersed and phenotypically diverse, limiting the effectiveness of single-marker or single-modality strategies. Together, these findings highlight the need for integrated, biologically informed imaging approaches to improve detection of residual disease and guide surgical decision making. Full article

Quantum random number generation (QRNG) provides fundamentally unpredictable randomness derived from intrinsic quantum processes. In this work we demonstrate two solid-state, room-temperature QRNG implementations based on nitrogen-vacancy (NV) centers in diamond, i.e., ensemble fluorescence from nanodiamonds and single-photon emission from single NV centers located at the tips of fabricated diamond nanopillars for enhanced light collection efficiency, spatial isolation and minimized crosstalk. We compare entropy rates (above 0.98 bits), statistical performance, and robustness of both approaches in our experimental setup, the results contribute to establishing diamond-based QRNG as a scalable solution for quantum-secure randomness generation. Full article

Geiger-mode avalanche photodiode (GM-APD) array light detection and ranging (LiDAR) has significant advantages in low-light scenes due to its single-photon-level detection sensitivity. However, it is susceptible to noise, which leads to a decrease in target localization accuracy. Traditional methods rely on long-term accumulation to distinguish signal photons from noise photons, making it difficult to achieve efficient processing, especially in scenarios with sparse echo photons and low signal-to-noise ratio (SNR), where performance is limited. To quickly and accurately obtain three-dimensional (3D) information of the target under such extreme conditions, this paper proposes a method for target detection and temporal window depth estimation based on intensity information guidance. First, noise suppression is performed on the intensity image according to its statistical characteristics, and an outlier detection mechanism based on neighborhood sparsity is introduced to remove outliers, thereby completing the target detection. Next, by exploiting the spatial continuity and reflectivity similarity of the target, local fusion of photon data within the target neighborhood is performed to construct highly consistent “superpixels”. Finally, according to the distribution difference between signal photons and noise photons on the time axis, temporal window screening is applied to the superpixels to extract depth information, and empty pixels are filled using a convex segmentation method to achieve depth estimation of the target. The experimental results demonstrate that under conditions of low photon counts and strong noise, the proposed method significantly outperforms traditional and existing methods in target recovery and depth estimation by effectively integrating target intensity information. Furthermore, this method achieves faster reconstruction speed, enabling high-precision and high-efficiency 3D target reconstruction. Full article

The on-chip detection of circularly polarized light is pivotal for advancing applications in quantum optics, information processing, and spectroscopic sensing. However, conventional chiral metasurfaces often suffer from complex multilayer fabrication, material incompatibility, or modest performance, hindering their integration with photonic circuits. Here, we introduce a monolithic all-silicon metasurface that overcomes these limitations through a singular structural innovation. By strategically truncating four corners of a conventional Z-shaped meta-atom, we induce a hybridization of optical modes that profoundly enhances chiral light–matter interaction. This deliberately engineered perturbation yields a colossal circular dichroism with an extinction ratio exceeding 66 dB, a performance that surpasses existing state-of-the-art designs by approximately three orders of magnitude. Furthermore, the proposed metasurface exhibits remarkable fabrication robustness, owing to its single-layer architecture and CMOS-compatible material. We demonstrate that this exceptional metasurface can be directly integrated with a Mercury Cadmium Telluride (MCT) photodetector to form a highly efficient, compact circular polarization detector. Our work provides a simple yet powerful paradigm for creating high-performance chiral photonic devices, paving the way for their widespread adoption in integrated optoelectronics. Full article

Active non-line-of-sight (NLOS) human detection aims to infer the presence of hidden individuals by analyzing indirectly reflected photons between a relay surface and occluded targets. In this study, a single-photon avalanche diode (SPAD) and time-correlated single-photon counting (TCSPC)-based acquisition system were used to measure time–photon waveforms in controlled NLOS environments designed to represent post-disaster rubble scenarios. Although the effective temporal resolution of the system is limited by the detector timing jitter and laser pulse width, the recorded transient signals retain distinguishable intensity and temporal delay patterns associated with the primary and secondary reflections. To construct a representative dataset, measurements were collected under varying subject poses, orientations, and surrounding object configurations. The recorded signals were processed using a unified preprocessing pipeline that included normalization, histogram shaping, and signal windowing. Three machine learning models, namely, Convolutional Neural Network, Gated Recurrent Unit, and Random Forest, were trained and evaluated for human presence classification. All models achieved full sensitivity in detecting human presence; however, notable differences emerged in the classification of human-absent scenarios. Among the tested approaches, random forest achieved the highest overall accuracy and specificity, demonstrating stronger robustness to statistical variations in time–photon histograms under limited photon conditions. These results suggest that tree-based classifiers capture amplitude distribution patterns and temporal dispersion characteristics more effectively than deep neural architectures under the present acquisition constraints. Overall, the findings indicate that low-cost SPAD-based NLOS sensing systems can provide reliable human detection in indirect-observation scenarios. Full article

With the increasing importance of securing quantum communication networks, practical and robust entity authentication is a critical requirement. Accordingly, we propose and experimentally validate a quantum entity authentication (QEA) protocol specifically designed for integration with BB84-type quantum key distribution (QKD) workflows and existing terminal architectures. We analyze the protocol’s security against intercept–resend man-in-the-middle (MitM) impersonation, showing that an unauthenticated adversary induces a characteristic 25% correlation error and that the rejection probability approaches unity as the number of detected authentication events increases. For practical realization, the protocol is deployed using weak coherent pulses (WCPs) with decoy-state estimation to bound single-photon contributions and mitigate photon-number-splitting (PNS)-enabled leakage. The system is demonstrated over a field-deployed fiber link of approximately 20 km with ~8 dB optical loss using signal/decoy intensities of ~0.5/~0.15 and sending probabilities 0.88/0.10/0.02 (signal/decoy/vacuum). Across both verification directions, stable operation is observed with quantum bit error rate (QBER) typically fluctuating between 1% and 4% while the sifted key rate remains constant over time. These results provide an experimental basis for integrating physical-layer entity authentication into deployed quantum communication networks. Full article

A monolithic digital Silicon Photomultiplier (SiPM) featuring 1024 microcells with a 30-micrometer pitch and a 50% fill factor has been designed in a 110-nanometer CMOS image sensor technology. The device under consideration integrates both SPAD sensors and front-end electronics in the same substrate. It can count up to 1024 photons in less than 22 ns, while assigning timestamps to the first and last detected photons with a time resolution of less than 100 ps. A parallel counter structure combined with a fast adder tree provides photon counting in digital form with low latency, whereas a carefully balanced fast NAND tree ensures a fixed-pattern time uncertainty not exceeding 26 ps. The architecture incorporates in-pixel memory for individual cell disabling and configurable thresholding on the timing signal for noise mitigation. In order to optimize the fill factor, a part of the electronics is placed outside the array, while the most sensitive elements of the timing and counting circuits are laid out close to the sensor, in the SPAD array. A serial readout is employed to provide a single output connection per SiPM, thereby simplifying system integration. Full article