Distributed fiber-optic hydrophone (DFOH) is an underwater acoustic detection system based on distributed acoustic sensing (DAS) technology, which has the ability of long-distance and high-sensitivity continuous monitoring. A single optical fiber can multiplex thousands of hydrophone units, facilitating the construction of large-scale arrays, and enabling extensive underwater acoustic surveillance, thereby overcoming the scale limitations inherent in traditional hydrophone arrays. Firstly, the basic sensing principle of distributed fiber-optic hydrophones was analyzed, and key technological advances were explained from the wet end (hydrophone array), dry end (demodulation system), and array signal processing methods, with a focus on core indicators such as sound pressure sensitivity and equivalent phase noise. Then, the application overview of distributed fiber-optic hydrophone technology in recent years was introduced. Finally, summarize and prospect the existing problems and future development trends.

The construction of computing power facilities requires optical fiber communication networks with high bandwidth, large capacity, and low time delay. However, optical fiber amplifiers with broadband gain, as key materials for relay amplification in optical transmission links, urgently need to be developed. Ultra-wideband gain optical fibers and their optical amplifiers have become research hotspots internationally. This paper elaborates in detail the luminescence characteristics of bismuth ions in different valence states and the research progress of bismuth-doped ultra-wideband gain fibers at home and abroad. It focuses on summarizing the preparation methods of bismuth-doped quartz fibers, the fiber amplification architecture, as well as their research progress in the fields of amplifiers and lasers.

Aiming at the problem of large volume of fiber optic acceleration sensors processed by traditional metal, a cantilever beam-mass block type on-chip acceleration transducer structure is developed. It is fabricated by metal etching process, with dimensions of only 12 mm×12 mm×0.2 mm, and a Fabry-Perot interference microcavity is constructed. By using the white light phase demodulation technology, a miniaturized one-dimensional fiber optic acceleration sensing is realized. The test results show that the response flat range of the fiber optic accelerometer is about 5?250 Hz, the sensitivity is 22.4 dB (re rad/g), and the minimum detectable acceleration is 228 ng/Hz1/2@100 Hz.

With the rapid growth of applications of embodied artificial intelligence system in complex environments, system performance increasingly faces higher challenges of low-latency collaboration, knowledge reasoning, and safe response. This paper proposes a theoretical architecture for edge-side embodied artificial intelligence systems integrated with anti-resonant hollow-core fiber (AR-HCF), leveraging its near-light-speed transmission, inherent electromagnetic interference resistance, and functional multiplexing capabilities to enhance communication efficiency and edge-side system integration at the foundational level. Taking smart firefighting and healthcare as representative scenarios, this work explores the integration paths of AR-HCF in large- and small-edge devices and evaluates its performance potential through multi-dimensional metrics. The proposed new framework presented herein offers a critical reference for cross-disciplinary research merging embodied artificial intelligence with advanced fiber-optic communication technologies.

Optical frequency domain reflectometry (OFDR), celebrated for its exceptional sensitivity and distributed strain sensing capabilities, has demonstrated significant application potential in critical domains such as aerospace and structural health monitoring. However, current OFDR-based strain sensing technologies encounter a critical challenge: position resolution degradation caused by positional mismatches, which impedes the simultaneous achievement of high resolution, broad measurement range, and high-precision measurement. To address this issue, this paper introduces a novel distributed strain sensing technology with an extended dynamic range, which integrates a position self-correction algorithm and non-uniform Gaussian image filtering. An OFDR-based distributed strain sensing system is constructed to validate the effectiveness of these two algorithms. Experimental results show that the proposed method can accurately measure strains up to 8000 με with a spatial resolution of 4 mm over a 5.4 m optical fiber. Compared with conventional approaches, this method significantly expands the strain measurement range, enhances measurement accuracy, and achieves a synergistic optimization between high resolution and large measurement range. These improvements provide a robust solution for deploying OFDR systems in complex strain monitoring scenarios.

Anti-resonant hollow-core fiber (ARF) is regarded as highly promising for high-speed communications, high-power laser delivery, and precision sensing due to its distinctive guidance mechanism and superior performance. In this review, we introduce the guiding mechanisms of ARF and the general overview of ARF development. Material absorption, Rayleigh scattering, and nonlinearity are suppressed via an air or low refractive index core, enabling low loss and stable transmission. Subsequently, recent results and progress in mode control of ARF are summarized, including single-mode, multi-mode, and polarization-maintaining realized via cladding structure optimization, gas filling, and introduction of symmetry breaking. In the end, prospective research directions are outlined to accelerate the adoption of ARF in precision laser machining, high-capacity communications, and optical imaging.

Memristors have emerged as key devices in neuromorphic computing due to their high parallel computing efficiency and low power consumption characteristics. However, array scale expansion is often constrained by traditional electrical interconnection bandwidth bottlenecks and signal attenuation effects. To address these limitations, we propose an integrated architecture for memristor arrays based on optical network-on-chip, utilizing photonic interconnections to overcome physical scaling constraints. We develope a topological packaging structure for memristor arrays and validate its sensitivity to task accuracy through analysis, demonstrating stable computational performance of memristor IP cores under complex conditions. To address the issue of cumulative computation delay within memristor arrays, we present a space-task collaborative optimization mapping algorithm for IP cores. This algorithm minimizes path transmission hops by reconstructing subtask mapping layouts. Additionally, to resolve the problem of multi-task path crosstalk in optical interconnection networks, we design a task-aware low-crosstalk mapping algorithm. This algorithm establishes a collaborative optimization model between photonic device physical characteristics and task communication graphs, reducing interference risks in non-blocking transmission. Experimental results demonstrate that this approach effectively enhances the scalability and computational reliability of large-scale memristor arrays, providing a theoretical framework and technical paradigm for optoelectronic co-design of high-density neuromorphic chips.

To ensure the stability and reliability of fiber optical current transformer (FOCT) long-term operation, this paper proposes a method for real-time monitoring of key state parameters of core components without affecting the normal operation of FOCT, such as second harmonic amplitude, fourth harmonic amplitude, power of super luminescent diode (SLD) light source, return signal power, and modulation signal. This method uses a 2×2 coupler with a splitting ratio of 95∶5 to split the optical path of FOCT. One end of the coupler monitors the light emitted by SLD, and the other end monitors the return signal of FOCT. And through the combination of actual measurement and theory, the feasibility and accuracy of the proposed method for FOCT state monitoring are verified. This method can comprehensively diagnose and troubleshoot equipment faults based on changes in FOCT key state parameters.

With the rapid development of smart healthcare, humanoid robotics, and virtual and augmented reality technologies, optic fiber force sensors attract increasing attention due to their advantages of high sensitivity, high precision, rapid response, and immunity to electromagnetic interference. To address the environmental disturbance susceptibility of traditional optical fiber force sensors, we propose a cascaded sensitivity enhancement scheme based on the vernier effect using tapered optical fibers. A TOF sensor with a 65 mm taper length is fabricated, achieving a sensitivity of -2.08 nm/N under pressures ranging from 0 to 1 N. After cascading this sensor with a second tapered optical fiber, the maximum sensitivity increased to 10.11 nm/N. The results indicate that the vernier effect can effectively enhance force sensitivity. This high sensitivity exhibits significant application potential in fields such as smart healthcare and robotic tactile sensing.

This study proposes a temperature compensation framework for monitoring the refractive index of lead-acid battery electrolytes. We combine parallel Fabry-Perot Fiber Bragg grating (FP-FBG) sensors with deep learning-based demodulation techniques to effectively suppress thermal interference effects. We innovatively construct a one-dimensional residual convolutional neural network (1D-ResCNN) architecture that directly processes raw two-dimensional spectral data for electrolyte densities ranging from 0.991 g/cm3 to 1.4687 g/cm3 at temperatures between 20 ℃ and 45 ℃, eliminating the need for traditional preprocessing procedures. Experimental results demonstrate that the model converges at the 34th epoch, achieving a mean absolute error of 0.0003 on the validation set with a coefficient of determination of 0.9878, significantly outperforming conventional regression methods. Through dynamic learning rate optimization, the total training time is reduced to just 20 min. The model completes predictions for 360 independent test samples within 3 s, demonstrating efficient real-time monitoring capabilities. This research provides an innovative solution for optoelectronic-enabled battery management systems, realizing the synergistic integration of optical fiber sensing and artificial intelligence.

Taking the transmission principle and transmission characteristics of communication optical fibers as the starting point, this paper systematically sorts out the common fault types in optical cable operation and maintenance (O&M), including fiber breakage, bending losses, environmental erosion, human-induced damage, and information security risks. Based on this foundation, the paper introduces both traditional and emerging technologies employed in optical cable O&M, such as optical cable survey instruments, optical time-domain reflectometers (OTDR), and distributed optical fiber sensing (DOFS), and discusses the applicability of these technologies in different O&M scenarios. Focusing on three typical application environments of buried cables, overhead cables, and submarine cables,the study further analyzes their O&M requirements under multiple stress factors such as natural environmental conditions, electrochemical corrosion, lightning strikes, anchor damage, and biological disturbances. Through a comparative analysis of various monitoring technologies used to ensure the secure operation of optical cable networks, the paper identifies a trend toward intelligent, distributed, and integrated development in O&M technologies. In terms of data analysis, the adoption of deep learning and other artificial intelligence techniques is shifting the O&M paradigm from passive repair to proactive defense and predictive maintenance. On the hardware side, the integration of unmanned aerial vehicle (UAV) -based inspections with DOFS is promoting autonomous maintenance operations. From the software perspective, technologies such as the internet of things and digital twins are enabling multi-source data fusion and the construction of digitalized O&M platforms. Looking ahead, optical cable O&M is expected to advance in accuracy, real-time responsiveness, and automation, leading to smarter and more efficient maintenance practices.

Optical fiber sensing technology shows broad application prospects in industrial monitoring, health detection and other fields with its significant advantages of anti electromagnetic interference, small size and easy reuse. Fiber Bragg grating sensing technology has the unique characteristics of high sensitivity of multi parameters, fast response speed and strong local measurement ability, which has excellent performance in high-precision multi-parameter monitoring. In recent years, thanks to the breakthroughs in key technologies such as on-line preparation of wire drawing tower and femtosecond laser direct writing, a single fiber can realize the high consistency industrial preparation of tens of thousands or even hundreds of thousands of gratings. Combined with the large-capacity distributed demodulation method and multi-parameter networking mechanism, people have successfully constructed a large-scale grating array sensor network suitable for long-distance, large-scale and complex environments. This paper systematically summarizes the preparation process, demodulation mechanism, network architecture and typical applications of grating array fiber, including the health monitoring of large engineering structures such as highways, subways and airport runways, as well as innovative applications in perimeter security, underwater acoustic detection, power cable fire warning and other fields, and focuses on the real-time processing methods of large-scale data. The research shows that the sustainable development of large-scale grating array optical fiber sensor network will promote the transformation of infrastructure and large equipment health monitoring mode from passive response to active prevention, and provide a solid sensing foundation for the operation of a new generation of intelligent infrastructure.

We propose a pH sensor based on calcium alginate (CaAlg) hydrogel-coated micro-nano fibers (MNFs) for the high sensitivity detection of sweat pH. The basic principle is that the change in refractive index induced by the swelling and contraction of the CaAlg hydrogel caused by a change in the solution pH promotes a change in the effective refractive-index difference of the MNF bimode interference, thereby causing a drift in its interference wavelength. The effect of the CaAlg hydrogel concentration on the pH sensitivity of the sensor was analyzed, and the performance indices related to sweat-pH sensing were evaluated. Experimental results show that the sensor can detect the pH of the aqueous solution in the range of 2 to 9 as well as achieve an ultrahigh sensitivity of -4.87 nm/pH. The average sensitivity for artificial sweat in the pH range of 4.4?8.8 is approximately -5.83 nm/pH, the linear coefficient exceeds 0.984, the response time is less than 2 min, and the stability is 95.000%?99.286% within 100 min. The proposed MNF-based pH sensor offers high sensitivity, a simple structure, stable performance, and easy fabrication, as well as demonstrates high feasibility and application potential for the detection of sweat pH.

A funnel-shaped Fabry-Perot fiber optic sensor is proposed to satisfy the demand for high-sensitivity measurement of flow velocity and temperature in ocean research. The sensor consists of an aluminum alloy membrane and optical fibers. It detects changes in the cavity length of the Fabry-Perot interferometer based on the deformation and thermal expansion effects of aluminum alloy, which are induced by seawater flow velocity and pressure. These changes shift the interference spectrum, facilitating simultaneous seawater flow velocity and temperature measurements. The flow velocity and temperature sensitivities were obtained through theoretical derivation and finite element simulation. A measurement system was constructed to assess the seawater flow velocity and temperature simultaneously. At a flow velocity of 0.45 m/s, the maximum flow velocity sensitivity reaches -20.13 nm/(m/s), with an average relative error of 4.12% compared to the theoretical sensitivity. The temperature sensitivity is obtained as 10.34 nm/℃, with an average relative error of 4.54% relative to the theoretical sensitivity. A sensitivity matrix dual-parameter demodulation method was employed to measure 10 different seawater flow velocities and temperatures. The results were compared with the measurements obtained via an acoustic Doppler current meter (ADV) and temperature salinity depth meter (CTD). The average relative errors for flow velocity and temperature measurements are 6.07% and 4.20%, respectively. These findings demonstrate that the funnel-shaped Fabry-Perot fiber optic sensor exhibits high sensitivity and can perform dual-parameter measurements. Thus, it is expected to play a substantial role in oceanographic measurements.

The performance and lifespan of composite materials used in aviation, automotive, manufacturing, and other fields are seriously affected by the occurrence of delamination damage and internal micro-cracks. A novel, effective, and large-area monitoring method is urgently needed to monitor the structural health of such materials. In this study, the deformation monitoring of composite materials is realized by analyzing the transverse stress-induced linear birefringence of single-mode fiber, based on the principle of distributed optical frequency domain reflection (OFDR) and polarization analysis technology. First, the relationship between the transverse stress and bending radius of fiber embedded in composite material is analyzed using ANSYS. Then, by measuring the linear birefringence of a single-mode fiber with a cladding diameter of 250 μm or 165 μm under different bending radii, we obtain the empirical expressions of linear birefringence and bending radius. The results are in concordance with the change trend demonstrated via simulation. A greater bending deformation implies a greater fiber linear birefringence. The proposed method points to a new direction for the effective and convenient monitoring the structural health of composite materials, and it possesses significance in the field of structural damage monitoring.

Underwater wireless optical communication (UWOC) technology has broad application prospects in high-rate and low-latency underwater real-time communication. This paper reports on a field-programmable logic gate array (FPGA)-based underwater laser communication system developed for the practical needs of a high-speed, long-distance, and real-time UWOC system. A laser diode of 450 nm wavelength was selected for the light source to realize a long transmission distance. At the transmitter side, a truncated zero-forcing digital pre-equalizer was applied to weaken the inter-symbol interference of the system at high speed and improve the communication rate. In addition, the system employed Reed-Solomon coding for error correction and an efficiently enhanced parallel inverse Berlekamp-Massey algorithm at the receiver side for real-time decoding to ensure reliable communication over long distances and at high rates. Eventually, the system realizes real-time transmission at a rate of 62.5 Mbit/s over a distance of 60 m with a bit error rate below 10-7.

In the field of deep space exploration, an optical system was designed to meet the imaging detection requirements for shadowed regions on celestial surfaces. The system features a 45°×45° field of view, a 27.2 mm focal length, a spectral range of 430?680 nm, and a relative aperture of 1/2. To achieve high imaging quality and compact size, the design incorporates a novel symmetric optical structure based on the complexification of a positive lens near the aperture stop. The primary optical power of this structure integrates telephoto design elements, helping to reduce the system size. Through passive athermal optical design, the system can operate within a wide temperature range from -40 ℃ to +55 ℃. Additionally, precise micro-thermal stress design was applied to the double-cemented lenses to improve performance stability. During the design process, comprehensive analysis and optimization of the optical structure and aberrations resulted in excellent performance indicators: full-field distortion less than 3%, modulation transfer function value greater than 0.5 at a spatial frequency of 45.5 lp/mm within 0.9 normalized field of view, and total length of 72.8 mm. With its large field of view, large relative aperture, and compact size, the system enables rapid acquisition of target information during multiple takeoffs and landings in shadowed regions on celestial surfaces, while also reducing energy consumption and extending mission lifespan.

The problems of low boring efficiency and high wear ratio of cutters affect tunnel-boring machines (TBMs) during hard rock tunnel excavation. Laser-assisted rock-breaking technology can reduce mechanical wear and accelerate rock removal and has the advantages of easy control and environment friendly. Furthermore, it may help improve rock-breaking efficiency. This article discusses the principle of laser-assisted TBM rock-breaking technology, introduces the recent development status of this technology, and analyzes existing problems and development trends.

Near-infrared organic photodetectors (NIR-OPD) have broad application prospects in flexible wearable devices, environmental detection, medical health monitoring, biomedical imaging, and other aspects. In recent years, high-performance NIR-OPD have received wide attention, and scholars at home and abroad have made great contributions in promoting the innovation of near-infrared organic materials and the structure of optoelectronic devices. The applications of narrow bandgap polymers, small molecule acceptors, and non-fullerene acceptor materials in devices are summarized considering the structure of optical conductivity, spectral response range, responsivity, external quantum efficiency, specific detection rate, and other performance parameters of transistor and diode devices. Various strategies for optimizing the performance of devices such as structure optimization, surface passivation treatment, and interface engineering, while reviewing the research progress of narrowband, full-color, and color-selective NIR-OPD are introduced, and the challenges and application prospects for future development are presented.

Blue laser diodes currently play a vital role in the processing of nonferrous metals such as copper and gold, as well as their composite materials. The development of high-brightness blue laser diodes is a key focus in the industry, leading to significant attention on high-brightness blue laser diode chips and beam combining technologies. This study reviews recent advancements in high-brightness blue laser diodes in the mentioned areas. It briefly covers the improvements in the brightness of high-brightness blue laser diode chips, as well as the principles behind various beam combining technologies and the related research. The review particularly focuses on blue laser diodes based on grating spectral beam combining, which is currently the most significant technological approach for enhancing brightness. Finally, the study summarizes the challenges associated with high-brightness blue laser diodes and discusses future prospects.

Bloodstains are one of the most important forensic evidences that play a crucial role in the detection and analysis of cases. This article reviews the research progress of bloodstain detection using spectral technology, both domestically and internationally. This study also introduces forensic and spectroscopic methods for bloodstain confirmation, bloodstain species identification, and bloodstain duration prediction. The accuracy and practicality of these methods are evaluated, discussing their advantages, disadvantages, and areas of application. Spectral detection technology achieves a bloodstain confirmation accuracy of over 96%, bloodstain species identification accuracy ranging from 70% to 100%, sensitivity between 0.92 and 1, and specificity between 0.78 and 1. The error range for bloodstain duration prediction spans from several hours to several days. And the study concludes by discussing the future development of bloodstain detection technologies. This study provides new technical insights into bloodstain detection in forensic medicine.

In high-end chip manufacturing, extreme ultraviolet (EUV) lithography has become indispensable for large-scale integrated circuit production, and is fundamental to the continued progress of future processing technologies. The laser-produced plasma (LPP)-EUV light source is a critical subsystem of EUV lithography machines, among which the liquid tin droplet generator is a key component. This generator must stably and continuously produce tin droplets of uniform size and spacing at a specific frequency to achieve a stable and efficient conversion efficiency (CE) under laser irradiation. Therefore, measurement and detection systems targeting tin droplet generation are essential for studying the droplet formation mechanism and interaction between droplets and lasers. Such systems play a crucial role in the development of LPP-EUV light sources by improving the droplet quality, increasing the optical CE, reducing debris generation, and ensuring source stability. Optical measurement, as the primary method of measurement and detection, lacks a systematic summary of its application in this field. This paper reviews the core metrics, key requirements, and current technological developments in the optical measurement and detection of tin droplet generators in EUV light sources. It provides a detailed analysis of the characteristics of mainstream measurement techniques and system solutions, which can serve as a technical reference and support for the development of tin droplet generation systems and research on LPP-EUV light sources.

Polarization-controllable high-order harmonics are an effective tool for exploring dichroism in photoelectron spectroscopy. They are extremely useful for examining the ultrafast dynamics processes, electronic state symmetry and topology, and evolution of electronic structures of chiral substances and quantum materials after photoexcitation. This study focuses on the technical solutions for controlling the polarization of high-order harmonics, analyzes two types of methods for characterizing the polarization of high-order harmonics in spectroscopy and electron spectroscopy, introduces the research progress and achievements of circularly polarized high-order harmonics in applications to atoms, molecules, and quantum materials, and summarizes and predicts the future development directions of polarization-controllable high-order harmonics.

In recent years, owing to the rapid development of science and technology, thermometric technologies have evolved, among which fluorescence thermometric technology has gradually garnered significant attention in academia and industry because of its unique advantages and potential. This paper focuses on the basic principles, latest progress, and innovative application of fluorescence thermometric technology in the design of thermometric clothing to provide reference and inspiration for researchers and engineers in related fields. First, we present the basic principles of fluorescence thermometric technology. Subsequently, we review the latest results achieved using fluorescence thermometric probe preparation technology. In thermometric clothing design, the introduction of fluorescence thermometric technology has enabled new developments of smart wearable devices. By cleverly embedding fluorescent temperature sensors into clothing fabrics, real-time monitoring and recording of human body temperature can be realized. In summary, fluorescence thermometric technology, as a sophisticated thermometric technology, demonstrates significant application potential and value in the field of thermometric clothing. As technological innovations continues to develop, fluorescence thermometric technology is anticipated to be widely used in more fields and thus contributes to the development of human society.

Recently, pulsed ytterbium (Yb)-doped fiber lasers have been increasingly manufactured. The high repetition rate, high peak power, significant operation wavelength, and advantages of fiber lasers, have promoted the wide use of pulsed Yb-doped fiber lasers in many fields, such as medical treatment, electro-optical countermeasures, target indication, radar, and processing. In this paper, we first review the development of high-repetition-rate long-pulse Yb-doped fiber lasers with a Q-switched mechanism and master oscillator power amplifier. Next, the output characteristics are summarized. The Q-switched mechanism can help achieve a larger pulse energy and adjust the repetition rate within a specific range, achieving a higher output power of the master oscillator compared with single-cavity all-fiber lasers, thereby meeting the demands of large-energy applications. Finally, the research trends of different pulsed Yb-doped fiber lasers are prospected for the near future. For Q-switched, the damage threshold, manufacturing difficulty, service life, and cost of the saturable absorbers must be improved. For master oscillator power amplifiers, studying and realizing more efficient gain media, simpler structures, and better stability would be a significant accomplishment.

In recent years, frequent bombing and terrorist attacks around the world have posed serious threats to national security and social stability. Therefore, achieving high sensitivity, anti-interference, and rapid response for the precise detection of various trace explosives in complex environments has become a major challenge in the detection of explosives. Optical fiber sensing technology has many advantages, such as high sensitivity, flexibility, electromagnetic interference resistance, corrosion resistance, compact size, and the ability to enable remote and real-time online monitoring, making it highly suitable for the safety detection of trace explosives. This article summarizes the application progress of various optical fiber sensing technologies and techniques in the field of explosive detection, including fluorescence-based fiber optic sensors, surface enhanced Raman spectroscopy (SERS), and surface plasmon resonance (SPR), and discusses their working principles. The performance and applications of different sensitive materials in explosive detection are also introduced. Finally, the current problems and challenges of optical fiber sensing technology in explosive detection are analyzed, and its future development directions are anticipated.

Optical waveguides play a crucial role in applications such as waveguide lasers, frequency converters, and supercontinuum generation. Among various fabrication methods, femtosecond laser writing emerges as one of the most efficient techniques for fabricating waveguides in transparent dielectric materials. This study primarily involves femtosecond laser direct machining induced refractive index modifications and femtosecond laser enhanced wet etching. This study provides a comprehensive review of the principles and recent advancements in femtosecond laser enhanced wet etching for optical waveguide fabrication. Key topics include the mechanisms of selective etching, the waveguide fabrication process, the influence of fabrication parameters on etching efficiency, and the applications of fabricated waveguides. Furthermore, the study addresses current challenges and potential solutions in using femtosecond laser enhanced wet etching for hollow-channel waveguide fabrication and discusses the future development of this promising technique.

Fingerprints contain both morphological and biochemical information, making them one of the most critical pieces of physical evidence for personal identification in crime scene investigations. While traditional fingerprint identification methods can only reveal morphological features of latent fingerprints, surface-enhanced Raman spectroscopy (SERS) offers a novel molecular spectroscopy technique characterized by high sensitivity, simplicity, and rapid analysis. This technique plays a pivotal role in fingerprint visualization and biochemical component detection. This study reviews the latest advancements in SERS-based detection of exogenous and endogenous fingerprint components over the past decade. Additionally, it explores future prospects for SERS in fingerprint analysis, aiming to provide a certain reference for related research, as well as for criminal investigation and case handling.

Stimulated Brillouin scattering (SBS), a significant optical nonlinear effect, has garnered considerable attention in the field of fiber-optic sensing technology, driving continuous research exploration and innovative applications. In this paper, we review the progress on the application of SBS effects in distributed optical fiber sensing technology over the past two decades. First, Brillouin optical time-domain analysis (BOTDA), single-ended BOTDA, and locally stimulated Brillouin optical time-domain reflectometry (BOTDR) emerged as well-engineered representatives of SBS optical time-domain sensing technology. These methods have gained popularity among engineers owing to their practical applications in fields such as civil engineering, rail transit, energy, and submarine cables, where temperature and strain serve as the primary monitoring parameters; these applications continue to expand. Subsequently, in the mid-stage of SBS technology research, new techniques such as Brillouin dynamic grating (BDG) and forward stimulated Brillouin scattering (FSBS) were proposed, advancing the measurement capabilities of fiber-optic sensing in terms of high precision and spatial resolution. These techniques have also broadened the range of measurable parameters, including lateral pressure, salinity, and other material compositions. By summarizing the advancements in SBS-related research and conducting comparative analyses and discussions of these technologies, we aim to provide new perspectives and insights to promote the development of distributed optical fiber sensing technology.

Residual stress is an unavoidable physical phenomenon in the coating process, and it directly affects the mechanical and optical properties as well as the long-term stability of the film. Owing to the development of modern materials science and engineering technologies, the detection of film residual stress is an important link in scientific research and industrial applications. Hence, it is crucial to evaluate the reliability of materials. In this study, seven types of residual stress detection methods for coating films, including traditional physical detection technology and a new combined detection technology, are reviewed from the perspectives of global and local stress detection. The detection principle, formula derivation, precision comparison, application cases, applicable conditions, and limitations of each method are described in detail. Significant differences exist in the applicability of different detection technologies, and it is necessary to comprehensively consider the material characteristics, application background, and actual requirements of the film to select the most suitable detection method. This study provides both a comprehensive overview of coating film stress detection technology for researchers and a reference for technology selection and optimization in practical applications.

With the rapid development of the technologies in electromagnetic and material fields, great progress has been made in the invisibility technology, which has significant application value in the military field. To date, researchers have made extensive and effective efforts in the field of optical invisibility and have proposed some optical invisibility methods based on transformation optics, scattering cancellation, and geometric optics. The presence of metamaterials has turned the optical invisibility technology from theory to reality. Based on the fundamental principles of optics, we introduce the basic principles and current research status of the above several mainstream optical invisibility technologies, analyze the advantages and disadvantages of each technology, and look forward to the future development tendency of the optical invisibility technology.

In high-temperature environments, the surface of alloy parts is easily oxidized, leading to performance degradation. This not only affects their service life, but may also cause equipment failure and safety risks. The coating prepared by laser cladding technology has the characteristics of dense structure, good bonding with the substrate, low dilution rate and deformation, and exhibits excellent oxidation resistance at high temperature. Therefore, this article provides a review of the high-temperature oxidation resistance of the coatings prepared by laser cladding, explores the effects of single element and rare earth oxides on the high-temperature oxidation resistance of laser cladding coatings, introduces the relevant research on new technologies and auxiliary fields, such as high-speed laser cladding, intense pulsed electron beam, ultrasonic vibration, and electromagnetic assistance, in improving the high-temperature oxidation resistance of laser cladding alloys, and summarizes and prospects the development trends of high-temperature oxidation resistance of laser cladding alloy coatings.

Laser cleaning has the characteristics of being green, environmentally friendly, and efficient, gradually replacing traditional cleaning techniques and becoming the most promising cleaning technology of the 21st century. This study reviews developmental history of laser cleaning technology; analyzes the current main research directions in laser cleaning technology, including mechanism, process, impact on material properties, and the status of online monitoring technology; compares the characteristics of different laser cleaning equipments; and delineates the typical applications of laser cleaning across industrial sectors such as aerospace, automotive, power generation, cultural heritage preservation, metal surface treatment, semiconductor manufacturing, and optics. Moreover, it highlights future challenges confronting laser cleaning technology and concludes with a discussion on strategies to enhance competitiveness and market share of laser cleaning technology in China. It provides readers with professional references.

To achieve rapid classification and identification of common cosmetic paper packaging boxes in public security practice, a packaging material recognition method based on X-ray fluorescence spectroscopy (XRF) combined with deep learning algorithms is proposed. First, XRF technology is used for non-destructive testing of 61 paper packaging box samples from different cosmetic brands to analyze their elemental composition, followed by manual classification based on key characteristic elements. Subsequently, random forest, multi-layer perceptron (MLP), deep neural network (DNN), and the proposed MLP-DNN model are constructed. A total of 70% of the samples are randomly selected as the training set for model development, while the remaining 30% serve as the test set for validation. The system evaluates the performance of each model in the classification task and checks the classification performance through cross-validation. The experimental results show that the MLP-DNN model achieves a classification accuracy of 0.89 on the test set, significantly outperforming the random forest (0.85), MLP (0.68), and DNN (0.74), thereby demonstrating its superiority in classifying complex samples. The proposed MLP-DNN model provides a more efficient technical solution for the rapid identification of forensic evidence in public security applications.

To address the insufficient extraction accuracy of the traditional discrete Fourier transform method and the low processing speed of the Levenberg-Marquardt (L-M) algorithm in ring-down time extraction, a periodic discrete Fourier transform (PDFT) algorithm is proposed. By applying the Fourier transform to periodic ring-down signals, the common characteristic frequency of the decay signal is extracted from the frequency domain, enabling the direct and highly accurate extraction of the ring-down time constant. By analyzing the relationship among extraction accuracy, fitting rate, and the number of periods, the optimal number of periods is determined to be 20. The accuracy, precision, and fitting rate of the PDFT algorithm are analyzed via simulations, and an ammonia detection system based on cavity ring-down spectroscopy (CRDS) is constructed to experimentally validate the simulation results. Experimental results demonstrate that the PDFT algorithm improves accuracy by a factor of 1.79 and fitting rate by a factor of 6.76 compared to the conventional L-M algorithm. Additionally, Allan deviation analysis reveals a detection limit below 1×10-9 under optimal integration time. These results highlight the promising potential of the PDFT algorithm for real-time gas sensing in CRDS systems.

In response to the demand for in-situ online detection of non-soluble deposit density (NSDD) on high-voltage insulators in power systems, this study investigated a quantitative measurement method for the NSDD of insulator pollution simulation samples based on laser-induced breakdown spectroscopy (LIBS). Initially, a sample preparation method that simulates the natural accumulation of contaminants was developed, through which multiple insulator pollution simulation samples with small and uniformly distributed NSDD gradients were fabricated for the first time. Then, microscopic imaging and binarization processing revealed a "saturation" trend in the dust accumulation process on the sample surfaces, indicating that contamination completely covers the sample surface at an NSDD of approximately 3 mg/cm2. A correlation between the area ratio of dust coverage and amount of contamination was established. Furthermore, the spectral characteristics of different NSDD samples and the variation patterns of their characteristic spectral lines were studied, revealing that the spectral intensity of high NSDD samples decays at a faster rate with increasing detection delay compared with low-NSDD samples. Finally, calibration experiments were conducted on the simulated samples using a direct focusing LIBS system. Based on the characteristics of dust accumulation on the samples, a piecewise calibration method is proposed, utilizing quadratic and linear fitting to establish calibration models for two distinct dust accumulation stages. The detection limit of this method is 0.0043 mg/cm2, with a quantification limit of 0.0129 mg/cm2. The coefficient of determination for the calibration models reached 0.99 and 0.97 in the two stages, respectively, with a root mean square error of 0.1578 mg/cm2. The methodologies presented in this paper closely approximate the actual detection conditions of real insulators in terms of sample preparation and experimental systems, thereby providing technical support for the field-based in-situ detection of NSDD on high-voltage insulators in power systems.

The combination of broadband filtering arrays and compressed sensing algorithms is an effective solution for achieving miniaturized spectrometers. However, high correlation in the measurement matrix can worsen spectral reconstruction errors. To address this, a spectral measurement and reconstruction scheme combining simulated soil microspore structure and the difference method is proposed. First, by simulating the microscopic pores of the soil, a set of initial filtering units with lower correlation is constructed through a high-degree-of-freedom random internal pore pattern. Next, correlation analysis is conducted, and a difference method is adopted to weaken the impact of shared features among different filtering units on correlation. Finally, the 64 channels with the least correlation are selected to construct the measurement matrix, and the compressed sensing algorithm is used to reconstruct the spectrum to be measured. The simulation results show that, compared to traditional schemes, when the average area ratio of the filtering pattern is 0.4, the proposed method using the simulated soil micropore structure and difference method reduces the correlation from 0.2867 to 0.0992, and the reconstruction error for different bandwidth spectra decreases by over an order of magnitude. This design approach can provide valuable insights for high-precision intelligent sensing.