Environmental pollutants, including organic dyes and plastic, have posed severe threats to the health of our ecosystem. Although a lot of efforts have been made to tackle this problem, these pollutants are still massively produced during industrial activities as well as human life. The ability to detect these environmental pollutants with high sensitivity is thus greatly desired. Herein, we propose a novel surface-enhanced Raman spectroscopy (SERS) substrate with high-density hot spots, high Raman signal enhancement, and good uniformity for trace detection of organic pollutants and nanoplastic. The SERS substrates consist of abundant ultranarrow nanogaps that are fabricated with cost-effective colloidal lithography. With the significantly enhanced near-field intensity, rhodamine 6G (R6G) molecules as low as 10u22128 M can be detected with good linear correlations between the signal intensity and molecular concentrations. Moreover, both nanowells and nanogaps are present on the SERS substrates fabricated by our method and the nanowells could be used to trap micro- or nanoplastic. We successfully demonstrate detecting polystyrene (PS) nanospheres (200 nm in diameter) with different concentrations (1.000% to 0.001%), showing the potential to detect micro- or nanoplastic pollutants in the environment. Our method provides a feasible approach to fabricating low-cost SERS substrates for the detection of organic pollutants and nanoplastic.
Accurate micro-force detection is essential for micro-operation and biomedical applications. However, conventional techniques, such as atomic force microscopy (AFM), are bulky and spatially demanding. In this study, we presented micro-spring probes fabricated by femtosecond-laser two-photon polymerization for flexible and precise mechanical sensing. The mechanical stiffness of the probes was tuned by adjusting the spring-wire diameter, with diameters of 2 u00B5m, 2.5 u00B5m, and 3 u00B5m, exhibiting the corresponding micro-force sensitivity of u22120.28 nm/u00B5N, u22120.09 nm/u00B5N, and u22120.07 nm/u00B5N, respectively. The probes enabled accurate measurement of Youngu2019s modulus of the polydimethylsiloxane (PDMS), exhibiting excellent consistency with AFM results. We further proposed a fiber-based self-referenced displacement detection scheme that integrated sensing and reference springs, allowing Youngu2019s modulus characterization without the need for a piezoelectric stage. With the growing development of the u201Clab-on-fiberu201D paradigm, the proposed micro-spring probe provides a promising platform for high-accuracy and compact micro-force sensing.
Respiratory viruses, such as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza A (H1N1), and respiratory syncytial virus (RSV), remain major public health threats due to overlapping clinical symptoms and the limited speed, sensitivity, and multiplexing capacity of conventional diagnostic methods. Here, we present a label-free optical biosensing platform based on subwavelength grating microring resonators (SGMRRs) for the sensitive and specific detection of viral antigens. The sensor surface is functionalized with antibodies against three representative viral proteins, enabling quantitative detection via resonance wavelength shifts upon antigen binding. The platform achieves the refractive index limit of detection (LoD) of 1.25u00D710u22124 RIU and enables the detection of the SARS-CoV-2 spike protein at 100 pg/mL, the H1N1 nucleoprotein at 10 pg/mL, and the RSV F-trimer protein at 10 pg/mL. The compact SGMRR design readily supports multiplexed integration through multi-ring or multi-channel architectures, highlighting its potential as a scalable and high-performance platform for rapid, quantitative, and point-of-care viral diagnostics.
Quasi-distributed smart sensing systems using fiber Bragg grating arrays have found many practical applications in structure health, electricity grid, aerospace, etc. However, the broadband light sources used for the sensing system are generally constrained to the telecom C-band, limiting the available number of sensors, hence hindering deployment of massive sensing heads for the next generation of Internet of Things (IoT) and integrated sensing and communication. Here, we demonstrate a hybrid sensing system enabled by an ultra-broadband Bi/Er co-doped fiber (BEDF) light source pumped at 830 nm. Leveraging the global excitation capability of the u03BB=830 nm pump, the source provides an unprecedented operating bandwidth spanning from O- to L-bands. Quasi-distributed sensing of the temperature and strain for 21 spatially separated nodes is demonstrated using the single BEDF-based Mach-Zehnder interferometer and 20 fiber Bragg gratings. Our proof of the principle system exhibits the maximum temperature sensitivity of 56 pm/u2103 and maximum strain sensitivity of 0.9 pm/u03BCu03B5. To address the issue of the colored noise measured across the spectrum arising from the source itself due to different contributions of varying environmentally sensitive defects responsible for Bi emission, not present in the Er component, we propose the use of data-driven statistical learning methods to quantitatively characterize and mitigate the measurement uncertainties that limit their applicability in precision sensing. Specifically, an adaptive residual bootstrap strategy for uncertainty quantification is used here for the first time, providing a more accurate evaluation of system uncertainty than the conventional normal distribution analysis. The system achieves measurement uncertainties of less than 4.1% for the temperature and 6.4% for the strain. Overall, the proposed sensing system has the huge potential for practical applications in large-scale structural health monitoring, the IoT, etc.
An intensity-interrogated optical fiber hot-wire anemometer employing a cobalt-doped fiber Bragg grating (CD-FBG) is proposed and experimentally demonstrated. The CD-FBG absorbs light energy from a 1480 nm laser and turns into a u201Chot wireu201D with its temperature decreasing and therefore reflection spectrum blue-shifting with the airflow velocity. To achieve intensity interrogation, a wavelength-switchable narrow-linewidth probe laser is used, which makes the reflected optical power from the CD-FBG change monotonously with the airflow velocity in a certain measurement range. In the experiment, the high sensitivity of u22121248 u03BCW/(m/s) is achieved at the airflow velocity of 0.05 m/s. The measurement range is extended to 0 m/su20138.0 m/s by switching the probe laser wavelength. The response time and recovery time of the anemometer are 0.5 seconds and 0.6 seconds, respectively. The intensity interrogation scheme and simple structure of the anemometer probe greatly reduce the cost and make it a promising solution for high-precision airflow velocity measurement in many practical applications.
We propose a wavelength-division multiplexing (WDM) fiber Bragg grating (FBG) array designed to mitigate the spectral shadow effect, thereby enhancing multiplexing capacity. The array comprises 7560 FBGs, which are periodically arranged across 21 distinct wavelength channels. Each FBG has an average reflectivity of 5.5 parts per thousand and a bandwidth of 0.113 nm. We employ an optical frequency-domain reflectometry (OFDR) system for interrogation, which enables high-density array demodulation and large-strain measurement. A convolutional localization algorithm is proposed to achieve fast and accurate addressing of each FBG. The sensing system achieves a maximum sensing-fiber length of 120 m and spatial resolution of 16 mm, along with a demonstrated strain range of 10000 mu epsilon and wavelength accuracy of 1.2 pm. Furthermore, a 21-fold enhancement in spectral demodulation speed is realized over identical FBG arrays. Consequently, the average demodulation time per FBG is substantially reduced from 11.25 ms to 0.53 ms. These results affirm the exceptional suitability of our system for applications demanding high precision, an extensive strain range, and substantial sensor capacity.
Addressing the urgent need for high-temperature vector vibration monitoring in extreme environments such as aerospace and oil exploration, this paper proposes and develops a novel accelerometer based on femtosecond laser-engraved eccentric fiber Bragg gratings (FBGs) and nickel-coated reflectors. This sensor employs a highly localized FBG with a 10 mm length and 1 mu m eccentricity fabricated within a single-mode fiber. It utilizes asymmetric refractive index modulation to achieve direction-sensitive cladding mode coupling. Simultaneously, a 30-nm-thick nickel film is sputter-deposited onto the fiber end-face to form a single-ended reflection structure. This design eliminates complex processes like fiber taper drawing and eccentric fusion splicing, overcoming the stability limitations of existing vector sensors at elevated temperatures. Experimental results demonstrate spectral stability across the 25 degrees C-1020 degrees C temperature range and effective vibration measurement at 800 degrees C. At the room temperature and 800 degrees C, the acceleration sensitivities are 0.169 V/g (R 2=0.993) and 0.0743 V/g (R 2=0.989), respectively, with a common frequency response range of 15 Hz-25 Hz. The maximum angular response sensitivities are 2.4 V/g and 1.2 V/g, respectively, fully validating its reliable vector detection capability across a wide temperature range. This study provides a compact, mechanically robust, and high-temperature-resistant solution for vibration monitoring in extreme environments.
Infrared photodetectors exhibit significant applications in the fields, such as the defense military, industry, and consumer electronics. Leveraging the advantages, like adjustable bandgap, high carrier mobility, solution processing ability, and low cost, the InX (X: As, Sb) quantum dots (QDs) emerge as the promising candidate u201Cgreenu201D materials for next-generation infrared photodetectors, compared to Hg- and Pb-based infrared QDs. However, the controllable synthesis and improved photoelectric properties of InX QDs are limited by the strong covalent bonding between indium and heavy pnictogens and the high-density surface defects, resulting in device metrics that are yet to match those of their toxic counterparts. In recent years, the synergistic innovations in the synthesis technique, ligand engineering, and device structure design have led to significant improvements in the performance of InX QDs infrared photodetectors. This review focuses on the advances of InX QDs-based infrared photodetectors. Firstly, various synthetic methods of InX QDs are reviewed. Secondly, the performance optimization strategies (synthesis process optimization, surface passivation, and device structure design) of InX QDs infrared photodetectors are discussed in detail. Finally, the challenges and prospects for future research in InX QDs infrared photodetectors are proposed. Through a comparative analysis of the InAs and InSb QDs systems, this review establishes a clear u201Cmaterial-to-deviceu201D optimization path to unlock the full potential of InX QDs photodetectors and accelerate the development of stable, efficient, and eco-friendly infrared devices.
Ultrasensitive detection of the epidermal growth factor receptor (EGFR) gene in non-small cell lung cancer (NSCLC) remains a critical challenge for early diagnosis and targeted therapy. While fiber-optic biosensors offer promising sensing capabilities, their performance is fundamentally limited by the temperature fluctuation and insufficient limit of detection (LOD). In this work, an approaching 4-fold amplification of EGFR-binding spectral shifts is achieved through the Vernier effect (VE) in the cascaded Sagnac interferometer (SI) and Mach-Zehnder interferometer (MZI), whose free spectral ranges (FSRs) are deliberately mismatched. Temperature compensation is achieved through a contour-based differential demodulation method enabled by integrating a fiber Bragg grating (FBG) into the biosensor, which effectively decouples temperature variations from the deoxyribonucleic acid (DNA) molecular hybridization signals. Functionalized with mercaptoethylamine (MEA)-mediated self-assembled monolayers and single-stranded probe DNA (pDNA) specific to the EGFR gene, the biosensor achieves 53.7-fold specificity discrimination with the 25.1593 nm wavelength redshift for complementary DNA (cDNA) versus 0.4683 nm for non-complementary DNA (nonDNA), caused by refractive index (RI) changes resulting from DNA hybridization between pDNA and cDNA. The biosensor achieves a prominent LOD of 0.03363 pM for the synthetic EGFR gene in the buffer, surpassing existing interferometric biosensors by four orders of magnitude. This work not only establishes a new paradigm for overcoming the temperature drift in photonic biosensing but also employs the VE to significantly enhance the LOD, offering transformative potential for early diagnosis of NSCLC in clinical settings.
The performances of fiber-optic distributed acoustic sensing (DAS) systems are fundamentally limited by the trade-off between the sensing distance and response bandwidth (RB), constraining the effectiveness of the DAS for long-haul sensing applications greatly. To break such a limitation, this paper proposes a novel Zadoff-Chu (ZC) based nonlinear frequency modulation (ZC-NLFM) scheme that combines the zero-correlation property of the ZC method with the chirp diversity of NLFM. The generated ZC-NLFM pulses exhibit excellent sidelobe and inter-pulse interference suppression, enabling high-sensitivity DAS demodulation even under low signal-to-noise ratio conditions. Furthermore, by employing the large-effective-area fiber (LEAF) with the lower attenuation, higher stimulated Brillouin scattering threshold, and Raman amplification, a wide-frequency-range, long-distance, and low-noise DAS (WLL-DAS) with high strain sensitivity of 94.34 p epsilon root Hz over a wide RB of up to 7 kHz and an ultralong sensing distance of 148 km at the spatial resolution of 10 m is achieved simultaneously. Compared to the conventional DAS, the proposed WLL-DAS achieves a 22-fold increase in the RB over an ultralong distance of >140 km, significantly extending the performance boundary and application range of the DAS.
The advancement of the optical fiber sensing (OFS) technology is strongly linked to the development of light sources, while lasers play a crucial role in determining the performances of OFS systems for diverse sensing applications. Over the past 15 years, the OFS group at the University of Electronic Science and Technology of China (UESTC) has focused on the OFS with various light sources. Here, we review the history of the OFS advancement at UESTC and conduct an in-depth examination of the sensing strategies involving advanced light sources and cutting-edge sensors. By employing single-frequency lasers (SFLs), multi-frequency lasers (MFLs), and optical frequency combs (OFCs) across various sensing scenarios, the research team reports a number of novel OFS devices and systems, and showcases their sensing capabilities from point sensors to distributed sensing, and sensor networks. We highlight the role of novel light sources, particularly integrated OFCs, in enhancing the OFS. Our findings show that OFCs, with outstanding merits of the ultrahigh coherence, broad bandwidth, ultrafast detectability, and multi-channel parallelism, can significantly improve the capabilities and performances of the OFS used for detecting both physical and biochemical parameters. To conclude, we provide a systematic overview of the OFS advancement at UESTC, with SFLs/MFLs, as well as OFCs, and discuss the technical challenges and prospects, as well as potential developments of the OFC empowered the OFS. Also, a roadmap is proposed for transitioning the OFCs-based OFS technology from laboratory settings to practical applications.
Distributed acoustic sensing(DAS),based on phase-sensitive optical time-domain reflectometry(Ф-OTDR),transforms optical fibers into distributed vibration sensors through Rayleigh backscattering,enabling real-time industrial monitoring with extensive coverage and high spatial resolution.This review systematically presents key advances and industrial applications made by the optical fiber sensing(OFS)group at University of Electronic Science and Technology of China(UESTC),which include a differential-frequency modulation scheme integrated with a polarization-multifrequency diversity fusion algorithm and achieve pe-level strain sensitivity and suppressed signal fading down to 0.1％,enabling high-fidelity and long-distance sensing using low-cost commercial DAS units.Based on the advanced sensing capability,our developed adaptive feature enhancement method combined with an incremental tree classifier achieves the remarkable 96.55％recognition accuracy for ten types of pipeline intrusion events while reducing retraining time by 98.5％and further attains 99.96％accuracy for five major intrusion types in real field deployments.For railway infrastructure monitoring,our RailFusion-DAS framework utilizes existing fiber-optic cables along the railway to precisely identify three typical track defects with the 98.73％accuracy.Furthermore,by implementing time-frequency analysis and a two-dimensional convolutional neural network classifier on an artificial intelligence(AI)hardware accelerator,we realize an on-chip AI-DAS system that achieves 98.7％accuracy in online fault detection for belt conveyor idlers.
Fiber-optic distributed acoustic sensing (DAS) offers a promising solution for continuous traffic monitoring; however, its widespread deployment is often hindered by poor signal quality, resulting in fragmented and faint vehicle trajectories. Existing techniques - including conventional signal processing and deep learning models - struggle to accurately reconstruct trajectories and estimate traffic parameters under such challenging conditions. To overcome these limitations, we propose the DAS-hierarchical vehicle estimation network (DAS-HiVENet), an end-to-end framework that fundamentally advances the state-of-the-art through three key innovations: a two-stage preprocessing pipeline for noise suppression and trajectory preservation; a novel generative adversarial network (GAN) with an enhanced U-shaped convolutional neural network (U-net) generator to reconstruct high-fidelity trajectories from degraded inputs; a rotated-you only look once (R-YOLO) detector using oriented bounding boxes to accurately detect slanted trajectories. Extensive field evaluations on multiple expressways confirm that it surpasses existing methods with breakthrough performance: a trajectory intersection over union (IoU) of 0.7076, vehicle counting detection rate of 96.7%, and speed estimation errors as low as 1.422 km/h for the mean absolute error (MAE) and 1.796% for the mean absolute percentage error (MAPE) over 30 minutes. Even in challenging bridge scenarios with severe trajectory adhesion, DAS-HiVENet maintains an over 96% detection rate and under 4% MAPE in speed estimation - significantly outperforming alternatives.
In recent years,the fiber-optic distributed acoustic sensing(DAS)technology has played an important role in the oil and gas exploration and development.We develop an industrialized ultra-sensitive DAS instrument,named uDAS,which has world-class performances and robust engineering capability.The uDAS achieves the pε/√Hz level strain resolution and broadband frequency response from millihertz(mHz)to 10 kHz.The uDAS system has been widely applied to onshore and offshore vertical seismic profiling(VSP),hydraulic-fracturing monitoring,surface seismic exploration,near-surface structural investigation,and DAS-uphole,with deployments spanning all oilfields of China National Petroleum Corporation(CNPC),and part oilfields of Saudi Aramco and Abu Dhabi National Oil Company(ADNOC).In this paper,we introduce the key technologies of uDAS and its typical applications over the years.These applications demonstrate the uDAS's ultrahigh sensitivity,broadband frequency response,and high fidelity,enabling near-wellbore fine imaging,high-resolution visualization of downhole fracturing processes,and production optimization.The uDAS is becoming the new generation of all-optical geophones to replace the conventional electronic geophone arrays.
Brillouin optical time-domain reflectometry (BOTDR) is a key technique for distributed fiber sensing of strain and temperature, but performance is constrained by the inherently weak spontaneous Brillouin signal. Here, we propose and experimentally demonstrate a novel frequency- and time-division multiplexed BOTDR (FTDM-BOTDR) based on a frequency-stepped light source generated from a frequency-shifting loop. In contrast with existing multi-frequency BOTDR, Brillouin signals from all frequency channels are coherently detected with a single local oscillator (LO) light, maximizing LO power and thus the heterodyne gain for all channels simultaneously. Furthermore, the temporal interleaving of different pump frequencies avoids excessive Kerr nonlinearities. A theoretical model is developed to analyze the signal-to-noise ratio (SNR) in FTDM-BOTDR and illustrate how this single-LO configuration overcomes the SNR limit in conventional multi-frequency BOTDR systems. Using 13 frequency channels, the system achieves the Brillouin frequency shift (BFS) precision of 0.298 MHz at 10 km and a maximum sensing range of 70 km with a 40 ms acquisition time, representing a 3.3-fold precision improvement and a 30 km range extension compared to single-frequency BOTDR. This FTDM-BOTDR technique overcomes key performance bottlenecks of conventional BOTDR and provides a scalable pathway toward high-SNR, long-distance, and real-time distributed temperature or strain sensing.
To achieve the large-multiplexing capability, identical weak fiber Bragg grating (WFBG) sensors typically adopt a short grating length to reduce the reflectivity. However, the corresponding broadband reflection spectrum compromises the attainable wavelength-shift measurement precision. In this work, to overcome this limitation, an array of identical weak FBGs with extended grating lengths is employed, which facilitates the narrower bandwidth and improved spectral precision. Weaker refractive-index modulation is required in the FBGs with a longer grating length, which makes it harder to locate the individual FBG. A correlation-based algorithm is proposed for accurate WFBG localization, while the reflection signal is extracted using a window length precisely matched to the physical grating length for the suppression of the system noise. Experimental results using an array with 4000 identical WFBGs, each WFBG with a 10 mm grating length, demonstrate the strain measurement precision of 3.92 mu epsilon. The proposed approach effectively balances the requirements for the high sensor density and high measurement precision, enabling practical applications for real-time structural health monitoring and high-precision sensing systems.
High-resolution spectral measurement is essential for revealing the intrinsic material and structural properties, with broad applications in gas detection, environmental monitoring, biosensing, and materials analysis. Conventional strategies for enhancing spectral resolution typically focus on improving spectrometer hardware or employing sophisticated computational techniques, but they often face trade-offs between the resolution and bandwidth, or the high cost and measurement complexity. Super-resolution spectroscopy enabled by random lasers recently emerged as a promising strategy, yet existing implementations suffering from uncontrolled sampling signals and inefficient data acquisition. Here, we propose a reconfigurable fiber random laser that enables computational super-resolution spectroscopy. By integrating a multimode-single mode fiber filtering structure with controllable input wavefront modulation inside the laser, the system generates narrow-linewidth, sparse, and randomized emission modes, enabling flexible and efficient one-path spectroscopy without relying on the extra reference path. Our experiment compares pre-recorded reference modes with selectively reloaded sampling modes to reconstruct high-resolution spectra. Experimental results demonstrate a 2.2-fold enhancement in spectral resolution compared to the baseline spectrometer, which originally had 70 pm resolution. This work offers a versatile and low-cost solution for super-resolution spectroscopy, with the significant potential for a wide range of optical sensing applications.
Microfluidic liquid samples are crucial in both biomedical and chemical engineering, however, their in-situ identification and testing remain a major challenge. Here, we developed a non-contact photoacoustic (PA) sensor for in-situ and real-time identification and concentration detection of substances in a microfluidic environment. The ultrasonic vibration of the microfluidic samples was generated by a free-space pulsed laser pump and detected by a non-contact laser Doppler vibrometer. The time- and frequency-domain responses of the PA signals were employed to achieve substance identification and concentration detection. Principal component analysis (PCA) and adaptive boosting (AdaBoost) algorithms were employed to extract the frequency-domain characteristics, and an identification accuracy of over 98% was achieved. Chemical samples down to the nanomolar (nM) level can be detected by analyzing either the time-domain or frequency-domain response. The proposed sensor with non-contact and fast detection provides a promising platform for in-situ and real-time monitoring of samples in microfluidic systems.
