Tian Ma

Real time sensing of trace carbon monoxide (CO) gas is of great importance in many areas. Here, we propose a novel CO sensor based on a single-mode–no-core–single-mode (SNS) fiber structure coated with a nanocomposite of reduced graphene oxide and α-Fe2O3 (rGO/α-Fe2O3). The nanocomposite is synthesized via a solvothermal approach and deposited on the fiber surface to form a sensing layer. When exposed to the CO gas, the rGO/α-Fe2O3 nanocomposite absorbs the gas molecules, and its permittivity changes, resulting a modulation of the transmission dip intensity. The results show that the proposed sensor has excellent sensitivity and selectivity for CO gas. When the concentration of CO gas increases in the range of 0 – 100 ppm, the intensity of transmission dip decreases, leading to a CO sensitivity of ~0.0083 dBm/ppm and a low detection limit of 0.14 ppm. The response/recover time for 50 ppm CO are estimated to be ~174 s and 612 s, respectively. Notably, the sensor shows excellent selectivity, with responses to interfering gases being less than 10% of that to CO. These results demonstrate that the proposed sensor is a highly promising candidate for accurate and reliable CO detection in real-world applications.

This work demonstrates a flexible terahertz metasensor based on symmetry-broken quasi-BIC resonances, achieving high- Q resonance and strong field confinement for ultrasensitive, label-free detection of trace biomarkers such as l -tyrosine.

This work presents an all-dielectric chiral metasurface using circular air holes in an asymmetric monoclinic lattice to achieve strong circular dichroism, which enables label-free biosensing of BSA with high sensitivity and wide detection range.

Pipelines are vital in global energy industries, providing efficient methods for transporting natural gas and oil. Pipeline monitoring is crucial for detecting third-party intrusions and potential threats. Several approaches have been investigated in the field of pipeline threat detection, each offering distinct advantages and disadvantages. In contrast to conventional techniques, this work employs, to our knowledge, a novel strategy that uses both spatial and temporal data obtained from OTDR signals to identify third-party events in long-distance oil and gas pipelines. The proposed approach combines empirical mode decomposition (EMD), Markov transition field (MTF), and principal component analysis (PCA) to improve classification performance through machine learning techniques. Vibration signals of five typical threat events, including Hammer Digging, Hoe Digging, Excavator Digging, Human Jumping, and Human Walking are processed and transformed into two-dimensional MTF images by utilizing this approach, which are subsequently classified using machine learning models like backpropagation neural network (BPNN), random forest (RF), adaptive boosting (AB), and decision tree (DT). By integrating temporal and spatial characteristics, this approach improves the ability to distinguish between different third-party activities even if signals display slight deviations. Results indicate that all the classifiers perform well, achieving an accuracy of more than 95% while the backpropagation neural network demonstrated the highest classification accuracy across all event types, accomplishing an overall accuracy and F1 score of 99.10% and 99.49%, respectively. This shows the effectiveness of the proposed method for detecting complex events in long-distance pipeline safety monitoring, offering a swift and precise solution for pipeline surveillance applications.

Over recent years, chiral metasurfaces have emerged as pivotal platforms for ultrasensitive biosensing, particularly in detecting and identifying chiral biochemical samples. However, the excitation of chiroptical responses in conventional chiral metasurfaces predominantly rely on intricate asymmetric meta-atoms or elaborate geometric configurations, which complicate fabrication process and limit scalability. Here, we report an all-dielectric chiral metasurface consisting of an array of circular air-hole in monoclinic lattice. By breaking in-plane mirror symmetries through introducing side-length differences δ and changing lattice angle θ, the proposed metasurface achieves strong intrinsic chirality, yielding an enhanced circular dichroism (CD) signal with a simulated peak value of 0.89 at 0.254THz and a quality factor of ~50.4. Theoretical analyses of induced electromagnetic fields reveal that the observed chiroptical responses originate from spin-selective multipole excitations and localized field enhancements, where the left-handed circularly polarized (LCP) waves exhibit significantly stronger optical chirality (C_E=251) than that of the right-handed circularly polarized (RCP) waves. Experimental validations based on the fabricated sample and terahertz characterization confirm the excitation of resonant CD signals with peak value of ~0.52 around 0.25THz. Furthermore, we demonstrate practical biosensing capabilities of the proposed chiral metasurface by detecting bovine serum albumin (BSA) samples with different concentrations, which manifests good sensing performances including high sensitivity (0.023(mg/mL)^(-1)) and wide detection range (0.3-50 mg/mL). This work paves a new avenue for designing chiral metasurfaces with simple structures but high-performance, advancing practical applications in label-free biosensing and chiral nanophotonics.

Over recent years, chiral metasurfaces have emerged as pivotal platforms for ultrasensitive biosensing, particularly in detecting and identifying chiral biochemical samples. However, the excitation of chiroptical responses in conventional chiral metasurfaces predominantly rely on intricate asymmetric meta-atoms or elaborate geometric configurations, which complicate fabrication process and limit scalability. Here, we report an all-dielectric chiral metasurface consisting of an array of circular air-hole in monoclinic lattice. By breaking in-plane mirror symmetries through introducing side-length differences δ and changing lattice angle θ, the proposed metasurface achieves strong intrinsic chirality, yielding an enhanced circular dichroism (CD) signal with a simulated peak value of 0.89 at 0.254THz and a quality factor of ~50.4. Theoretical analyses of induced electromagnetic fields reveal that the observed chiroptical responses originate from spin-selective multipole excitations and localized field enhancements, where the left-handed circularly polarized (LCP) waves exhibit significantly stronger optical chirality (C_E=251) than that of the right-handed circularly polarized (RCP) waves. Experimental validations based on the fabricated sample and terahertz characterization confirm the excitation of resonant CD signals with peak value of ~0.52 around 0.25THz. Furthermore, we demonstrate practical biosensing capabilities of the proposed chiral metasurface by detecting bovine serum albumin (BSA) samples with different concentrations, which manifests good sensing performances including high sensitivity (0.023(mg/mL)^(-1)) and wide detection range (0.3-50 mg/mL). This work paves a new avenue for designing chiral metasurfaces with simple structures but high-performance, advancing practical applications in label-free biosensing and chiral nanophotonics.