This study proposes and validates a fabric-based multi-sensor integration solution: using an alkali-free glass fiber yarn woven substrate, it synergistically integrates fiber Bragg grating (FBG), optical frequency domain reflectometry (OFDR), and strain gauges onto a flexible fabric carrier via bonding and embroidery fixed on pipes for soil settlement monitoring. Load tests under exposed/buried conditions (1/3/5 cm soil cover) enable multi-source synchronous data acquisition, simulating soil settlement's impact on signals. Validated by finite element simulations, a Multilayer Perceptron (MLP) model integrated multi-source data to yield a strain prediction model (accuracy >93.9 %) and a load depth classification model (avg accuracy 96.57 %), establishing a data acquisition-strain prediction-operational condition assessment closed loop. The flexible fabric + multi-sensor collaboration concept adapts to complex scenarios, providing a scalable, low-cost paradigm for intelligent structural health monitoring and advancing infrastructure monitoring toward proactive risk prediction.

Pressure and temperature monitoring has become increasingly important in a wide range of industrial and biomedical applications. This study proposes a dual-mode demodulation sensor based on a packaged ring-shape microfiber interferometer (MFI) and a tilted fiber Bragg grating (TFBG), realizing simultaneous monitoring of pressure and temperature. The sensing region is realized by three functional components: the interference dip of the ring-shaped MFI for wavelength-shift interrogation, the TFBG core mode contributed to both wavelengthshift and intensity demodulation, and the spectral overlap between the TFBG cladding-mode resonances and the MFI for intensity interrogation. Under pressure loading, the sensor exhibits the wavelength sensitivities of -0.0949 nm/kPa (MFI interference dip) and 0 nm/kPa (TFBG core-mode), and the intensity sensitivities of -0.85074 dB/kPa (the overlapping peaks) and 0.06631 dB/kPa (TFBG core-mode). Under temperature variation, the sensor has the wavelength sensitivities of -1.3509 nm/ degrees C (MFI interference dip) and 0.01 nm/ degrees C (TFBG core-mode) are obtained, with the intensity sensitivities of -3.3821 dB/ degrees C (the overlapping peaks) and 2.06341dB/ degrees C (TFBG core-mode). The pressure and temperature changes are successfully retrieved through matrix-based decoupling method to feature temperature compensation capability. The sensor is compact and simple to implement, offering a feasible solution for pressure-temperature simultaneous sensing with temperature compensation.

The separation of minor actinides, especially americium, from lanthanides in spent nuclear fuel remains a critical challenge in nuclear waste management, primarily due to their nearly identical chemical behavior in the trivalent state. To address this, we target the linear dioxo configuration of pentavalent americium (AmO2+), which offers distinct steric and electronic features compared to spherical trivalent lanthanides. This work investigates Am(V) adsorption using a phenanthroline-based covalent organic framework (DAPhen-COF), where the pre-organized N,O-donor environment from the phenanthroline-amidine motif is designed for strong actinide coordination. Multiscale computations show that DAPhen-COF forms a highly stable complex with AmO2+. Density of states analysis reveals strong orbital hybridization between Am-5f and ligand N/O-2p states, underscoring substantial covalent interaction. Topological analysis of electron density confirms the existence of bonds with pronounced covalent character within highly polarized coordination environments, while electrostatic potential analysis verifies complementary electrostatic contributions. Energy decomposition analysis further quantifies the binding as a cooperative interplay between orbital and electrostatic forces. Quantitative adsorption energy calculations further corroborate these findings, revealing that DAPhen-COF exhibits a strong affinity for Am(V) (-151.9 kcal/mol) and clear selectivity over Eu(III), with the most stable configuration arising from cooperative actinide-actinide interactions within the confined COF interlayer space. This study not only sheds light on the unique coordination chemistry of pentavalent americium but also provides a robust theoretical foundation for designing ligand architectures capable of distinguishing actinides from lanthanides based on oxidation-state-specific motifs.

We experimentally investigate the superfluid-Mott insulator transition in a 23Na spin-1 Bose-Einstein condensate (BEC) with approximate SU(3) spin-rotation symmetry, focusing on the role of spin configurations in shaping the critical behavior. Rabi oscillation images of sodium atoms (F = 1) among three magnetic sublevels in an optical lattice are obtained, with experimental results aligning well with theoretical predictions, indicating robust quantum coherence in the lattice. The phase transition from the superfluid to the Mott insulator is observed by varying the lattice depth. We find the critical behavior is universal for different spin states, which is attributed to the SU(3) rotation symmetry among the spin components. The experimentally proposed critical regimes are consistent with the theoretical estimation given by the Thomas-Fermi approximation and strong-coupling expansion. These findings demonstrate that the SF-MI transition exhibits relatively unchanged critical behavior across different spin states due to SU(3) symmetry, revealing the universal phase transition for different spin configurations.

Due to the support of scattering wavefront shaping technology, scattering medium (SM) have significant potential in large-capacity, high-fidelity and crosstalk-free three-dimensional (3D) holographic projections. Here, an accumulation of multiplication algorithm (AOMA) was proposed to calculate binary holograms, so that the intensity distribution of 3D space can be simultaneously modulated behind SM using a hologram. In particular, AOMA is free from the need for signal feedback. It is simple and efficient to generate binary holograms with multiplication and addition. Experiments demonstrate that the intensity of axial four planes can be controlled simultaneously with a binary hologram, and the proposed AOMA is able to achieve high-fidelity four-plane focusing in the different modulation elements. Moreover, a wide-angle holographic focusing on two planes is also presented with a binary hologram in the high-dimensional modulation elements. To explore the anti-noise ability of AOMA, we further demonstrate 3D focusing performance with high-dimensional binary holograms at different interference environment. These advancements are expected to be beneficial to generate holograms for 3D scattering-enabled holographic projections.

Interlayer exciton-trion interconversion is central to two-dimensional excitonics, while electrically modulating the exciton interconversion in van der Waals heterostructures remains underexplored yet. Herein, we report a systematic investigation of interlayer many-body dynamics in a WS2/MoS2 van der Waals heterostructure subjected to a micrometer-scale vertical electric field generated by an atomic-force-microscope probe. By synergizing hyperspectral photoluminescence mapping with density-functional calculations, the abrupt and reversible switching of the trion/exciton intensity ratio has been observed at two critical biases (-0.054 and +0.076 V Å-1), which coincide with a type-II to type-I band-alignment crossover and a direct-to-indirect gap transition, respectively. The quantitative agreement between experimental values and mass-action theory across the entire electric field window demonstrates that a local vertical field affords spatially selective, continuous, and non-volatile control over interlayer exciton conversion, establishing a route toward reconfigurable 2D excitonics and field-programmable quantum emitters.

High-fidelity quantum state preparation is a central task in quantum information science. In practice, it is commonly guided either by full quantum state tomography, which becomes prohibitively resource-intensive as system size grows, or by empirically chosen measurement settings that lack principled optimality. Here we show that quantum state verification (QSV) can be elevated from a purely diagnostic tool to a prescriptive framework for quantum state preparation, directly specifying experimentally optimal measurements and quantitative fidelity indicators without full state reconstruction. We experimentally realize this prescriptive paradigm using a three-qubit nonstabilizer W state and a modified homogeneous QSV protocol. The verification measurements not only certify the prepared state with high confidence but also serve as a tomography-free indicator that systematically informs the preparation procedure. Using only nine measurement settings and 10^4 samples, we achieve high-fidelity state preparation consistent with full tomography that requires orders of magnitude more resources. Beyond the present implementation, the prescriptive structure of QSV is naturally compatible with closed-loop feedback control, outlining a pathway toward genuine real-time quantum state preparation in future low-latency platforms.

ABSTRACT Quantum‐correlated techniques enable high‐contrast and super‐resolution imaging through the feature of correlated photons. The superbunching effect with a second‐order correlation larger than 2, i.e., g (2) (0) > 2, demonstrates the existence of strong correlations between photons, which can enable stray light resistance and achieve high‐contrast imaging. Here, we present a scheme for quantum correlated imaging using single colloidal quantum dots (CQDs) with strong superbunching emission. The optimized CdSe/ZnS CQDs with g (2) (0) up to 69 and 20 under continuous‐wave and pulsed laser excitation have been prepared. We achieved noise‐resistant correlated biphoton imaging (CPI) based on single CQDs with noise intensity 104 times stronger than their photoluminescence. By modulating photoluminescence intensity, the Fourier‐domain CPI was determined with reasonably good contrast, despite noise 75 600 times stronger than biphoton counts. Our proposal may enable laboratory‐based quantum imaging to be applied to real‐world applications with the desired suppression of intense stray light.

InP/ZnSe/ZnS quantum dots (QDs) are promising candidates for advancing optoelectronic devices. However, their applications are limited by their low emission efficiency caused by photo-oxidation. In this study, we investigate the impact of photo-oxidation on the emission of InP/ZnSe/ZnS QDs at the ensemble and single-particle levels. Transient absorption spectroscopy reveals that photo-oxidation-induced ultrafast exciton trapping exhibits complex, multitime scale decay dynamics ranging from sub-nanoseconds to picoseconds, indicating that photo-oxidation-induced surface defects form high-density trap states with a broad, continuous energetic distribution. Single-QD spectroscopy shows that these trap states act as multiple nonradiative recombination centers that trigger band-edge carrier blinking. The extensive formation of photo-oxidation-induced defects results in photoluminescence (PL) quenching of single QDs. Monte Carlo simulations reproduce ultrafast exciton trapping-induced PL blinking and quenching and quantify the nonradiative recombination rates involved in these processes. These findings provide new insights into the photodegradation of InP QD materials and devices due to photo-oxidation and contribute to the design of novel antioxidant materials.

A highly sensitive COF-V@ENR Apt/DA-modified fiber ring laser (CED-FRL) system is developed to detect trace-level enrofloxacin (ENR). The system is constructed by integrating a microfiber coated with a composite film of dopamine (DA), covalent organic framework (COF-V) and enrofloxacin aptamer (ENR Apt) into a fiber ring laser (FRL). This system exhibits a refractive index (RI) sensitivity of 1240.288 nm/RIU and a temperature sensitivity of -0.0379 nm/°C. For ENR detection, it shows a significant response over 0.01-100 nM, with a sensitivity of 8.668 nm/nM in 0.01-0.1 nM and a limit of detection (LOD) of 0.009 nM. This biosensor shows high specificity for ENR and performed reliably in real samples. Furthermore, the Gradient Boosting (GB) model is applied for training and validation of the data, achieving a coefficient of determination (R2) of 0.9970. With high sensitivity, strong specificity and good stability, this system has great potential for food safety and environmental monitoring.

To tackle challenge of achieving both flexible deployment and precise response in monitoring the vertical shear deformation of deep slopes, this study proposes a composite sensor-the fiber Bragg gratings (FBG) based on aramid fabric-for slope vertical shear deformation monitoring, which uses high-strength aramid fabric as the flexible substrate and integrates polydimethylsiloxane (PDMS)-encapsulated FBGs. We have conducted experiments to explore the relationship among soil cover thickness, strain variations, and grating wavelength shifts, and have carried out numerical simulations incorporating the mechanical parameters of aramid fabric to verify the strain gradient distribution at the shear interface and the patterns of deformation concentration to receive the consistent with experimental results and simulation results. Furthermore, utilizing the Gradient Boosting Decision Tree (GBDT) model, the prediction accuracy for soil cover thickness and strain sensing point position reached 0.9688 and 0.9583, respectively, further validating the reliability of the experimental data. This study demonstrates that this composite sensor can accurately capture strain gradients, identify the initiation and expansion of sliding surfaces, and thus enable full-process dynamic tracking of the slope’s overall deformation.

In the field of landslide disaster monitoring, optical fiber sensing, with its advantages such as anti-electromagnetic interference, corrosion resistance, and intelligent monitoring, has solved the problems of traditional landslide monitoring systems and has become a core technical means for real-time grasp of the deformation, strain, and environmental conditions of landslide bodies. This study proposes an emerging combined optical-fiber inclinometer composed of a single-mode optical fiber (for distributed sensing) and two groups of fiber Bragg grating (FBG) arrays (for high-precision point monitoring), which is symmetrically adhered to the inner wall of a polyvinyl chloride (PVC) tube using an epoxy resin adhesive. The strain data are collected by the optical frequency domain reflectometer (OFDR), combined with the wavelength drift data obtained by the fiber grating demodulator, which enables large-scale capture of the overall dynamic trend of the landslide mass and precise acquisition of the displacement size of local key points, providing more comprehensive and reliable multi-dimensional data support for landslide disaster early warning. In addition, by combining strain data and wavelength drift data with deep learning, the displacement of the grating position can be accurately predicted, with an overall prediction accuracy rate exceeding 97%. This proposed combined optical-fiber inclinometer is of great significance for improving the timeliness and accuracy of landslide monitoring and early warning, and also provides a new technical path for landslide prevention and mitigation efforts in complex geological environments.

Accurate real-time soil settlement monitoring in geological hazard prone areas is critical for engineering safety warnings. While fiber Bragg grating (FBG) sensors offer immunity to electromagnetic interference and corrosion, they are prone to mechanical damage during construction and long-term use. To address this issue, this study proposes a dual-array FBG nested-tube sensor to enhance field operability and protection performance. The feasibility of strain transfer of the nested-tube structure is first verified, and then settlement experiments of gradient fill thicknesses (0, 1, 2, 4, and 6 cm) are carried out in a simulation chamber while strain is monitored simultaneously using an optical frequency domain reflectometer (OFDR). Furthermore, machine learning algorithms are employed: a Support Vector Regression (SVR) model to predict continuous settlement displacement, and a Random Forest classifier to identify displacement states. The SVR model demonstrates high prediction accuracy, while the Random Forest classifier achieves an accuracy exceeding 96.67 % across all fill thickness conditions. Results indicate that the nested-tube structure effectively protects the FBG sensors from mechanical fracture, and isolates environmental interference to ensure consistent wavelength shift trends across varying thicknesses. This study clarifies the application potential of the FBG nested-tube sensor and provides a solid technical foundation for its practical use in geotechnical deformation monitoring.

Thouless pumping provides a paradigmatic platform for studying the effects of interactions on topological transport in periodically driven systems. However, most studies have been constrained by adiabatic conditions, which preclude exploration of interaction-driven novel topological states at high driving frequencies. Here, we experimentally investigate the interplay between interaction and modulation frequency in Thouless pumping realized in a periodically modulated lattice in momentum space of atomic Bose-Einstein condensate. We observe fast Thouless pumping of matterwave solitons at intermediate interactions, with no counterpart in the non- or weakly interacting regimes. Beyond the boundary of topological phase transition induced by interaction, nonadiabatic quantized pumping of solitons emerges at high modulation frequencies over a broad interaction range, in good agreement with theoretical calculations, while the solitons remain trapped in the low-frequency adiabatic pumping regime. Our work opens new avenues for accelerating topological transport in driven quantum systems and engineering fast topological devices.

Colloidal quantum dots (QDs) are promising optical gain materials that require a reduction in the threshold to reach their full potential. While QD charging theoretically reduces the threshold to zero, its effectiveness has been limited by strong Auger recombination and unstable charging. In this study, we theoretically determine the optimal combination of charging number and Auger recombination to minimize the lasing threshold. Experimentally, we develop stable, self-charged perovskite quantum rods (QRs) as an alternative to QDs via the state engineering and Mn (manganese) doping strategy. A two-order-of-magnitude reduction in nonradiative Auger recombination enables QRs to support a charging number of up to 6. We then achieve QR liquid lasing with a sub- 1 / 10 exciton threshold (an average of 0.098 excitons per QR) using 5-nanosecond pulse pumping. This threshold is exceptionally low among all reported QD lasers. These achievements demonstrate the potential of specially engineered QRs as excellent gain media and pave the way for their applications.

Urgent demand for point-of-care testing (POCT) in the fields of biomedicine, environmental monitoring, and food safety has driven the rapid development of biosensors. With its significant advantages of low cost, strong portability, and ease of use, paper-based biosensors have become an ideal platform. Metal-organic frameworks (MOFs), with their high specific surface area, tunable structure, and designable functions, provide a key breakthrough for paper functionalization to meet the growing demands of various applications. This article systematically summarizes recent advances in MOFs integrated paper-based biosensors for POCT. It begins by outlining the types of paper-based devices and MOFs, as well as strategies for functionalizing MOFs onto paper substrates. Subsequently, the design principles and signal amplification mechanisms of MOFs integrated paper-based biosensors are discussed separately under different signal reading methods. Furthermore, it demonstrates the potential applications of such biosensors in detecting disease biomarkers, monitoring environmental pollutants, and ensuring food safety. Ultimately, the current challenges in stability, large-scale production, and applicability to real samples are summarized. It is envisioned that incorporating artificial intelligence and machine learning technologies into MOFs integrated paper-based biosensors will further enhance their performance and advance the development of intelligent platforms for POCT.

Traditional soil settlement monitoring fails to capture dynamic evolution accurately, endangering engineering safety. Here, a fiber Bragg grating-integrated 3D trajectory pipe sensor (SST-3D) is developed for soil settlement strain monitoring, combined with machine learning for loess settlement stage prediction. Air tests verify FBG wavelength shift has a good linear strain relationship; soil burial tests identify four strain response stages during drainage, namely initial rapid response, relative stability, pre-collapse dynamic stage, and post-collapse sustained response. The Frenet frame enables accurate 3D morphological reconstruction of SST-3D in both conditions. Among four machine learning algorithms, Random Forest performs best, with 95.65% classification accuracy for the loess collapse stage and only 4.02% regression relative error. The successful development and experimental verification of the SST-3D sensor has achieved precise perception and dynamic monitoring of the multi-directional settlement morphology of soil.