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Abstract The electrochemical splitting of water for hydrogen production faces a major challenge due to its anodic oxygen evolution reaction (OER), necessitating research on the rational design and facile synthesis of OER catalysts to enhance catalytic activity and stability. This study proposes a ligand‐induced MOF‐on‐MOF approach to fabricate various trimetallic MnFeCo‐based Prussian blue analog (PBA) nanostructures. The addition of [Fe(CN)6]3− transforms them from cuboids with protruding corners (MnFeCoPBA‐I) to core–shell configurations (MnFeCoPBA‐II), and finally to hollow structures (MnFeCoPBA‐III). After pyrolysis at 800 °C, they are converted into corresponding PBA‐derived carbon nanomaterials, featuring uniformly dispersed Mn2Co2C nanoparticles. A comparative analysis demonstrates that the Fe addition enhances catalytic activity, while Mn‐doped materials exhibit excellent stability. Specifically, the optimized MnFeCoNC‐I‐800 demonstrates outstanding OER performance in 1.0 m KOH solution, with an overpotential of 318 mV at 10 mA cm−2, maintaining stability for up to 150 h. Theoretical calculations elucidate synergistic interactions between Fe dopants and the Mn2Co2C matrix, reducing barriers for oxygen intermediates and improving intrinsic OER activity. These findings offer valuable insights into the structure‐morphology relationships of MOF precursors, advancing the development of highly active and stable MOF‐derived OER catalysts for practical applications.

According to the characteristics of ant colony optimization (ACO) algorithm in mobile robot path planning, such as local optimal solution, slow convergence speed, low search efficiency, and propensity to produce numerous deadlock ants, an improved ACO algorithm based on island type (insular ACO (INACO)) is introduced. In this algorithm, firstly, several islands are established between the starting and the ending position of environment, serving as intermediate nodes for the paths searched by the ants. This greatly reduces the number of deadlock ants. Additionally, rectangular areas are initialized with non-uniform pheromone levels between adjacent islands, while other areas are set to a constant minimum pheromone value. This prevents blind searches during the initial stages of path planning. Furthermore, an adaptive volatilization coefficient is introduced into the global pheromone update rules to balance the convergence and global search ability. Finally, optimal parameter combinations of INACO are determined by simulation. INACO algorithm is simulated in various grid maps and compared with other improved ACO algorithms. Results demonstrate its superior global optimal search capability and rapid convergence speed. The average iterative times is 2.7 in a 20 × 20 grid environment and 4.7 in a 30 × 30 grid environment. Notably, INACO produces very few lost ants, with mean values of 50.1 and 95.2 in 20 × 20 and 30 × 30 grid environments, respectively.

Highly thermostable RhB@Zr-Eddc composites with the Rhodamine B (RhB) enclosed into the nanocages of Zr-Eddc was synthesized by one-pot method under hydrothermal conditions, whose structure, morphology and stability were characterized through the X-ray powder diffractometry (XRD), scanning electron microscopy (SEM) and thermogravimetric analysis (TGA). RhB@Zr-Eddc showed the highly thermal stability up to 550°C and emitted the bright red-light emission at 605 nm, which could highly selective detect the nitrofurazone (NFZ) among eleven other antibiotics in aqueous solution. Furthermore, via combining the RhB@Zr-Eddc with commercial green phosphor (Y3Al5O12:Ce3+, Ga3+), the mixture was encapsulated onto a 455 nm blue LED chip, creating an ex-cellent white light emitting diode (WLED) device with the correlated colour temperature (CCT) of 4710 K, luminous efficiency (LE) of 43.17 lm/w and Color Rendering Index (CRI) of 89.2.

To solve the problems of limited computing power resources, low accuracy of small target detection, high miss rate, and poor real-time detection of mobile vehicle platforms in the automatic driving environment, The present study introduced a one-stage target detection algorithm TTD-YOLO (Traffic Target Detection YOLO) that improved YOLOV5-S, which is enhanced in four aspects: Enhanced the network’s multi-scale feature extraction performance through the utilization of the improved M-ELAN architecture; added 3D attention mechanism SimAM to the network structure to enable the network to learn important feature information and enhance the efficiency of detecting accuracy; the parameter ratio of backbone and neck is adjusted to close to 1:1 by adjusting the number of output channels and stacking times of CSPLayer modules in the backbone and neck, while maintaining the model complexity, experiments show that improving the neck’s parameter ratio helps enhance the efficiency of detecting accuracy without changing the network structure; used EIoU loss instead of the bounding box loss function accelerates network convergence and improved detection accuracy. Under the condition of avoiding significantly changing the network structure, our TTD-YOLO outperforms the baseline model and other mainstream object detection algorithms such as Faster RCNN, SSD, and YOLOX-S on the autopilot dataset SODA10M with fewer parameters, higher detection accuracy, and faster inference speed. Compared to the baseline model, the model parameters decreased by 8.6%, average precision(mAP@.5:.95)increased by 2.5%, and the inference speed under the same experimental platform increased by 4.8%.

The strategic development of reverse logistics networks is crucial for addressing the common challenge of low recovery rates for end-of-life vehicles (ELVs) in China. To minimize the total cost of the reverse logistics network for ELVs, this paper proposes a mixed-integer linear programming (MILP) model. The model considers the recycling volume of different vehicle types, facility processing capacity, and the proportions of parts and materials. Building on this foundation, a fuzzy mixed-integer nonlinear programming (FMINLP) model is developed to account for the inherent uncertainty associated with recycling volumes and facility processing capacities. The model was solved using Lingo, and its effectiveness was validated using Jiangsu Province of China as a case study, followed by a sensitivity analysis. The results indicate that dismantling and machining centers incur the highest processing costs. Variations in recycling volume and facility handling capacity significantly impact total costs and site selection, with the former having a more pronounced effect. Increasing facility processing capacity effectively increases the recovery rate. Moreover, a higher confidence level corresponds to higher total costs and a greater demand for facilities.

Accurate and robust localization is one of the key modules of autonomous driving and multi-sensor robotic systems in complex urban scenes. Compared with camera-based localization, which is sensitive to the influence of light changes caused by different environments, LiDAR-based localization has higher accuracy and robustness. However, the existing LiDAR localization often assumes that the scene is static and ignores the impact of moving objects on localization and mapping. At present, globally consistent multi-sensor localization is an open issue, especially in the complex dynamic environment. We propose a LiDAR-based dynamic scene perception and multi-sensor localization framework. To improve the localization robustness in dynamic complex scenes, we design a moving object segmentation (MOS) module based on spatio-temporal information, and further optimize ground segmentation. On this basis, we design a lightweight, tightly-coupled LiDAR-IMU-GNSS odometry framework, which achieves accurate and real-time position estimation. In the front-end, based on the iterative Extended Kalman filter, we directly register the original 3D point cloud to the map without a feature extractor, which can adapt to different LiDAR scanning patterns, and then can be tightly-coupled with IMU data. Compared with the existing methods, we verify the proposed MOS performance on KITTI datasets, and our approach achieves state-of-the-art performance. In addition, we demonstrate the localization performance of the proposed framework on two public datasets and one solid-state LiDAR dataset. The results show that our system is more accurate than the existing advanced fusion-based localization method.

For intelligent transportation systems, moving object segmentation (MOS) provides valuable information for robots and intelligent vehicles, such as collision avoidance, path planning, and static map construction. However, all existing 3D point cloud MOS methods are based on LiDAR-only, which limits the ability to fuse supplementary information from different sensors. In this article, we solve the robust and accurate 3D MOS problem by designing a dual-stream network that integrates point clouds and images. We propose a perspective residual mechanism to mine the spatio-temporal motion information of point clouds, and design a fusion module based on Transformer Attention to extract multi-scale feature information from point clouds and images, improving the segmentation integrity of moving objects. Many experiments on the benchmark dataset show the superiority of our method. On the Semantic-KITTI, we outperform the advanced method by 6.5% mIoU. And we further apply our proposed model to the Semantic-KITTI: Moving Object Segmentation competition and achieve an advanced ranking on the leaderboard.

Motion planning between dynamic obstacles is an essential capability to achieve real-world navigation. In this study, we investigated the problem of avoiding dynamic obstacles in complex environments for a car-like mobile robot with an incompletely constrained Ackerman front wheel steering. To address the problems of weak dynamic obstacle avoidance and poor path smoothing in motion planning with the traditional Timed Elastic Band (TEB) algorithm, We proposed a hybrid motion planning algorithm (TEB-CA,Timed Elastic Band-Collision Avoidance) that combines an improved traditional TEB algorithm and Optimal Reciprocal Collision Avoidance (ORCA) model to improve the ability of the robot to predict dynamic obstacles in advance and avoid collisions safely. Moreover, We also add new constraints to the traditional TEB algorithm, including: jerk constraints, smoothness constraints, and curvature constraints. The algorithm is implemented in $C++$ and evaluated experimentally in the Gazebo and Rviz simulation environments of the Robot Operating System (ROS), as well as in actual experimental tests on our car-like autonomous mobile robot “Little Ant” which proves the effectiveness of the method, and that the motion planning scheme is more effective in avoiding dynamic obstacles than the traditional TEB and DWA algorithms.

Wireless power transmission technology based on coil coupling has been widely applied in various fields. However, the performance of the system is affected by the malposition of the transmission coil-couple, which is inevitable in the wireless power transmission system (WPTS). In this study, a multi-transmitter coil array is proposed to build a more uniform magnetic flux density for the WPTS, intending to enhance the performance of the WPTS in the case of coil-couple malposition. The model of the transmission system is built and different coil arrangement methods are analyzed. Then, the magnetic field distributions of the proposed WPTS with different coil arrays are compared using numerical simulations. Experiments are conducted to investigate the performances of the designed WPTS. The results show that WPTS with a seven-coil array can provide a more uniform magnetic field for the WPTS, whose relative deviation of output power is less than 28.55%. This study provides some clues for improving the performance of the WPTS through different arrangements of the transmitter coils.

Purpose – This paper aimed a fractional-order sliding mode-based lateral lane-change control method that was proposed to improve the path-tracking accuracy of vehicle lateral motion. Design/methodology/approach – In this paper the vehicle presighting and kinematic models were established, and a new sliding mode control isokinetic convergence law was devised based on the fractional order calculus to make the front wheel turning angle approach the desired value quickly. On this basis, a fractional gradient descent algorithm was proposed to adjust the radial basis function (RBF) neuron parameter update rules to improve the compensation speed of the neural network. Findings – The simulation results revealed that, compared to the traditional sliding mode control strategy, the designed controller eliminated the jitter of the sliding mode control, sped up the response of the controller, reduced the overshoot of the system parameters and facilitated accurate and fast tracking of the desired path when the vehicle changed lanes at low speeds. Originality/value – This paper combines the idea of fractional order calculus with gradient descent algorithm, proposed a fractional-order gradient descent method applied to RBF neural network and fast adjustment the position and width of neurons.

Abstract The photocatalytic transformation of carbon dioxide (CO2) into carbon‐based fuels or chemicals using sustainable solar energy is considered an ideal strategy for simultaneously alleviating the energy shortage and environmental crises. However, owing to the low energy utilization of sunlight and inferior catalytic activity, the conversion efficiency of CO2 photoreduction is far from satisfactory. In this study, a MOF‐derived hollow bimetallic oxide nanomaterial is prepared for the efficient photoreduction of CO2. First, a unique ZIF‐67‐on‐InOF‐1 heterostructure is successfully obtained by growing a secondary Co‐based ZIF‐67 onto the initial InOF‐1 nanorods. The corresponding hollow counterpart has a larger specific surface area after acid etching, and the oxidized bimetallic H‐Co3O4/In2O3 material exhibits abundant heterogeneous interfaces that expose more active sites. The energy band structure of H‐Co3O4/In2O3 corresponds well with the photosensitizer of [Ru(bpy)3]Cl2, which results in a high CO yield of 4828 ± 570 µmol h−1 g−1 and stable activity over a consecutive of six runs, demonstrating adequate photocatalytic performance. This study demonstrates that the rational design of MOF‐on‐MOF heterostructures can completely exploit the synergistic effects between different components, which may be extended to other MOF‐derived nanomaterials as promising catalysts for practical energy conversion and storage.

Owing to the disadvantages of the segmental baffle heat exchanger (SBHE–STHE), a novel type of supporting baffle longitudinal flow heat exchanger is proposed and numerically studied. This equipment includes hexagonal cinquefoil, regular quadrangular, trefoil fillet, and reticulated orifice baffle heat exchangers. The flow and heat transfer performance of the four noncircular orifice supporting baffle longitudinal flow heat exchangers are investigated. Combined sections were fabricated, and local performance characteristics of temperature, pressure, and flow field contours were examined. A composite dimensionless index based on SBHE–STHE is proposed to quickly estimate the comprehensive characteristics of the four supporting baffle longitudinal flow heat exchangers. Results show that the noncircular orifices within the supporting baffle induce jet flow and fluid disturbance. Consequently, periodic pulsating vortices among adjacent supporting baffles are generated, explaining the heat transfer enhancement mechanism. The heat transfer capability of the reticulated orifice baffle heat exchanger is higher than that of the other three orifice baffle schemes and similar to that of the SBHE–STHE. All the comprehensive performance indices of the four noncircular orifice schemes are higher than those of the SBHE–STHE.

A mixed lanthanide organic framework was prepared via hydrothermal methods using m-phthalic acid (m-H2BDC), 1,10-phenanthroline (1,10-Phen), and Ln3+ ions, formulated as [HNMe2][Eu0.095Tb1.905(m-BDC)3(phen)2] (ZTU-6). The structure and stability of ZTU-6 were characterised by X-ray diffraction (XRD) and thermogravimetric analysis (TGA), which revealed a three-dimensional pcu topology with high thermal stability. Fluorescence tests showed that ZTU-6 emitted orange light with a high quantum yield of 79.15%, and it can be effectively encapsulated in a light-emitting diode (LED) device emitting orange light. In addition, ZTU-6 was found to be compatible with BaMgAl10O17:Eu2+ (BAM) blue powder and [(Sr,Ba)2SiO4:Eu2+] silicate yellow and green powder to create a warm white LED with a high colour rendering index (CRI) of 93.4, a correlated colour temperature (CCT) of 3908 K, and CIE coordinates of (0.38, 036).

The thermoelectric characteristics of the thermoelectric power generation based on waste heat recovery, including the influence factors of cooling water flow rate, the overlapping value between load resistance and internal resistance and pressing block weight, were experimentally discussed. In addition to the experimental analyses of simple series-parallel configuration, the thermoelectric characteristics of complex series-parallel configurations were numerically simulated. The fast locating method was proposed to achieve the optimal thermoelectric characteristic. The results showed that the cooling water flow rate makes slight impact on total pressing block weight. All the thermoelectric characteristics increase with increasing pressing block weight. The overlapping value between internal resistance and load resistance is an core index, which determines the optimum thermoelectric efficiency. The changing law of thermoelectric characteristics of numerical simulations are identical with testing data, but the smoothness of simulation curves are better. Three complex series-parallel configurations perform identical total output power characteristic, which increases with increasing thermoelectric modules. However, the output power of a single thermoelectric module exhibits unique characteristic. The inflection points and peak value points in DSIP, ISDP and ISIP configurations are used to examine the output power characteristics of thermoelectric power generation and a single thermoelectric module.

Robust DUT-67 was synthesized by the hydrothermal method and characterized by powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), and thermogravimetric analysis (TGA). To systematically study the removal of Cr(VI) ion by DUT-67, single-factor, competition ion, material regeneration, kinetic, and thermodynamic experiments were designed. The experimental results show that DUT-67 had a maximum removal rate of 96.1% and a maximum adsorption capacity of 105.42 mg g−1 with material regeneration and outstanding selective adsorption. In addition, the process of removal of the Cr(VI) ion from an aqueous solution by DUT-67, which accorded with the pseudo-second-order kinetics model and Langmuir model, was studied, and its adsorption mechanism was reasonably explained by the theoretical calculation.

Introduction: Speed modulation methods have been studied and even used clinically to create extra pulsation in the blood circulatory system with the assistance of a continuous flow rotary blood pump. However, fast speed variations may also increase the hemolysis potential inside the pump.Methods: This study investigates the hemolysis performance of a ventricular assist rotary blood pump under sinusoidal, square, and triangular wave speed modulation profiles using the computational fluid dynamics (CFD) method. The CFD boundary pressure conditions of the blood pump were obtained by combining simulations with the pump’s mathematical model and a complete cardiovascular lumped parameter model. The hemolysis performance of the blood pump was quantified by the hemolysis index (HI) calculated from a Eulerian scalar transport equation.Results: The HI results were obtained and compared with a constant speed condition when the blood pump was run under three speed profiles. The speed modulations were revealed to slightly affect the pump hemolysis, and the hemolysis differences between the different speed modulation profiles were insignificant.Discussion: This study suggests that speed modulations could be a feasible way to improve the flow pulsatility of rotary blood pumps while not increasing the hemolysis performance.

The prediction of reservoir bank collapse width is a unique problem encountered in the construction of hydropower projects. Existing empirical graphic methods are based on the final state of bank collapse and can be used to predict only bank collapse width, and they thus do not adequately reflect the characteristics of the bank collapse process. To solve this problem, a prediction model for bank collapse width based on the limit equilibrium theory was established, and the key parameters and bank collapse process of the model were analyzed. The results reveal the necessity of selecting a reasonable underwater accumulation rate when predicting the bank collapse width using the limit equilibrium theory. At a constant ratio of water depth to bank slope height, the underwater accumulation rate increases with increasing bank slope height, with a linear relationship between them. In contrast, the bank slope angle has little impact on bank collapse width. Specifically, it mainly affects the width of the first bank collapse but has little effect on the width of subsequent bank collapses. With an increase in the bank slope angle, the bank collapse width fluctuates and rises. The prediction model of bank collapse width based on the limit equilibrium theory can better explain the time-dependent behavior of bank collapse. The research results are of high significance for the prediction of loess bank collapse.

Thermal discomfort, fuel wastage, health risks, and the death threat of passengers/infants due to the hot soak of car cabin is a hot spot topic all the time. Therefore, the transient analysis method is used to study the distribution of the heat soak temperature in the passenger compartment under different orientation. Besides the research analyzed the effects of four ventilation cases on the driver and rear infant. The results show that both of the driver and infant are subjected to the lowest heat load while the vehicle parked outdoors is facing east at 14:00 and the air temperature around the driver is about 52 °C. The roof ventilation is a effective energy conservation ventilation way for both of driver and infant, as there is the most heat removal efficiency(0.471) and the best cooling effect. The head temperature of driver and infant in roof ventilation is at least 7 °C and 3 °C lower than the other three cases. In addition, the seats ventilation is a better heating way for driver than other ventilation cases, because the air temperature is more even and can be heated to 26.5–29.2 °C for the driver.

To improve the finding path accuracy of the ant colony algorithm and reduce the number of turns, a jump point search improved ant colony optimization hybrid algorithm has been proposed in this article. Firstly, the initial pheromone concentration distribution gets from the jump points has been introduced to guide the algorithm in finding the way, thus accelerating the early iteration speed. The turning cost factor in the heuristic function has been designed to improve the smoothness of the path. Finally, the adaptive reward and punishment factor, and the Max–Min ant system have been introduced to improve the iterative speed and global search ability of the algorithm. Simulation through three maps of different scales is carried out. Furthermore, the results prove that the jump point search improved ant colony optimization hybrid algorithm performs effectively in finding path accuracy and reducing the number of turns.

Abstract This study was focused on Hangzhou in China that are undergoing large‐scale subway construction, and an improved momentum back‐propagation (BP) neural network model was trained. The model can analyze the complex traffic data, evaluate the service quality of bus line, and improve the estimation accuracy and convergence speed. For the same training data set, the convergence time of the BP algorithm with momentum term is reduced by 0.043 secs, the iterative convergence speed is improved by 0.66%, and the estimation accuracy is improved by 26.7% compared with the standard BP algorithm. Under similar conditions, the convergence time is 1.562 secs less than that of the standard BP algorithm, and the convergence speed was 24.1% higher than that of the standard BP algorithm, and the absolute value of the estimated error was less than 1%. Finally, a representative bus line in Hangzhou was used as an example to evaluate the model. The results showed that the improved momentum BP neural network model had a faster convergence speed and higher prediction accuracy of the comprehensive weight of bus line service quality. The prediction results of the model are consistent with the actual survey results, which indicates that the model constructed is reasonable.

Implanted medical devices that have poor friction property or biofilm formation can limit their service life and cause discomfort in patients. Recently, some zwitterionic coatings have been studied to modify the biomaterials surface for lubricating function, but the grafting methods of coatings are complicated and also seldom take the bacterial antiadhesion property into account at the same time. In our studies, motivated by the properties of nature mussels and human articular, we firstly successfully synthesized double adhesion protection of self-adhesive ternary polymer coating and achieved the excellent lubrication and antifouling functionalization of the medical devices surface. In details, the X-ray photoelectron spectroscopy, scanning electron microscope and the water contact angles could characterize the successful modification on the surface of titanium substrate. Additionally, the tribological tests carried out by atomic force microscope verified the ternary polymer could enhance the lubrication property owing to the hydration lubrication mechanism. Meanwhile, it also possessed the bacterial antiadhesion property for the initial 24 h attributed to the hydration repulsive force. We believe that, as a simple and universal preparation method, the ternary polymer could make a great significance for improving the surface function of biomaterials and alleviating patients’ discomfort.

Purpose – The operation state of lithium-ion battery for vehicle is unknown and the remaining life is uncertain. In order to improve the performance of battery state prediction, in this paper, a joint estimation method of state of charge (SOC) and state of health (SOH) for lithium-ion batteries based on multi-scale theory is designed. Design/methodology/approach – In this paper, a joint estimation method of SOC and SOH for lithium-ion batteries based on multi-scale theory is designed. The venin equivalent circuit model and fast static calibration method are used to fit the relationship between open-circuit voltage and SOC, and the resistance and capacitance parameters in the model are identified based on exponential fitting method. A battery capacity model for SOH estimation is established. A multi-time scale EKF filtering algorithm is used to estimate the SOC and SOH of lithium-ion batteries. Findings – The SOC and SOH changes in dynamic operation of lithium-ion batteries are accurately predicted so that batteries can be recycled more effectively in the whole vehicle process. Originality/value – A joint estimation method of SOC and SOH for lithium-ion batteries based on multi-scale theory is accurately predicted and can be recycled more effectively in the whole vehicle process.

Mediating the divergent interest of vehicle stability and strengthened path tracking performance when aiming at the design of a path tracking controller for autonomous vehicles is a challenging issue. Accordingly, this paper proposes an improved-LQR (linear quadratic regulator) control applied using an improved path planning algorithm. A feedforward and feedback LQR control is constructed by applying the path optimization solution method, which is a different traditional polynomial trajectory fitting method, and then solving the path planning information and the control input parameter in real time to make the tracking error as convergent as possible. To verify the superiority of the improved-LQR, this study compares the proposed controller and model predictive control by the traditional path solving method on a closed-loop test road using Carsim/Simulink. The comparative results show the efficiency, accurate tracking, vehicle stability, and reliability of the proposed controller.

Inspired by shallow-water sloshing in a moving tank, a novel type of vibration-based piezoelectric energy harvesting device composed of a piezoelectric bimorph beam and an extension tank is proposed in this paper. The structure and working principle of the proposed device are provided. Then, the effects of different heights of water filling in the tank on the performances of the harvester are studied and analyzed. Experiments are set up to investigate the actual device performance by changing the base excitation frequency and load resistance for different water heights. The results show that by modulating the water height, the resonant frequency and bandwidth can be adjusted, which can enhance the energy harvesting performance of the device at different ambient vibration frequencies. This study provides some clues to improve the performance of the vibration-based energy harvesting devices.

A new type of specimen is proposed for further research on the structure of glass-fiber-reinforced resin matrix composite lamina, which holds the potential to significantly improve the fatigue property of materials while having limited effect on the tensile strength. Herein, the fatigue life, based on the monotonic tensile test, was simulated utilizing ANSYS and nCode analysis software. The results show that the tensile strength of the local notched fiber specimens is slightly lower than that of the continuous long-fiber specimens. However, when extending the notches’ longitudinal distance, the impact to tensile strength becomes smaller and smaller. The results show that, when the longitudinal distance of the notched fiber is greater than 80 mm, the reduction in tensile strength is less than 0.65%. At the same time, the fatigue property of the specimens is improved considerably. It has been found in this experiment that when the notches’ longitudinal distance is 100 mm, the notches’ length is 1.5 mm, and the notches’ width is 1.75 mm, the fatigue cycles number of the specimens reaches 126,000 cycles, which is about 180% higher than that of the 0-0 type long fiber specimens without notches. This investigation provides a robust foundation and is a compelling basis for further exploration of new fatigue specimens.

A novel terbium-tetracarboxylate framework with the 5,5’-(diazene-1,2-iyl)diisophthalic acid (H4abtc) ligand, formulated as [Tb(Habtc)(DMSO)(H2O)2]n (ZTU-5), has been synthesized and structurally characterized. ZTU-5 features a 2D-layered structure constructed by the binuclear terbium secondary building units (SBUs) and abtc4− ligand, which can be further expanded into a 3D-supramolecular framework by the hydrogen bond interactions. In addition, the magnetic and fluorescence properties of ZTU-5 are investigated and ZTU-5 exhibits highly selective and sensitive detection of nitrofurazone (NZF).