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A novel tungsten-based heterojunction nanocomposite material was developed for the efficient oxidative desulfurization (ODS) of fuel oil, enabling the production of low-sulfur fuel and a reduction in harmful SOx emissions. In this material, the WC/W2C heterojunction was uniformly immobilized on a porous nitrogen-doped carbon (NC) matrix structure through facile in situ pyrolysis of polyaniline–phosphotungstic acid (PANI/PTA) precursors. The resultant WC/W2C@NC catalyst demonstrated remarkable desulfurization performance, achieving 100% removal of 4000 ppm dibenzothiophene (DBT) in just 15 min at 60 °C in the presence of 0.03 g of WC/W2C@NC and a H2O2/S molar ratio of 2. This exceptional activity is attributed to the synergistic effects stemming from the accelerated electron transfer by the NC matrix, the intricate porous network, and the abundant WC/W2C heterojunction active sites. Moreover, the in situ formation of NC around WC/W2C mitigated active site leaching, ensuring remarkable stability, with a DBT removal rate of 97.2% maintained even after eight recycling cycles. This work provides a versatile and scalable approach for fabricating tungsten-based heterojunction catalysts and highlights the potential of WC/W2C@NC as a high-performance, durable ODS catalyst, paving the way for further advancements in sustainable desulfurization technologies. [ABSTRACT FROM AUTHOR]

Highly active Keggin-type silicotungstic acid (SiW12) with oxygen vacancy (Ov) defects was encapsulated into the magnetic floral N-doped carbon microspheres (γ-Fe2O3@NC-300) through the facile one-step air pyrolysis of the precursor comprising core–shell Fe3O4@polydopamine (Fe3O4@PDA) and SiW12 to prepare γ-Fe2O3@NC@SiW12-300. The fabricated catalysts were systematically characterized and subsequently employed for the oxidation desulfurization (ODS) of the model fuel. The magnetic floral γ-Fe2O3@NC@SiW12-300 catalyst exhibited nearly perfect catalytic activity, which under mild conditions could remove 100% amount of 4000 ppm DBT in model fuel within 20 min (0.03 g catalysts and n(H2O2)/n(S) of 2). The catalyst activity is mainly attributed to the high activity SiW12 with the Ov defect and its outstanding dispersibility in γ-Fe2O3@NC, along with the high number of exposed active sites. A selected catalyst, γ-Fe2O3@NC@SiW12-300, showed a noticeable turnover frequency (TOF) (110.07 h−1) and lower activation energy (38.79 kJ mol−1) in oxidative desulfurization (ODS) with good recyclability. HO˙ radical was found to be the active species involved in ODS as confirmed by the EPR and scavenger experiments. Additionally, the fabricated catalyst can be conveniently separated and recycled within an externally applied magnetic field. [ABSTRACT FROM AUTHOR]

Metal cutting is a complex process with strong randomness and nonlinear characteristics in its dynamic behavior, while tool wear or fractures will have an immediate impact on the product surface quality and machining precision. A combined prediction method comprising modal decomposition, multi-channel input, a multi-scale Convolutional neural network (CNN), and a bidirectional long-short term memory network (BiLSTM) is presented to monitor tool condition and to predict tool-wear value in real time. This method considers both digital signal features and prediction network model problems. First, we perform correlation analysis on the gathered sensor signals using Pearson and Spearman techniques to efficiently reduce the amount of input signals. Second, we use Complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) to enhance the local characteristics of the signal, then boost the neural network's identification accuracy. In addition, the deconstructed signal is converted into a multi-channel input matrix, from which multi-scale spatial characteristics and two-way temporal features are recovered using multi-scale CNN and BiLSTM, respectively. Finally, this strategy is adopted in simulation verification using real PHM data. The wear prediction experimental results show that, in the developed model, C1, C4, and C6 have good prediction performance, with RMSE of 8.2968, 12.8521, 7.6667, and MAE of 6.7914, 9.9263, and 5.9884, respectively, significantly lower than SVR, B-BiLSTM, and 2DCNN models. [ABSTRACT FROM AUTHOR]

Two‐dimensional metal‐organic frameworks (2D MOFs) with more exposed active sites and stable structures are auspicious electrode materials for high‐performance lithium‐ion batteries (LIBs). In the current work, ultrasonic treatment was used to prepare two‐dimensional CoNi‐BDC ultrathin nanosheets (N‐CoNi‐BDC) by coordinating Ni2+, Co2+, and benzenedicarboxylic acid (BDC). The N‐CoNi‐BDC was used as the anode of LIBs, demonstrating an exceptional reversible storage capacity of 1358 mAh g−1 after 200 cycles at 0.1 A g−1. In addition, a charging capacity of 757 mAh g−1 was observed at a high current density of 1 A g−1 without observable capacity degradation up to 300 cycles. The superior behavior of N‐CoNi‐BDC was attributed to its distinct morphology of ultrathin nanosheets with more exposed active sites and stable structures. Ex‐situ FTIR and XPS results revealed that the benzene ring, carboxylate, and Ni2+ in N‐CoNi‐BDC were the active parts of lithium‐ion storage. [ABSTRACT FROM AUTHOR]

The dynamic characteristics of a multi-span double-curved brick arch thin-shell factory of Changleyuan in Baoji City and the dynamic response to train vibration load were studied using field dynamic tests and finite-element numerical simulations, and a vibration evaluation of the thin-shell factory was carried out. The results showed that the first-order frequency of the thin-shell factory was 6.24 Hz in the horizontal direction (east–west) and 9.31 Hz in the vertical direction. Moreover, it was established that the horizontal vibration is the overall vibration of the factory, while the vertical vibration is the individual vibration of the double-curved brick arch. In addition, the self-oscillation frequency obtained from the numerical simulation results was greater compared with the field measurements, with a maximum error rate of 7.14%. Both in acceleration and velocity, the vertical vibration for each measurement point was larger than the horizontal vibration, and the farther away from the railroad, the smaller the vibration. The vibration of the velocity at the bottom of the arch was almost the same as that at the top of the arch, while the acceleration vibration at the bottom of the arch was significantly larger than that at the top of the arch, with an average amplitude of 40.64%. For every 20 km/h increase in train running speed, the average increase in vertical acceleration amplitude, vertical velocity amplitude, horizontal acceleration amplitude, and horizontal velocity amplitude for each measurement point of the thin-shell factory was 35.4%, 29.8%, 23.7%, and 12.5%, respectively. When v = 150 km/h, the maximum velocity amplitude for each measurement point of the thin-shell factory was 1.163 mm/s, which is less than the security specification limit of 2.5 mm/s, such that the security of the thin-shell factory meets the requirement, and the maximum horizontal velocity amplitude was 0.272 mm/s, which is close to the integrity specification limit of 0.27 mm/s, such that the integrity of the thin-shell factory just exceeds the requirement; so it is suggested that train running speeds should not exceed 150 km/h and that the thin-shell factory needs to strengthen the monitoring and protection of its integrity. [ABSTRACT FROM AUTHOR]

This study puts forward a powerful new strategy that allows highly efficient generation of the shaping transverse nondiffracting caustics that concentrate around the expected curve. First, under the condition of stationary phase approximation, as the typical example of caustic beams, the analytical formula of nondiffracting deltoid and pentagram caustics is theoretically derived. Based on the obtained analytical formula, the desired caustics of deltoid and pentagram are numerically simulated. Hence, their optical shape and the propagation characteristics of nondiffracting caustics can be investigated. Then, based on the given generating mechanism, the corresponding experimental system to experimentally explore the nondiffracting deltoid and pentagram caustics with good self‐healing properties is constructed. Compared with the previous generating methods, the proposed method has a high light energy utilization. [ABSTRACT FROM AUTHOR]

Stochastic configuration network (SCN) is a mathematical model of incremental generation under a supervision mechanism, which has universal approximation property and advantages in data modeling. However, the efficiency of SCN is affected by some network parameters. An optimized searching algorithm for the input weights and biases is proposed in this paper. An optimization model with constraints is first established based on the convergence theory and inequality supervision mechanism of SCN; Then, a hybrid bat-particle swarm optimization algorithm (G-BAPSO) based on gradient information is proposed under the framework of PSO algorithm, which mainly uses gradient information and local adaptive adjustment mechanism characterized by pulse emission frequency to improve the searching ability. The algorithm optimizes the input weights and biases to improve the convergence rate of the network. Simulation results over some datasets demonstrate the feasibility and validity of the proposed algorithm. The training RMSE of G-BAPSO-SCN increased by 5.57 × 10 − 5 and 3.2 × 10 − 3 compared with that of SCN in the two regression experiments, and the recognition accuracy of G-BAPSO-SCN increased by 0.07% on average in the classification experiments. [ABSTRACT FROM AUTHOR]

The tendon-to-bone interface is a special structure connecting the tendon and bone and is crucial for mechanical load transfer between dissimilar tissues. After an injury, fibrous scar tissues replace the native tendon-to-bone interface, creating a weak spot that needs to endure extra loading, significantly decreasing the mechanical properties of the motor system. Macrophages play a critical role in tendon-bone healing and can be divided into various phenotypes, according to their inducing stimuli and function. During the early stages of tendon-bone healing, M1 macrophages are predominant, while during the later stages, M2 macrophages replace the M1 macrophages. The two macrophage phenotypes play a significant, yet distinct, role in tendon-bone healing. Growing evidence shows that regulating the macrophage phenotypes is able to promote tendon-bone healing. This review aims to summarize the impact of different macrophages on tendon-bone healing and the current immunomodulatory biomaterials for regulating macrophages, which are used to promote tendon-bone healing. Although macrophages are a promising target for tendon-bone healing, the challenges and limitations of macrophages in tendon-bone healing research are discussed, along with directions for further research. [ABSTRACT FROM AUTHOR]

Based on the ever-growing interest of heteroatoms (e.g., P, N, S, transition metals) doping into molybdenum carbide and graphene for electrochemical reactions, herein, a ternary phosphomolybdic acid-polyethyleneimine/graphene oxide nanocomposite as a suitable precursor was developed to not only uniformly hybridize molybdenum and carbon source to perform the controllable in situ growth of well-defined molybdenum carbide nanostructure on graphene by annealing, but also synchronously dope N and P atoms into molybdenum carbide crystal lattice and graphene. The as-prepared hybrid showed remarkable electrocatalytic activity and high stability for hydrogen evolution reaction in basic media, due to the following favorable features, i.e. a large accessible active sites afforded by the ultrafine molybdenum carbide, the heteroatoms doped, the regulated electronic structure, the balanced thermodynamics between hydrogen adsorption and desorption, the accelerated charge/mass transfer ability by the ultrathin and defective carbon layer, and the protection of molybdenum carbide by carbon layer. As a result, it only needed a small overpotential of 47 mV to drive 10 mA cm−2 and a low onset potential of 10 mV, as well as a small Tafel slope of 56.8 mV·dec−1, thus suggesting its promising potential for hydrogen evolution electrocatalyst. [Display omitted] • Mo 2 C were facilely prepared using only phosphomolybdic acid and polyethyleneimine. • Mo 2 C was in situ grown on graphene and synchronously doped by N and P atoms. • N, P–Mo 2 C/NPrGO displayed remarkable HER performances (η 10 = 47 mV). [ABSTRACT FROM AUTHOR]