Dalian Jiaotong University

About: Dalian Jiaotong University is a education organization based out in Dalian, China. It is known for research contribution in the topics: Microstructure & Finite element method. The organization has 4577 authors who have published 3833 publications receiving 28084 citations. The organization is also known as: Dàlián Jiāotōng Dàxué.

Contributions of Phase, Sulfur Vacancies, and Edges to the Hydrogen Evolution Reaction Catalytic Activity of Porous Molybdenum Disulfide Nanosheets

Abstract: Molybdenum disulfide (MoS2) is a promising nonprecious catalyst for the hydrogen evolution reaction (HER) that has been extensively studied due to its excellent performance, but the lack of understanding of the factors that impact its catalytic activity hinders further design and enhancement of MoS2-based electrocatalysts. Here, by using novel porous (holey) metallic 1T phase MoS2 nanosheets synthesized by a liquid-ammonia-assisted lithiation route, we systematically investigated the contributions of crystal structure (phase), edges, and sulfur vacancies (S-vacancies) to the catalytic activity toward HER from five representative MoS2 nanosheet samples, including 2H and 1T phase, porous 2H and 1T phase, and sulfur-compensated porous 2H phase. Superior HER catalytic activity was achieved in the porous 1T phase MoS2 nanosheets that have even more edges and S-vacancies than conventional 1T phase MoS2. A comparative study revealed that the phase serves as the key role in determining the HER performance, as 1T ...

An Improved Ant Colony Optimization Algorithm Based on Hybrid Strategies for Scheduling Problem

Abstract: In this paper, an improved ant colony optimization (ICMPACO) algorithm based on the multi-population strategy, co-evolution mechanism, pheromone updating strategy, and pheromone diffusion mechanism is proposed to balance the convergence speed and solution diversity, and improve the optimization performance in solving the large-scale optimization problem. In the proposed ICMPACO algorithm, the optimization problem is divided into several sub-problems and the ants in the population are divided into elite ants and common ants in order to improve the convergence rate, and avoid to fall into the local optimum value. The pheromone updating strategy is used to improve optimization ability. The pheromone diffusion mechanism is used to make the pheromone released by ants at a certain point, which gradually affects a certain range of adjacent regions. The co-evolution mechanism is used to interchange information among different sub-populations in order to implement information sharing. In order to verify the optimization performance of the ICMPACO algorithm, the traveling salesmen problem (TSP) and the actual gate assignment problem are selected here. The experiment results show that the proposed ICMPACO algorithm can effectively obtain the best optimization value in solving TSP and effectively solve the gate assignment problem, obtain better assignment result, and it takes on better optimization ability and stability.

Synergistic Phase and Disorder Engineering in 1T‐MoSe2 Nanosheets for Enhanced Hydrogen‐Evolution Reaction

Abstract: MoSe2 is a promising earth-abundant electrocatalyst for the hydrogen-evolution reaction (HER), even though it has received much less attention among the layered dichalcogenide (MX2 ) materials than MoS2 so far Here, a novel hydrothermal-synthesis strategy is presented to achieve simultaneous and synergistic modulation of crystal phase and disorder in partially crystallized 1T-MoSe2 nanosheets to dramatically enhance their HER catalytic activity Careful structural characterization and defect characterization using positron annihilation lifetime spectroscopy correlated with electrochemical measurements show that the formation of the 1T phase under a large excess of the NaBH4 reductant during synthesis can effectively improve the intrinsic activity and conductivity, and the disordered structure from a lower reaction temperature can provide abundant unsaturated defects as active sites Such synergistic effects lead to superior HER catalytic activity with an overpotential of 152 mV versus reversible hydrogen electrode (RHE) for the electrocatalytic current density of j = -10 mA cm-2 , and a Tafel slope of 52 mV dec-1 This work paves a new pathway for improving the catalytic activity of MoSe2 and generally MX2 -based electrocatalysts via a synergistic modulation strategy

A novel intelligent diagnosis method using optimal LS-SVM with improved PSO algorithm

Abstract: Aiming at the problem that the most existing fault diagnosis methods could not effectively recognize the early faults in the rotating machinery, the empirical mode decomposition, fuzzy information entropy, improved particle swarm optimization algorithm and least squares support vector machines are introduced into the fault diagnosis to propose a novel intelligent diagnosis method, which is applied to diagnose the faults of the motor bearing in this paper. In the proposed method, the vibration signal is decomposed into a set of intrinsic mode functions (IMFs) by using empirical mode decomposition method. The fuzzy information entropy values of IMFs are calculated to reveal the intrinsic characteristics of the vibration signal and considered as feature vectors. Then the diversity mutation strategy, neighborhood mutation strategy, learning factor strategy and inertia weight strategy for basic particle swarm optimization (PSO) algorithm are used to propose an improved PSO algorithm. The improved PSO algorithm is used to optimize the parameters of least squares support vector machines (LS-SVM) in order to construct an optimal LS-SVM classifier, which is used to classify the fault. Finally, the proposed fault diagnosis method is fully evaluated by experiments and comparative studies for motor bearing. The experiment results indicate that the fuzzy information entropy can accurately and more completely extract the characteristics of the vibration signal. The improved PSO algorithm can effectively improve the classification accuracy of LS-SVM, and the proposed fault diagnosis method outperforms the other mentioned methods in this paper and published in the literature. It provides a new method for fault diagnosis of rotating machinery.