Southwest University

About: Southwest University is a education organization based out in Chongqing, China. It is known for research contribution in the topics: Gene & Population. The organization has 29772 authors who have published 27755 publications receiving 409441 citations. The organization is also known as: Southwest University in Chongqing & SWU.

Design and Construction of Sodium Polysulfides Defense System for Room-Temperature Na-S Battery.

Abstract: Room-temperature Na-S batteries are facing one of the most serious challenges of charge/discharge with long cycling stability due to the severe shuttle effect and volume expansion. Herein, a sodium polysulfides defense system is presented by designing and constructing the cathode-separator double barriers. In this strategy, the hollow carbon spheres are decorated with MoS2 (HCS/MoS2) as the S carrier (S@HCS/MoS2). Meanwhile, the HCS/MoS2 composite is uniformly coated on the surface of the glass fiber as the separator. During the discharge process, the MoS2 can adsorb soluble polysulfides (NaPSs) intermediates and the hollow carbon spheres can improve the conductivity of S as well as act as the reservoir for electrolyte and NaPSs, inhibiting them from entering the anode to make Na deteriorate. As a result, the cathode-separator group applied to room-temperature Na-S battery can enable a capacity of ≈1309 mAh g-1 at 0.1 C and long cycling life up to 1000 cycles at 1 C. This study provides a novel and effective way to develop durable room-temperature Na-S batteries.

Two types of coverings based multigranulation rough fuzzy sets and applications to decision making

Abstract: Covering based multigranulation rough fuzzy set, as a generalization of granular computing and covering based rough fuzzy set theory, is a vital tool for dealing with the vagueness and multigranularity in artificial intelligence and management sciences. By means of neighborhoods, we introduce two types of coverings based (optimistic, pessimistic and variable precision) multigranulation rough fuzzy set models, respectively. Some axiomatic systems are also obtained. The relationships between two types of coverings based (optimistic, pessimistic and variable precision) multigranulation rough fuzzy set models are established. Based on the theoretical discussion for the covering based multigranulation rough fuzzy set models, we present an approach to multiple criteria group decision making problem. These two types of basic models and the procedure of decision making methods as well as the algorithm for the new approach are given in detail. By comparative analysis, the ranking results based on two different models have a highly consensus. Although there exist some different ranking results on these two methods, the optimal selected alternative is the same.

A modified weighted TOPSIS to identify influential nodes in complex networks

Abstract: Identifying influential nodes in complex networks is still an open issue. Although various centrality measures have been proposed to address this problem, such as degree, betweenness, and closeness centralities, they all have some limitations. Recently, technique for order performance by similarity to ideal solution (TOPSIS), as a tradeoff between the existing metrics, has been proposed to rank nodes effectively and efficiently. It regards the centrality measures as the multi-attribute of the complex network and connects the multi-attribute to synthesize the evaluation of node importance of each node. However, each attribute plays an equally important part in this method, which is not reasonable. In this paper, we improve the method to ranking the node’s spreading ability. A new method, named as weighted technique for order performance by similarity to ideal solution (weighted TOPSIS) is proposed. In our method, we not only consider different centrality measures as the multi-attribute to the network, but also propose a new algorithm to calculate the weight of each attribute. To evaluate the performance of our method, we use the Susceptible–Infected–Recovered (SIR) model to do the simulation on four real networks. The experiments on four real networks show that the proposed method can rank the spreading ability of nodes more accurately than the original method.

Sensitive detection of gallic acid based on polyethyleneimine-functionalized graphene modified glassy carbon electrode

Abstract: A new electrochemical sensor was developed based on polyethyleneimine-functionalized graphene oxide (PEI-rGO) modified glassy carbon electrode (PEI-rGO/GCE). The synthetic positive charged PEI-rGO had good electron transfer ability, large specific surface area, prominent biocompatibility, and excellent adsorption. Its morphology and microstructure was characterized by scanning electron microscopy. The new electrode was firstly used for the detection of gallic acid, which exhibits superior performance in comparison to the bare glassy carbon electrode and graphene oxide modified glassy carbon electrode. The experimental conditions such as pH, adsorption time, and scan rate were optimized for the determination of gallic acid. Under optimum conditions, the linear regression equation of gallic acid was i p = 12.76 c − 11.44 ( i p : μA, c : mg/L, R = 0.9887) from 0.1 to 10 mg/L with a detection limit (S/N = 3) of 0.07 mg/L. The method has been successfully applied to the determination of gallic acid in samples of green tea and black tea.