A Typha Angustifolia-like MoS2/carbon nanofiber composite for high performance Li-S batteries

A Typha Angustifolia-like MoS2/carbon nanofiber composite as both a chemically trapping agent and redox conversion catalyst for lithium polysulfides has been successfully synthesized via a simple hydrothermal method. Cycling performance and coulombic efficiency have been improved significantly by applying the Typha Angustifolia-like MoS2/carbon nanofiber as the interlayer of a pure sulfur cathode, resulting in a capacity degradation of only 0.09% per cycle and a coulombic efficiency which can reach as high as 99%

Modeling and Detecting Network Communities with the Fusion of Node Attributes

As a fundamental structure in real-world networks, communities can be reflected by abundant node attributes with the fusion of graph topology. In attribute-aware community detection, probabilistic generative models (PGMs) have become the mainstream fusion method due to their principled characterization and interpretation. Here, we propose a novel PGM without imposing any distributional assumptions on attributes, which is superior to existing PGMs that require attributes to be categorical or Gaussian distributed. Based on the famous block model of graph structure, our model fuses the attribute by describing its effect on node popularity using an additional term. To characterize the effect quantitatively, we analyze the detectability of communities for the proposed model and then establish the requirements of the attribute-popularity term, which leads to a new scheme for the model selection problem in attribute-aware community detection. With the model determined, an efficient algorithm is developed to estimate the parameters and to infer the communities. The proposed method is validated from two aspects. First, the effectiveness of our algorithm is theoretically guaranteed by the detectability condition, whose correctness is verified by numerical experiments on artificial graphs. Second, extensive experiments show that our method outperforms the competing approaches on a variety of real-world networks.Comment: other authors do not want to preprin

Adsorption of Phosphate from Aqueous Solution Using an Iron-Zirconium Binary Oxide Sorbent

In this study, an iron-zirconium binary oxide with a molar ratio of 4:1 was synthesized by a simple coprecipitation process for removal of phosphate from water. The effects of contact time, initial concentration of phosphate solution, temperature, pH of solution, and ionic strength on the efficiency of phosphate removal were investigated. The adsorption data fitted well to the Langmuir model with the maximum P adsorption capacity estimated of 24.9 mg P/g at pH 8.5 and 33.4 mg P/g at pH 5.5. The phosphate adsorption was pH dependent, decreasing with an increase in pH value. The presence of Cl-, SO (4) (2-) , and CO (3) (2-) had little adverse effect on phosphate removal. A desorbability of approximately 53 % was observed with 0.5 M NaOH, indicating a relatively strong bonding between the adsorbed PO (4) (3-) and the sorptive sites on the surface of the adsorbent. The phosphate uptake was mainly achieved through the replacement of surface hydroxyl groups by the phosphate species and formation of inner-sphere surface complexes at the water/oxide interface. Due to its relatively high adsorption capacity, high selectivity and low cost, this Fe-Zr binary oxide is a very promising candidate for the removal of phosphate ions from wastewater